THE CATHOLIC UNIVERSITY OF AMERICA

Investigating Relationships between the Subscales of the Mayer-Salovey-Caruso Emotional

Intelligence Test and the General Ability Measure for Adults General Intelligence Test

A DISSERTATION

Submitted to the Faculty of the

Department of Education

School of Arts and Sciences

Of The Catholic University of America

In Partial Fulfillment of the Requirements

For the Degree

Doctor of Philosophy

By

Tabitha Susanne Harper

Washington, D.C.

2014

Investigating Relationships between the Subscales of the Mayer-Salovey-Caruso Emotional

Intelligence Test and the General Ability Measure for Adults General Intelligence Test

Tabitha S. Harper, Ph.D.

Director: John Convey, Ph.D.

Research concerning traditional college student populations has demonstrated a

relationship between cognitive ability, often measured by academic success or grade point

average, and the ability to manage one’s emotions both within and outside of the classroom.

Studies further show that emotional intelligence plays an integral role in daily educational

activities, self-regulation, and the establishment of goals, particularly for first-year students.

Colleges and universities have begun to develop resources for all levels of undergraduates in

order to ensure a smooth transition into the college environment and continued success, socially

and academically throughout their college residency. This study examined the relationships

between the constructs of emotional intelligence and general, or cognitive, intelligence as

measured by the subscales of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)

and the General Ability Measure for Adults (GAMA) and determined to what extent the

relationship between the subscales varied by gender.

The participants consisted of 86 traditional, undergraduate students from a cross-section

of classes in the Department of Education at a southern university. Two data collection

instruments were used in this study: the Mayer-Salovey-Caruso Emotional Intelligence Test,

(MSCEIT), and the General Ability Measure for Adults (GAMA). One of the study’s most

important results is that the General Ability Measure for Adults Total score is a significant

predictor of the MSCEIT Understanding Emotions (UE) subscale score when controlling for the

students’ grade point average. In addition, grade point average is a significant predictor of the

Managing Emotions and Perceiving Emotions subscale scores when controlling for the total

GAMA IQ scores. Lastly, when the MSCEIT Understanding Emotions (UE) subscale was

controlled for, gender proved to be significant in the prediction of grade point average. However,

no additional statistically significant differences were discovered for females and males on the

remaining MSCEIT (Perceiving Emotions, Facilitating Thought, and Managing Emotions) and

GAMA subscale scores (Matching, Analogies, Sequences, and Construction).

In conclusion, the results of this study add to the literature in Educational Psychology

concerning the relationships between the emotional and cognitive intelligence of college students

and provide a better understanding of the role that emotions play when college students are

trying to solve complex cognitive problems.

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This dissertation by Tabitha Susanne Harper fulfills the dissertation requirement for the doctoral

degree in Educational Psychology approved by John Convey, Ph.D., as Director, and Kathleen

C. Perencevich, Ph.D., Agnes Cave, Ph.D, and Lynn M. Gangone as readers.

________________________________

John Convey, Ph.D., Director

________________________________

Kathleen C. Perencevich, Ph.D., Reader

_________________________________

Agnes Cave, Ph.D., Reader

_________________________________

Lynn M. Gangone, Ed.D., Reader

iii

Dedication

This dissertation is dedicated to my husband, John, and my daughter, Annabel. I would

not have been able to complete such a monumental accomplishment without their patience,

dedication, and eternal support.

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Table of Contents

Chapter 1 – Introduction……………………………………………………………1

Statement of the Problem…………………………………………………...1

Purpose of the Study……………………………………………………….. 4

Significance of the Study………………. ……………………..………….. 4

Background for the Study………………………………………………….. 5

Conceptual Framework…………………………………………………….. 10

Research Questions………………………………………………………… 11

Hypotheses…………………………………………………………………. 12

Definition of Terms…………………………………………………………12

Limitations…………………………………………………………………. 13

Chapter 2 – Review of the Literature………………………………………………. 14

History of Emotional Intelligence………………………………………….. 15

Emotional Intelligence Construct………………………………………….. 18

Constructs Similar to Emotional Intelligence……………………… 19

Models of Emotional Intelligence………………………………………….. 22

Evaluation and Assessment of Emotional Intelligence…………………….. 28

Mayer-Salovey-Caruso Emotional Intelligence Test………………. 29

History, Definition, Theories, and Beginnings of General Intelligence…… 35

General (Cognitive) Intelligence Construct………………………………... 37

General Intelligence Theories……………………………………………… 38

Evaluation and Assessment of General (Cognitive) Intelligence………….. 40

General Ability Measure for Adults……………………………….. 42

The College Student and Intelligence……………………………………… 51

Academic Outcomes and Grade Point Average……………………………. 53

Controversial Issues………………………………………………………... 56

Chapter 3 – Methodology………………………………………………………….. 64

Research Problem………………………………………………………….. 64

Research Purpose…………………………………………………………... 66

Research Questions and Hypotheses………………………………………. 66

Design of Study……………………………………………………………. 67

Variables…………………………………………………………… 68

Participants…………………………………………………………………. 68

Instrumentation…………………………………………………………….. 69

Mayer-Salovey-Caruso Emotional Intelligence Test………………. 69

General Ability Measure for Adults……………………………….. 74

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Procedure……………………………………………………………………79

Data Management and Assessment Scoring……………………………….. 81

Data Analysis………………………………………………………………. 81

Human Subjects……………………………………………………………. 83

Limitations…………………………………………………………………. 83

Threats to Validity…………………………………………………………. 85

Chapter 4 – Results………………………………………………………………… 87

Variable Relationships and Descriptive Statistics…………………………..87

Mayer-Salovey-Caruso Emotional Intelligence Test and the General

Ability Measure for Adults Subscale Relationships……………….. 91

Emotional Intelligence, Gender, and Grade Point Average……………….. 93

Emotional Intelligence, General (Cognitive) Intelligence, and Grade

Point Average……………………………………………………… 100

Chapter 5 – Discussion…………………………………………………………….. 106

Summary of Findings……………………………………………………… 106

Subscale Relationships between the Mayer-Salovey-Caruso Emotional

Intelligence Test and the General Ability Measure for Adults…….. 107

Gender, Emotional Intelligence, and Grade Point Average……………….. 108

Emotional Intelligence, General (Cognitive) Intelligence, and Grade

Point Average……………………………………………………….110

Educational Implications……………………………………………………112

Relationships between the Mayer-Salovey-Caruso Emotional Intelligence

Test and General Ability Measure for Adults Assessments……….. 112

Gender, Academic Achievement, and Emotional Intelligence…………….. 113

Limitations and Future Research……………………………………………115

Appendices

Appendix A – Recruitment Script………………………………………….. 120

Appendix B – Copy of Informed Consent Agreement……………………... 122

Appendix C – Administrative Procedures for the Delivery of the General

Ability Measure for Adults Assessment and the Mayer-Salovey-

Caruso Emotional Intelligence Test………………………………... 127

Appendix D – Administrative Procedures for Delivery of the General

Ability Measure for Adults………………………………………… 129

Appendix E – Administrative Procedures for the Delivery of the Mayer

Salovey-Caruso Emotional Intelligence Test……………………….131

Appendix F – Codebook for SPSS Data Entry…………………………… 133

References………………………………………………………………………….. 138

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List of Tables

Table 1 – Multiple Conceptualizations of Emotional Intelligence………………… 20

Table 2 – Constructs Commonly Described as Related to Ability EI and

Trait EI………………………………………………………………………28

Table 3 – Historical Overview of the Influences on the Development of

Intelligence…………………………………………………………………. 36

Table 4 – Means (Standard Deviations) for Variables as a Function of

Student Group and Gender………………………………………………….49

Table 5 – Overview of the MSCEIT Scores………………………………………...71

Table 6 – Guidelines for Interpreting MSCEIT Scores……………………………..72

Table 7 – GAMA IQ Scores and Subtest Scores……………………………………76

Table 8 – Descriptive Statistics for Dependent Variable: GPA……………………. 85

Table 9 – Case Processing Summary………………………………………………. 87

Table 10 – Summary Table of Means for Variables………………………………. 88

Table 11 – Pearson Product Moment Correlations for the GAMA Subtests………. 90

Table 12 – Pearson Product Moment Correlations for the MSCEIT Subtests…….. 90

Table 13 – Pearson Product Moment Correlations between the GAMA

and MSCEIT Scores……………………………………………………….. 91

Table 14 – Eigenvalues and Canonical Correlation………………………………... 92

Table 15 – Standardized Coefficients for GAMA Variables………………………. 93

Table 16 – Standardized Coefficients for MSCEIT Variables…………………….. 94

Table 17 – Regression of GPA on the Total MSCEIT Scores and Gender…………95

Table 18 – Regression of GPA on the MSCEIT PE Scores and Gender……………97

Table 19 – Regression of GPA on the MSCEIT FE Scores and Gender……………98

Table 20 – Regression of GPA on the MSCEIT UE Scores and Gender…………...99

Table 21 – Regression of GPA on the MSCEIT ME Scores and Gender………….100

Table 22 – Regression of the MSCEIT ME Scores on GPA and Overall GAMA

IQ Scores…………………………………………………………………… 102

Table 23 – Regression of the MSCEIT FE Scores on GPA and Overall GAMA

IQ Scores……………………………………………………………………103

Table 24 – Regression of the MSCEIT UE Scores on GPA and Overall GAMA

IQ Scores…………………………………………………………………… 104

Table 25 – Regression of the MSCEIT PE Scores on GPA and Overall GAMA

IQ Scores…………………………………………………………………… 105

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Acknowledgements

I would like to gratefully acknowledge my committee, professors, and in particular, my

advisor and Chair, Dr. John J. Convey of The Catholic University of America for his thoughtful

guidance. I would also like to fondly remember Dr. Rick Yekovich and Dr. Thomas Long.

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CHAPTER 1 - INTRODUCTION

There are many theories, particularly in the field of educational psychology, that

define what it means to be intelligent as it relates to the human species. In most of the current

existing theories and definitions, intelligence is considered to encompass higher-level thinking

processes and problem solving abilities (Mayer, Roberts, & Barsade, 2008, Sternberg, 2000a,

2000b). Questions have been put forth since the early 1990s as to whether there is more to being

intelligent than advanced mental processing, learning, and possessing an ability to adapt to one’s

environment, or what may otherwise be defined as a type of emotional intelligence (EI)

(Sternberg, 2000a, 2000b). Researchers have found plausible, moderate correlations between

general (cognitive) intelligence, often measured by the Intelligence Quotient, or IQ, and

academic achievement, gender and academic achievement, and grade point average and

academic achievement (Neisser et al., 1996; Brody, 2000).

Statement of the Problem

While there has been a significant amount of research conducted concerning both the

emotional intelligence and general (cognitive) intelligence constructs in relation to academic and

life success, there is a gap in the literature relating the two, and studying potential relationships

between the two constructs, particularly for the college student population.

Previous research has evaluated the construct of emotional intelligence and academic

achievement, as measured by verbal ability; the construct of emotional intelligence, via self-

report measures, personality traits, and academic achievement; the construct of emotional

2

intelligence against itself using self-report measures with an ability measure; and psychometric

analyses of the various emotional intelligence assessments (Barchard, 2003; Newsome, Day, &

Catano, 2000; O’Connor & Little, 2003; Schutte, Malouff, Hall, Haggerty, Cooper, et al., 1998).

Other researchers have conducted studies of the construct of emotional intelligence as a

component of multiple intelligences extraneous to that of cognitive intelligence; and some

writers have controversially proposed that emotional intelligence is even more important than

cognitive intelligence altogether (Gardner, 1983; Goleman, 1997).

As a measure of the emotional intelligence construct, the Mayer-Salovey-Caruso,

Emotional Intelligence Test (MSCEIT) has been used in tandem with cognitive, or IQ

assessments, such as Raven’s Progressive Matrices and the Vocabulary scale of the Wechsler

Adult Intelligence Scale III but has not been directly compared, subscale to subscale with the

non-verbal General Ability Measure for Adults (GAMA) cognitive intelligence test.

Therefore, this dissertation will conduct a study of the emotional intelligence construct

and the Intelligence Quotient (IQ) construct through the use of the Mayer-Salovey-Caruso

Emotional Intelligence Test (MSCEIT) (Mayer, Caruso, & Salovey, 2002) and the General

Ability Measure for Adults (GAMA) (Naglieri & Bardos, 1997) intelligence test to determine if

there are any significant relationships exhibited between the two constructs. More specifically,

the overall scores and subscales (sub-tests) of the two assessments will be evaluated through

various statistical analyses to determine if there are any existing relationships between emotional

and cognitive intelligence, gender, and grade point average within a sample of college students.

3

The emotional intelligence and IQ constructs will firstly be examined through the

evaluation of the mean scores on the subscales of the MSCEIT and GAMA assessments. A

quasi-experimental design with one set of variables: Matching, Sequences, Analogies, and

Construction (GAMA) and a second set of variables: Perceiving, Facilitating, Understanding,

and Managing Emotions (MSCEIT) will be employed to analyze the differences on the

subscales, and the relationships among the subscales, of the two assessments. In addition, the

variables of gender and grade point average will be examined. The variable of gender will be

examined in order to determine if there are any significant relationships, or differences, exhibited

for females and males on the MSCEIT assessment. The variable of grade point average (GPA)

will be included to examine overall academic ability in relation to the subscales on the MSCEIT.

A review of the literature has demonstrated that there are often distinct relationships

between cognitive ability, often measured by academic success or overall GPA, and being able to

manage one’s emotions on college campuses, both inside and outside of the classroom

(Barchard, 2003; Evenson, 2007). For those students who have difficulty managing their

emotions, the adaptation to, and success within, the higher education environment often proves

to be too difficult. For those students who cannot emotionally and academically cope and adapt,

the results are often disastrous.

Some colleges and universities currently offer on-campus programs and support systems

for in-coming (freshmen and transfer students). However, many of these are still limited in scope

and access. Research has found that emotions play an integral role in daily educational activities,

self-regulation, and goal-setting within an academic environment, particularly for first-year

4

students (Schutz & DeCuir, 2002). It is proposed that through findings generated by this study,

academic institutions develop such programs on more campuses nation-wide and their services

will be made available to more students.

Purpose of the Study

The purpose of this study is to examine the relationship between the constructs of

emotional and general (cognitive) intelligence within a sample of a college student population by

comparing the subscales of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)

and the General Ability Measure for Adults (GAMA). Statistical analyses will be conducted to

evaluate any meaningful, or significant, relationships between, for example, students who are

able to better manage their emotions and the ability to comprehend analogies and other difficult

cognitive tasks as demonstrated by performance on the MSCEIT and GAMA assessments. In

addition, gender and grade point averages will be examined to present additional findings

concerning potential differences that may exist in emotional and general intelligence abilities.

If such relationships are found to exist by examining the data from the study, the

implications for colleges in regards to student matriculation and retention could be valuable in

further developing and enhancing support programs for freshmen and upper-classmen.

Significance of the Study

Throughout history, the study of intelligence and emotion has played a prominent role in

the fields of psychology and philosophy. It is important to examine any meaningful relationships

between, for example, students who are able to better manage their emotions and the ability to

comprehend analogies and other difficult cognitive tasks. The college years are a period of

5

maturation and change, and the various emotions experienced by these students often has an

impact, sometimes derogatory, upon academic outcomes. If such relationships do exist, the

implications for colleges in regards to student matriculation, retention, and academic guidance

could be valuable to college administrators and faculty.

Background for the Study

General or cognitive intelligence

Scholarly research concerning general, or cognitive, intelligence has been in existence

for many years and has been contemplated and discussed in great detail in historical plays,

literature, and poetry (Oatley, 2004). The construct and measurement of what is commonly

known as the Intelligence Quotient, or IQ, has evolved through various iterations, developments,

and assessments throughout the years (Sternberg, 2000a; Brody, 2000; Oatley, 2004). General, or

cognitive intelligence, is often described as g, and the concept of the g construct was developed

by Charles Spearman in the early 1900s. General intelligence, according to Spearman, may be

defined as “a two-factor theory of intelligence in which performance is determined by a general

factor, g, a universal due to a person’s general intelligence, and a specific factor, s, due to a

unique ability or activity related to a particular test” (Embretson & Schmidt McCollam, 2000, p.

424). Spearman’s model proposed that the variation demonstrated in any measurement of

intelligence quotient (IQ) scores could be explained by the g and s factors (Sternberg, 2000a;

Embretson & Schmidt McCollam, 2000; Spearman, 1904, 1927).

Spearman’s model and framework was further developed by Louis Thurstone in the early

1930s. Thurstone was the first researcher at the time to analyze ability measures that could be

6

considered independent of Spearman’s g (Brody, 2000; Thurstone, 1931; Guilford, 1972). His

study looked in-depth at the matrix of correlations concerning abilities. Thurstone developed the

multiple factor analysis method to search for independent factors that might exist within the

matrix and found that there was a profile of strengths and weaknesses for individuals on specific

abilities. Thurstone’s research led him to the conclusion that there are several primary ability

factors: verbal comprehension, number facility, spatial reasoning, memory, and deductive and

inductive abilities (Brody, 2000; Thurstone, 1931; Guilford, 1972).

More recently the research surrounding the study of general intelligence continues to be

abundant in academic, workplace, and military settings and has employed the use of the

Stanford-Binet Intelligence Quotient assessment, the Army Alpha/Beta Group IQ tests, and the

Wechsler Intelligence Scales. Various assessments have been developed in order to assess

academic achievement, job placement and rank, and assist in the prediction of mental and

learning disorders (Kaufman, 2000; Brody, 2000; Sternberg, 1985). A multitude of general

intelligence assessments have been created and utilized, and researchers have often embraced

samples in higher education to evaluate proposed relationships between intelligence and

academic achievement (Sternberg, 1985; Brody, 2000; Kaufman, 2000; Embretson & McCollam,

2000).

Emotional Intelligence

Beginning in the early 1990s, a copious amount of research concerning the construct of

emotional intelligence began to evolve. Many researchers and scholars maintain that there is

more to being intelligent than was initially believed and that general or cognitive intelligence is

7

only part of what makes one intelligent (Mayer, Roberts, & Barsade, 2008; Gardner, 1983;

Sternberg, 1985; Parker, Summerfeldt, Hogan, & Majeski, 2004; Farrelly & Austin, 2007;

Brody, 2000; Goleman, 1997).

The early conceptualization of the construct of emotional intelligence was closely related

to that of social intelligence. One of the first references to social intelligence, an intelligence that

stood apart from general or cognitive intelligence, was that of Edward Thorndike in 1920.

Thorndike defined social intelligence as the ability to manage relationships and to act

appropriately in a given social context (Thorndike, 1920).

In addition to Thorndike’s social intelligence theory in the early 1900s, other theories

emerged including Howard Gardner’s Theory of Multiple Intelligences and Robert Sternberg’s

Triarchic Theory. Gardner and Sternberg believed that there are additional factors besides

general or cognitive intelligence at play in any given situation (Gardner, 1983; Sternberg, 1985;

Bonham, 1987). Gardner’s Theory of Multiple Intelligences proposes that there are eight kinds

of biologically-based, human abilities, including interpersonal and intrapersonal intelligences;

intelligences which would be most closely related to a social intelligence (Gardner, 1983).

Robert Sternberg was one of the first human intelligence researchers to take a stand against the

tradition of the psychometric approach to the evaluation of intelligence that had become so

commonplace. He based his definition on three aspects of intelligence: componential

(analytical), experiential (creative), and practical (contextual) intelligence (Sternberg, 1985).

Research concerning the emotional intelligence construct continued to evolve, and some

of the first theory-based models were developed. Mixed and Trait models of emotional

8

intelligence were introduced. These EI models measured and described emotional intelligence as

a personality characteristic (Mayer, Salovey, & Caruso, 2000; Mayer, Robert, & Barsade, 2008;

Goleman, 1997). In the early 1990s, the first ability model of emotional intelligence was

introduced (Mayer & Salovey, 1997).

In 1997, Dr. Reuven Bar-On developed the Bar-On EQ- i mixed model of emotional

intelligence. The Bar-On EQ-I model is based upon five areas or abilities: intrapersonal

relationships, interpersonal relationships, stress management ability, adaptability, and general

mood. The Bar-On EQ-I was the first true assessment of the emotional intelligence construct in a

self-administered format (Bar-On EQ-I; Bar-On, 1997). Bar-On posits that emotional and

general or cognitive intelligence work in unison to contribute to one’s overall intelligence (Bar-

On, 1997).

A second mixed model of emotional intelligence is that proposed by Daniel Goleman.

Goleman’s initial work in emotional intelligence was initially based upon the research conducted

by John Mayer, Peter Salovey, and David Caruso. Goleman wrote and popularized the idea of

emotional intelligence, particularly in workplace settings, through his book Emotional

Intelligence (Goleman, 1997).

Similar in nature to the mixed models of emotional intelligence is the trait model

developed by Karen Petrides and her colleagues. This model views the construct of emotional

intelligence as a personality trait, specifically, the belief in oneself (Petrides, Frederickson, &

Furnham, 2004). The trait model of emotional intelligence uses the Trait Emotional Intelligence

Questionnaire (TEIQue) to evaluate several facets of emotional intelligence: Adaptability,

9

Assertiveness, Emotion Perception and Expression, etc. (Petrides, Frederickson, & Furnham,

2004).

In the early 1990s, the team of John Mayer, Peter Salovey, and David Caruso developed a

new model of emotional intelligence based on ability. The Mayer, Salovey, Caruso model is

comprised of four branches: Perceiving Emotions, Facilitating Thought, Understanding

Emotions, and Managing Emotions and is assessed via the Mayer-Salovey-Caruso Emotional

Intelligence Test (MSCEIT) (Mayer & Salovey, 1997; Mayer, Robert, & Barsade, 2008; Mayer,

Salovey, & Caruso, 2000).

The Bar-On and Mayer, Salovey, and Caruso emotional intelligence models have

typically been used in academic and higher education settings. The Goleman and Trait models

and assessments are more prevalent in workplace settings in assessing human resource needs

(Goleman, 1997; Petrides, Frederickson, & Furnham, 2004).

In the existing literature, various researchers have analyzed the construct of emotional

intelligence and possible correlations to academic success, higher grade point averages, and

transitions from high school to college (Barchard, 2003; Parker, Summerfeldt, et al., 2004;

Wraight, 2006). The majority of these studies have used the mixed-model Bar-On Emotional

Quotient Inventory (Bar-On EQ-I; Bar-On, 1997) paired with an evaluation of end-of term

course grades, grade point averages, surveys, and other self-report measures (Barchard, 2003;

Parker, Summerfeldt, Hogan, & Majeski, 2004; Hogan & Weiss, 1974; Newsome, Day, &

Catano, 2004). Other researchers have evaluated the validity of specific emotional intelligence

10

assessments, including the MSCEIT (Farrelly & Austin, 2007; Newsome, Day, & Catano, 2000;

O’Connor & Little, 2003).

