Development of Math Anxiety Rating Scale

Math Anxiety Rating Scale

Development of Math Anxiety Rating Scale

Draper, Shaira

Liwanag, Anette L.

Serafico, Monique Anne

Villafuerte, Arianne Joie

St. Paul University Manila


Abstract

Math Anxiety is the main subject of this scale development paper. A group of researchers have

come up to develop a Math Anxiety Rating Scale because of the gaps they have found on the

past researches about the Math Anxiety Test. A test consisting of 30 items were constructed by

the researchers through following and understanding underlying constructs and theories that

cover Math Anxiety. Therewith, two main dimensions that serve as the factors of encountering

Math Anxiety, those are the Cognitive dimension and the Affective Dimension. From the past

researches, there have been arguments on what really are the factors that cover Math Anxiety.

That was the gap that the researchers were trying to answer in. Samples of 291 non-math major

college students were the respondents of the Math Anxiety Rating Scale. The test was conducted

with two different approaches. Data gathering was simultaneously done through (1) Direct

Approach; paper-and-pencil-test wherein they and (2) through online testing. The data were

encoded to IBM software called SPSS. This tool was able to help the researchers find out the

result on the different statistical techniques. Relevant results from the SPSS made the researchers

to go back again to their test and observe if there must be items to be eliminated. Statistical

results such, Cronbach Alpha .970, suggested a good internal consistency estimate of items.

KMO Measure, .963 suggesting an acceptable sampling adequacy, Bartlett’s Test of Spherecity

as 0.000. As a conclusion, this current study can still be developed and improved. There were

evident conflicts between the theoretical basis of the researchers and the results given by the

SPSS.


Development of Math Anxiety Rating Scale

A group of college students have come up with scale development paper that focuses the

anxiety of (also) college students towards Math in Academic setting. As defined, Mathematics,

either can be a major subject or a minor subject to college students significantly gives anxiety

especially in school (academic setting) when doing activities such as homeworks, boardworks in

a class discussion and seatworks after a series of lessons in Mathematics. Mathematics is a

subject which elicits many different attitudes and feelings.

Among these attitudes are general feelings towards the subject, such as liking or

enjoyment, and more specific attitudes such as confidence and anxiety. There is a considerable

body of studies which examines attitudes towards mathematics, one of the earliest reviews being

that by Feierabend (1960, in Aiken, 1970) A marked increase in the number of articles and

dissertations in the ten years following Feierabend's report provided the stimulus for a

reappraisal by Aiken (1970). As anxiety and mathematics have been combined to for a one

construct which what we call Math Anxiety, we can simply define that this math anxiety often

leads to avoidance of math by those who experience it and it is noticeable that students who are

anxious, bored and fearful towards math or who do not comprehend the importance of math in

professional and personal life are the once most likely to avoid the study of math.

In this present study of the researchers, they have found the two main constructs that

cover Math Anxiety. A multidimensional rating scale is developed to find out if really is these

two factors affect anxiety towards Mathematics and these two dimensions are the Cognitive

Factor and the Affective Factor.


A lot of scales were developed and constructed to measure an individual’s math anxiety.

In this research paper, a Math Anxiety Scale is being developed. Through underlying theories

that make up this Math Anxiety Scale and definitions of constructs, the researchers will be able

to construct and even more, develop a Math Anxiety Scale with multi-dimensions.

Construct and Construct Definition

Math Anxiety is found to have no single underlying theory. There is a noticeable lack of

any clear theoretical basis for mathematics anxiety, in either the research or the treatment

literature. Parallel to this, there also no single and fixed definition that could describe Math

Anxiety. However, there were authors and theorists that gave Math Anxiety specific definitions

despite of it, being a wide range of study. Math Anxiety was not only described through a single

dimension or a factor. Since there were theoretical considerations, researchers found that there

are number of theories which might be applicable, these being general anxiety theories and

theories taken from the field of test anxiety.

Considerations to these many applicable theories lead the researchers to define Math

Anxiety with two dimensions; Cognitive and Affect.

Mathematics

Mathematics is a subject which elicits many different attitudes and feelings. Among these

attitudes are general feelings towards the subject, such as liking or enjoyment, and more

specific attitudes such as confidence and anxiety. Feierabend (1960, in Aiken, 1970

Math Anxiety


Feelings of tension and anxiety that interefere with the manipulation of numbers and

the solving of mathematical problems in a wide variety of ordinary life and academic

situations (Richardson and Suinn, 1972).