The constructs of emotional and general (cognitive) intelligence continue to evolve based

on research conducted in the field. The possession of a certain level of general intelligence is

typically required for one to be successful in academic environments, specifically in higher

education. It is proposed in the literature that emotional intelligence also contributes to success in

academia and student matriculation and retention.

Conceptual Framework

The conceptual framework for this dissertation is primarily concerned with two aspects:

the Mayer, Salovey, and Caruso four-branch model of emotional intelligence and the model of

general intelligence as defined by Jack Naglieri and Achilles Bardos. Each of these is described

in further detail in the below paragraphs and in Chapter Two.

The Mayer, Salovey, and Caruso four-branch model of emotional intelligence is currently

the only one of its kind and consists of the following four branches, or abilities: 1) Perceiving

Emotions, or the ability to identify emotions in oneself and others; 2) Facilitating Thought, or

using emotions in cognitive activities and problem solving; 3) Understanding Emotions in

relationships and meaning; and 4) Managing Emotions in oneself and others (Mayer & Salovey,

1997; Mayer, Robert, & Barsade, 2008; Mayer, Salovey, & Caruso, in ed. Sternberg, 2000a,

2000b).

The General Ability Measure for Adults (GAMA) was developed by Jack Naglieri,

George Mason University, VA, and Dr. Achilles Bardos, University of Northern Colorado, in

11

order to assess general intelligence (IQ), or general cognitive ability, using a non-verbal

assessment. Based upon their research of various populations, including those who needed to be

assessed in a non-verbal manner, the authors developed the GAMA instrument. An overall

intelligence score, along with four sub-scale scores, (Matching, Analogies, Sequences, and

Construction) are provided in the data and general scoring reports (Bracken & Naglieri, in ed.,

Reynolds & Kamphaus, 2003).

Research Questions (RQ)

Primary Research Question

RQ1: What is the relationship between/among the subscales, or four branch scores, (Perceiving

Emotions, Facilitating Thought, Understanding Emotions, and Managing Emotions), of the

Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the subscales, or four branch

scores, (Matching, Analogies, Sequences, Construction), of the General Ability Measure for

Adults general intelligence test (GAMA)?

Secondary Research Questions

RQ2: Do females and males demonstrate a different relationship between emotional intelligence,

as measured by the Mayer-Salovey-Caruso Emotional Intelligence Test and grade point average

(GPA)?

RQ3: : Is the relationship between/among the variables of the Branch and Total Emotional

Intelligence scores on the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and

12

Grade Point Average (GPA) different for students who exhibit high IQ versus low IQ as

measured by the General Ability Measure for Adults (GAMA) intelligence test?

Hypotheses

The hypotheses proposed for this study are as follows:

1. There is a positive relationship (correlation) between each of the subscales of the two

assessments.

2. Women will demonstrate overall higher grade point averages than males as a result of

higher scores on the Perceiving Emotions, Facilitating Thought, and Understanding

Emotions subscales on the MSCEIT.

Definition of Terms

For the purpose(s) of this study, the following terms are defined:

1. general or cognitive intelligence – The true definition of intelligence depends upon the

context within which the construct resides and the theorist(s) definition within that same

context. For the purpose of this study, intelligence may be defined as the abilities and

knowledge that one acquires and uses to solve problems in her or his world (Woolfolk,

2007).

2. Intelligence Quotient or IQ – The intelligence quotient may be calculated in the

following manner:

Intelligence Quotient = Mental Age/Chronological Age x 100. The definition for

the purpose of this study will be as follows: A score that compares mental and

13

chronological ages. Intelligence quotient scores have statistical characteristics and follow

a normal, bell-shaped curve. The typical score range for the general population is

between 85-115 (Woolfolk, 2007).

3. emotional intelligence or EI – Emotional intelligence is defined as the ability to perceive,

appraise, and express emotion; the ability to generate feelings when facilitating thought;

the ability to understand emotion and emotional knowledge; and the ability to regulate

emotions to promote emotional and intellectual growth (Mayer & Salovey, 1997, p.10).

In this study, the Mayer, Salovey,.Caruso Emotional Intelligence Test (MSCEIT), based

upon the authors’ four-branch model of emotional intelligence, will be used to define,

measure, and evaluate the construct of emotional intelligence.

Limitations

The following limitation has been identified in the study:

1. While the variable of grade point average (GPA) will be included in the study, it should

be noted that the collection of this particular variable will be via self-report. The possible

difficulty of obtaining true self-reports, as provided by the students in the study, may

present some data integrity concerns.

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CHAPTER 2 – A REVIEW OF THE LITERATURE

Definitions and theories of human intelligence are plentiful. The basic understandings of

intelligence evolved as early as 400 years ago and were often referred to in poetry, literature, and

plays (Oatley, 2004). In most of the current existing theories and definitions, intelligence is

considered to encompass higher-level thinking processes and problem solving abilities, although

a universal definition of intelligence remains elusive. Many scholars view intelligence as being

an overall hierarchical representation of various mental abilities. Aristotle viewed intelligence as

quick wit. More contemporary views are grounded in metaphors: geographic, computational,

biological, anthropological, etc. (Mayer, Roberts, & Barsade, 2008, Sternberg, 2000a, 2000b).

Questions have been posed since the early 1900s as to whether there is more to being intelligent

than advanced mental processing, learning, and possessing an ability to adapt to one’s

environment (Sternberg, 2000a). Thus began the research surrounding emotional intelligence, a

later iteration of social intelligence.

The following literature review aims to provide a selective overview of the emotional

intelligence and general (cognitive) intelligence constructs and some relevant studies and

criticisms as the concepts relate to this dissertation. The intention of this literature review is to

set forth the framework for the purpose of the study and to propose how this study will address

the existing gap in the literature concerning traditional college student populations. The structure

of the review of the relevant literature is as follows: history and definitions of the constructs,

assessments, studies, and conclusions.

15

The History of Emotional Intelligence, Definitions of the Construct, and Models

History and Beginnings

The study of emotions has been a topic of research for many years for scholars, scientists,

and philosophers. One of the earliest references to emotions and expression is Darwin’s work in

the Expression of the Emotions in Man and Animals (1872). Darwin maintained that it was

necessary for one to recognize emotional changes in others, and possible predators, in order to

survive and adapt to a specific environment (Darwin, 1872). Then, beginning in the early 1900s,

researchers began to postulate that there was more to being intelligent than cognitive ability

(Mayer, Roberts, & Barsade, 2008; Gardner, 1983; Sternberg, 1985; Parker, Summerfeldt,

Hogan, & Majeski, 2004; Farrelly & Austin, 2007; Brody, 2000; Goleman, 1997).

The emotional intelligence construct is rooted in the historical concept of social

intelligence. In 1909, Dewey developed the social intelligence theory: the ability to manage

relationships with others and act in the appropriate manner in various social situations (Joseph &

Newman, 2010; Thorndike, 1920). The social intelligence theory was further refined and

developed by Thorndike in the 1920s. In 1940, Wechsler proposed that there existed “non-

intellective factors on intelligent behavior” (Bar-On, 1997).

Over the past two decades or so, there has proven to be a tremendous interest in what has

come to be defined as the emotional intelligence construct. Initial reference to the topic of

emotional intelligence as a construct can be seen as early as the 1960s. During the 1980s

scholars began the earnest analysis of multiple intelligences (Mayer, Roberts, & Barsade, 2008).

The first reference to the term emotional intelligence was in a dissertation written by Payne in

16

1986 titled A Study of Emotion: Developing Emotional Intelligence (Mayer, Salovey, & Caruso,

2000). Following these earlier theories came the concept of possible multiple intelligences.

Gardner’s Theory of Multiple Intelligences and Sternberg’s Information Processing, or

Triarchic Theory, are two of the existing models that incorporate factors beyond a general

intelligence and appear to be possible ancestors of the emotional intelligence construct.

Gardner’s theory states that there are eight kinds of biologically-based, human abilities,

including logical-mathematical, linguistic, musical, spatial, kinesthetic, interpersonal,

intrapersonal, and naturalist (Gardner, 1983). Gardner developed his theory based upon the

argument that traditional, psychometric intelligence assessments only address a limited number

of verbal, spatial, and logical-reasoning abilities (Gardner, 1983; Davidson & Downing, 2000).

Sternberg’s theory states that there is a relationship demonstrated in intelligence between

the internal and external worlds of the individual and the experiences of that individual within

those worlds (Sternberg, 1985). Sternberg’s Triarchic Theory of Intelligence is comprised of

three primary intelligences: componential (analytical), experiential (creative), and practical

(contextual) intelligence. Analytical intelligence is typically utilized when one is required to

analyze, judge, or evaluate a problem of an abstract nature. Creative intelligence is often seen in

writing and art. Lastly, Contextual or practical intelligence is most evidently exhibited in daily

life tasks and problems. Sternberg posits that practical intelligence is based on the concept of

tacit knowledge: the unspoken, non-verbal rules of operation and knowing (Sternberg, 1985;

Sternberg, 2000a.).

17

Both Gardner’s and Sternberg’s theories of multiple intelligences are well-studied and

prominent in the fields of education and psychology. However, they are not without criticism.

Both of these theories have proven to be difficult to test empirically for validity. Gardner’s

Theory of Multiple Intelligences faces a major criticism in professional arenas in that it has not

been properly tested nor subjected to peer review. A second major criticism of Gardner’s theory

is that he claims that intelligence does not exist in the manner in which it has been historically

understood and studied and that such cognitive intellectual abilities may not be relevant at all

(Davidson & Downing, 2000; Sternberg, 1983). Lastly, many critics believe that each of the

eight intelligences is actually a separate cognitive style versus an intelligence that contributes to

the theory as a whole (Morgan, 1996).

In addition, Sternberg’s Triarchic Theory of Intelligence has been very contentious within

academic and scientific communities. In a study and ongoing debate conducted by Gottfredson

(2002), several claims are made concerning Sternberg’s theory, particularly around the construct

of Practical Intelligence: the misrepresentation of data and findings, the inflated support of

research results, and the disregard for findings that obviously contradict the Triarchic Theory in

its entirety. Further, Gottfredson, along with other critics, posit that there is simply not enough

empirical evidence to support the theory and that more theoretical research needs to be

conducted especially concerning the acquisition of tacit knowledge (Gottfredson, 2001; Torff &

Sternberg, 1998).

Despite the controversies concerning Gardner’s and Sternberg’s theories of intelligence,

the two theories continue to hold an important place in the fields of education, psychology, and

18

the social sciences. The conceptualization of emotional intelligence may be viewed as being

similar to theories such as those of Gardner and Sternberg in that emotional intelligence in

interpersonal and intrapersonal skills, as well as the ability to self-govern through metacognition,

plays an important role in one’s ability to act in an intelligent manner (Sternberg, 1985).

The Emotional Intelligence Construct

From the very onset of its introduction, the latent psychological construct of emotional

intelligence has followed in the footsteps of general (cognitive) intelligence as being rather

difficult to define. There is consistent disagreement and confusion among scholars and

practitioners as to how the construct should be defined and operationalized. The initial

conceptualizations of the construct defined emotional intelligence as an interrelated set of

abilities which aided one in understanding, managing, and controlling emotions (Mayer &

Salovey, 1997; Mayer, Salovey, & Caruso, 2008). The addition of various dispositional and

personality traits (self-esteem, optimism, happiness, self-management, etc.) to the initial

terminology has compounded the confusion surrounding the exact definition of the emotional

intelligence construct (Bar-On, 2004; Mayer, Salovey, & Caruso, 2008). Further, some

researchers have defined the emotional intelligence construct as a person’s preference when

making decisions to rely upon feelings instead of logic (Tett, Wang, Gribler, & Martinez, 1997).

For the requirements of this study, the Mayer and Salovey definition of emotional

intelligence will be used to define the construct. Mayer, Salovey, and Caruso define the

emotional intelligence construct as an ability-related construct versus a personality trait-related

construct. Therefore, emotional intelligence is “the ability to perceive and express emotion,

19

assimilate emotion in thought, understand and reason with emotion, and regulate emotion in the

self and others” (Mayer & Salovey, 1997, p.10).

Constructs Similar in Nature to the Emotional Intelligence Construct

In the existing literature concerning the emotional intelligence construct, much of the

criticism has centered on a proper definition of the construct. Because of the varied terminology

used to define the emotional intelligence construct, many researchers question whether the

emotional intelligence construct can stand alone as a separate entity. Much of the confusion that

is a result of defining the construct of emotional intelligence is often placed upon the mixed

models of emotional intelligence given that these models incorporate various personality traits

such as conscientiousness, self-control, and empathy (Mayer, Salovey, & Caruso, 2000; Locke,

2005). Therefore, it is important to distinguish the emotional intelligence construct from those

that are similar in nature.

Table 1 on the following page depicts some of the more common constructs that are considered

to be closely related to emotional intelligence.

20

Table 1

Multiple Conceptualizations of Emotional Intelligence

Construct Possible Current Measure Equivalent in IQ

Research Key Processes

Temperament

Scales for Big Five

EQ-I (Bar-On, 1997)

None Neural & cognitive

processes controlling

arousal, attention, and

reinforcement

sensitivity

Information

Processing JACBART, Emotional

Stroop, RAFL

Choice RT, inspection

time, working

memory

Specific Processing

modules

Emotional

self-regulation

Selected scales from

questionnaires for EI (e.g.,

TEIQue

Self-assessed

intelligence

Monitoring and

regulation of internal

states; self-efficacy

Emotional

knowledge

and skills

MSCEIT

Gc and/or Gk Multiple procedural

and declarative skills

(Adapted from The Science of Emotional Intelligence: Current Consensus and Controversies,

Zeidner, Roberts, & Matthews, 2008).

In addition to the above conceptualizations, there are quite a number of terms that are

associated with the emotional intelligence construct: alexithymia, empathy, emotional self-

efficacy, and socio-emotional effectiveness (Mayer & Ciarrochi, 2006). Alexithymia, a

personality trait, is defined as the inability to express, define, and describe emotions (Parker,

Bagby, & Taylor, 2001). Emotional self-efficacy is defined as a “person’s belief that they

possess empathy and assertiveness…as well as elements of social intelligence…personal

intelligence…and Ability EI” (Mayer & Ciarrochi, 2006, p. 427). Lastly, socio-emotional

effectiveness is defined as possessing the ability to accomplish goals through appropriate

navigation of one’s world (Mayer & Ciarrochi, 2006).

21

There are several studies in the literature that describe the various forms of the emotional

intelligence construct. For example, in a study conducted by Barchard and Hakstian the authors

demonstrated that Ability EI, as measured by some of the subtests of the MSCEIT, shows a

statistical overlap with some areas of empathy and alexithymia, r = -.10 (2004).

Additional studies such as one conducted by Schulz et al. in 2006 within a sample of 138

undergraduate, psychology students proposed the existence of some conceptual similarities

between the emotional intelligence construct, as measured by the MSCEIT, and social

intelligence.

Further, Schulte, Ree, and Carretta found significant relationships among the emotional

intelligence construct, as measured by the MSCEIT, and some of the Big Five personality

dimensions: Neuroticism, Extraversion, Openness to Experience, and Conscientiousness (2004).

On the other hand, Joseph and Newman found that the mixed-models of emotional intelligence,

not the ability-based models such as the Bar-On EQ-I, were the models most likely to overlap

with the Big Five, particularly concerning the variables of Nervousness and Anxiety (2010).

Additional constructs such as emotion regulation, emotional congruence, and social

perceptiveness have also been described as being similar in nature to the emotional intelligence

construct. Emotional congruence is defined as “the similarity between the perceived affective

quality of a stimulus for the subject and the perceived affective quality of the stimulus for most

other people” (Barchard & Hakstian, 2004, p. 453). Barchard and Hakstian found significant

correlations between some of the subtests on the Mayer-Salovey-Caruso Emotional Intelligence

Test (MSCEIT) and emotional congruence (2004). For example, on the Emotion Management

22

subtest of the MSCEIT and emotional congruence, r = .46 and the Task item of Faces on the

MSCEIT and emotional congruence, r = .22 (2004). The possible correlations may be related to

the fact that emotional congruence and MSECEIT scores often use the consensus method of

scoring (Barchard & Hakstian, 2004).

Concerning the construct of self-esteem, Ciarrochi, Chan, and Caputi found significant

correlations with the Overall EI score of the Multi-Factor Emotional Intelligence Scale (MEIS),

the previous version of the MSCEIT, r = .31, at the P < 0.005 level (2000, p. 550). The authors,

therefore, have posed additional questions for future researchers concerning the underlying cause

for such correlations, and whether, for example, those who obtain lower emotional intelligence

scores exhibit lower self-esteem due to the inability to properly manage their emotions

(Ciarrochi, Chan, & Caputi, 2000).

Models of Emotional Intelligence

There are currently three primary types of models of emotional intelligence: mixed, trait,

and ability. Another quasi-model, the Integrative Model, focuses primarily on emotional

perception and understanding of emotions and serves as the basis for the ability-based, four-

branch model of Mayer and Salovey (Mayer, Robert, & Barsade, 2008). In summary, there are

two mixed-models of emotional intelligence, proposed by Bar-On and Goleman, one trait model

per Petrides and colleagues, and one ability-based model, proposed by Mayer and Salovey.

(Mayer, Salovey, & Caruso, 2000).

The following will review the Mayer and Salovey ability model of emotional intelligence

in detail since it will serve as the emotional intelligence model used in this study. The mixed and

23

trait models of emotional intelligence will be discussed only briefly to provide a more complete

overview of all of the currently existing models.

The ability model of emotional intelligence developed by Mayer and Salovey was based

upon their early conceptualizations of the construct and development of a theory in the 1990s.

Mayer and Salovey created their model with the belief that non-ability characteristics such as

general mood and the ability to manage stress, for example, should be evaluated separately from

true emotional characteristics or constructs (Woitaszewski & Aalsma, 2004). Mayer and Salovey

refined their initial concept of emotional intelligence into the following definition:

Emotional intelligence involves the ability to perceive accurately, appraise,

and express emotion; the ability to access and/or generate feelings when

they facilitate thought; the ability to understand emotion and emotional

knowledge; and the ability to regulate emotions to promote emotional and

intellectual growth (Mayer & Salovey, 1997, p.10).

Mayer and Salovey’s ability model has four branches, or abilities, that serve as the foundation

for the subscales within the model: perceiving emotions, facilitating thought, understanding

emotions, and managing emotions (Mayer & Salovey, 1997; Mayer, Robert, & Barsade, 2008;

Mayer, Salovey, & Caruso, in ed. Sternberg, 2000a). The four branches may be more specifically

defined in the following manner:

1. Perceiving emotions: the ability to identify emotions in oneself and others

through facial expressions, pictures, and voices. This branch serves as the

foundation for being emotionally intelligent in the other three branches.

24

2. Facilitating thought (or using emotions): the ability to employ one’s emotions

in cognitive activities such as thinking and problem solving.

3. Understanding emotions: the ability to comprehend the meaning of emotions

and relationships among various emotions.

4. Managing emotions: the ability to control emotions in oneself and others.

(Mayer & Salovey, 1997; Mayer, Robert, & Barsade, 2008; Mayer, Salovey, & Caruso,

2000).

The ability model of emotional intelligence proposed by Mayer and his colleagues has

typically been held in higher regard for use in academic institutions than the mixed models due

to its cognitive focus and ability-based, versus self-report, status. Furthermore, the ability

model/theory of emotional intelligence defines the measurement and assessment of emotions in

terms of one’s ability to carry out abstract reasoning and the ability to think through complex,

cognitive problems while properly employing emotions (Mayer, Caruso, & Salovey, 2003).

Mixed and Trait Models of Emotional Intelligence

Mixed Models. The mixed models of emotional intelligence incorporate the evaluation

of non-cognitive capabilities, emotionally and socially intelligent behaviors, and personality

through the analysis of test items on non-ability scales such as happiness, stress tolerance, self-

regard, adaptability, and social competence (Mayer, Robert, & Barsade, 2008).

The first mixed-model of emotional intelligence developed, by Dr. Reuven Bar-On, was

based on over 20 years of research in the field of social and emotional competencies. Bar-On’s

model of emotional intelligence is similar to the model developed by Goleman in that Bar-On

25

includes several personality and social characteristics such as interpersonal skills, mood, and

stress-management as a basis for the assessment and understanding of one’s emotional

intelligence (Woitaszewski & Aalsma, 2004; Mayer, Robert, & Barsade, 2008).

The second mixed-model of emotional intelligence is proposed by Goleman. Goleman’s

model of emotional intelligence was popularized through his authorship of a book, Emotional

Intelligence, based on the work done by Salovey and Mayer. The premise of Goleman’s model

states that in the mature adult there are two forms of intelligence: The first form of intelligence is

an individual’s Intelligence Quotient (IQ), a genetic given that contributes only 20 percent to

success in life (Goleman, 1997). The second is emotional intelligence. According to Goleman,

emotional intelligence is defined as “self-control, zeal and persistence, and the ability to motivate

oneself and persist in the face of frustrations” (Goleman, 1997, p. xii). Goleman maintains that

biology and culture can play a significant part in how people deal with their emotions since some

temperaments are biologically inherited and culturally influenced by parents. Goleman also

believes that there are two minds at work in the human body: the emotional mind and the rational

mind and that there is a constant struggle between the two in order to maintain control of one’s

emotions. Goleman argues that being able to control one’s emotions leads to more rational and

intelligent decisions.

Goleman’s conclusions emphasize the benefits of educating adults and children when it

comes to comprehending and dealing with their emotions. The key to emotional intelligence and

to managing one’s emotions is self-awareness, or the ability to recognize a feeling as it is

26

occurring. The ability to manage emotions, handle relationships, and recognize emotions in

others builds upon a developed sense of self-awareness (Goleman, 1997).

Several scholars offer criticism of the mixed-models, particularly Goleman’s model

(Mayer, Salovey, & Caruso, 2000). The belief is that the claims made by Goleman are quite

inflated regarding the predictive validity of emotional intelligence, stating that success in

academics and life is correlated at levels as high as r = .45 (Mayer, Salovey, & Caruso, 2000).