Affective Anxiety

Refers to the emotional component of anxiety, feelings of nervousness, tension, dread,

fear, and unpleasant physiological reactions to testing situaions

Cognitive Anxiety

Refers to the worry component of anxiety, which often displayed through negative

expectation, preoccupation with and self-deprecatory thoughts about an anxiety-causing

situation.

Review of Literature

Mathematics. Mathematics is the science of quantity. It is the classification and study of

all possible patterns (Sawyer, 1995). Mathematics is also a gateway to engineering, scientific and

technological fields (Mahmood, 2011). Mathematics, either can be a major subject or a minor

subject to college students significantly gives anxiety especially in school (academic setting)

when doing activities such as home works, board works in a class discussion and seat works after

a series of lessons in Mathematics. Mathematics is a subject which elicits many different

attitudes and feelings. Among these attitudes are general feelings towards the subject, such as

liking or enjoyment, and more specific attitudes such as confidence and anxiety. There is a

considerable body of studies which examines attitudes towards mathematics, one of the earliest

reviews being that by Feierabend (1960, in Aiken, 1970) A marked increase in the number of

articles and dissertations in the ten years following Feierabend's report provided the stimulus for


reappraisal by Aiken (1970). As anxiety and mathematics have been combined to for a one

construct which what we call Math Anxiety, we can simply define that this math anxiety often

leads to avoidance of math by those who experience it and it is noticeable that students who are

anxious, bored and fearful towards math or who do not comprehend the importance of math in

professional and personal life are the once most likely to avoid the study of math. A lot of scales

were developed and constructed to measure an individual’s math anxiety. In this research paper,

a Math Anxiety Scale is being developed. Through underlying theories that make up this Math

Anxiety Scale and definitions of constructs, the researchers will be able to construct and even

more, develop a Math Anxiety Scale with multi-dimensions. Math Anxiety is found to have a no

single underlying theory. There is a noticeable lack of any clear theoretical basis for mathematics

anxiety, in either the research or the treatment literature. Parallel to this, there also no single and

fixed definition that could describe Math Anxiety. However, there were authors and theorists that

gave Math Anxiety specific definitions despite of it, being a wide range of study. Math Anxiety

was not only described through a single dimension or a factor. Since there were theoretical

considerations, researchers found that there are number of theories which might be applicable,

these being general anxiety theories and theories taken from the field of test anxiety.

Considerations to these many applicable theories lead the researchers to define Math Anxiety

with two dimensions; Cognitive and Affect. Test anxiety and mathematics anxiety were among

the different types of anxiety being studied in the 1950's and since that time mathematics anxiety

research has grown in parallel with, although lagging slightly behind, research in the field of test

anxiety. In spite of an apparently close relationship between mathematics anxiety and test

anxiety there has been less cross-fertilization between these two fields than would be expected.

Of the many researchers into test anxiety only Suinn (1970, 1971, 1972, 1982, 1988) and


Richardson (1972, 1973, 1980) appear to have shown a consistent interest in mathematics

anxiety. Other theory of test anxiety involves its dimensionality. Where areas test anxiety was

originally seen as a unidimensional construct. Libert and Morris (1967) were first to propose a

two-factor model of test anxiety that distinguished between an affective “emotionality” and a

cognitive worry dimension of test anxiety. More recently, Deffenbacher has noted that

emotionality may relate more to the degree of awareness or attention paid to affective-

autonomic arousal rather than to the level of arousal per se (1980, p. 123). According to

Richadson and Suinn (1972), feelings of tension and anxiety interfere with the manipulation of

numbers and the solving of mathematical problems in a wide variety of ordinary life and

academic situations. Liebert and Morris (1967) distinguished two components of math anxiety;

affective and cognitive. Affective Anxiety refers to the emotional component of anxiety, feelings

of nervousness, tension, dread, fear, and unpleasant physiological reactions to testing situations.

Cognitive Anxiety refers to the worry component of anxiety, which often displayed through

negative expectation, preoccupation with and self-deprecatory thoughts about an anxiety-causing

situation.