Trait Model. Lastly, the trait model of emotional intelligence was developed by Petrides

and her colleagues in the belief that there is a distinction to be made between being emotionally

intelligent and possessing personality traits that may lead to emotional perceptions about one’s

environment. Trait emotional intelligence, (TEI), is defined as a “constellation of behavioral

dispositions and self-perceptions concerning one’s ability to recognize, process, and employ

emotion-laden information” (Petrides, Frederickson, & Furnham, 2004, p.278). The trait

emotional intelligence model states that emotional intelligence is a personality trait that only

some people possess (Petrides & Furnham, 2001). Furthermore, trait emotional intelligence is

often viewed as self-efficacy, or the belief in oneself (Petrides, Frederickson, & Furnham, 2004).

Trait emotional intelligence is typically assessed using the Trait Emotional Intelligence

Questionnaire (TEIQue). The TEIQue is a 153 item test that “yields scores on 15 distinct facets,

four factors, and global trait emotional intelligence” (Vernon, Petrides, Bratko, & Schermer,

2008, p. 636).

The framework that is proposed by the trait model is in opposition to the MSCEIT ability

model and shares some similarities with Goleman’s model. The majority of the research

27

concerning trait emotional intelligence has sought to analyze how it predicts variance beyond the

Big Five Personality Traits (Vernon et al., 2008).

Two separate studies, one involving monozygotic twins, conducted by Vernon et al.

investigated the relationship between Trait EI (as measured by the TEIQue) and heritability.

Their findings suggested that the existence of genetic influences will cause one to have a higher

or lower Trait EI score; and that the trait emotional intelligence of a parent has an extensive

impact upon the trait emotional intelligence of offspring (Vernon et al., 2008). Because the

results of their study suggested that emotional intelligence was best considered to be a

personality trait, it is important to note that such a conclusion is in direct opposition to the view

of Ability EI as proposed by Mayer, Salovey, and Caruso’s model.

Table 2 provides an overview of some of the constructs that are commonly associated with the

ability and trait models.

28

Table 2

Constructs commonly described as related to Ability EI and Trait EI

__________________________________________________________________

Abilities (Ability EI) Personality Traits (Trait EI)

Perception of emotions in the self Attending to emotions

Perception of emotions in others Assertiveness

Perception of emotions in objects Emotional expressivity

Managing emotions in the self Impulse control

Managing emotions in others Motivation

Understanding emotions Optimism

Social competence Responsive distress

Emotional integration Self-esteem

Stress management

______________________________________________________________

(Adapted from The Nature and Measurement of Emotional Intelligence Abilities: Basic

Dimensions and their Relationships with other Cognitive Ability and Personality Variables,

Barchard & Hakstian, 2004).

While each of the models has a different view, theory, and associated assessment, all of

the models are grounded in the belief that emotional intelligence is associated with being able to

recognize emotions in oneself and others and to in turn regulate actions based upon this

recognition and understanding.

The Evaluation of Emotional Intelligence Abilities: Assessments

There are several assessments that scholars have developed to evaluate the emotional and

general intelligence of a given individual, or in some instances, a group of individuals. The early

emotional intelligence assessments consisted of essentially three different approaches: self-report

tests that employed the use of Likert-type scales to evaluate characteristics such as patience,

tolerance of stress, and relationship management; reports made by others, typically in the

29

workplace, with direct report, fellow employee, and management feedback (360 degree

assessments); and ability-based tests such as the Mayer-Salovey-Caruso Emotional Intelligence

Test , or MSCEIT (Salovey & Grewal, 2005).

Such assessments eventually evolved into various formats based upon the predominant

models of emotional intelligence: Mayer and Salovey’s ability, or cognitive-based assessment,

Bar-On’s and Goleman’s mixed models and related assessments, and the Trait Emotional

Intelligence Questionnaire (TEIQue) (Mayer, Salovey, & Caruso, 2000; Petrides & Furnham,

2001).

For the purposes of this study, the ability-based, Mayer-Salovey-Caruso Emotional

Intelligence Test (MSCEIT) has been selected and will therefore be reviewed in the paragraphs

that follow.

The Mayer-Salovey-Caruso- Emotional Intelligence Test (MSCEIT)

The Multifactor Emotional Intelligence Scale (MEIS), the predecessor to the Mayer-

Salovey-Caruso- Emotional Intelligence Test (MSCEIT), was first developed in the mid 1990s

by the team of Mayer, Salovey, and Caruso as an ability and cognitive-based measure of

emotional intelligence. The MEIS consisted of eight separate tasks and subtests that

corresponded to the four branches: Perceiving Emotions, Assimilating Emotions, Understanding

Emotions, and Managing Emotions defined within the four branches of the ability model of

emotional intelligence. In 2002, the MEIS was refined and pared down from a cumbersome 400-

plus questions and evolved into the current assessment as it is used today (Woitaszewski &

Aalsma, 2004; Mayer, et al., 2003).

30

The current MSCEIT format is composed of 141 questions and can be administered to

individuals or in a group setting, via paper or on-line via the Internet. The MSCEIT can be given

to those persons ages 17 and older and can be completed in approximately 45 minutes, although

there is no specified time limit. The MSCEIT assessment yields an overall emotional intelligence

score, two area scores, and four branch scores grounded within individual branches set forth in

the ability model. Either Consensus or Expert scoring may be utilized on the MSCEIT. The

Consensus scoring method is the scoring that is generally recommended and compares an

individual’s performance to the 5,000 people in the normative database used in the

standardization of the MSCEIT. The Expert scoring method evolved through research conducted

with a sample of 21 panel members of the International Society for Research on Emotions

(ISRE) (Mayer et al., 2002; Mayer et al., 2003).

The MSCEIT exhibits structural and predictive validity as examined by the authors

through an extensive literature review. Content validity is also demonstrated, and therefore, it is

proposed that the MSCEIT measures those aspects of emotional intelligence that it sets out to

measure. Furthermore, test-retest reliability is .86 based on a sample of 62 people (Mayer et al.,

2002; Mayer et al., 2003). The particular aspects and more detailed psychometrics of the

MSCEIT assessment will be discussed in Chapter Three.

Some Studies and Criticisms of Emotional Intelligence using the MSCEIT. There is a

significant amount of literature concerning the use of the Mayer, Salovey, and Caruso ability

model of emotional intelligence and its associated assessment, the Mayer-Salovey-Caruso

Emotional Intelligence Test (MSCEIT). The MSCEIT appears to have escaped some of the more

31

scathing criticisms of the mixed emotional intelligence models and has received support as a

reliable measure of emotional intelligence, particularly when concerned with the measurement of

EI as a cognitive ability (Schutte, Malouff, Hall, Haggerty, & Cooper, et al., 1998; O’Connor &

Little, 2003). Overall, much of the literature has focused on the validity and reliability of the

MSCEIT assessment along with a search for a more precise definition of the emotional

intelligence construct. Other authors have conducted research using the MSCEIT, or another

emotional intelligence assessment, within academic samples to determine if there are correlations

between emotional intelligence attributes and academic success, grade point average, and social

success, for example (Evenson, 2007; Wraight, 2006). A sampling of the more prominent

research encountered while reviewing the literature is discussed in the paragraphs that follow.

Validity Studies of the MSCEIT. Several studies concerning the Mayer-Salovey-Caruso

Emotional Intelligence Test are concerned with the definition of the emotional intelligence

construct and validity evidence. It has been questioned throughout various studies as to whether

the emotional intelligence construct is truly a measure that can stand as a separate entity in the

assessment of intelligence.

Schulze, Roberts, O’Brien, MacCann, Reid, and Maul, (2006) conducted a study that

compared the MSCEIT to the constructs of crystallized (Gc) and fluid intelligence (Gf), two

components of general intelligence often used to assess general IQ. The theory of fluid and

crystallized intelligence was developed by Raymond Cattell in the 1950s and 1960s. Fluid

intelligence may be briefly defined as being able to solve problems, learn, and recognize

32

patterns. Crystallized intelligence relies upon the ability to use previously acquired knowledge

(Horn & Cattell, 1966).

In the study conducted by Schulze et al., 2006, the following hypotheses were tested

concerning the MSCEIT and possible relationships with crystallized and fluid intelligence: What

is the MSCEIT measuring – emotional processes and/or components; and, can emotional

intelligence, as measured by the MSCEIT, be considered a separate form of intelligence? The

study utilized a sample of 138 undergraduate, psychology students from the University of

Sydney. The authors had participants complete the MSCEIT and the Japanese and Caucasian

Brief Affect Recognition Test (JACBART) assessments to measure emotional intelligence and

several, additional cognitive assessments to measure general intelligence (Matsumoto & Ekman,

2000).

The analysis of the descriptive statistics found means similar to those posited by the

authors of the MSCEIT in their 2002 study (Schulze et al., 2006). Through the evaluation of

exploratory and confirmatory factor analyses, Schulze et al. found that the third branch,

Understanding Emotions, of the Mayer, Salovey, and Caruso model is related to intelligence

factors. Furthermore, the authors concluded that there is a slight relationship between the

Strategic emotional intelligence are score, as measured within the MSCEIT, and Intelligence, as

measured by Gc and Gf. The authors therefore concluded that the MSCEIT does demonstrate

some of the required criteria as posited by academic researchers to be considered an intelligence.

However, overall, there were only small to medium inter-correlations (r = .17, p < .05) found

33

among the branches of the MSCEIT and the other assessments used in the study (Schulze et al.,

2006).

In conclusion, Schulze et al. provide mixed empirical support for the two-area/four-

branch model of EI and state that the overall validity of the MSCEIT as an ability measure is still

in question and warrants further investigation by researchers. There appear to be some significant

relationships with other measures of emotional and general, or cognitive, intelligence, thus

demonstrating validity evidence of the MSCEIT. However, the authors have made

recommendations that future research examine in more detail the sub-scales outside of the

Strategic Area Scores (Schulze et al., 2006).

Pfeiffer MSCEIT study. In contrast, a study conducted by Pfeiffer (2001), provides a

strong grounding and support for the MSCEIT as a measure of intelligence, particularly when

used within academic settings, but follows in proposing that additional research needs to be

conducted concerning the conceptual issues associated with the measurement of emotional

intelligence in general. Pfeiffer, like Schulz, Roberts, O’Brien, MacCann, Reid, & Maul, 2006,

also concedes that a possible relationship exists between emotional intelligence and other forms

of intelligence, such as crystallized and fluid.

Schulte, Ree, and Carretta MSCEIT Study. In 2004, Schulte, Ree, and Carretta

conducted a study to analyze the emotional intelligence construct within the context of human

performance, personality, and ability. The authors analyzed the construct validity of emotional

intelligence by reviewing possible, existing relationships among general cognitive ability or

intelligence (g) as measured by two assessments: the Wonderlic Personnel Test (WPT)

34

(Wonderlic, 2007), a brief, timed, 50-question assessment often used in the workplace with

prospective employees and the Big Five personality dimensions as measured by the NEO-Five-

Factor Inventory (NEO-FFI) (Costa & McCrae, 1992).

The NEO-FFI is a commonly-used assessment that measures five personality dimensions.

The first personality dimension is that of Neuroticism (N), or the degree to which one

experiences feelings of anxiousness, depression, and impulsiveness. A lower score on (N)

demonstrates a higher level of emotional stability. The second dimension is Extraversion (E)

which is measured by the level of activity, sociability, and positive emotions. The third

dimension is Openness to Experience (O) and is comprised of traits such as imagination and

intellectual independence. The fourth dimension is Agreeableness (A) and measures how

compliant, trusting, and modest one is. The last and fifth dimension is Conscientiousness (C)

which is measured by the degree of competence, dutifulness, and self-discipline one possesses

(Costa & McCrae, 1992; Schulte, Ree, & Carretta, 2004).

The study utilized a sample of 102 individuals from two small colleges, and administered

the Wonderlic Personnel Test (WPT) to measure g, the NEO Five-Factor Inventory, and the

MSCEIT to measure emotional intelligence. The authors used a regression model for their

statistical analyses and found a R of 0.617 between the Agreeableness (A) construct as measured

by the NEO-FFI and emotional intelligence as measured by the MSCEIT. In addition, a

correlation of r = 0.454 was observed between the scores on the WPT and the MSCEIT. Given

the results of the study, the authors made recommendations that future research further evaluate

35

the construct validity of emotional intelligence, specifically as measured by the MSCEIT

(Schulte, Ree, & Carretta, 2004).

Leung et al. MSCEIT Study. Leung, Meier, and Cook Cottone (2002) proposed that

overall, the MSCEIT is a solid instrument and ability measure of emotional intelligence with a

strong theoretical grounding. The researchers state that additional distinctions need to be made

between the two scoring methods: expert and consensus scoring. Furthermore, a statistical

analysis needs to be conducted to evaluate the potential for racial bias. It appears in some

instances that the questions on the branches of the MSCEIT may be biased against non-whites

(Leung et al, 2002).

The History of General (Cognitive) Intelligence, Definitions of the Construct, and Theories

History and Beginnings

The study of general, or cognitive, intelligence has been in existence for many centuries.

The initial roots of study can be traced back to the seventeenth century and possibly earlier.

Aristotle proposed that intelligence was rooted in one’s biological nature and that greater

knowledge was mainly acquired through the five senses (Brody, 2000). Galton conducted studies

that furthered an understanding of the role that heredity plays in intellectual growth (Simonton,

2003).

There have been many schools of thought and influences on the study of intelligence. The

study of general intelligence acquired popularity during the 1800s when research and empirical

studies became abundant. In recent years, the study of general intelligence has focused more on

36

understanding multiple intelligences in light of advances in biology, genetics, and neuroscience

(Plucker, 2003).

Table 3 presents an overview of some of the most prominent philosophers and researchers who

have contributed to the study of intelligence throughout the years.

Table 3

Historical Overview of the Influences on the Development of Intelligence

Historical Foundations Plato Aristotle Smith Kant (to 1690) Pascal Hobbes Huarte

Augustine Aquinas Itard

Modern Foundations Darwin Charcot Galton

(to 1869)

The Great Schools Binet Stern Simon Piaget

(to 1901) Thorndike Vygotsky Pearson Spearman

Contemporary Burt Guilford Thurstone

Explorations

(to 1969)

Current Efforts Sternberg Gardner Simonton Jensen

(Adapted from Human intelligence: Historical influences, current controversies, teaching

resources Plucker, 2003).

For example, in the fields of education and psychology, some of the most profound and

important contributions concerning the development of intelligence and human development are

from Jean Piaget.

The work of Piaget has a long-standing history in the fields of education and human

development. Piaget defined intelligence as

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Intelligence is assimilation to the extent that it incorporates all the

given data of experience within its framework…There can be no doubt

either, that mental life is also accommodation to the environment.

Assimilation can never be pure because by incorporating new elements

into its earlier schemata the intelligence constantly modifies the latter in

order to adjust them to new elements" (Piaget, 1963, p. 6-7).

Piaget helped establish and refine the literature around how children grow and develop

intellectually through four stages: Sensorimotor, Preoperational, Concrete, and Formal

Operations. Further, Piaget developed the concepts of assimilation, accommodation, and the

schema to explain how children deal with new information they encounter (Piaget, 1963).

Other concepts and theories of intelligence evolved from Piaget’s work in the

development of intelligence including Vygotsky’s sociocultural-historical theory and the

information processing theory. Such theories aided scholars in the further refinement of the

general intelligence construct and associated assessments and experiments.

The General (Cognitive) Intelligence Construct or Intelligence Quotient (IQ)

The construct of general intelligence has proven since its initial inception to be extremely

difficult to define in a concise manner. Many of the existing academic definitions have evolved

from the development and use of psychometric assessments of intelligence. The true definition of

the general intelligence construct is often considered to be dependent upon the context in which

it operates. An overall definition of general intelligence consists of the ability to learn and pose,

recognize, and solve problems within a given context. Gardner & Gottfredson define general

intelligence as “the ability to acquire basic knowledge and use it in novel situations given that

people are born with a fixed, potential intelligence, and general intelligence can be measured”

38

(Gottfredson, 1998). Thurstone defines general intelligence as “a mental trait, the capacity to

make impulses focal, at their early, unfinished stage of formation. Intelligence is therefore the

capacity for abstraction, which is an inhibitory process” (Thurstone, 1924/1973).

General (Cognitive) Intelligence Theories

Several significant theories of general intelligence have emerged throughout the last

century. In its earliest years, the development of a theory and model of general (cognitive)

intelligence was a sort of geographic mapping of the brain by F.G. Gall. At the beginning of the

20th century, psychologists viewed this literal mapping in a more abstract manner and searched

for statistics that would aid them in furthering their understandings of intelligence (Sternberg,

1985; Brody, 2000).

Spearman’s g. The general cognitive factor, g, was developed by Spearman in 1904, and

may be defined as “a two-factor theory of intelligence in which performance is determined by a

general factor, g, a universal due to a person’s general intelligence, and a specific factor, s, due to

a unique ability or activity related to a particular test” (Embretson & Schmidt McCollam, 2000,

p. 424). Before Spearman’s research came into play, actual theories of general intelligence were

limited in scope and nature. Spearman proposed that “intelligence could be understood in terms

of a single latent factor that pervaded performance on tests of mental ability and a set of specific

factors…and the general factor, g, provided the key to understanding intelligence (Sternberg,

1985, p.1113). Spearman believed that in each cognitive, or intellectual, undertaking that both

factors would always be in existence, however, the relative weights associated with each would

39

vary depending upon the activity at hand (Sternberg, 2000a; Embretson & Schmidt McCollam,

2000; Spearman, 1904, 1927).

During the 1930s, Thurstone developed a theory of general intelligence quite different

from that of Spearman. Thurstone’s Theory of Primary Mental Abilities was developed from his

advanced factor analytic techniques in which he was able to ascertain the number of latent

constructs when observing a variable set. He proposed that general intelligence in no way

consisted of a single factor, g, and that Spearman’s single factor was simply a result of his

statistical analysis using a less sophisticated version of factor analysis (Thurstone, 1924/1973;

1931).

Thurstone’s Primary Mental Abilities. Thurstone’s Theory of Primary Mental Abilities

maintains that there are seven independent factors, versus a single g, that contribute to general

intelligence: verbal comprehension, number facility, spatial reasoning, memory, and deductive

and inductive abilities (Brody, 2000; Thurstone, 1931; Guilford, 1972). It is of interest to note

that Thurstone conducted studies with samples of both adults and children and obtained findings

in contradiction to one another. In his studies with adult samples of fairly similar general

intelligence, he found evidence of differences on his seven independent factors which supported

his theory and further disputed Spearman’s theory. However, when the same study was

conducted using a sample of children, results showed that his proposed primary abilities were not

separate and actually supported Spearman’s theory (Ruzgis, 1994).

Cattel & Horn’s Gf/Gc Theory. The theory of fluid and crystallized intelligence was

developed by Cattell and Horn. Fluid intelligence (Gf) may be briefly defined as being able to

40

solve problems, learn, and recognize patterns. Crystallized intelligence (Gc) relies upon the

ability to use previously acquired knowledge (Horn & Cattell, 1966). The initial theory was

based upon Spearman’s theory of g and was used to evaluate the development of intelligence in

children and adults. Cattell and Horn proposed that the development of fluid intelligence

continued to grow through adolescence at which point it then began to decline. Crystallized

intelligence, on the other hand, is acquired more slowly over time and then declines in late life

(Horn & Cattell, 1966).

The work of Thurstone, Spearman, and Horn and Cattell helped lay the foundation for

theories of intelligence that have since been developed including those of Gardner (Multiple

Intelligences) and Sternberg (Triarchic Theory) with less of a focus on the standardized testing of

intelligence and more of a focus on individual ability through various assessment.

The Evaluation of General (Cognitive) Intelligence Abilities (IQ Tests and Assessments)

One of the first general intelligence measures to use statistics was developed by Sir

Francis Galton. Galton took the ideas of Charles Darwin and the statistical work from the

Belgian statistician, Quetelet, and combined them into a book concerning human differences and

intelligence. He then established a laboratory in the South Kensington Museum of London in

1882 where he conducted some of the very first mental intelligence tests (Brody, 2000).

In the late 1800s, James McKeen Cattell published a paper called “Mental Tests and

Measurements” (Brody, 2000). In this paper, Cattell described a number of psychological

abilities and possible ways to measure these abilities. After the publication of Cattell’s research,

41

several psychologists began in earnest to develop batteries of tests to assess group and individual

intelligence based upon cognitive abilities (Brody, 2000).

Stanford-Binet Intelligence Quotient Test

Two research projects made a significant and lasting contribution to the study of mental

intelligence in the early 1900s. In 1905, Alfred Binet and his colleague, Theodore Simon,

developed the Intelligence Quotient (IQ) instrument in order to examine what intellectual skills

were needed by students to excel in a French school classroom. The IQ instrument initially

consisted of 58 tests and assisted the evaluator in determining a mental age for a student. The

instrument was given the name of the IQ test, as it is known today, after it was revised in the

United States at Stanford University. The results of this revision produced the Stanford-Binet IQ

test. The formula for the commonly used Stanford-Binet IQ test is as follows:

Intelligence Quotient = Mental Age/Chronological Age x 100

Intelligence Quotient scores all have statistical characteristics, and the average score for

any given individual is 100. Approximately 50% of individuals from the general population will

score between 100 and above, and 85% will score between 85 and 115 (Brody, 2000). The scores

from a large population generally form a normal, bell-shaped curve with a center, or mean value

of 100, and standard deviations of 15, although these statistics could vary depending upon the

population tested and the assessment utilized (Brody, 2000).

Other General Intelligence Tests

In addition to the Stanford-Binet Intelligence Quotient, a multitude of theoretically based

assessments have been scientifically developed to measure general (cognitive) intelligence. The

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First World War had a tremendous influence upon this initiative, both positive and negative, on

the development of IQ testing within the United States. On the positive side was the work of the

President of the American Psychological Association, Robert Yerkes, and the development of the

first group IQ tests: the Army Alpha and Army Beta (Kaufman, 2000). On a more negative note,

after the conclusion of World War I, these same IQ tests were often used to screen and limit the

access of immigrants entering the United States, a purpose in complete contradiction to the initial

intent of the researchers who had developed the tests (Kaufman, 2000).

Shortly thereafter, researchers began evaluating various contexts and developing methods

for what would constitute the practical applications of intelligence testing, and thus began

analyzing large samples of both adults and children. The result of such studies was the

development of additional tests of intelligence, utilizing more sound and ethical standards,

including the widely-used Wechsler Intelligence Scales (WISC) for children and adults

(Wechsler, 1949). While there exists a quantifiable number of assessments in the area of general

intelligence testing, for the purposes of this study, the General Ability Measure for Adults

(GAMA) (Naglieri & Bardos, 1997) will be utilized. The psychometrics of the GAMA

assessment are described briefly in the paragraphs that follow and in comprehensive detail in

Chapter Three.

The General Ability Measure for Adults (GAMA)

The General Ability Measure for Adults (GAMA) (Naglieri & Bardos, 1997) is a self-

administered test of general intelligence for adults that are 18 years of age or older. It may be

administered either via paper or on-line via the Internet. The GAMA was developed by the team

43

of Naglieri and Bardos. The assessment provides an overall intelligence score based upon the

scores of four subtest scales: Matching, Analogies, Sequences, and Construction. It is proposed

that the score provides an overall view of general cognitive ability and is equivalent in nature to

other assessments of general intelligence, or IQ tests (Bracken & Naglieri, 2003).

The General Ability Measure for Adults (GAMA) was normed on a sample size of 2,360

adults from the general population. The sample was further stratified into subsets by: age,

gender, race/ethnicity, and geographic location. A bias-check was completed using the Mantel-

Haenszel statistical procedure to ensure there would be limited bias in the individual test items.

The Mantel-Haenszel test checks the strength of association between variables and was used

during the standardization of the GAMA to check for potential bias against certain age and

ethnic groups. Reliability is reported within a range from 0.74 to 0.94 across the stratified age

groups. In addition, test-retest reliability is 0.67 based on a two to six week interval (Bracken &

Naglieri, in ed., Reynolds & Kamphaus, 2003). Additional psychometrics and a more detailed

description of the GAMA assessment will be provided in Chapter Three.

Some Studies and Criticisms of the General Ability Measure for Adults (GAMA)

There are a few criticisms that exist concerning the General Ability Measure for Adults

(GAMA). The majority of the proposed issues are concerned with whether the assessment can be

considered a true test of overall general ability. Conflicting findings in the literature have

indicated that the GAMA is perhaps more appropriately used in the measure of visual and

perceptual skills than as a general measurement of intelligence given its non-verbal, graphical,

questioning technique (Lassiter, Bell, Hutchinson, & Matthews, 2001).

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In general, the existing research concerning the GAMA has revolved around the

comparison of the assessment to other intelligence measures. However, the majority of these

studies have not been concerned with the traditional college student population age group of 18-

24 years (Lassiter et al., 2001). Psychometric studies of the GAMA instrument are few in

number, and prior to the study by Lassiter, Bell, Hutchinson, and Matthews, only two previous

validity studies of the test had ever been conducted (Lassiter et al., 2001).

GAMA standardization study. Only one study concerning concurrent validity was

conducted during the standardization of the GAMA. Using a sample of 194 adults (age range 25-

74, M = 49), the GAMA was compared to three subscales on the Wechsler Adult Intelligence

Scale (WAIS-R or WAIS III): the Verbal IQ (VIQ), Performance IQ (PIQ), and Full Scale IQ

(FSIQ) (Wechsler, 1949). When comparing scores on the four subscales (Matching, Sequences,

Analogies, and Construction) of the GAMA, and Verbal IQ (VIQ), Performance IQ (PIQ), and

Full Scale IQ, of the WAIS III, the following correlations were found: .65, .74, and .75. Based

upon these findings, the authors of the GAMA, Naglieri and Bardos, proposed that the GAMA

could be considered a general cognitive ability measure. The statistical comparison with an

existing, well-established measure of cognitive intelligence provided credibility to the proposed

argument for the concurrent validity of the GAMA (Lassiter et al., 2001).

To further substantiate their findings, Naglieri and Bardos conducted a study that

correlated scores on the GAMA with the Wonderlic Personnel Test (WPT), and the Shipley

Institute of Living Scale (SILS) with a sample of 80 adults, ages 25-45. The WPT is a brief,

timed, 50-question assessment often used in the workplace with prospective employees and the

45

SILS is a 60-question, verbal and abstract thinking assessment often used in clinical domains

(Wonderlic, 2007; Shipley, 1940). Once again, the authors of the GAMA found significant

correlations between the GAMA IQ score and the Shipley and Wonderlic IQ scores (r = .70).

These results also led the authors of the GAMA to propose that the assessment is related to

school activities such as vocabulary and mathematical ability, and consequently, academic

achievement (Lassiter et al., 2001).

Lassiter et al. GAMA-WAIS study. Based upon the initial findings set forth in the

GAMA manual and literature, Lassiter, Bell, Hutchinson, and Matthews (2001) conducted a

second study to evaluate the concurrent validity of the GAMA and the third edition of the

Wechsler Adult Intelligence Scale (WAIS – III) within a sample of 60 college students (50 male,

10 female; age range: 18-47, M = 21, SD = 5). This age group had not previously been evaluated

in validity studies using the two aforementioned assessments. The study was initiated in response

to substantial conflicting results described in the various literature concerning the GAMA’s

concurrent validity. The sample of 60 students was completed both the GAMA and the WAIS –

III assessments, and mean scores on the two assessments were compared. Results indicated that

in contrast to Naglieri and Bardos’ initial findings that the GAMA acts as an overall assessment

of IQ, the stronger correlations actually exist in only subsets of the GAMA and verbal and

performance IQ (as measured by the WAIS-III). The association was much stronger between the

WAIS Performance IQ (PIQ) scores and the overall GAMA IQ scores. The relationship

exhibited between the Verbal IQ (VIQ) scores and the overall score on the GAMA was much

lower than originally stated by Naglieri and Bardos. Lassiter et al. stated that “if the GAMA

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provides a nonverbal means to assess general intelligence, as suggested by Naglieri and Bardos

(1997), then the GAMA should show a similar association with both VIQ and PIQ constructs”

(Lassiter et al., p. 6, 2001). Lassiter et al. concluded that the GAMA has a strong association

with organizational skills used in perception, a known contributor to general knowledge and

intelligence. In conclusion, however, the findings from the two studies did not fully support the

validity studies previously conducted by the authors of the GAMA assessment.

Lassiter et al. GAMA-KAIT Study. In a second study conducted by Lassiter et al.

(2002), the GAMA was reviewed in comparison to the Kaufman Adolescent and Adult

Intelligence Test (KAIT) in a sample of 94 college-aged students (51 female, 43 male; age range

18 to 54; M = 27; SD = 7.97) to further examine concurrent validity. In brief, findings from this

research study indicated that the overall mean GAMA IQ score was similar to the KAIT mean IQ

scores for the sample of participants. This finding provided support for the GAMA as an overall

measure of general intelligence, for those of average ability, or those scoring typically in the

range of 85-115 on a general intelligence measure (Brody, 2000). In addition, a second aspect of

this study evaluated the GAMA IQ scores in comparison to the KAIT composite scores. Results

indicated that “performance on the GAMA is not strongly associated with comprehensive

knowledge, long-term retrieval, short-term memory, or auditory comprehension” (Lassiter et al.,

p. 504, 2002). However, additional findings of the above study do demonstrate that the GAMA

does assess fluid (.49) and crystallized (.35) intelligence capabilities, thus offering some support

for convergent validity, or the likelihood that the GAMA is theoretically related to, and assesses,

general intelligence or its components. The authors concluded that additional studies utilizing

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perhaps different assessments of intelligence, including those that use words and verbal

descriptions, in addition to pictures and diagrams, should be helpful in further evaluating the

overall usefulness of the GAMA as an assessment of general intelligence.

Gender and Emotional and General (Cognitive) Intelligence

The majority of the literature concerning emotional, social, and general intelligence

typically alludes to the role that gender plays in any given situation. In many cases, the opinions

and conclusions posited by the authors have been developed from a scientific point of view, but

popular literature and the press often distort such views and create negative stereotypes.

Gender and Emotional Intelligence

Concerning emotional intelligence, the stereotype that women are more emotionally

astute continues to exist (Salovey & Grewal, 2005). Research has suggested that females learn

how to develop their emotional competencies in early childhood well before males (Feldman

Barret, Lane, Sechrest, & Schwartz, 2000). Scientific studies have also demonstrated that the

brain mass and cerebral activity for those areas dedicated to emotions in humans is larger in

women than men (Baron-Cohen, 2003).

Many researchers believe that the role that the parents, or parent, plays in the life of the

young child has a significant impact on the development of emotions. For example, Scharfe

proposes that the role of the mother’s expressions varies towards male and female children;

mothers tend to show more positive expressivity towards their daughters than their sons. This

maternal expressivity shown in childhood continues to impact the child throughout life (Scharfe,

2000). Therefore, one of the implications of this expressivity is that females tend to grow up

48

being able to understand and read emotions in others, as well as express emotions, better than

males (Scharfe, 2000).

In the process of trying to ascertain whether true gender differences exist for the construct

of emotional intelligence, the type of assessment used, self-report or ability-based, may affect the

data obtained. Because self-report measures of emotional intelligence can be biased in general

since they are rely upon an individual’s self-interpretation of abilities, there may be a natural bias

towards one or the other sex given previous research concerning females. An ability-based

measure of emotional intelligence, such as the MSCEIT, is expected to provide a more objective

rendering of the data as related to gender (Mayer, 2001; Mayer, Salovey, & Caruso, 2000).

Previous studies, including one conducted by Petrides & her colleagues, have found that females

(mean = 88.4) tend to score higher on overall emotional intelligence scores than males (mean =

79.3) with a standardized mean difference of d = 0.58 (Petrides & Furnham, 2000).

Further, a study conducted by Castro-Johnson and Wang also found that women had

higher scores than men on overall emotional intelligence as measured by the MSCEIT within a

sample of first year students separated into two strata: Honors students (Female n = 156; Male n

= 144) and Non-Honors students (Female n = 145; Male n = 85). The researchers’ findings as

presented in detail for all MSCEIT branches and totals in Table 4, lends support to the existence

of significant differences for females and males concerning the emotional intelligence construct.

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Table 4

Means (Standard Deviations) for variables as a function of student group and gender

Honors Students Non-Honors Students Female (n = 156) Male (n = 144) Female (n = 145) Male (n = 85)

Total EI 104.55 (14.64) 96.88 (17.49) 99.44 (12.83) 95.37 (16.29)

Branch 1 105.91 (101.28) 101.28 (15.97) 100.85 (13.66) 101.99 (13.29)

Branch 2 101.84 (12.55) 96.61 (15.81) 99.97 (13.79) 96.57 (15.54)

Branch 3 106.42 (15.09) 100.90 (18.44) 100.93 (14.47) 95.14 (18.73)

Branch 4 101.94 (14.20) 94.33 (16.37) 99.09 (15.93) 94.71 (18.47

Area 1 104.91 (14.06) 98.48 (16.28) 100.18 (12.97) 98.99 (13.73)

Area 2 104.66 (15.13) 97.21 (18.05) 99.92 (15.49) 94.12 (19.56)

(Adapted from Emotional Intelligence and Academic Performance of College Honors and Non-

Honors Freshment, Castro-Johnson & Wang, 2003).

Lastly, in a study conducted by Brackett and Mayer to investigate the discriminant,

incremental, and convergent validity of the MSCEIT with two other emotional intelligence

assessments the authors found similar results regarding gender differences. The MSCEIT, an

ability-based assessment, was analyzed in comparison to the two mixed-model emotional

intelligence assessments: the Bar-On EQ-i and the Schutte et al, Self-report EI Test, or SREIT.

The authors found statistically significant gender differences, but only for the MSCEIT: females

(M = 105.13, SD = 11.09) versus the males at (M = 95.17, SD = 13.43) t (200) = -5.69, p < .001

(Brackett & Mayer, 2003, p. 1150).

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The literature has suggested that additional research needs to be conducted concerning

gender and emotional intelligence before any solid correlations, or conclusions, be established,

especially concerning the differences found when utilizing the MSCEIT, an ability-based

measure of emotional intelligence.

Gender and General Intelligence

There is limited evidence to suggest that one sex has a true advantage over another

concerning general or cognitive intelligence. Periodically, a controversial paper, book, or

comment will emerge, thus fueling the heated debate over female versus male intellectual

abilities. Scholarly research often follows and provides clarification, and thus establishes the fact

that while clear differences in the sexes may have existed in the past, they have since

disappeared among the sexes in general.

Some research has demonstrated that on average girls are better at using their verbal

skills from an early age versus boys (Fiveush, Brotman, Buckner, & Goodman, 2000). In

addition, the previously held notion that males are better in mathematics than females no longer

holds true, thanks to a 2008 study funded by the National Science Foundation (Hyde, Lindberg,

Linn, Ellis, & Williams, 2008). Other studies have indicated the existence of memory and spatial

differences in the sexes; that females are better able to maintain medium-long term memories

better than males (Lynn, 1999).

In regards to intelligence tests and IQ scores, no truly statistically significant

differences have been found between females and males. A few studies have indicated a possible

three to four point difference in favor of males over females, specifically on the Wechsler Adult

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Intelligence Scales (Lynn, 1999). Many tests of intelligence now control for possible differences

by assigning different weights to questions in order to provide a more accurate score and to limit

potential bias in questions (Jensen, 1980).

The effects of gender in emotional and general intelligence scores differ depending upon

the context and the type of assessment that are utilized. Gender is being included in the study at

hand for the following reasons. Firstly, given that there are reported gender differences on the

MSCEIT in the existing literature, it seems necessary to also see if these differences exist in the

proposed sample and to perhaps try to understand why such differences emerge. Secondly, some

of the literature concerning retention in higher education indicates that there are significant

differences between women and men: men are less likely to complete their college degree once

matriculated (Tinto, 1975). Lastly, given that gender bias has often been reported in ability

assessments, it will be important to have current findings at hand as researchers work toward the

elimination of testing bias in the future in yet to be developed assessments for emotional and

general intelligence.

Emotional and General (Cognitive) Intelligence and the Traditional College Student

The transition from high school to a traditional college environment can be very complex.

Research has demonstrated that students who have a positive first-year experience on campus are

more likely to persist and experience success throughout their college career (Tinto, 1975;

Schutz & DeCuir, 2002; Parker, Summerfeldt, Hogan, & Majeski, 2003). Further, researchers

have also found that an integral part of the integration into the college environment, and success

as an undergraduate within that environment, are dependent upon a student’s ability to manage

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social, emotional, and academic challenges that differ from prior experiences (Tinto, 1975;

Schutz & DeCuir, 2002). The number of stressors that a first-year student faces upon entry into a

higher education environment are numerous: new relationships with family members, existing

friends, and making new friends; learning to live in a different environment from the home in

which the student previously resided; and learning how to form successful study habits in a

completely new environment (Parker et al., 2003). Researchers have found that one of the

primary reasons that students leave an institution after, or prior to the completion of their first

year, tends to be due to the inability to handle such novel and complicated demands (Gerdes &

Mallinckrodt, 1994: Parker et al., 2003).

Over the years a number of variables have been studied in order to determine the

underlying cause of the unexplained variance between academic success in secondary education

(as measured by academic performance, grade point average, and standardized test results) and

post-secondary educational environments (Mayer & Salovey, 1997; Berger & Milem, 1999;

Parker et al., 2003).

Several studies have been conducted in the higher education environment to assess what

factors contribute to success for traditional, undergraduate college students. A study conducted

by Levitz and Noel demonstrated that there are a significant number of factors outside of

academic records, high school grade point averages, standardized test scores, and demographics

that affect matriculation and retention in a traditional undergraduate environment (1989).

Further, MacCann and Roberts found that the Third Branch, Understanding Emotions, of the

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Mayer, Salovey, Caruso ability model appeared to be a strong predictor of, and may have

implications for college success, particularly for college readiness courses (2008).

Academic Outcomes and Grade Point Average (GPA)

For many years, educators and researchers have suggested that academic performance is

best understood by the consideration of a combination of both cognitive and non-cognitive

abilities. Some research has indicated that the validity coefficients above general intelligence do

not surpass 0.60 which suggests that perhaps personality and/or emotional intelligence play a

role in academic achievement (Jensen, 1998). Further, a significant number of researchers have

suggested that emotional intelligence, not unlike the concept of social intelligence, is a

prominent factor in one’s success in academic settings (Mayer & Salovey, 1997).

Early studies, such as that conducted by Hogan and Weiss (1974) found that within a

sample of male undergraduate students that those who were high achievers differed from their

peers in that they could be “characterized by unusual conscientiousness, industry, and

dependability” (p. 148).

In another study Lam and Kirby found within a sample of 304 undergraduates (152 men

and 152 women), that results indicated that emotional intelligence did present an advantage when

working on cognitive tasks. More specifically, for their first hypothesis the authors found a

positive relationship as to whether emotional intelligence contributed to “cognitive-based

performance over and above the level attributable to general intelligence” (Lam & Kirby, 2002,

p. 138). The relationship was reported as R2 change = .034, F(2, 291) = 11.37, p<.001. For their

second hypothesis the authors also found a significant relationship: whether Branch 1 of the

54

MSCEIT (Perceiving Emotions) contributed to “cognitive-based performance over and above the

level attributable to general intelligence” (Lam & Kirby, 2002, p. 138). The relationship was

reported as R2 change = .074, F(2, 292) = 23.24, p<.001. The authors believed that even though

the relationships found were not large, the significance is still of importance to note. Further Lam

and Kirby proposed that the ability to avoid “guarding against distracting emotions” through

buffering and personal engagement assists one in performing complex cognitive tasks (Lam &

Kirby, 2002, p. 140).

Further evidence of support for emotional intelligence and its relationship with academic

achievement (operationalized as grade point average) is presented through a study conducted by

Castro-Johnson and Wang. In this study, a sample of 300 Honors students and 230 non-Honors

students within a first-year class were administered the Mayer-Salovey-Caruso Emotional

Intelligence Test (MSCEIT) in order to determine what effect was exhibited on first semester

college grade point averages. Other variables that were considered included High School GPA,

Scholastic Aptitude Test (SAT) Scores, and gender (Castro-Johnson & Wang, 2003).

After conducting correlational analyses, the authors found significant relationships for

four variables when considering the Honors sample and GPA. Most importantly as related to this

section of the literature review, Branch 2 scores (Facilitating Thought) of the MSCEIT and GPA

showed correlations as follows [r (168) = +.22)], Area 1 Scores (Experiential Emotional

Intelligence) [r (168) = +.16)], and Total MSCEIT Scores [r (165) = +.16)]. However, no

MSCEIT scores presented statistically significant correlations when analyzed for the non-Honors

sample subset. Therefore, the conclusions presented demonstrate that in cases of Honors students

55

it is quite likely that emotional intelligence may predict academic achievement as measured by

first-semester GPA (Castro-Johnson & Wang, 2003, p. 111).

On the other hand, a few studies have obtained contradictory results to those in the above

paragraphs. In research conducted by Barchard, the author took a sample of undergraduate

psychology students, (n=150; 94 women; mean age = 21.5 years), and using year-end grades as

the criterion, examined whether emotional intelligence could serve as a predictor of academic

achievement. The study found that only some measures of the emotional intelligence construct

predicted academic success. Each participant in the study completed 31 emotional intelligence

measures (assessments). One of the findings was that the measure of Verbal Ability, only one

component of emotional intelligence, had a significant correlation with academic success (r=.43),

when p is less than .01 (Barchard, 2003).

Further, in a study of college students that used both self-report (EQ-i) and ability

measures of emotional intelligence (MSCEIT), it was found that neither assessment proved to be

a solid predictor of academic achievement (operationalized as GPA). O’Connor and Little, like

Barchard, found that in a sample of 90 (37 females and 53 males) introductory psychology

students that both emotional intelligence assessments had limited predictive validity. The Total

MSCEIT score had no significant relationship with GPA; however, the subscale score for the

Understanding Emotions branch showed a significant correlation with GPA with r = 0.227, p <

0.05. This was the only significant correlation found between GPA and a measure of emotional

intelligence (O’Conner & Little, 2003; Barchard, 2003).

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Lastly, in a study conducted by Van Rooy and Viswesvaran it was found that emotional

intelligence only accounted for approximately 1% of the variance in academic performance. The

researchers only found correlations of .10 between emotional intelligence and academic

achievement (2004).

Scholarly research has continued to be conducted concerning the plausible correlations

between emotional intelligence and academic achievement. Findings have thus far indicated that

only some components of emotional intelligence are directly related to higher achievement,

however, the significance of these relationships is of importance for future researchers.

Controversial Issues

Because the proposed study utilizes both an emotional and a general (cognitive)

intelligence assessment, it is imperative to address the substantive controversies and criticisms

surrounding both constructs.

Emotional Intelligence

Much of the criticism of the emotional intelligence construct, and its associated theories

and assessments, is related to the difficulty in defining the construct and establishing it as a form

of intelligence, solidifying a theoretical base for the construct, and differentiating the construct

from personality or trait-based theories.

Several researchers have maintained that there is a tremendous absence of theoretical

clarity around the emotional intelligence construct. In order for a construct to be considered

valid, it should not exhibit overlap with other established scientific constructs. Critics have noted

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that emotional intelligence seems to overlap with other factors such as skills, attitudes, values,

various emotional states, and personality traits (Locke, 2005).

More specifically, much of this criticism is centered on the mixed model emotional

intelligence construct given that there appears to be a significant overlap with the Big Five

personality factor model and certain aspects of cognitive intelligence. Joseph and Newman state

that

there are two senses in which the term emotional intelligence has been

used: a) as a narrow, theoretically specified set of constructs pertaining to

the recognition and control of personal emotion (called ability-based EI),

and b) as an umbrella term for a broad array of constructs that are

connected by their nonredundancy with cognitive intelligence (called

mixed-based EI) (2010, p.55).

Upon conducting meta-analyses, the authors found very low correlations (as low as .12) among

emotional intelligence construct-method pairings (self-report/ability based) suggesting that the

two constructs are not measuring the same concept (Joseph & Newman, 2010).

In addition, Mayer et al. (2002) maintain that ability assessments, such as their Mayer-

Salovey-Caruso Emotional Intelligence Test (MSCEIT) is “measuring emotional intelligence as

a cognitive ability whereas self-report measures, such as the Bar-On EQ-I, are measuring

personality traits and characteristics” (O’Conner & Little, 2003).

The above research findings hold merit when reviewing a study that compared the

MSCEIT and the Self-Report Emotional Intelligence Scale (SREIS) in a sample of 233 and

found no correlation between the two assessments: r = -.03 on the subscale perceiving emotions;

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r = -.02 on the subscale using emotions; and r = .04 on the subscale managing emotions

(Waterhouse, 2006).

These studies have claimed that even among assessments that are developed to measure

the same construct, emotional intelligence, that there exists discrepancies particularly when

comparing an ability EI construct to a mixed-model or trait EI construct.