Measurement and Dimensionality of Mathematics Anxiety

By: James B. Rounds, Jr., and Darwin D. Hendel

The purpose of this study was to examine the dimensionality of one such measure of

mathematics anxiety, the Mathematics Anxiety Rating Scale (MARS). The results of the study

indicated that contrary to previous statements (Richardson & Suinn, 1972), mathematics anxiety

as measured by the MARS is not a unidimensional construct. Two factors were identified and

labeled Mathematics Test Anxiety and Numerical Anxiety. The results of this study suggest that


for the female sample, the domain of mathematics anxiety as measured by the MARS is best

described not as anxiety about everyday numerical manipulation, but primarily as test anxiety

and secondarily as anxiety associated with mathematics courses. The data indicate that the

female participants were relatively unconcerned about numerical manipulation in the context of

daily activities. The distribution of the Mathematics Test Anxiety Scale and Numerical Anxiety

Scale scores indicate that anxiety about mathematics is situationally specific and not Tran

situational. Also, the article suggests that the usefulness of present instrumentation of

mathematics anxiety is hampered by the lack of an adequate definition of mathematics. Results

also said that mathematics anxiety as conceptualized by Richardson and Suinn (1972) can be

measured with the factor-derived scales. Compared to the 98-item MARS, these two 15-item

factor-derived scales will take less time to complete. Since the assessment of a client's status

with multifactorial rather than uni-factorial measures may mask changes, Bergin and Lambert

(1978) have recommended the development of indices that are more situation specific than the

presently used global-improvement indices. Another assessment tool that may be helpful for

participants in mathematics anxiety treatment programs is a measure of test anxiety. Results from

the present study also showed that the participants were almost as apprehensive about tests in

general as tests in particular (i.e., mathematics tests). The MARS factor-derived scales provide

descriptive information; they do not provide explanations of anxiety about mathematics.

Attention to the client's background data can be useful in exploring possible explanations, as for

example, in the present study in which a mean of 16.5 years had elapsed since the participants

had had formal mathematics training. It is a reasonable assumption that anxiety about

mathematics can occur when future career and educational goals in part depend on success in

mathematics courses for which an individual feels inadequately prepared and insufficiently


experienced. Until more is known about the characteristics of individuals who elect to enter

mathematics-anxiety treatment programs, counselors may want to supplement the MARS factor-

derived scales with other types of measures (e.g., mathematics attitude scales, mathematics skill

tests) to aid in the description of individual constellations of mathematics difficulties. The

application of multimodal treatment plans (see Mathison, Note 1) emphasizing some

combination of remediation or math-skills building, mathematics curricular intervention (e.g.,

math labs, individualized instruction), and psychological intervention seems to be sound strategy

for counselors involved in mathematics-anxiety treatment programs. In terms of psychological

intervention, it should be noted that the cognitive and self-control treatments as presented by

Suinn and Richardson (1971) and Hendel and Davis (1978) seem more effective in reducing

mathematics anxiety than do insight-oriented counseling and systematic desensitization.

Mathematics anxiety has been postulated—especially for women—to affect enrollment in

mathematics courses, learning of mathematics, and mathematics performance, thereby affecting

a student's educational and career goals. These results and the results from this study suggest that

the concept and/or measures of mathematics anxiety may need revision to be of sufficient value

to enrich our understanding of mathematics learning and performance.

www.researchgate.net/...Rounds/.../0912f5123d9e6bd134000000.pdf

The Affective and Cognitive Dimensions of Math Anxiety: A Cross-National Study

By: Hsiu-Zu Ho, Deniz Senturk, Amy G. Lam, Jules M. Zimmer, Sehee Hong, and Yukari

Okamoto


This study focuses on math anxiety, comparing its dimensions, levels, and relationship with

mathematics achievement across samples of 6th-grade students from China, Taiwan, and the

United States. First, the study fills in research gaps showing that the heuristic distinction between

affective and cognitive dimensions of math anxiety found in the United States is also relevant for

samples in other nations, specifically China and Taiwan. Second, the findings also generalize the

negative effect of math anxiety, specifically the affective factor, on mathematics achievements in

samples in China and Taiwan. Given the possibility that the high-achieving Asian students may

not experience debilitating math anxiety, the finding that affective math anxiety was also a

debilitating factor in mathematics performance in Asian samples is significant. The distinction

between affective and cognitive effects on performance has important implications for

intervention strategies. The study cannot presume that the etiology of math anxiety is the same

across the three cultures; hence further research would be needed to examine the effectiveness of

such interventions in reducing math anxiety in Asian students. Although the desirability of

facilitative tensions in learning situations is recognized, environments that provoke nervousness,

dread, and fear are not in the best interest of students.

http://mina.education.ucsb.edu/ho/documents/%2338.pdf

Current Study

According to Bergin and Lambert (1978), the development of indices that are more

situation specific than the presently used global-improvement indices would be more useful. This

gap was not filled by further scale developments made so the researchers came to a decision to

make a scale about specific setting: academic. Mathematics, either can be a major subject or a

minor subject to college students significantly gives anxiety especially in school (academic


setting) when doing activities such as home works, board works in a class discussion and seat

works after a series of lessons in Mathematics. Tertiary students have been chosen due to lack of

thorough studies about Math Anxiety which particularly concentrates on them. In the previous

studies, lack of attention towards the clients’ backgrounds has been suggested to be given more

focus. Clients’ backgrounds can be useful in providing sufficient explanations as to why these

people have this anxiety towards math. In line with this, future researches can be made by

finding these explanations that would lead to the advancements of solutions and treatments that

could alleviate math difficulties/anxieties. With this gap, the researchers have chosen non-math

major college students as their primary source of data and subjects. Non-math major college

students might be helpful in providing more concrete explanations as to why they are anxious

towards math (e.g. think they lack of advanced mathematical training). Another gap observed is

the clarification of the potential distinction between cognitive anxiety that serves as a facilitator

and cognitive anxiety that is a debilitator but the researchers have not focused on this particular

opening.

The researchers have observed research gaps to fill in the course of the Math Anxiety

Scale history. A lot of scales were developed and constructed to measure an individual’s math

anxiety. Through underlying theories that make up this Math Anxiety Scale and definitions of

constructs, the researchers will be able to construct and even more, develop a Math Anxiety

Scale with multi-dimensions: affective and cognitive. The main purpose of this scale

development is to develop a scale which is directed to measure Math Anxiety of Non-math major

tertiary students. In the hope of promoting further research that will advance understanding of

the relationship between anxiety of students towards math and their goal/career orientation.


Item Writing

The researchers have conducted a thorough study about Math Anxiety in educational setting,

brought up relevant data about the construct, review of related literature, defining the construct

Math Anxiety as feelings of tension and anxiety that interfere with the manipulation of numbers

and the solving of mathematical problems in a wide variety of ordinary life and academic

situations. (Richardson and Suinn, 1972) With the gathered theory, the items are brought up by

the following manifestations and attitudes when anxiety arises. We have come up of two

proponents from our definition and construct by the following:

1. Affective Anxiety refers to the emotional component of anxiety, feelings of nervousness,

tension, dread, fear, and unpleasant physiological reactions to testing situations. (Liebert

and Morris, 1967)

2. Cognitive Anxiety refers to the worry component of anxiety, which often displayed

through negative expectation, preoccupation with and self-deprecatory thoughts about an

anxiety-causing situation. . (Liebert and Morris, 1967)

The researchers formed the test questionnaires that can be an indicator of the two proponents

when solving mathematical equations in educational setting, such as seatwork, board work, class

recitation and homework. Initial item inventory consisted of 30 items. The following proponents:

affective anxiety comprised of 15 items and cognitive component also comprised of 15 items.

(See Appendix A. 1) Expert Validation however revisions were suggested to indicate the

following manifestations as before onset of encountering and solving mathematical equations,

avoid test questionnaires that rather assess self-efficacy, avoid double-negative propositions,

correct grammatical errors and expound ideas. The revised item inventory however remained

consisting of 30 items; Factor 1 (Cognitive) still comprised of 15 items and Factor 2 (Affective)


consisted of 15 items. The two dimensions were developed, revised and reviewed carefully

designed in order to avoid overlapping of the formulated definitions and constructs (See

Appendix A. 2)

Method

The researchers made the data gathering possible through two different approaches. First, is by

going room-to-room on different universities and colleges to encourage respondents who are non-math

majors to be part of their study and second, by online testing.

Participants

The data was gathered from 291 Non-math Major College Students, ranging from First to

Senior Year, either private or public of different universities. The sample ranged in age 17-20 to

years. 156 Male (53.61%) and 135 Female (46.39%). The sample was chosen through criterion-

based sampling. The key characteristic needed must be a non-math major undergraduate college

student. They have been picked due to their availability.