In contrast, in a study conducted by O’Connor and Little, the authors found correlations

between a mixed model of emotional intelligence, the Bar-on EQ-i, and the ability model as

measured by the MSCEIT. The total scores for both assessments correlated with one another at r

= 0.340; P < 0.01. In addition, the authors reported that all of the scale scores of the Bar-On EQ-i

were significantly related to the Total Score on the MSCEIT (O’Connor & Little, 2003).

Therefore, it likely stands that performance-based measures based on the ability model of

emotional intelligence are more likely to assess emotional intelligence as a construct separate

from other traits (Matthews, 2001). Further, if what Mayer et al. say holds true concerning their

ability model and associated assessment, the Mayer-Salovey-Caruso Emotional Intelligence Test,

versus the “other” mixed and trait models, then it would also hold true that there would be little

relationship between the two types of emotional intelligence constructs, thus aligning the above

research findings.

Another major criticism surrounding the construct of emotional intelligence is whether or

not it may actually be considered a separate intelligence by definition of the construct. On the

one hand, researchers such as Mayer, Salovey, and Caruso present evidence that their ability

model of emotional intelligence, along with its associated assessment, the Mayer-Salovey-

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Caruso Emotional Intelligence Test, is indeed a measure of intelligence and exhibits structural,

face, content, and construct validity (Mayer, Salovey, & Caruso, 2002).

On the other hand, the affirmations of Mayer et al., Goleman, and other proponents of the

emotional intelligence construct are in direct opposition to the views of Locke (2005) who

maintains that the construct of emotional intelligence would be better presented as a skill and

that the definition of emotional intelligence encompasses too many varied components and other

personality traits.

In addition, researchers have indicated that the emotional intelligence construct is not

clearly defined and cannot be considered a true, stand-alone, intelligence because it does not

clearly exhibit discriminant validity. Scarr states that “to call (EI) intelligence does not do justice

either to theories of intelligence or to the personality traits and special talents that lie beyond the

consensual definition of intelligence” (1989).

In a multivariate study conducted by Pelletteri (1999), there was a moderate correlation

between the MEIS (the previous version of the MSCEIT) and the Cattell Scale B (IQ) on the

16PF (Personality Factor) within a sample of 107 college students (r = .34, p < .05). Given such

a finding, it appears that there exists at least a minimal correlation with general intelligence

(Mayer, Salovey, & Caruso, 2002).

Additional criticisms of emotional intelligence have concerned controversy over where

the capacity for emotional intelligence resides in the brain. Shaw et al. have posited that the brain

function of emotional intelligence may not be able to be scientifically excluded from that of

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cognitive intelligence given some of the significant findings of the overlap between emotional

and general intelligence (Shaw et al., 2006; Schulte, Ree, & Carretta, 2004).

General (Cognitive) Intelligence

From the very first introduction of the construct into education and psychology, general

(cognitive) intelligence, and its associated tests and assessments, has proven to be controversial

in nature. Some of the most prevalent controversies as related to this study are addressed in the

following paragraphs.

The use of IQ tests within the classroom. One of the most important criticisms facing

the use of intelligence assessments, and standardized testing in general, is the impact upon the

individuals whom are tested. For example, general intelligence tests have faced criticism that the

results of such tests reduce the ability to demonstrate creativity and unfairly label and stratify by

race, gender, and socioeconomic class. Further, results of such assessments have typically shown

that minority and economically disadvantaged students obtain lower scores than their peers.

Because the results are often used for placement in honors and gifted programs, these students

may be excluded from programs for which they may otherwise be selected (Plucker, 1998).

Advocates for fair testing practices have endorsed the use of multidimensional approaches that

include not only intelligence assessments but an examination of other factors including

emotional and social intelligence capabilities and teacher and parent assessments (Plucker, 1998;

Gardner 1983).

The Flynn Effect. In recent years, the Flynn Effect has been reported when analyzing IQ

scores for various populations. Named for the researcher associated with the initial study, James

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R. Flynn, the Flynn Effect shows that since the beginning of the twentieth century, average IQ

scores, specifically those in the lower half of the curve, have been rising at approximately three

points per decade (Flynn 1999). Through his research, Flynn has proposed that there is

approximately a one standard deviation increase on the normal bell curve per generation in fluid

intelligence (Gf) ability (Flynn, 1987, 1999). Flynn’s hypothesis for this effect is that “IQ tests

do not measure intelligence but rather correlate with a weak causal link to intelligence” (Flynn,

1987). Flynn had initially hypothesized three possible explanations for the observed effect: test

sophistication and advances in development, sampling issues and other unobserved phenomena

(artifacts), and increases in actual intelligence (Flynn, 1987). Since Flynn’s initial hypothesis,

however, other researchers have proposed that perhaps the gains exhibited in IQ are related to

better nutrition, better education, societal changes, or years spent in formal education (Flynn,

1994; Neisser, 1998).

These findings may hold implications for the use and development of future general

intelligence and IQ assessments (Flynn, 1999). In addition, because the Flynn Effect has been

demonstrated predominantly through the use of non-verbal intelligence tests such as Raven’s

Progressive Matrices, it is important to note here that there may be a similar effect observed

through use of assessments such as the General Ability Measure for Adults.

Conclusions

The review of the literature demonstrates that there continues to exist a great deal of

interest in both emotional intelligence and general, or cognitive, intelligence. The construct of

emotional intelligence is less defined than that of general intelligence and appears to be more

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controversial in some aspects such as whether it may be considered a true intelligence and how it

should be utilized in work and educational settings. The construct of general intelligence has an

extensive history, and several well-established assessments are in use while new instruments are

continuously being developed.

While there has been a significant amount of research about both the emotional

intelligence and cognitive intelligence constructs in relation to academic success, grade point

average, grades, and test anxiety, there appears to be a significant gap in the literature relating

the two, and studying potential relationships between the two constructs, particularly for the

traditional college student population (Schutz & DeCuir, 2002). To date, there are no studies in

the literature that have directly compared the subscales of an ability-based emotional intelligence

test with a non-verbal general (cognitive) intelligence test within a sample of undergraduate

college students. This study will address this gap in the existing literature.

Further, the existing research has demonstrated that there are often distinct relationships

between cognitive ability, often measured by academic success or overall grade point average,

and being able to manage one’s emotions on college campuses, both inside and outside of the

classroom. Existing studies concerning students within higher education have indicated that

emotional management plays an integral role in daily educational activities, self-regulation, and

the establishment of goals, particularly for first-year college students (Barchard, 2003; Evenson,

2007). The higher education environment often proves to be too challenging for students that

exhibit difficulty in the management of their emotions and may therefore lead to a higher risk of

failure or drop-out. It is hypothesized that emotional intelligence can assist students in facing

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both academic and non-academic challenges on a college or university campus. In addition,

administrators and campus leaders realize that assisting students with their transition and success

within the college environment often holds promise for students as campus and future workplace

leaders (Schutz & DeCuir, 2002; Castro-Johnson & Wang, 2003).

It is believed that this study will be valuable because it will help educators and

researchers further develop their understanding of the potential role that emotions play when

students are trying to solve complex cognitive problems. The proposed study will contribute to

the existing literature on the possible relationships between emotional and cognitive intelligence

concerning college student populations. It is hoped that through the findings generated by this

study that colleges and universities will continue to grow and develop on-campus programs and

support systems for in-coming freshmen and transfer students, and in turn, increase the number

of students who graduate from their designated programs.

Colleges and Universities have begun to develop resources for all levels of

undergraduates in order to ensure a smooth transition into the college environment and continued

success, socially and academically, throughout their college residency. Some colleges and

universities currently offer on-campus programs and support systems for in-coming freshmen

and transfer students.

In addition, it is expected that the findings may be generalized to other academic settings

to further understand how emotional and general (cognitive) intelligence interact with one

another.

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CHAPTER 3 – METHODOLOGY

Research Problem

Research concerning traditional college student populations has demonstrated a

relationship between cognitive ability, often measured by academic success or grade point

average, and the ability to manage one’s emotions both within and outside of the classroom

(Barchard, 2003; Evenson, 2007). Emotional Intelligence, or EIQ, may be defined as the ability

to recognize, understand, and manage emotions in order to grow cognitively and emotionally

(Mayer & Salovey, 1997). The definition of general, or cognitive, intelligence varies depending

upon theory and the context in which it resides. For the purpose(s) of this study, general

intelligence may be defined as the abilities and knowledge that one acquires and uses to solve

problems in her/his world (Brody, 2000).

There are different ways to assess emotional intelligence that are grounded in three types

of emotional intelligence models: mixed, trait, and ability. Mixed models of emotional

intelligence incorporate the evaluation of non-cognitive capabilities, emotionally and socially

intelligent behaviors, and personality through the analysis of test items on non-ability scales such

as happiness, stress tolerance, self-regard, adaptability, and social competence (Mayer, Robert, &

Barsade, 2008).

Trait models consider emotional intelligence to be a grouping of behavioral dispositions

and personality traits evaluated through self-report, personality measures (Petrides, Frederickson,

& Furnham, 2004).

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Lastly, the ability model of emotional intelligence proposed by Mayer and colleagues has

a cognitive focus and defines the measurement and assessment of emotions through a cognitive

assessment (Mayer, Caruso, & Salovey, 2002). General intelligence may be assessed using either

verbal or non-verbal assessments.

Existing studies concerning students within higher education have indicated that

emotional management, or emotional intelligence, plays an integral role in daily educational

activities, self-regulation, and the establishment of goals, particularly for first-year college

students. Colleges and Universities have begun to develop resources for all levels of

undergraduates in order to ensure a smooth transition into the college environment and continued

success, socially and academically, throughout their college residency. The higher education

environment often proves to be too challenging for students that exhibit difficulty in the

management of their emotions and may therefore lead to a higher risk of failure or drop-out.

Further, studies have demonstrated that differences exist between males and females and their

ability to manage emotions within an educational context (Schutz & DeCuir, 2002; Castro-

Johnson & Wang, 2003). There is therefore a need to understand better the relationship among

emotional intelligence, gender, and the ability to solve complex, cognitive problems. To date,

there are no studies in the literature that have directly compared the subscales of an ability-based

emotional intelligence test with a non-verbal general (cognitive) intelligence test within a sample

of undergraduate college students. Therefore, it is expected that this study will add to the existing

literature concerning the construct of emotional intelligence for a college student population.

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Research Purpose

The purpose of this study was to examine the relationships between the constructs of

emotional intelligence and general (cognitive) intelligence by comparing the subscales of the

Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the General Ability Measure

for Adults (GAMA) and to determine to what extent the relationship between the subscales

varies by gender.

Research Questions

Primary Research Question

RQ1: What is the relationship between/among the subscales, or four branch scores,

(Perceiving Emotions, Facilitating Emotions, Understanding Emotions, and Managing

Emotions), of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the

subscales, or four branch scores, (Matching, Analogies, Sequences, Construction), of the General

Ability Measure for Adults general intelligence test (GAMA)?

Hypothesis A: There is a positive relationship (correlation) between each of the subscales

on the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and each of the subscales

on the General Ability Measure for Adults (GAMA).

Secondary Research Questions

RQ2: Do females and males demonstrate a different relationship between emotional

intelligence and Grade Point Average (GPA)?

Hypothesis B: Females will demonstrate overall higher grade point averages than males

as well as overall higher emotional intelligence scores as measured by the MSCEIT assessment.

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Previous studies have indicated that there are distinct differences between females and males

concerning emotional intelligence, coping, and academic achievement.

This hypothesis is based on studies that have indicated that there are distinct differences

between females and males concerning emotional intelligence, coping, and academic

achievement (Scharfe, 2000; Castro-Johnson & Wang, 2003; Baron-Cohen, 2003; MacCann,

Fogarty, Zeidner, et al., 2011).

RQ3: Is the relationship between/among the variables of the Branch, and Total Emotional

Intelligence scores on the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and

Grade Point Average (GPA) different for students who exhibit high IQ versus low IQ as

measured by the General Ability Measure for Adults (GAMA) intelligence test?

Design of Study

The research design was a quasi-experimental study that examined the relationships

between the constructs of emotional and general intelligence and how the relationships varied by

gender with a sample size of 86 participants from a traditional, college student population at

North Carolina State University in Raleigh, North Carolina. The students in the total sample

were tested during two different times, one group of 40 participants during the fall semester

2011, and the remaining group of 46 during the spring semester of 2012, using two instruments:

the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the General Ability

Measure for Adults general intelligence test (GAMA). Both assessments, the MSCEIT and the

GAMA, were administered via paper and pencil during one sitting for each participant; in other

words, each participant completed both assessments only one time and during one sitting.

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The Variables

Independent variables. The independent variables in this study included gender and the

Total MSCEIT scores.

Dependent variable. The dependent variables included grade point average (GPA) and

the MSCEIT subscales.

Participants

A sample of participants was solicited in collaboration with the Department of

Curriculum and Instruction at North Carolina State University.

North Carolina State University in Raleigh, North Carolina, is a public institution with

approximately 23, 014 full-time, undergraduate students. The campus also houses a medical

school and other graduate and professional schools.

The total participant group, across both the fall and summer assessment sessions,

consisted of traditional-aged (18-22 years) college, undergraduate students from a cross-section

of classes within the Educational Psychology and Curriculum and Instruction departments.

The racial composition of the sample was 5.8% African American, 1.2%

Hispanic/Latino, 5.8% Asian/Pacific Islander, 3.5% American Indian (Native American), 81.4%

Caucasian, and 2.3% other. In regards to gender, 59 (68.6%) of the sample was female and 27

(31.4%) of the sample was male. The mean age for the participants was 20.26 years of age.

Instrumentation

Two data collection instruments were used in this study: the Mayer-Salovey-Caruso

Emotional Intelligence Test (MSCEIT) and the General Ability Measure for Adults (GAMA).

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Inclusive descriptions and the psychometric properties of each of the two assessments are

described in the following paragraphs.

Mayer-Salovey-Caruso Emotional Intelligence Test

The Mayer- Salovey-Caruso Emotional Intelligence Test (MSCEIT) Version 2.0

assessment is the latest version of the Mayer-Salovey-Caruso battery of emotional intelligence

tests. The MSCEIT is an ability-based assessment that measures one’s ability to solve problems

using emotions. The MSCEIT consists of 141 questions that measure abilities as defined by the

four Mayer-Salovey-Caruso branches of emotional intelligence: Branch One: Perceiving

Emotions, Branch Two: Facilitating Thought, Branch Three: Understanding Emotions, and

Branch Four: Managing Emotions (Mayer & Salovey, 1997). The MSCEIT may be administered

to anyone that is 17 years of age or older, hence it is therefore appropriate for the proposed

sample age group for this study. The average time to complete the assessment ranges from 30-45

minutes, however, there is no imposed time limit. The test-taker may take as long as she or he

needs to complete the assessment (Mayer, Caruso, & Salovey, 2002).

Materials and administration. The publisher of the MSCEIT, Multi-Health Systems,

Inc., provides two formats for administration of the assessment: a test booklet with a mail/fax-in

response sheet and an Internet-based version. For the Internet version, participants complete the

assessment via computer, and responses are recorded in a database, scored, and comprehensive

reports are generated. In either case, the responses are scored and compiled into a comprehensive

data set including total, branch, and task scores, along with norming information, demographics,

and percentiles. The data set is forwarded directly back to the researcher in an Excel document

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for further analysis, or the researcher has immediate access to the report if the data entry and

self-scoring online system is utilized (Mayer, Caruso, & Salovey, 2002).

Scoring. The MSCEIT assessment yields a total of fifteen scores: a Total EIQ score, two

Area EIQ scores (Experiential and Strategic), four Branch EIQ scores, and eight Task scores

(Sensations, Transitions, Blends, and Emotional Management). The Experiential Emotional

Intelligence Quotient (EEIQ) measures how well one is able to recognize and evaluate emotions

in relation to one’s thoughts. The Strategic Emotional Intelligence Quotient measures how well

one understands emotions in oneself and others and the implications associated with those

emotions (Mayer, Caruso, & Salovey, 2002).

In addition to the overall Emotional Intelligence Score (EIQ), or Total MSCEIT score,

and the two area scores, three supplemental scores are reported: a Scatter Score, a Positive-

Negative Bias Score, and an Omission Rate Score (Mayer, Carsuo, & Salovey, 2002). The

Scatter Score demonstrates the variation in the examinee’s responses to the questions on the

MSCEIT assessment. The Positive-Negative Bias Score demonstrates the examinee’s propensity

to respond in an overall positive or negative manner to the questions in the Pictures Task. Lastly,

the Omission Rate is simply the number of questions that the examinee did not answer (Mayer,

Caruso, & Salovey, 2002).

An overview of the MSCEIT scores is shown below in Table Five. For the purposes of

this study, the Total MSCEIT score and the four Branch MSCEIT scores will primarily be used

in evaluating the data obtained during the study.

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Table 5

Overview of MSCEIT Scores

Total EIQ (Overall Score)

Type of Score Hierarchy of Specific Scores

Area Scores Experiential EIQ Strategic EIQ

Branch Scores Per. Emotions Fac. Thought Und. Emotions Man. Emotions

Task Scores Individual Task Scores

Faces

Pictures

Sensations

Facilitation

Blends

Changes

Management

Relations

Supplemental Scores Scatter Score, Positive-Negative Bias Score, Omission Rate

(Adapted from MSCEIT Manual, Mayer Salovey, & Caruso, 2002).

The scores on the MSCEIT can be placed on a normal curve with a Mean of 100 and a

standard deviation of 15. The examinee’s score is compared with the normative sample and not

the general population. The range of MSCEIT scores is interpreted as a numerical range with an

associated qualitative descriptor as shown in Table Six.

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Table 6

Guidelines for Interpreting MSCEIT Scores

EIQ Range Qualitative Range

69 or less Consider Development

70-89 Consider Improvement

90-99 Low Average Score

100-109 High Average Score

110-119 Competent

120-129 Strength

130+ Significant Strength

(Adapted from MSCEIT Manual, Mayer, Caruso, & Salovey, 2002).

Standardization. Three samples, consisting of 5,000 participants, were used to compile

the normative data for the MSCEIT (Mayer, Caruso, Salovey, 2002). The final, combined sample

of 5,000 had a higher percentage of females at 52% than males at 37.3 percent. A small

percentage, 10.7% were unreported on gender. The mean age of the sample was 24.13 with a

standard deviation of 9.89 and a range of 17-79 years of age. Ethnicity was reported by

approximately 70% of the sample (Mayer, Caruso, & Salovey, 2002).

Reliability. The reliability of the MSCEIT was based on an analysis of the

standardization sample. The MSCEIT exhibits a test-retest reliability of r = .86 for the full-scale

test and a range from .74 to .89 for the Branch Scores. The full-scale reliability for the MSCEIT

is .91, and the two area reliabilities, experiential and strategic, are .90 and .85 (Mayer, Caruso, &

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Salovey, 2002). The authors of the MSCEIT state that the test scores at the subtask level

(Perceiving Emotions, Facilitating Thought, Understanding Emotions, and Managing Emotions)

are less reliable and that caution should be used when interpreting or using these scores (Mayer,

Caruso, & Salovey, 2002).

Validity. The authors of the MSCEIT maintain that overall the MSCEIT is a valid

instrument and that it measures those aspects of emotional intelligence that it proposes to

measure. Face validity is exhibited, and is demonstrated, through an inter-rater reliability of r =

.83. In addition, content validity, as based upon the 1997 Mayer-Salovey, and Caruso four-

branch model of emotional intelligence, is confirmed.

The construct validity of the MSCEIT was also examined, specifically in regards to

discriminant validity. Concerning discriminant validity, there has been much discussion as to

whether there is an overlap between the MSCEIT, as an ability-based measure of emotional

intelligence, and other assessments which appear to measure similar constructs: cognitive

intelligence and self-report scales concerning personality (Mayer, Caruso, & Salovey, 2002).

Concerning cognitive intelligence, or general IQ, some studies have indicated that

emotional intelligence does indicate a moderate relationship with analytical intelligence as

defined in Sternberg’s Triarchic Theory. Therefore it is proposed that emotional intelligence may

“qualify as a conventional intelligence operationalized as mental ability” (Mayer, Salovey, &

Caruso, 2000, p. 408). The MSCEIT, as an ability-based measure of emotional intelligence, is

thought to provide an assessment of one’s ability to solve complex, cognitive problems, such as

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those presented on traditional intelligence tests (Mayer & Salovey, 1997; Mayer, Caruso, &

Salovey, 2000).

In addition, moderate correlations were found between the MSCEIT and self-report

measures of emotional intelligence such as the Bar-On Emotional Quotient Inventory (r = .39)

and a select group of general personality tests: The Big Five (defined in Chapter Two), The

16PF, and the FIRO-B, for example. In brief, the 16PF assessment is a personality trait

questionnaire. The questionnaire was created by psychologist Raymond Cattell to test the 16

primary factors of personality he obtained through a factor analysis of 181 clusters of words that

describe one’s personality: Warmth, Reasoning, Emotional Stability, etc. (Cattell, 1957). The

Fundamental Interpersonal Relations Orientation (FIRO-B) was developed by psychologist

William Schutz in 1958 and later revised during the 1970s. The FIRO-B assesses interactions

within small group settings through a complex, typically clinical evaluation, of one’s feelings,

work relationships, and behavior that result in rankings on three types: Inclusion, Control, and

Affection (Ryan, 1977).

In addition, overall findings concluded that there is some degree of overlap for those who

obtain high scores on the tasks in emotional intelligence assessments and the agreeability,

empathy, and conscientiousness tasks in personality assessments (Mayer, Caruso, & Salovey,

2002).

General Ability Measure for Adults

The General Ability Measure for Adults, (GAMA), was developed by Dr. Jack Naglieri

of The Ohio State University and Dr. Achilles Bardos of the University of Northern Colorado as

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a tool for measuring general intellectual ability. Unlike many of the existing general intelligence

tests, the GAMA assesses intelligence through the examinee’s use of logic and reasoning to

solve problems composed of abstract shapes and designs (Naglieri & Bardos, 1997). The GAMA

is comprised of 66 questions of four types: Matching, Analogies, Sequences, and Construction.

More specifically, the sections may be defined in the following manner:

Matching: examinee is expected to choose which of six pictures presented as an

option is most like the stimulus presented;

Analogies: examinee is expected to understand a presented relationship between

two abstract figures presented as the stimulus and find two other figures that

demonstrate the same structure;

Sequences: examinee is expected to understand and choose next pattern in a

sequence;

Construction: examinee is expected to choose a shape that can be created from the

several shapes presented in the stimulus (Naglieri & Bardos, 1997).

Materials and administration. The publisher of the General Ability Measure for Adults

(GAMA), Pearson Assessments, provides the following test materials for administration: test

manual with general information and psychometric properties; the test book for the examinee;

the demographic self-scoring record form that includes gender, age, academic year, etc.; a

scannable answer sheet; and computer scoring and reporting software. The examiner may choose

to use the software in lieu of having the publisher, Pearson Assessments, score and report the

data obtained from an administration. The GAMA may be administered to individuals or a group

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of individuals and takes approximately 25 minutes to complete. The GAMA is a timed

assessment and must be concluded within the 25 minute timeframe (Naglieri & Bardos, 1997).

Scoring. The GAMA yields an overall IQ score and four subtest scaled scores with

ranges as represented below in Table Seven.

Table 7

GAMA IQ Scores and Subtest Scores

GAMA IQ Score Descriptive Category Subtest Scaled Score

130 and above Very Superior 16-19

120-129 Superior 14-15

110-119 High Average 12-13

90-109 Average 8-11

80-89 Low Average 6-7

70-79 Below Average 4-5

69 and Below Well Below Average 1-3

(Adapted from GAMA Manual, Naglieri & Bardos, 1997).

To obtain the overall GAMA IQ score, the sum of the four subtest scaled scores are computed.

The standard score obtained for the overall GAMA IQ has a mean of 100 and a standard

deviation of 15. The GAMA subtest scores have a mean of 10 and a standard deviation of three.

The range of GAMA IQ scores are from 43 to 156. The range of GAMA subtest scores are from

1-19 (Naglieri & Bardos, 1997).

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In addition to the above scores, percentile ranks based on the normal, statistical bell curve

are also computed to indicate each individual examinee’s standing in relationship to the

standardized sample. Scores are provided in individual profile reports and include the Total

GAMA IQ score, percentile, and subtest scores with related means and standard deviations. The

profile reports are forwarded to the researcher for further analysis and interpretation.

Standardization. The initial conceptualization of the General Ability Measure for Adults

(GAMA) consisted of 200 assessment items. The GAMA test items were developed “to assess

general ability using several approaches including mental rotation, spatial analysis, analogical

reasoning, and matching to a standard” (Naglieri & Bardos, 1997, p. 29).

For the standardization sample, a stratified random sample was employed in order to

most closely match the population in the 1990 U.S. Census (Naglieri & Bardos, 1997). This

sample included nine age groups further stratified by gender, race or ethnicity, educational level,

and geographic region (80 cities; 23 states). The final sample for the standardization of the

GAMA was comprised of 2,360 persons with a range of 18- 96 years of age. There were

approximately 200 more females than males in the standardization sample, and Caucasians

represented the largest race/ethnic group with a sample size of 1,802 (Naglieri & Bardos, 1997).

Reliability. To evaluate the reliability of the General Ability Measure for Adults

(GAMA), two statistical methods were used: split-half to measure internal consistency and the

test-retest method to evaluate the stability of GAMA scores over time (Naglieri & Bardos, 1997).

The internal consistency of the GAMA was measured across the 11 age groups of the

standardization sample using two groups derived from the four subtests. Average reliability

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statistics for the four subtests were as follows: Matching .66, Analogies .81, Sequences .79, and

Construction .65 (Naglieri & Brados, 1997). The overall GAMA IQ score, which was measured

based upon a composite of the spilt-half reliabilities of the subtests, was .90. The range was from

.79 (80+ years of age) to .94 (35-44 years of age), therefore, indicating that the GAMA is a

consistently reliable assessment of general intelligence (Naglieri & Bardos, 1997).

Concerning the test-retest reliability of the GAMA, the stability of the GAMA scores was

assessed via a group of 86 participants who completed the GAMA test within two to six week

intervals (mean interval = 25 days). Overall, test-retest reliability was found to be statistically

significant with a coefficient of .67 at p < .001 (Naglieri & Bardos, 1997).

Validity. The validity tests conducted for the General Ability Measure for Adults

(GAMA) consisted of content validity, concurrent validity, and criterion-related validity

analyses.

To evaluate the content validity of the GAMA, several studies were conducted. Age

trends were evaluated based upon the assumption that overall general intelligence performance is

“expected to decline across the adult life span” (Naglieri & Bardos, 1997, p. 43). Similar to

findings from previous studies, the GAMA data demonstrated a peak for the 20-24 year old

group with an approximate three-point drop in scores for each following age group (Naglieri &

Bardos, 1997).

Additional content validity studies concerning Item-total GAMA Score, Item-GAMA

Subtest Total, Subtest-total GAMA Score, and Subtest Inter-correlations were conducted.

Findings suggested that overall, the high quality of the inferences that can be made based upon

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the aforementioned inter-correlations provides support for the measurement of general

intelligence via non-verbal constructs as represented on the GAMA. The inter-correlations were

statistically significant at the p < .001 and p < .01 levels (Naglieri & Bardos, 1997).

Concurrent validity was examined via several studies involving other general ability

assessments, including the WAIS-R (Wechsler Adult Intelligence Scale-Revised), the K-Bit

(Kaufman Brief Intelligence Test), and the Wonderlic Personnel Test. In each of these studies, it

was demonstrated that the GAMA scores were similar to those scores obtained via other general

intelligence assessments, and therefore, concurrent validity was exhibited (Naglieri & Bardos,

1997). These studies were previously discussed in detail in Chapter Two.

Lastly, research conducted concerning the validity of the GAMA offers support for the

assessment’s use with special populations: deaf adults, nursing home residents, individuals with

learning disabilities, and traumatic brain injury (Naglieri & Bardos, 1997).

Procedure

In working in collaboration with the Department of Education and the Department of

Educational Psychology, the primary researcher obtained a total sample of 86 undergraduate

students from a cross-section of classes within the two departments. The students participated in

one of two sessions, fall session 2011 or spring session 2012, with a choice of day and time on

which they would participate. The participants were provided notification of the opportunity to

participate in the study through their individual classes and were instructed to sign up via an on-

line survey link. Participants then received confirmation of their designated assessment times and

reporting locations from the primary researcher.

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Upon arrival for an assigned session, participants were welcomed, provided with further

detailed instructions about what would transpire during their time in the study, and then given an

informed consent document to read and sign. All participants, at each session, were informed

that their participation in the study was strictly voluntary and that in no way would their

performance on the two assessments affect their grades or academic standing. One exception to

this statement occurred in the case where an incentive was offered for extra credit, and agreed

upon, between the primary researcher and the Department of Educational Psychology professors

for their individual students who participated in, and completed, the study.

After completing the Informed Consent documents, the primary researcher provided the

participants with copies of the General Ability Measure for Adults (GAMA) assessment booklet

and self-scoring answer sheet. Participants were asked to complete the demographic profile,

including ethnicity, birth date, and self-reported grade point average on the left-hand side of the

GAMA answer sheet. Participants were instructed that the GAMA was a timed assessment and

that they would have 25 minutes to complete the questions. The researcher read aloud the

directions for group administration of the GAMA and after responding to questions, informed the

participants to begin the assessment. When 25 minutes had transpired, participants were

instructed to close their GAMA assessment booklets and answer sheets at which time they were

collected by the primary researcher.

The second set of assessment materials, the Mayer-Salovey-Caruso Emotional

Intelligence Test (MSCEIT) item booklet and response sheet, were then distributed to the

participants. The primary researcher then read the group administration instructions for the

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MSCEIT and answered questions from the participants. The participants were informed that the

MSCEIT was an untimed assessment and that the average completion time was 45 minutes.

Upon completion of the MSCEIT, participants handed in all assessment documents and were

provided with the researcher’s contact information. The researcher answered any remaining

questions that the participants had upon exiting the session.

Data Management and Assessment Scoring

For the purposes of this study the identity of each of the participants need not be known.

Coding of the data, including all scoring sheets and test booklets, beginning with 001 and

concluding with the code 086, was completed in order to disguise specific names and other

identifiable personal information. The primary data utilized for this study consisted of the scores

on the assessments, gender of the participants, and overall, self-reported grade point averages

(GPA).

The scoring of both the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)

and the General Ability Measure for Adults (GAMA) assessments was completed by the primary

researcher using the publishers’ standard scoring materials. The MSCEIT scores, and additional

statistical information, were provided to the researcher in a research data set that was

downloaded from the MSCEIT scoring on-line site once all scores were entered into the online

system. The GAMA scores were manually computed by the primary researcher using the

GAMA Self-Scoring Sheet for each participant.

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Data Analysis

It was anticipated that there would be significant effects for the GAMA IQ score, gender,

and the subscales of the MSCEIT thus indicating that relationships exist among the variables.

Descriptive statistics were evaluated for race/ethnicity, gender, age, and grade point average. The

descriptive data included means, tests of normality, and standard deviation.

Descriptive statistics were also computed for the mean scores on the overall Emotional

Intelligence Quotient (EIQ) and the sub-scores on the four branches (Perceiving Emotions,

Facilitating Thought, Understanding Emotions, and Managing Emotions) obtained via the

MSCEIT and the overall GAMA mental ability score and the respective four sub-scores

(Matching, Analogies, Sequences, and Construction).

Independent Variables: Gender and Total MSCEIT Score

The independent variables of gender and the Total MSCEIT Score were analyzed in two

of the research questions. As previously discussed, research has indicated that there are

significant correlations between one’s gender and her or his ability to manage emotions (Scharfe,

2000; Castro-Johnson & Wang, 2003; Baron-Cohen, 2003; MacCann, Fogarty, Zeidner, et al.,

2011).

A set of standard regression analyses evaluated the relationships among gender, grade

point average, and Overall GAMA IQ. The researcher anticipated that the data would

demonstrate a significant finding for differences between females and males.

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Dependent Variable: Grade Point Average (GPA)

The variable, GPA, was analyzed in two of the research questions in the study. For the

first question, it was hypothesized that females and males would demonstrate a significant

difference in the overall emotional intelligence score, with females scoring higher, thus leading

to a higher general IQ due to the ability to manage and control emotions (Scharfe, 2000; Castro-

Johnson & Wang, 2003; Baron-Cohen, 2003; MacCann, Fogarty, Zeidner, et al., 2011). This in

turn would be reflected in an overall higher GPA. In order to evaluate this question, standard

regression analyses were used in order to ascertain whether there were any significant

differences demonstrated for females and males.

The GPA variable was also evaluated in secondary research question two which used a

series of standard regression analyses to evaluate whether significant relationships were found

among the MSCEIT and GAMA test results and GPA, which for the purposes of this research

question, served as an indicator of higher or lower academic achievement.

Human Subjects

Given that the research involved psychological assessments, the primary researcher

completed a full IRB review at the Catholic University of America as well as an abbreviated review

at North Carolina State University in Raleigh. An informed consent document was reviewed by

both academic institutions. Students who participated in the study were required to sign the

document and were provided a copy upon request. In addition, specific contact information for

both the primary researcher and the faculty sponsors were provided to the participants and faculty

contacts in the event of questions or a request to withdraw from the study arose.

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Limitations of the Study

Sample Size

There are several limitations of the study that need to be taken into consideration. First, in

regards to sample size, the researcher had anticipated having a sample of at least 100 participants

from a cross- section of courses at the university. The researcher did obtain a diverse sample across

years, ages, and gender, but due to resource and time constraints, a smaller final sample was

obtained than what was originally planned. The smaller sample size may, therefore, lead to

difficulty in generalizing the findings of this study to larger populations.

Grade Point Average

In addition to the aforementioned limitation of sample size, the variable of Grade Point

Average (GPA) presents an additional concern. Participants were asked to provide a best

estimate of their self-reported GPA in their individual demographic profile. Out of the sample of

86 participants, six participants neglected to report a GPA. Furthermore, it is important to note

that the participants GPAs were not cross- checked against official transcripts. Therefore, any

number of those that were reported could have been incorrect.

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Table 8

Descriptive Statistics for Dependent Variable: GPA

Standard Attributes Label GPA

N Valid 80

Missing 6

Central Tendency and Dispersion Mean 3.2

Standard Deviation .54

Percentile 25 2.6

Percentile 50 3.4

Percentile 75 3.6

Threats to Validity

Several threats to validity were anticipated and addressed as much as feasible either prior

to, or during, the study. Because the study involved the use of assessments and testing, the

Hawthorne Effect presented one threat to internal validity. Participants understood when they

signed up for participation in the study that they were being singled out and treated as an

experimental study. Due to the nature of the study and assessments, it was difficult to control this

threat by using a non-reactive measure.

A threat to external validity was discussed previously in that the ability to generalize the

results of this particular study to a larger, and different, population may be limited due to the

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smaller than anticipated sample size. Future replications of the study using a wider range of

universities for obtaining the sample should help to remedy this threat.

Conclusion

In conclusion, this study fulfilled the need for further investigation into the relationships

among emotional intelligence, gender, and the ability to solve complex, cognitive problems using

the combination of an ability-based emotional intelligence assessment combined with a non-

verbal, general ability assessment. The analyses used in the study provided a thorough examination

of the data and will add to the literature regarding the roles that emotions play when college

students are trying to solve complex cognitive problems. Furthermore, it is proposed that the

findings from the study will continue to help colleges and universities continue to develop on-

campus programs for first-year students and beyond.

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CHAPTER 4 – RESULTS

Variable Relationships and Descriptive Statistics

The relationship between gender and the subscales on the Mayer-Salovey-Caruso

Emotional Intelligence Test (MSCEIT) and the General Ability Measure for Adults (GAMA)

intelligence test were investigated. Before completing the analyses for the three research

questions, preliminary analyses were conducted to ensure that there were no violations of

assumptions in regards to normality, linearity, and homoscedasticity. Table 9 provides a

summary of the sample size data, and Table 10 provides the descriptive statistics for the

variables.

Table 9

Case Processing Summary

Variable Total N Missing N Total Valid N

GPA 86 2 84

Total GAMA IQ 86 0 86

Total MSCEIT 86 2 84

Because of the missing data for participants labelled 35 and 84, particularly given the incomplete

scores for both the MSCEIT and GAMA assessments, these two cases were eliminated from

further analyses thus resulting in a total sample size of 84 participants (57 female; 27 male).

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Table 10

Summary Table of Means for Variables

Variable M - Females M - Males t P

GPA 3.25 3.00 -1.84 .069

GAMA Match 11.73 12.00 .455 .657

GAMA Analogy 12.00 12.77 1.45 .151

GAMA Sequence 11.67 12.44 1.33 .192

GAMA Construction 11.09 12.30 1.73 .087

GAMA Overall Score 109.67 114.63 2.00 .049

MSCEIT Perceiving Emotions 99.48 106.24 1.71 .097

MSCEIT Facilitating

Emotion/Thought

102.21 108.26 1.80 .077

MSCEIT Understanding

Emotion

107.53 125.04 3.67 .001

MSCEIT Managing Emotion 97.60 105.17 2.78 .007

Total MSCEIT 100.89 109.23 2.54 .013

T-tests were completed to check for additional differences that existed between females

and males on each of the variables. The results of the t-tests found significant differences

between females and males in three instances. There was a significant effect for gender, and

males were found to have a better sense of Understanding Emotions (per the MSCEIT) than

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females t (35.80) = 3.67, p < .05. Similar significant findings apply to the MSCEIT Managing

Emotions subscale and the Total MSCEIT score as well. Males were found to possess a better

sense of Managing Emotions than females (per the MSCEIT): t (82) = 2.78, p < .05. Lastly,

males demonstrated overall higher scores associated with the Total MSCEIT than females with t-

test results: t (82) = 2.54, p < .05.

In addition to the tests conducted for violations of assumption, zero-order correlations

were completed to check for interdependencies among the GAMA and MSCEIT scores before

conducting the analyses for the research questions. Overall, there were positive correlations

demonstrated between the GAMA Sequence and GAMA Analogy subscales, r = .629, n = 86, p

< .001; the MSCEIT Facilitating and Perceiving Emotions subscales, r = .528, n = 86, p < .001,

and the GAMA Analogy and MSCEIT Understanding Emotions subscales, r = .385, n = 86, p <

.001. The three sets of correlations are provided below.

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Table 11

Pearson Product-Moment Correlations for the GAMA Subtests

GAMA Match GAMA Ana. GAMA Seq. GAMA Construct.

GAMA Match 1 .128 .002 -.061

GAMA Analogy .128 1 .629** .496**

GAMA Sequence .002 .629** 1 .593**

GAMA Construct. -.061 .496** .593** 1

GPA .222* .178 .241* .118

N = 86

*p<.05

**p<.001

Table 12

Pearson Product-Moment Correlations for the MSCEIT Subtests

MSCEIT PE MSCEIT UE MSCEIT FE MSCEIT ME

MSCEIT PE 1 .339** .528** .390**

MSCEIT UE .339** 1 .314** .410**

MSCEIT FE .528** .314** 1 .379**

MSCEIT ME .390** .410** .379** 1

GPA -.244* .026 -.164 -.249*

N = 86

*p<.05

**p<.001

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Table 13

Pearson Product-Moment Correlations between the GAMA and MSCEIT Scores

MSCEIT PE MSCEIT FE MSCEIT UE MSCEIT ME

GAMA Match .028 -.050 .113 .002

GAMA Analogy .033 .212 .385** -.070

GAMA Sequence -.074 .129 .226* -.056

GAMA Construct. -.156 -.066 .223* -.066

N = 86

*p<.05

**p<.001

Relationships among the Mayer-Salovey-Caruso Emotional Intelligence and General

Ability Measure for Adults Subscales

What is the relationship between/among the subscales (Perceiving Emotions, Facilitating

Emotions, Understanding Emotions, and Managing Emotions of the Mayer-Salovey-Caruso

Emotional Intelligence Test (MSCEIT) and the subscales (Matching, Analogies, Sequences, and

Construction) of the General Ability Measure for Adults (GAMA)?

A canonical correlation analysis (CCA), using the MANOVA syntax in SPSS, was used

to evaluate this research question and to examine the multivariate shared relationships between

the two sets of variables. The Emotional Intelligence (EIQ) and Intelligence Quotient (IQ)

constructs were statistically examined through the evaluation of the mean scores on the subscales

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of the MSCEIT and GAMA instruments. The two sets of variables were defined in the following

manner:

Criterion Variables, Set One: Scores on the sub-scales of the GAMA Assessment for Matching,

Sequences, Analogies, and Construction (Y1 Y2 Y3 Y4)

Predictor Variables, Set Two: Scores on the sub-scales of the MSCEIT Assessment for

Perceiving, Facilitating, Understanding, and Managing Emotions (X1 X2 X3 X4)

Through the evaluation of Wilk’s λ, it was found that the full model was indeed

statistically significant: Wilk’s λ = .662 criterion, F (16, 232.82) = 2.101, p < .001. The

canonical correlation was .506, and thus indicates a moderate correlation between the two sets of

variables (subscales on the GAMA and MSCEIT assessments). As indicated in the Table 14, the

canonical correlation of .506 is larger than any of the other correlations (Table 13).

Table 14

Eigenvalues and Canonical Correlation

Root No. Eigenvalue Percent Cumulative % Canon Cor. Sq. Cor.

1 .343 73.89 73.89 .506 .255

2 .095 20.53 94.43 .295 .087

3 .025 5.54 99.97 .158 .025

4 .000 .033 100.00 .012 .000

Additional analysis of the correlations showed that the GAMA Analogy subtest variable

had the strongest correlation at .944 with the canonical variate, the linear combination of the

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GAMA subtests that produced the canonical correlation. For the MSCEIT Understanding

Emotions subtest, the correlation of .764 was produced as the strongest correlation with the

canonical variate, the linear combination of the MSCEIT subtests that produced the canonical

correlation. The correlation data aforementioned is outlined below in Tables 15 and 16.

Table 15

Standardized Coefficients for GAMA Variables

Variable Std. Coefficient for

Covariates

Standardized Coefficients

GAMA Match Subtest .029 .148

GAMA Analogy Subtest .408 .944

GAMA Sequence Subtest .051 .665

GAMA Construction Subtest .034 .532

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Table 16

Standardized Coefficients for MSCEIT Variables

Variable Std. Coefficient for

Covariates

Standardized Coefficients

MSCEIT PE Subtest .303 .045

MSCEIT FE Subtest .487 .401

MSCEIT UE Subtest .960 .764

MSCEIT ME Subtest .600 .140

Emotional Intelligence and Grade Point Average

Do females and males demonstrate a different relationship between emotional

intelligence and Grade Point Average (GPA)?

As previously discussed, studies have indicated that females will typically score higher

than their male counterparts on assessments of emotional intelligence which may therefore

contribute to higher grade point averages due to better (emotional) coping abilities (Scharfe,

2000; Castro-Johnson & Wang, 2003; Baron-Cohen, 2003; MacCann, Fogarty, Zeidner, et al.,

2011).

To evaluate this research question, the Total Mayer-Salovey-Caruso score was examined

in relation to gender using the MSCEIT assessment. A standard regression analysis was

conducted to evaluate the differences between females and males. For the analysis, grade point

average (GPA) was entered as the dependent variable and the predictors were gender, the Total

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MSCEIT scores, and the product of gender and the Total MSCEIT scores. The third predictor,

the product term, was initially included to examine whether a different relationship between

GPA and Total MSCEIT existed for females and males. After completing the three-predictor

analysis, it was determined that the product term was not significant, and therefore a second

regression analysis was completed using only two predictors: gender and the Total MSCEIT

scores. In addition, preliminary analyses were conducted to check for any violation of the

assumptions of normality, linearity, homoscedasticity, and multicollinearity. Table 17 provides a

summary of the regression weights and significance levels for both the three and two predictor

models.

Table 17

Regression of GPA on the Total MSCEIT Scores and Gender

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

Gender -.709 -.554 .481 .205 .160 .157

Total MSCEIT -.020 -.473 .207 -.006 -.146 .197

Product of Gender and Total

MSCEIT

.009 .708 .359

N = 84, R2 = .059

*p<.05

**p<.001

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The findings from the two-predictor model demonstrated that 6% of the variance in the

dependent variable of GPA was explained by this second, two-predictor analysis. The regression

model produced the following: r2 = .059, F (2, 81) = .084, p < .05. Gender was found to make the

strongest, unique contribution to explaining grade point average but did not indicate statistical

significance, p = .157, at the .05 level. Furthermore, Total MSCEIT did not demonstrate

statistical significance at p = .197, thus indicating that neither Gender or Total MSCEIT is a

significant predictor of GPA when each is controlled for the other.