Instrument

A group of third year psychology students developed a scale which attempts to measure

anxiety of non-math major college students towards Math. The scale is a two-dimensional tool

which measures the affective and cognitive aspects of math anxiety in academic settings. The

affective dimension asked questions about the emotional component of anxiety while the

cognitive dimensions are questions that referred to the worry component of anxiety which occurs

because of math.

Statements are presented in a negative manner which of consists of the negative behavior,

emotion and attitude they manifests when encountered a Math problem or a question primarily


happening inside school, classroom/ class discussions which may applies into doing board

works, recitations and answering seatwork.

In total, there are 30 items and the response format used is the Likert-Type Scale. The

range captures the intensity of the participants’ response: Strongly Disagree, Disagree,

Somewhat Disagree, Somewhat Agree, Agree, and Strongly Agree.

Data Gathering Procedures

An indirect or questionnaire approach consisting of 30 items was used to explore the

following depth dimensions of the study. The data was gathered through online forms and paper-

and-pencil tests. The examiners asked if the participant is a non-math major college student

before he or she could partake into the study. The examiners explained to each participant that he

or she would answer a math anxiety test and all data collected would be given with outmost

confidentiality. The test only took about fifteen minutes or less of the participants’ time. None of

the participants was paid for participating and they partook voluntarily.

All responses collected in the online forms are encoded automatically through Microsoft Excel

Worksheets while the paper-and-pencil tests data were encoded manually.

Data Analysis

An IBM tool called SPSS was used to determine different statistical elements or to

present statistical analysis. This consists of the discussion of the different descriptive statistical

techniques used to compute for the Mean, Standard Deviation Skewness and Kurtosis.


The Mean is the arithmetic mean across the observations. It is the most widely used

measure of central tendency. On getting the mean, it does not only gives you the total summation

mean of all the items rather each mean of the 30 items of the Math Anxiety Rating Scale. On the

other hand, Standard Deviation is the square root of the variance. It measures the spread of a set

of observations. The larger the standard deviation is, the more spread out the observations are.

We define Skewness as the measure of the degree and direction of asymmetry. A symmetric

distribution such as a normal distribution has a skewness of 0, and a distribution that is skewed to

the left, e.g. when the mean is less than the median, has a negative skewness. Related to

Skewness is another technique known as Kurtosis. Kurtosis on the other is

In determining the number of factors the researchers still chose their conceptualization

and the theory of constructs they have researched although it can be also be distinguished

through a scree plot on which on the result they got from SPSS is only one (1) factor. The elbow

of the scree plot falls on one (1) which means there is only one factor. Promax, on the other way

around which is a good method for the items of the rating scale which is a Multidimensional with

highly correlated factors. Based also on the conceptualization of the researchers, the Cognitive

Factor and the Affective factor which are the two dimensions of the test show a high correlation.

Theoretically speaking, there are only few distinguishable differences from these two factors.

Nevertheless, they still differ psychologically. On developing a rating scale, sample is very

relevant. A method called Kaiser-Meyer-Olkin was used to determine if the sample was

adequate. Note that the value of KMO must be greater than .05 (>.0.5) to prove that the sample

was adequate. After identifying and knowing if the sample was adequate, it is important also to

know if there really is enough correlation among the items. The researchers used the Bartlett’s

Test of Sphericity. KMO & Bartlett’s Test of Sphericity is a measure of sampling adequacy that


is recommended to check the case to variable ratio for the analysis being conducted. In most

academic and business studies, KMO & Bartlett’s test play an important role for accepting the

sample adequacy. While the KMO ranges from 0 to 1, the world-over accepted index is over 0.6.

Also, the Bartlett’s Test of Sphericity relates to the significance of the study and thereby shows

the validity and suitability of the responses collected to the problem being addressed through the

study. For Factor Analysis to be recommended suitable, the Bartlett’s Test of Sphericity must be

less than 0.05. An Exploratory Factor analysis was done by the reaserchers to find out and see

the results of the different techniques on in descriptive statistics (mean, sd, Skewness and

Kutosis). EFA may require many different analyses involving different numbers of factors,

different types of rotation, and different sets of items that made the researchers look over again

on their test items because there might be problem on determining the factors of the test. CFA or