To further evaluate this research question and examine any differences that may exist

between females and males, additional standard regression analyses were run on each of the

individual subscales of the MSCEIT assessment: Perceiving Emotions, Facilitating Emotions,

Understanding Emotions, and Managing Emotions. The same protocol as that outlined above

was followed for each of the analyses: if the three-predictor model did not demonstrate statistical

significance for the product term, then the product term in each instance was dropped and a two-

predictor model was used to check for any significant findings. In each of the analyses, the

three-predictor models indeed proved no statistical significance at the .05 levels, and therefore,

only the results of the two-predictor models are provided in the below narrative.

MSCEIT PE and Gender Differences

A standard regression analysis was conducted to evaluate any gender differences that

exist on the Perceiving Emotions subscale on the MSCEIT using a two-predictor model: gender

and the MSCEIT Perceiving Emotions subtest score. The results from the two-predictor model

indicated that 8% of the variance in the dependent variable of GPA was explained. The

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regression model produced the following: r2 = .081, F (2, 81) = 3.58, p < .05. In this two-

predictor analysis, neither gender nor the MSCEIT PE subtest score made a significant

contribution to the prediction of grade point average indicating that there is no difference for

females and males. Table 18 provides a summary of the p-values and regression weights used in

the analysis.

Table 18

Regression of GPA on MSCEIT PE Scores and Gender

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

Gender .155 .121 .878 .194 .152 .168

MSCEIT PE Subtest -.010 -.222 .505 -.009 -.209 .059

Product of Gender and MSCEIT

PE Subtest

.000 .031 .968

N = 84, R2 = .081

*p<.05

**p<.001

MSCEIT FE and Gender Differences

A standard regression analysis was conducted using the predictors of gender and the

MSCEIT Facilitating Emotions subtest scores. The findings from the two-predictor model

showed that 6% of the variance in GPA could be explained by the model and that gender once

again made the strongest, unique contribution to explaining grade point average with a beta value

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of .17. The regression model produced the following: r2 = .056, F (2, 81) = .097, p < .05. Lastly,

neither of the two predictors demonstrated statistical significance at the p <.05 level: gender, p =

.117 and MSCEIT FE, p = .242. Table 19 provides a summary of the data used in the analysis.

Table 19

Regression of GPA on the MSCEIT FE Scores and Gender

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

Gender -.396 -.309 .707 .223 .174 .117

MSCEIT FE Subtest -.015 -.369 .379 -.005 -.130 .242

Product of Gender and MSCEIT

FE Subtest

.006 .500 .554

N = 84, R2 = .056

*p<.05

**p<.001

MSCEIT UE and Gender Differences

Standard regression analysis was conducted to evaluate gender differences on the third

MSCEIT subscale, Understanding Emotions. The two-predictor regression analysis showed that

6% of the variance in grade point average could be explained by the model. The regression

model produced the following: r2 = .055, F (2, 81) = 2.36, p < .05. The predictor, gender, was

found to be statistically significant at p = .034, which demonstrates in this instance that there

exists a difference between females and males on the dependent variable of grade point average,

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when controlling for the Understanding Emotions (UE) scores. Table 20 provides a summary of

the regression data used in the analysis.

Table 20

Regression of GPA on the MSCEIT UE Scores and Gender

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

Gender -1.055 -.825 .232 .330 .258 .034

MSCEIT UE Subtest -.013 -.418 .256 .004 .137 .256

Product of Gender and MSCEIT

UE Subtest

.012 .997 .112

N = 84, R2 = .055

*p<.05

**p<.001

MSCEIT ME and Gender Differences

Lastly, to evaluate any gender differences that may exist on the MSCEIT Managing

Emotions subscale, a final standard regression analysis was conducted. The two-predictor model

indicated that 8% of the variance in the dependent variable, GPA, was explained. The regression

model produced the following: r2 = .079, F (2, 81) = 3.50, p < .05. Neither of the two predictors,

gender nor the MSCEIT Managing Emotions subtest score, proved to be statistically significant.

The MSCEIT Managing Emotions subscale was negatively correlated with the dependent

variable and therefore indicates that a higher score on the MSCEIT ME subtest is not directly

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associated with a higher grade point average. Table 21 provides a summary of the regression data

used in the analysis.

Table 21

Regression of GPA on the MSCEIT ME Scores and Gender

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

Gender .371 .290 .764 .177 .138 .219

MSCEIT ME Subtest -.007 -.144 .731 -.010 -.208 .065

Product of Gender and MSCEIT

ME Subtest

-.002 -.148 .874

N = 84, R2 = .079

*p<.05

**p<.001

Emotional, General Intelligence, and Grade Point Average

Is the relationship between, or among, the variables of the subscales of the Mayer-

Salovey-Caruso Emotional Intelligence Test (MSCEIT) and total grade point average different

for students who exhibit a high versus low IQ as measured by the subscales of the General

Ability Measure for Adults?

The analysis for this research question was conducted via a series of standard multiple

regression analyses which tested whether there were effects demonstrated for emotional

intelligence as measured by each of the MSCEIT subscales. The regression analyses were

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computed using each of the MSCEIT subscales as dependent variables and the predictors of

GPA, GAMA IQ, and the product of GAMA IQ and GPA. If the three-predictor models did not

prove to be statistically significant for the product of grade point average and GAMA IQ, then

the product term was eliminated and a second, two-predictor regression analysis was conducted.

In each of the below analyses the three-predictor models did not indicate statistical significance,

therefore, only the two-predictor results are detailed in the narrative. In addition, preliminary

analyses were conducted to check for any violation of the assumptions of normality, linearity,

homoscedasticity, and multicollinearity.

MSCEIT Managing Emotions and GAMA IQ

In evaluating the relationship between the MSCEIT Managing Emotions subscale and

GPA as modified by GAMA IQ, it was found that 6% of the variance in the dependent variable

of the MSCEIT Managing Emotions subscale was explained. The regression model produced the

following: r2 = .062, F (2, 81) = 2.69, p < .05 using the two predictors: GAMA IQ and GPA.

Furthermore, the GPA predictor was found to be significant in this model at p = .026.Table 22

below provides a summary of the regression data used for this analysis.

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Table 22

Regression of the MSCEIT ME Scores on GPA and Overall GAMA IQ scores

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

GPA -39.03 -1.93 .086 -5.09 -.253 .026

GAMA IQ -.974 -.872 .145 .016 .014 .900

Product of GAMA IQ and GPA .309 2.11 .132

N = 84, R2 =.062

*p<.05

**p<.001

MSCEIT Facilitating Emotions and GAMA IQ

To evaluate the relationship between the MSCEIT Facilitating Emotions subscale and

GPA as modified by GAMA IQ a two-predictor, standard regression analysis was used. The

results of the analysis indicated that 5% of the variance in the dependent variable of the MSCEIT

Facilitating Emotions subtest was explained by the model. The regression model produced the

following: r2 = .045, F (2, 81) = 1.92, p < .05. The predictors of GPA and the Total GAMA IQ

scores were found once again to not be statistically significant at p = .08 and p = .213, and

therefore, did not demonstrate a different relationship for students with a lower or higher general

intelligence score as measured by the GAMA. Although the GPA predictor did exhibit a higher

beta value (beta = -.202 p < .05), the regression weight was negatively correlated with the

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dependent variable of MSCEIT FE. A summary of the regression weights for the MSCEIT

Facilitating Emotions data is provided in Table 23.

Table 23

Regression of the MSCEIT FE Scores on GPA and Overall GAMA IQ scores

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

GPA -36.05 -1.48 .194 -4.91 -.202 .077

GAMA IQ -.717 -.530 .381 .191 .141 .213

Product of GAMA IQ and GPA .284 1.60 .259

N = 84, R2 = .045

*p<.05

**p<.001

MSCEIT Understanding Emotions and GAMA IQ

In evaluating the relationship between the MSCEIT Understanding Emotions subscale

and GPA as modified by GAMA IQ, the results of the two-predictor regression analysis, using

grade point average and the Overall/Total GAMA IQ score only, indicated that 13% of the

variance was explained. The model produced the following: r2 = .133, F (2, 81) = 6.21, p < .05.

The GPA predictor was found to not be significant at p = .484, however, the Overall/Total

GAMA IQ score predictor proved to be statistically significant in this model at p = .001. It may

be inferred from this significance that there is a different relationship on the MSCEIT

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Understanding Emotions subscale for those students demonstrating a higher, versus a lower,

Overall/Total GAMA IQ score.

A summary of the regression weights and p-values for the MSCEIT Understanding

Emotions data is provided in Table 24.

Table 24

Regression of the MSCEIT UE Scores on GPA and Overall GAMA IQ scores

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

GPA .861 .027 .980 -2.41 -.076 .484

GAMA IQ .762 .431 .458 .667 .377 .001

Product of GAMA IQ and GPA -.030 -.129 .925

N = 84, R2 = .133

*p<.05

**p<.001

MSCEIT Perceiving Emotions and GAMA IQ

For the last regression analysis, a similar approach to the previous analyses was

completed. In evaluating the relationship between the MSCEIT Perceiving Emotions subscale

and GPA as modified by GAMA IQ, it was found that 6% of the variance in the dependent

variable of the MSCEIT PE subtest was explained. The regression analysis produced the

following: r2 = .059, F (2, 81) = 2.56, p < .05. The GPA predictor had the higher beta value (beta

= -.24, p < .05), thus indicating that grade point average makes the strongest unique contribution

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to explaining the dependent variable of MSCEIT PE (Perceiving Emotions). Furthermore, GPA

also exhibited statistical significance in the two-predictor model, p = .034, at the .05 level. A

summary of the regression weights for the MSCEIT Perceiving Emotions data is provided in

Table 25.

Table 25

Regression of the MSCEIT PE Scores on GPA and Overall GAMA IQ scores

With Interaction Two-Predictor

Variable Weights

b β

Sig. Weights

b β

Sig.

GPA -2.37 -.102 .928 -5.63 -.242 .034

GAMA IQ .086 .066 .912 -.009 -.007 .951

Product of GAMA IQ and GPA -.030 -.175 .902

N = 84, R2 = .059

*p<.05

**p<.001

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CHAPTER 5 – DISCUSSION

Summary of Findings

This study sought to demonstrate the identifiable relationships between a non-verbal

intelligence assessment and an emotional intelligence assessment for educators and researchers

regarding the role of emotions in complex, cognitive problem solving situations by college

students. There are several important findings from the study. The relationship demonstrated

between the subscales of the Mayer-Salovey-Caruso Emotional Intelligence Test and the General

Ability Measure for Adults provides some insight as to how emotional intelligence and general

intelligence may interact with one another when used in tandem in an academic setting. In

addition, the third hypothesis results indicate, through one of the analyses of the subscales, that

the Overall GAMA IQ score is a significant predictor of the MSCEIT Understanding Emotions

(UE) subscale when controlling for the students’ GPA. Furthermore, when controlling for the

Overall GAMA IQ scores, GPA is a significant predictor of Managing Emotions and Perceiving

Emotions.

Lastly, it is believed that further contributions of this study are the addition to the

knowledge base in Educational Psychology concerning the relationships between the emotional

and cognitive intelligence of college students and a better understanding of the role that emotions

play when college students are trying to solve complex cognitive problems.

The findings from the analyses are detailed through the stated hypotheses and associated

research questions in the paragraphs that follow. Notable effects are included for the

relationships among the subscales on the Mayer-Salovey-Caruso Emotional Intelligence Test and

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the General Ability Measure for Adults; relationships concerning gender, grade point average,

and general intelligence; and emotional and general intelligence as related to grade point

average.

Subscale Relationships between the MSCEIT and GAMA

Hypothesis A: There is a positive relationship, or correlation, between each of the subscales on

the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and each of the subscales on

the General Ability Measure for Adults (GAMA).

The completion of both the Mayer-Salovey-Caruso Emotional Intelligence Test and the

General Ability Measure for Adults by the 84 participants provided an overview of how the two

assessments interact with one another when taken in conjunction during a single sitting. The

analysis of the subscale scores on both assessments demonstrated a moderate, positive

relationship with a canonical correlation of .506 between the two sets of scores (see Table 14).

This finding demonstrates the amount of shared variance between the two assessments and the

common dimensions. Further analysis showed that the GAMA Analogy subtest had the strongest

relationship with the MSCEIT Understanding Emotions subtest, followed by the GAMA

Sequence and then the GAMA Construction subtests (see Table 8).

Therefore, previous research concerning the relationship between emotional and general

intelligence was further supported using the MSCEIT and GAMA assessments (Barchard, 2003;

Evenson, 2007; Mayer & Salovey, 1997; Mayer, Robert, & Barsade, 2008; Schutz & DeCuir,

2002).

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Gender, Emotional Intelligence, and Grade Point Average

Hypothesis B: Females will demonstrate overall higher grade point averages than males

as well as overall higher emotional intelligence scores as measured by the MSCEIT assessment.

Previous studies have indicated that there are distinct differences between females and males

concerning emotional intelligence, coping, and academic achievement (Scharfe, 2000; Castro-

Johnson & Wang, 2003; Baron-Cohen, 2003; MacCann, Fogarty, Zeidner, et al., 2011).

The testing of Hypothesis B was evaluated using a series of separate standard regression

analyses that employed the use of the Total MSCEIT Score and then separate, individual

analyses for each of the subscales. For the Total MSCEIT Score, the results of the standard

regression analysis did not indicate a significant difference between females and males on GPA

and the Total MSCEIT assessment: Even though females as a whole possess higher grade point

averages, females and males proved to be the same on this variable. Therefore, this finding did

not support the hypothesis that females would earn a higher GPA and also score higher on the

MSCEIT assessment. This finding is also in contradiction to some of the previous literature that

states that females will not only have higher grade point averages, but they will also prove to be

better at overall emotional perception, management, and utilization (Freudenthaler, Neubauer, &

Haller, 2008; Scharfe, 2000; Castro-Johnson & Wang, 2003; Baron-Cohen, 2003; MacCann,

Fogarty, Zeidner, et al., 2011).

There are several possible explanations for the above findings. One explanation may be

that the final sample size was smaller than originally anticipated with a total of 57 females and

27 males. There were at least five outlier scores (ranging from 164.90 to 165.31) for males on the

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MSCEIT Understanding Emotions subscale, however, the researcher was hesitant to discard the

outlier scores given the even smaller sample size that would result for males. The higher scores

on the MSCEIT Understanding Emotions subscales for the males would have also contributed to

a higher Total MSCEIT score for these individuals, thus further skewing the data and offering

limited to no support for the stated hypothesis.

The fourth regression analysis in this series analyzed differences between females and

males that exist on grade point average and the MSCEIT Understanding Emotions subscale. The

data revealed the following findings for this sub-analysis. Firstly, gender demonstrated a

significant contribution to the prediction of grade point average when controlling for the

MSCEIT Understanding Emotions subtest scores at p = .034, meaning that one’s gender can help

determine one’s ability to better understand emotions in oneself and others (see Table 20). Given

that females have higher grade point averages than males in the study, the results from this

analysis are aligned with previous literature findings as noted in the above paragraphs.

The additional standard regression analyses conducted using each of the MSCEIT

subscales (Perceiving Emotions, Facilitating Emotions, and Managing Emotions) produced

similar results obtained from the Total MSCEIT scores analysis. Gender was found to not be a

significant predictor of grade point average when controlling for the aforementioned subscales.

Hypothesis B was not supported in the additional analyses, and no differences were demonstrated

for females and males.

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Emotional Intelligence, General Intelligence, and GPA

The last set of analyses in this study evaluated the question of whether the relationship

between/among the variables of the Area, Branch, and Total Emotional Intelligence scores on the

Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and grade point average is

different for those students who exhibit a higher general IQ as measured by the General Ability

Measure for Adults (GAMA).

The analysis of the data for this last research question was conducted using a second set

of standard regression analyses to evaluate the differences. For the total of 84 participants, 80

self-reported GPA. The mean GPA for the participant sample was 3.17 on a 4.00 scale. Females

demonstrated overall higher GPAs than males: 3.25 versus 3.00.

The first regression analysis in this series analyzed the relationship between the MSCEIT

Managing Emotions subscale and grade point average (GPA) as modified by the Total GAMA

IQ score. It was found that GPA made the strongest unique contribution to explaining the

MSCEIT subscale of Managing Emotions and proved to be statistically significant at p = .026,

therefore indicating that grade point average is a significant predictor of the MSCEIT Managing

Emotions subscale when controlling for the GAMA IQ score.

The second standard regression analysis in this series analyzed the relationship of the

MSCEIT Facilitating Emotions subscale with the predictor of GPA as modified by GAMA IQ.

Once again, GPA made the strongest contribution to the explanation of the dependent variable, in

this case, the Facilitating Emotions subscale. However, in this analysis, the product of GPA and

GAMA IQ was found to not be significant, and therefore, did not demonstrate evidence of a

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relationship between the variables. This finding is in contradiction to the other four in this

regression series where significant results indicate that relationships may exist between the

academic environment and the ability to solve complex, cognitive problems.

The third standard regression analysis in this series, once again, provided some additional

insight into the relationship between the MSCEIT and GPA as modified by GAMA IQ. This

analysis evaluated the relationship between the MSCEIT Understanding Emotions subscale and

grade point average, as modified by the general IQ score (Overall GAMA IQ). In this case, the

GAMA IQ scores made the strongest, unique contribution to the explanation of the dependent

variable (MSCEIT subtest, Understanding Emotions). In addition, GAMA IQ is a significant

predictor of Understanding Emotions when controlling for the students’ grade point averages.

The significant finding of one’s ability to solve complex, cognitive problems (as

demonstrated via the GAMA assessment), aids in the ability to understand emotions in oneself

and others and offers support to the research question in that a different relationship is exhibited

for those students who possess a higher overall general IQ (as measured by the GAMA). In

addition, support is offered for previous findings that demonstrate that academic success in an

academic environment may be directly related to the ability to understand emotions when

solving complex, cognitive problems (Barchard, 2003; Evenson, 2007).

The last standard regression analysis in the series for this research question analyzed the

relationship between the MSCEIT Perceiving Emotions subscale and grade point average, as

modified by the Overall GAMA IQ score. Similar to the preceding regression analyses in this

series, grade point average once again made the strongest unique contribution to the explanation

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of one of the MSCEIT subscales: Perceiving Emotions. In addition, the dependent variable of

GPA makes a statistically significant contribution to the prediction of the MSCEIT subscale,

Perceiving Emotions, meaning that there is a relationship demonstrated between one’s ability to

perceive emotions in oneself and others and one’s grade point average. This analysis offers some

additional support to the research question, given the significant findings, that students who

exhibit a higher general IQ score (on the GAMA assessment) and higher grade point average

also demonstrate a different relationship on the MSCEIT subscale, Perceiving Emotions. This

finding may indicate that the ability to perceive different emotional reactions in one’s

environment may play a significant role in academic achievement.

Educational Implications

This study makes some important contributions to the Educational Psychology

knowledge base and academic understanding of educators and researchers regarding the role that

emotional intelligence plays in four-year, undergraduate academic settings. The analysis of the

emotional intelligence and general intelligence constructs through the chosen assessments, the

Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the General Ability Measure

for Adults (GAMA) general intelligence test, purposefully chosen because they had not been

previously used in such a study, provide some findings that can be used by colleges and

universities as they continue to develop their freshman and undergraduate on-campus services.

Relationships between the MSCEIT and GAMA Assessments

This study was unique in that it utilized the Mayer-Salovey-Caruso Emotional

Intelligence Test (MSCEIT) and a non-verbal general intelligence test, the General Ability

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Measure for Adults (GAMA), in a traditional, undergraduate college sample. Similar studies

previously conducted had not combined the two assessments used in this study in a four-year,

undergraduate setting. The particular use of a strictly non-verbal, general intelligence

assessment, the GAMA, was chosen to allow for easier interpretation by non-native English

speakers (Bracken & Naglieri, 2003). The use of these two assessments together adds to the

literature regarding emotional and general intelligence testing in a four-year higher education

institution.

After the completion of several of the testing sessions, participants in the study had

verbalized to the researcher that they had not had the opportunity to complete such assessments

before during their academic career and were intrigued by the non-verbal, GAMA, general

intelligence assessment. Several of the participants claimed that the assessments were “fun” as

well as challenging.

The results of the study did indicate that there exists a moderate relationship between the

two sets of subscales on the two assessments as analyzed via a canonical correlation. This

finding lends support to the theory that emotional intelligence may play a significant role in

general, cognitive abilities as measured by these two assessments within this particular sample

(Barchard, 2003; Evenson, 2007; Mayer & Salovey, 1997; Castro-Johnson & Wang, 2003).

Gender, Academic Achievement, and Emotional Intelligence

This study provides evidence that there also exists a moderate relationship among the

constructs of gender, grade point average, and emotional intelligence, however, there were

apparent contradictions concerning the proposed relationships between grade point average and

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the MSCEIT Perceiving Emotions and Managing Emotions subscales, particularly for males.

The result of the GAMA Overall IQ score and its relationship to the prediction of grade point

average, was confirmed (Table 11). The results of regression analyses and correlations (Table

12) demonstrate that students with lower grade point averages, in this sample, males, actually

had higher Perceiving Emotions and Managing Emotions subscale scores. These distinct

differences were demonstrated between females and males on the MSCEIT Understanding

Emotion subscale. Contrary to what the researcher had stated via hypothesis and previous

findings, males in the sample actually showed an overall better sense of Understanding Emotions

than their female counterparts (Table 10). T-tests were conducted and confirmed that males also

have a better sense of Managing Emotions per the MSCEIT, and with the combination of these

two subscales, an overall higher Total MSCEIT score (see pages 87 and 88).

The aforementioned results are in contradiction to some of the previous findings

concerning the relationships among the constructs of grade point average, gender, and emotional

intelligence and do not offer support to the researcher’s hypothesis. The researcher reviewed the

data and found that overall, at least five of the males had substantially high Understanding

Emotions subscale scores ranging from 164.90 to 165.31. Due to the smaller, final sample size

that consisted of 57 females and 27 males, the outliers for the MSCEIT Understanding Emotions

subscale scores therefore also increased these individuals’ Total MSCEIT scores and made an

unexpected impact on the findings.

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Limitations and Future Research

There are several recommendations that the researcher believes could improve the study.

The study overall provided insight into how emotional and cognitive intelligence variables relate

to one another in a traditional, undergraduate academic environment. Significant relationships

were found for several of the variables, including grade point average, emotional management,

and overall general intelligence (GAMA IQ). The researcher predicts that the study would be

more impactful if larger sample sizes were obtained from various institutions and the study itself

were conducted across multiple semesters. Given some of the findings that were in contradiction

to previous studies concerning gender, the study should be replicated to further evaluate whether

the higher emotional intelligence construct in males has perhaps evolved throughout the years.

Lastly, studies similar in nature have employed the use of larger, more diverse samples and

therefore, indicated stronger significant relationships between emotional intelligence and general

intelligence as related to academic achievement (MacCann, Fogarty, Zeidner, & Roberts, 2011;

Evenson, 2007; Barchard, 2003). The researcher therefore, believes that significant relationships

would be further demonstrated between emotional intelligence and academic achievement given

an extended length study over multiple academic semesters.

In addition, this study is limited by the small sample size obtained from a single

university. At the inception of the study, the researcher had proposed obtaining a sample of a

minimum of 100 participants across multiple institutions and cross-sections of humanities

courses. The final sample consisted of 84 participants from the Department of Education at

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North Carolina State University with limitations occurring due to IRB requirements across

institutions and additional resource constraints.

Furthermore, it would be of interest to extend the study beyond the traditional, four-year

academic institution and examine samples obtained from community colleges to better

understand the relationship between emotional intelligence and general intelligence in a two-year

academic environment, where transition to an academic environment is not compounded by

living away from home. Because of the relative homogeneity of the sample at the host university,

where 81.4% were Caucasian, future studies are recommended for populations of college

students that have not yet been the focus of research in this arena. For example, it might be of

interest to analyze a sample of 100 Latino students, using both the MSCEIT and GAMA

assessments to better understand the effects of emotional intelligence on academic achievement

in a sample where English is not the first language.

Finally, because grade point average (GPA) was self-reported in this study for the sample

population, out of the initial 86 participants, six neglected to self-report their GPA. A further

recommendation for future studies would be to find a way to obtain grade point averages without

the risk of missing or erroneous data.

Conclusion

For this study, the researcher examined the relationships between the constructs of

emotional and general (cognitive) intelligence by comparing the subscales of two assessments: the

Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the General Ability Measure

for Adults (GAMA). In addition, the relationship between the two assessments was further

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analyzed to determine to what extent gender played a role in accounting for differences. The

findings from this study contribute to the literature on the relationships among the constructs of

emotional intelligence, cognitive intelligence, and gender of undergraduate college students and

add to the knowledge base regarding the use of a non-verbal intelligence assessment in conjunction

with the Mayer-Salovey-Caruso Emotional Intelligence assessment (Barchard, 2003; Castro-

Johnson & Wang, 2003; Evenson, 2007; MacCann, Fogarty, Zeidner, & Roberts, 2011; Petrides,

Frederickson, & Furnham, 2004).

Through the data collection and analysis, the goals of this study were met in

consideration of the sample size. Some evidence of a relationship was demonstrated between the

subscales of the MSCEIT and GAMA assessments, particularly between the MSCEIT

Understanding Emotions subscale and GAMA IQ, thus confirming previous research concerning

the connections between some of the possible connections between emotional and cognitive

intelligence. Furthermore, when controlling for grade point average, GAMA IQ proved to be a

significant predictor of Understanding Emotions meaning that the ability to solve complex

problems can also help one better understand emotions in themselves and others.

Furthermore, the canonical correlation result demonstrated that the MSCEIT

Understanding Emotions subscale showed a strong relationship with the subscales of the GAMA,

in particular, the Analogy subscale. This finding lends additional support to previous research

concerning the linkages that may exist between emotional and cognitive ability (Barchard &

Hakstian, 2004; Lassiter, Bell, Hutchinson, & Matthews, 2001; Castro-Johnson & Wang, 2003).

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Lastly, the use of a non-verbal intelligence assessment, the GAMA, in combination with the

MSCEIT, had not previously been employed in such a study.

The study can be generalized across similar four-year colleges and universities but may

be limited due to the final sample size. It is expected that the study may also be replicated, using

the same two assessments, the MSCEIT and GAMA, across similar academic institutions. The

researcher believes that a more substantial sample size will provide additional support for the

relationships between emotional and general intelligence, gender, and grade point average. In

addition, as previously mentioned, the researcher plans to replicate the study in a community

college environment and with a sub-set of the population.

The study was based upon previous research that had incorporated the use of various

emotional and cognitive intelligence tests in higher education but none utilizing the MSCEIT and

non-verbal GAMA assessments. Because of the use of the non-verbal general intelligence

assessment, the GAMA, diversity was allowed in the sample that other cognitive intelligence

assessments do not accommodate as readily. Therefore, this study contributed to the existing

literature in educational psychology concerning the results obtained from using such instruments

in combination with one another in a traditional, four-year college environment.

In conclusion it is hoped that this study will assist college campuses, both traditional four

year institutions and community colleges, in several ways. Firstly, the results of this study

provide insight regarding the relationships between emotional and cognitive intelligence as

campus administrators, and constituents, continue to develop on-campus assistance and resources

for undergraduates to ensure smooth transitions for incoming students and continued academic

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and social success. The researcher further proposes that the understanding of how college

students manage their emotions when solving complex, cognitive problems, plays an important

role in the classroom during the completion of difficult tasks. This study provided additional

information through the results of the analyses demonstrating correlations among the subscales

of the two assessments. Furthermore, addition to the academic literature concerning the

construct of emotional intelligence for traditional college student populations is valuable.

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Appendix A

Recruitment Script used for Recruitment of Participants at North Carolina State University

Recruitment Script for “Investigating Relationships between the Subscales of the Mayer-

Salovey-Caruso Emotional Intelligence Test and the General Ability Measure for Adults General

Intelligence Test”

We are inviting you to participate in a research study to be conducted on a set date towards the

end of this semester. The purpose of this study is to examine the relationships among emotional

intelligence, general (cognitive) intelligence, and gender by comparing the subscales of two tests:

an emotional intelligence test and a general (cognitive or Intelligence Quotient) test. Previous

academic research and scholarly discussion on this topic has recognized that emotions often play

a role in one’s ability to solve complex problems in the classroom.

We will be asking you to complete a demographic profile sheet, which will include things like

your gender, self-reported Grade Point Average (GPA), etc. Then we will ask you to complete

two different assessments. The entire process should take approximately one and one-half to two

hours in total. We will also ask you to sign a consent document before the commencement of the

study, and any questions you have will be addressed.

121

One of the most important things that you need to know about this research is that you are free to

participate or not participate. There is no relationship between the proposed research (study) and

this class. You are also free to cease your participation part way through the study. In addition,

your decision to participate or not participate will have absolutely no impact on your grade for

this course/semester at North Carolina State University.

Thank you for considering participation in this research study.

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Appendix B

Copy of Informed Consent Agreement

INVITATION TO PARTICIPATE

You are being invited to take part in a research study that is being conducted as partial

fulfillment of the requirements for a doctoral degree (Doctor of Philosophy). This study is being

conducted in collaboration with Dr. John Nietfeld, Associate Professor, Educational Psychology,

College of Education, North Carolina State University.

Before you decide to participate in this study, it is important that you understand why the

research is being done and what it will involve. As a student at North Carolina State University,

please note that your participation in this study is not a course requirement, and your

participation, or lack thereof, will not affect your class standing or grade at NC State. This

research study is not related to this course/class.

Please take the time to read the following information carefully. Please ask the researcher if there

is anything that is not clear or if you need more information.

PURPOSE

The purpose of this study is to examine the relationships among emotional intelligence, general

(cognitive) intelligence, and gender by comparing the subscales of two tests: an emotional

intelligence test and a general (cognitive or Intelligence Quotient) test. Emotional Intelligence, or

EIQ, may be defined as the ability to recognize, understand, and manage emotions in order to

grow cognitively and emotionally (Mayer & Salovey, 1997).

DESCRIPTION OF THE PROCEDURES

Your expected time commitment for this study is one and one-half to two hours.

After the study is explained and all questions are answered, the remainder of the Research

Consent Form will be reviewed and you will be asked to sign the form (on page 7) if you agree

to participate in the study.

Next, codes to protect confidentiality will be assigned to each participant/subject. You will then

be asked to fill out some demographic forms associated with each of the tests using your new

“code.” You will also be asked to voluntarily provide your current Grade Point Average (GPA)

on the documentation.

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Next you will be asked to complete the two assessments (tests).

The first assessment will be distributed and will consist of an answer sheet and a test booklet.

After the instructions are communicated, and all questions have been answered, the timed

assessment will begin. There are 66 questions on this test, and it is timed. You will have 25

minutes to complete this test. Time notices will be communicated at 10 minutes and then a five

minute warning for time remaining.

The first assessment is a general, or cognitive, intelligence test. This is similar to an Intelligence

Quotient (IQ) Test but is non-verbal in nature. The test questions are pictorial in nature and

consist of four types of items: Matching, Sequences, Analogies, and Construction. The Matching

questions require you to choose a picture from the six presented that best matches the sample

(stimulus) shown in the figure. The Sequences questions ask that you determine the next

“picture” in a sequence, or what comes next. The Analogies questions ask that you choose a pair

of pictures (shapes) that most resembles the one shown in the sample (stimulus). The

Construction questions show pieces of a “puzzle” and ask that you mentally manipulate the

pieces to create a single picture.

You are expected to answer as many of the 66 questions as possible during the allowed 25

minutes. When time is called, answer sheets and test booklets will be collected. There will then

be a short break before the commencement of the second assessment.

The second assessment is an emotional intelligence test. This assessment is an untimed multiple

choice test and should take approximately 30-45 minutes to complete. There are 141 questions

that will measure four of your emotional intelligence “abilities.” The abilities are measured on

four areas of emotional intelligence: Perceiving (Identifying) Emotions, Facilitating Thought

(Using Emotions), Understanding Emotions, and Managing Emotions. The questions concerning

Indentifying Emotions may present a photograph of a person and ask you to rate on a scale of 1 –

5 how happy the person in the photograph appears to be. The questions dealing with Using

Emotions may ask you to rate on a scale of 1-5 how useful it would be to feel a certain way

(happy, tense, sad) in a certain situation (during a job interview). The Understanding Emotions

questions occur typically in a multiple choice format and ask you to fill in the blank with one of

the presented choices about how a character may feel in a scenario. The Managing Emotions

questions present a scenario and ask you to rank on a scale of 1-5 three separate actions in

relation to the presented scenario.

Once you have completed the emotional intelligence assessment, you may turn in any remaining

materials and any additional questions you may have will be answered. You will then be excused

from the session and no additional effort will be required on your behalf.

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DISCOMFORTS AND RISKS

There is a possible risk of physical discomfort due to the length of time that it will take to

complete the two assessments (the emotional intelligence and general intelligence tests). It is

expected that completion time for the assessments, including the introduction by the researcher,

the completion of the preliminary data sheets, and any questions that need to be answered either

before or after the administration of the assessments, may take up to one and one-half to two

hours. In addition, there may be some discomfort associated with the idea of being tested or

answering questions that may seem ambiguous in nature (test anxiety).

RISKS DURING PREGNANCY

There are no additional known risks or discomforts associated with this study for those who may

be pregnant.

EXPECTED BENEFITS

There will be no direct benefit to you for your participation in this study. However, it is hoped

that the information obtained from this study will help researchers and educators further develop

their understanding of the potential role that emotions play when college students are trying to

solve complex cognitive problems.

WITHDRAWL FROM THE STUDY

You may terminate your involvement (withdraw from the study) and/or refuse to answer any

particular question at any time without any penalty.

COSTS AND PAYMENTS

There are no costs to you for your participation in this study.

For participation in this study, a drawing will be held, and the “winner” will receive a $40.00 gift

card.

CONTACTS

Name: Tabitha S. Harper, Graduate Student at The Catholic University of America

Address (Home): 559 Heligan Lane, Unit 2, Livermore CA 94551

Phone: (Work): (510) 271-4609; (Cell): (703) 216-0169; (Home): (925) 292-8751

E-mail: 17Harper@cardinalmail.cua.edu

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Or:

Name: Dr. John Nietfeld, Associate Professor, Educational Psychology, College of Education

Address: 602D Poe Hall, Campus Box 7801, Raleigh, NC, 27695

Phone: (919) 513-7444

E-mail: john_nietfeld@ncsu.edu

RESEARCH SUBJECT RIGHTS

I have read or have had read to me all of the above.

_____________________ has explained the study to me and answered all of my questions. I

have been told of the risks or discomforts and possible benefits of the study.

I understand that I do not have to take part in this study, and my refusal to participate will

involve no penalty or loss of rights to which I am entitled. I may withdraw from this study at

any time without penalty or loss of benefits to which I am entitled.

I understand that any information obtained as a result of my participation in this research study

will be kept as confidential as legally possible.

The results of this study may be published, but my records will not be revealed unless required

by law.

NOTE

If I have any questions about the conduct of this study or my rights as a subject in this study, I

have been told that I can contact The North Carolina State University Sponsored Programs &

Regulatory Compliance (SPARCS) Office at: 2701 Sullivan Drive, Suite 240, Campus Box

7514, Raleigh, NC, 27695-7514. Main phone: (919) 515-2444.

I understand my rights as a research subject, and I voluntarily consent to participate in this study.

I understand what the study is about and how and why it is being done. I will receive a signed

copy of this consent form.

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I certify that I am 18 years of age or older.

___________________________________________ ___________________________

Subject’s Signature Date

______________________________ ___________ ___________________________

Signature of Subject’s Representative* Date Subject’s Representative (Print)

______________________________ ___________ ___________________________

Signature of Witness Date Witness (Print)

___________________________________________ ____________________________

Signature of person obtaining consent** Date

___________________________________________ ____________________________

Signature of Principal Investigator Date

*Only required if subject is not competent.

**Only required if not investigator.

REFERENCE

Mayer, J.D. & Salovey, P. (1997). What is emotional intelligence? In P. Salovey & D.J.

Sluyter (Eds.), Emotional development and emotional intelligence (pp. 3-31). New York:

Basic Books.

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Appendix C

Administrative Procedures for Delivery of the General Ability Measure for Adults (GAMA) and

the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)

After completion and collection of the Informed Consent Agreements, participants in the session

(average of 20 per session) were then asked to complete the demographic profiles for both the

GAMA and the MSCEIT for the following fields: test date, date of birth, class year, gender, and

self-reported Grade Point Average (G.P.A.). After the participants completed the demographic

profiles they were instructed that they would first complete the General Ability Measure for

Adults (GAMA) and that it would be timed with a completion point of 25 minutes. General

administrative procedures are outlined below and then respectively in Appendices D and E for

the GAMA and MSCEIT assessments.

Specifics of the General Administrative Procedure

1. Have the participants sign in on the relevant session sign-in sheet. Each session sign-in

sheet is dated for that particular session and requires the following information be

completed: name, contact information (email and phone), class year, and gender.

2. Hand out the Research Consent Forms to each participant.

3. Read through the Research Consent Forms with the participant. Read the form in its

entirety out loud and have the participants follow along.

4. Ask if there are any questions about the form or the study. Answer all questions.

128

5. Have each participant sign and date the Research Consent Form in the following manner:

write name and date at the top of page one, and then initial and date at the bottom of each

consecutive page. On page seven, the participant must sign her or his full name and date.

6. Verbally remind the participants that their participation in the study is strictly voluntary

and that if at any time they wish to withdraw from the study, they may do so without

penalty or question.

7. Collect and store all Research Consent Forms.

8. Proceed to General Ability Measure for Adults administration.

129

Appendix D

Administrative Procedures for Delivery of the General Ability Measure for Adults

1. Show participants the copies of the GAMA test booklet and the GAMA self-scoring

answer sheet.

2. Pass out the GAMA answer sheets (pre-coded) to each participant. Note that the MSCEIT

answer sheets are within the folded GAMA answer sheets. The MSCEIT answer sheets

are also pre-coded.

3. Tell participants to place the MSCEIT demographic sheet to the side for the duration of

the GAMA assessment.

4. Pass out the GAMA test booklets to the participants.

5. Tell participants to leave the test booklet closed until instructed to open it.

6. Tell participants to open their GAMA test booklet to the first page where “Sample

Directions” is written at the top of the page.

7. Make certain that all participants are on the correct page.

8. Read the “Sample Directions” out loud to the participants so that they may follow along

in their test booklets.

9. Ask if participants have any questions about the “Sample Directions.”

10. If there are no questions, or once questions have been answered, instruct the participants

to complete the three sample items and record their answers in the correct place on the

corresponding answer sheet. Instruct participants to stop and put down their pencils once

they have completed the sample questions.

130

11. Once the participants have completed the “Sample Items,” and all questions have been

answered, read the script for the actual assessment.

12. Instruct participants to begin. Start timing for 25 minutes. Throughout timing, provide

“warnings” at 10 and five minutes (remaining).

13. At the conclusion of the 25 minute testing session, collect GAMA booklets and answer

sheets from all participants.

14. Proceed to Mayer-Salovey-Caruso Emotional Intelligence Test administrative

procedures.

Script for the Administration of the General Ability Measure for Adults (GAMA)

1. You will have 25 minutes to complete the problems in the GAMA test book.

2. Work as carefully as you can and complete as many of the problems as you can.

3. Make certain to completely erase the markings should you make a mistake.

4. You will be stopped at 25 minutes and the books and answer sheets will be collected.

5. Are there any questions?

6. Please begin.

131

Appendix E

Administrative Procedures for Delivery of the Mayer-Salovey-Caruso Emotional Intelligence

Test (MSCEIT)

1. Show participants copies of the MSCEIT test booklet and the MSCEIT bubble answer

sheet.

2. Pass out the MSCEIT test booklets to the participants.

3. Have participants retrieve their pre-coded MSCEIT bubble/demographic answer sheets

(from when they were previously handed out enclosed in the folded GAMA answer

sheet).

4. Tell participants to leave the test booklet closed until instructed to open it.

5. Instruct participants to make certain that the ID # on their individual MSCEIT bubble

sheet matches that on the front of their GAMA answer sheet.

6. Explain to the participants that there are eight separate sections to complete within the

MSCEIT booklet and that there is no time limit. They should read the individual

instructions for each section prior to answering the questions. Answer questions as

needed.

7. Once all preliminary questions have been answered, instruct the participants to open up

their MSCEIT test booklets, read the instructions for Section A, and commence the

assessment.

132

8. Because the MSCEIT is untimed, participants will not all complete the assessment at the

same time. As the individual participants complete the MSCEIT, collect both the bubble

answer sheet and the MSCEIT test booklet.

9. Review MSCEIT answer sheets and booklets for correct markings (for example, not more

than one answer is marked per question).

10. Answer any remaining questions. Confirm that the participant knows how to contact the

researcher. Thank the participants once again for their time.

133

Appendix F

Codebook for SPSS Data Entry

Variable SPSS variable name Coding instructions

Identification number ID Number assigned to each participant

Gender Sex/gender 1 = Males

2 = Females

Age Age Age in years

Grade Point Average GPA Actual GPA of participant

GAMA Subtest Scaled score GAMA Match Actual scaled score for Matching

Matching

GAMA subtest scaled score GAMA Analogy Actual scaled score for Analogies

Analogies

GAMA subtest scaled score GAMA Sequence Actual scaled score for Sequences

Sequences

GAMA subtest scaled score GAMA Construction Actual scaled score for Construction

Construction

134

GAMA Sum of Subtest GAMA sum of subtest scores Actual sum of scores

scaled score

Total GAMA IQ Score Overall GAMA IQ Score Actual Total GAMA IQ Score

MSCEIT Subtest Score MSCEIT PE Actual total score for PE Branch

Perceiving Emotions

MSCEIT subtest score MSCEIT FE Actual total score for FE Branch

Facilitating Emotions

MSCEIT subtest score MSCEIT UE Actual score for UE Branch

Understanding Emotions

MSCEIT subtest score MSCEIT ME Actual score for ME Branch

Managing Emotions

Overall MSCEIT Score as a MSCEIT TOTAL CAT 1 = Scores 130+

categorical variable 2= Scores 120 – 129

3 = Scores 110 – 119

4 = Scores 100 – 109

5 = Scores 90 – 99

6 = Scores 70 – 89

7 = Scores 69 or les

135

MSCEIT subtest categorical MSCEIT PE CAT 1 = Scores 130+

score: Perceiving Emotions 2= Scores 120 – 129

3 = Scores 110 – 119

4 = Scores 100 – 109

5 = Scores 90 – 99

6 = Scores 70 – 89

7 = Scores 69 or less

MSCEIT subtest categorical MSCEIT UE CAT 1 = Scores 130+

score: Understanding Emotions 2 = Scores 120 – 129

3 = Scores 110 – 119

4 = Scores 100 – 109

5 = Scores 90 – 99

6 = Scores 70 – 89

7 = Scores 69 or less

MSCEIT subtest categorical MSCEIT FT CAT 1 = Scores 130 +

score: Facilitating Emotion (thought) 2 = Scores 120 – 129

3 = Scores 110 – 119

4 = Scores 100 – 109

5 = Scores 90 – 99

6 = Scores 70 – 89

7 = Scores 69 or less

136

MSCEIT subtest categorical MSCEIT ME CAT 1 = Scores 130 +

score: Managing Emotions 2 = Scores 120 - 129

3 = Scores 110 – 119

4 = Scores 100 - 109

5 = Scores 90 – 99

6 = Scores 70 – 89

7 = Scores 69 or less

MSCEIT Area Score MSCEIT EXP EIQ Actual Experiential EIQ Score

Experiential EIQ

MSCEIT Area Score MSCEIT STRA EIQ Actual Strategic EIQ Score

Strategic EIQ

MSCEIT Positive-Negative MSCEIT BIAS Actual bias score

Bias Score

MSCEIT Scatter Score MSCEIT SCAT Actual scatter score

GAMA subtest classification GAMA CLASS MAT 1 = High: 90 to 130+

variable score: Matching 2 = Low: 90 and below

GAMA subtest classification GAMA CLASS ANA 1 = High: 90 to 130 +

variable score: Analogies 2 = Low: 90 and below

137

GAMA subtest classification GAMA CLASS SEQ 1 = High: 90 to 130 +

variable score: Sequences 2 = Low: 90 and below

GAMA subtest classification GAMA CLASS CON 1 = High: 90 to 130+

variable score: Construction 2 = Low: 90 and below

Product of gender and the TGENDPEMSCEIT

MSCEIT Perceiving Emotions

subtest score

Product of gender and the TGENDFEMSCEIT

MSCEIT Facilitating Emotions

subtest score

Product of gender and the TGENDMEMSCEIT

MSCEIT Managing Emotions

subtest score

Product of gender and the TGENDUEMSCEIT

MSCEIT Understanding Emotions

subtest score

Product of grade point average TGPAGAMAIQ

and Overall GAMA IQ score

138

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