Confirmatory Factor Analysis on the other hand is used to test whether measures of a construct

are consistent with a researcher's understanding of the nature of that construct (or factor). The

goal of EFA is to identify factors based on data and to maximize the amount of variance

explained. The researcher is not required to have any specific hypotheses about how many

factors will emerge, and what items or variables these factors will comprise. If these hypotheses

exist, they are not incorporated into and do not affect the results of the statistical analyses. By

contrast, CFA evaluates a priori hypotheses and is largely driven by theory. CFA analyses

require the researcher to hypothesize, in advance, the number of factors, whether or not these

factors are correlated, and which items/measures load onto and reflect which factors. As such, in

contrast to exploratory factor analysis, where all loadings are free to vary, CFA allows for the

explicit constraint of certain loadings to be zero. The EFA does not only gives the descriptive

part, it also aids the researchers for the reduction of items and the rotation. The type of rotation


used in the development of the scale is Promax. This was used since the researchers constructed

the scale with two dimensional, or a multidimensional scale with highly correlated factors.

The Cronbach’s Alpha reliability test was used to determine if the established internal

consistency is as good as what the rule stated. Cronbach's alpha is a measure of internal

consistency, that is, how closely related a set of items are as a group. It is considered to be a

measure of scale reliability. A "high" value for alpha does not imply that the measure is

unidimensional. If, in addition to measuring internal consistency, you wish to provide evidence

that the scale in question is unidimensional, additional analyses can be performed. Exploratory

factor analysis is one method of checking dimensionality. Technically speaking, Cronbach's

alpha is not a statistical test - it is a coefficient of reliability (or consistency). A good and

acceptable internal consistency for the factors must be greater than .5 ( n>.5 ).

Results

Descriptive Statistics.

Four Descriptive Statistical techniques were used by the researchers to know the average,

square root of variance and the normality of distribution of the test items (See Appendix B, Table

1). For the mean, the average of the test items range from 2.96- 4.02, considering estimations,

we can say the mean range from 3.00-4.02. This means that from the average score or the mean

of the test items, mostly the answers of the respondents were between “Somewhat disagree” (3)

and “Somewhat agree”(4) following the 6-point Likert Scale in the scale. As for the standard

deviation, the square root of the variance show it ranges from 1.30-1.54, this is the range

measurement of the spread of a set of observations. The larger the standard deviation is, the


more spread out the observations are. In Skewness, the highest score gathered from the items is

.408 which falls on the positive skew. Positive skew means that the right tail is longer; the mass

of the distribution is concentrated on the left of the figure. The distribution is said to be right-

skewed, right-tailed, or skewed to the right. Also, a positive skew means that the mode and

median are both higher than the mean (2-4). For Kurtosis, all items resulted a negative kurtosis

the values for asymmetry and kurtosis between -2 and +2 are considered acceptable in order to

prove normal univariate distribution (George & Mallery, 2010).

Factor structure.

For Factor structure, it is important to know if the sample size is enough for the scale

development. Initially, when the researchers entered only a few number of respondents which

mean a small sample size, there were only 89 number of respondents they have encoded KMO

resulted with a saying that it is not yet enough to continue with a series of factor analysis tests

and methods. Until finally they have reached and encoded 291 respondents, KMO result now is

.963. For Kaiser-Meyer-Olkin Measure of Sampling Adequacy, it is already a good and

acceptable score. On the other hand, Bartlett’s Test of Sphericity score is highly significant. The

researchers got a score of 0.000 which is basically lower than 0.001 ( p < 0.001).

For the Keirser criterion, there is a noticeable result if it is compared from the theoretical

framework and constructs of the researchers. The scree plot has shown only one factor. This can

be identified on the elbow of the scree plot, which for this scale falls on one which means that

there must be really one factor. Apparently, there might be switch of conclusions for this because

of the conflict between the factor shown by the Keirser criterion and the proposed number of

factors.


For the initial run of factor analysis, there is one item that was crossed-loaded. This item is part

of the Factor 1, item number 6 (COG 6). The item that was eliminated is about getting worried

that a teacher might choose you to solve a mathematical equation. The researchers immediately

eliminated this item and continue the succeeding run. Fortunately, there were no more cross-

loads present on the Pattern Matrix of the test items. While eliminating item with a cross-load,

items were also mixed. Initially, items were labeled and arranged according to its factor (COG1,

COG2, COG3,…AF1, AF2, AF3…) but after cleaning the Pattern Matrix and removing the

cross-load, the items were grouped into a new set. The researchers assumed that the first 14 items

are under a different factor and the succeeding 15 items were of another different factor. After a

clean factor loading was achieved, there are now only 29 items left which are newly grouped.

(See Appendix A, Table 2 for the Revised Scale from SPSS)

Considering the internal consistency from the Cronbach’s Alpha result which is very high, .970

we can assume that the test is unidimensional. From the clean run of the pattern matrix, the items

were not grouped according to their initial group (initial factors: Cog and Af). We can assume

here that there might be different factors for this newly grouped items or the test is really

unidimensional .

Discussion

Math Anxiety Rating Scale by the researchers of this study was not developed for only

this time. There have been few researchers who have already developed their own rating scale.

The main objective of this study is to fill in the gaps that were also presented by the researchers

of this study. These gaps are believed by the researchers relevant. From the past studies, Math

Anxiety Rating Scales that are being developed are used by various people. It seemed to be a

generic rating scale to test Anxiety towards Mathematics. It could be answered in the context of


our experiences of math on our daily living; it could be in academic setting, business setting a

many more different fields. But what the researchers wanted to construct is a rating scale that can

be used only in the academic setting. The rating scale that is being developed by the researchers

is limited only for non-math majors in college. Primarily, the respondents of this test are college

students. Another is the underlying theory that supports the development of Math Anxiety. There

have been arguments that there is really no fixed theoretical framework for this study. There is

noticeable lack of any clear theoretical basis for mathematics anxiety, in either the research or

the treatment literature. (Reyes 1980, 1984 & Hembree, 1990).

The initial constructs for this rating scale is the, Math Anxiety comes off with two

dimensions namely Cognitive and Affective. It is really confusing once we have already take in

to a part on how we can directly ask a questions which could be answerable when we consider

our cognitive aspect and the other one which is affective. The “I Feel” and “I think” are now

being misconceptualized by many Filipinos. That might be one factor that can affect the

consistency and reliability of the two factors.

Until the researchers have come to know via Exploratory Factor Analysis based on the

Scree plot that shows that there is only one factor and the Cronbach’s alpha which has a very

high rate. These are strong results that can replace theory as the basis of the researchers. The test

can be unidimensional. Also the rotated factor shows also one factor (See Appendix, table…).

Practically speaking, the test might have been just unidimensional because of the results coming

from the SPSS. The assumed number of factors or the initial number of factors of the researchers

does not jive on the real number of factors (which is 1) according to SPSS.


Appendix A

Table 1. Math Anxiety Rating Scale Item no.

Factor 1

Item 01

I feel nervous knowing that I will encounter math questions in a class.

Item 02 I am scared of answering any math problem.

Item 03 I feel nervous when my teacher calls me to answer a math problem.

Item 04 I panic the moment I am faced with math equations.

Item 05 I start to get nervous before I present my answers in Math class.

Item 06 I am afraid of attending math classes.

Item 07 I feel uncomfortable when my classmate/s is/are asking me my math answer/s.

Item 08 I feel distressed when I show my math solutions on the board.

Item 09 I feel tension when I am the only who is not yet done answering a math question.

Item 10 I am ashamed of presenting and sharing my answers on a math problem.

Item 11 I am afraid and nervous when I enter a math class.

Item 12 I easily panic when I encounter a math problem that I cannot answer.

Item 13 I feel inflexible before solving math seat works when I am alone.

Item 14 I am apprehensive when the teacher presents a lot of math equations on the board.

Item 15 The thought of answering future math problems frightens me.

Factor 2

Item 16 I feel nervous knowing that I will encounter math questions in a class.


Item 18 I feel nervous when my teacher calls me to answer a math problem.



Item 21 I am afraid of attending math classes.



Item 24 I feel tension when I am the only who is not yet done answering a math question.





Item 29 I am apprehensive when the teacher presents a lot of math equations on the board.



Table 2. Revised Scale from SPSS Item no.

Factor 1

Item 01

I worry that I will have a low standing in our math class.

Item 02 I feel nervous when my teacher calls me to answer a math problem

Item 03 I worry that I might encounter difficult math equations.


Item 05 I am much concern that I am doing something wrong in the middle of solving mathematical problem.

Item 06 I feel nervous knowing that I will encounter math questions in a class.







Item 13 I am preoccupied with the thought that I might fail math class.


Item 15 I am preoccupied with thought of being the center of attention when I get a wrong answer during class

recitations.

Factor 2


Item 17 It worries me to know that I might have mental blocks before solving math equations.

Item 18 I always have second thoughts before I enrol on a math-related class.


Item 20 Although I have followed the suggested procedure of a math problem, I still have doubts about my

answer.


Item 22 I get worried knowing that I have to solve a mathematical problem.

Item 23 I am engrossed with the thought that I will be the lowest among my other classmates in Math-related

courses.


Item 25 I worry that I might not able to solve long math problems properly with limited time.

Item 26 I always have doubts on what I might answer on a math problem even if I listen on class discussions.

Item 27 Sometimes I think that it would just be an easy day for me if I don’t go on my math class.

Item 28 I am much concern that I am doing something wrong in the middle of solving mathematical problems.

Item 29 I worry that I might not able to solve long math problems properly with limited time.

Item 30 I worry that I will not understand a lesson in Math even if I listen attentively.


Appendix B

Table 2. Means, SDs, Skewness, and Kurotsis of Each of the Revised Set of Items

Mean Std. Deviation Skewness Kurtosis

Item1 3.91 1.348 -.370 -.642

Item2 3.95 1.430 -.238 -.931

Item3 3.90 1.423 -.070 -.896

Item4 3.88 1.409 -.163 -.940

Item5 4.02 1.335 -.408 -.537

Item6 3.65 1.390 -.215 -.785

Item7 3.36 1.426 .065 -.768

Item8 3.95 1.312 -.224 -.684

Item9 3.90 1.304 -.212 -.442

Item10 3.88 1.455 -.250 -.798

Item11 3.60 1.433 .003 -.890

Item12 3.51 1.461 .107 -.924

Item13 3.87 1.491 -.246 -.987

Item14 3.41 1.355 .189 -.727

Item15 3.47 1.393 .042 -.924

Item16 3.86 1.349 -.286 -.555

Item17 3.77 1.414 -.250 -.741

Item18 3.79 1.451 -.196 -.900

Item19 3.41 1.458 .131 -.878

Item20 3.67 1.511 -.146 -.920

Item21 3.69 1.448 -.113 -.856

Item22 3.46 1.429 .088 -.830

Item23 3.47 1.453 .167 -.899

Item24 2.96 1.539 .435 -.819

Item25 3.36 1.384 .151 -.759

Item26 3.21 1.482 .141 -1.101

Item27 3.47 1.388 .104 -.830

Item28 3.63 1.344 -.053 -.601

Item29 3.46 1.402 .010 -.836


Item FACTOR

No. College Adaptation Statements 1 2

Item 01 My study habits are efficient. 0.774

Item 03 I have developed an effective study skill. 0.717

Item 02 I am able to get sufficient information about matters related to my studies. 0.666

Item 05 I feel competent with my school performance. 0.665

Item 04 I am satisfied with my school’s ambiance. 0.662

Item 08 I perform well in classroom activities. 0.624

Item 06 I could explain what I have learned from class. 0.62

Item 07 I am satisfied with my college experience in general. 0.591

Item 09 I ask my professor when I have not fully understood the lesson. 0.549

Item 10 I get along very well with my classmates.

0.71

Item 11 I have no trouble making friends inside the campus.

0.696

Item 12 I feel confident introducing myself to others.

0.669

Item 16 I am happy with my friends in school.

0.66

Item 13 I have no trouble making friends inside the campus.

0.651

Item 14 I can communicate with my fellow students easily.

0.639

Item 17 I am comfortable interacting with the opposite sex.

0.638

Item 15 I spend some time with my friends after class.

0.613

Item 18 I have been able to make friends with others who are from a different degree

program. 0.598

Item 19 I can approach my classmates easily.

0.571

Item 20 I have genuine friends in the campus.

0.536

Item 21 I handle stress from school efficiently.

Item 22 I remain calm despite numerous school works.

Item 23 I remain calm during class presentations

Item 24 I always think positively about my school requirements.

Item 25 I find time to relax from school works.

Item 26 I feel energized in school.

Item 29 I can easily cope up with stress in school.

Item 27 I can control my emotions even during stressful events in school.

Item 28 I manage to eat regularly despite workloads from school.

Item 30 I feel healthy and fit despite having stress from school.

Item 32 I wouldn’t want to be in another university.

Item 31 I made the right decision in choosing this school.

Item 33 I am satisfied with my college experience in general.


References

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Development of Math Anxiety Rating Scale

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