Design Fixation and Cooperative Learning Strategies in Elementary Engineering Education

Running head: DESIGN FIXATION, COOPERATION IN ELEMENTARY ENGINEERING 1

Design Fixation and Cooperative Learning Strategies in

Elementary Engineering Education

1Nikki Kim,

1Mariana Tafur,

1Woori Kim,

1Ronald L. Carr,

1Yi

Luo, 1Yan Sun,

1Tugba Yuksel,

2Nicole R. Weber,

1Melissa

Dyehouse & 1Johannes Strobel

1Purdue University;

2Lesley University

DESIGN FIXATION, COOPERATION IN ELEMENTARY ENGINEERING 2

Abstract


Introduction

The shrinking STEM workforce pipeline has become a national concern (Jobs for the

Future, 2007). To address this concern, the educational system needs to engage in innovative

practices to promote science, technology, engineering, and math learning and encouraging

pursuit of engineering and technology careers, and such practices should begin in primary and

secondary educational settings (Nugent, Kunz, Rillet & Jones, 2010). One of the innovative

practices some educators are currently devoted to is integrating engineering into elementary

classrooms.

The design process is an essential part of engineering (Poth, Little, Barger & Gilbert,

2005). It is important for elementary engineering education to promote an understanding about

the engineering design process among elementary students. To serve this purpose, small group

engineering design projects are included in elementary engineering education curricula (e.g.

Crawford, Wood, Fowler & Norrell, 1994; EiE, n.d.) with a vision to build upon young

children’s natural inclination to design and build things (Hester & Cunningham, 2007). These

design projects, like real-world engineering projects, require elementary students to design and

produce products like a floating toy, a paper table, or a windmill. Finding alternative solutions is

an essential design ingredient (Benenson, 2001) taking place in the initial two phases of the

design process. Finding alternative solutions is also one of the important problem-solving skills

elementary education aims to foster (Hester & Cunningham, 2007). However, it is quite possible

that elementary students might have problems with finding alternative solutions due to design

fixation which is well documented in engineering education research concerned with secondary

and post-secondary education (e.g. Chrysikou and Weisberg, 2005; Jansson & Smith, 1991;

Linsey et al, 2010).


According to Jansson and Smith (1991), design fixation refers to “a blind, and sometimes

counterproductive, adherence to a limited set of ideas in the design process (p. 4).” Literature is

replete with studies delving into adult design fixation problems related to alternative design

solution finding. However, despite the agreement on the importance of developing creativity in

young children and the detriment of fixation as opposite to creative thinking, little research has

been conducted to reveal design fixation in young learners

To understand this form of design fixation involved in elementary engineering design

projects, one has to take into consideration the teamwork element associated with such projects.

Like real work engineering design projects, elementary engineering design projects are social

endeavors requiring a large amount of teamwork. Elementary students engaged in engineering

design projects are involved in a cooperative learning process because, according to Siegel

(2005), cooperative learning involves students working in small groups with shared goals and for

the accomplishment of a common task. In the cooperative learning environment of an

engineering design project, elementary students are going to make their decision on a group

design solution based on their respective individual ones. Therefore, an investigation of design

fixation on solution finding in elementary design projects entails an understanding about the

collective decision-making process taken place in a cooperative learning environment.

The present study focuses on the “Imagine” phase of the engineering design process

where elementary students generate and make decisions on their design solutions in a

cooperative learning environment. With such a focus, this study sought to reveal if design

fixation on solution finding exits in elementary engineering design projects and, if it exists, how

it looks like and how it is related to the collective decision making process in the cooperative

learning environment of elementary engineering projects. The specific research questions of this


study are as follows: 1) What does design fixation look like in elementary engineering

education? 2) What is the effect of grade level and cooperative learning strategies on fixation

during an elementary engineering design project?

Literature Review

Elementary engineering design projects and engineering design process

Despite a consensus among U.S. science, business, and education leaders about the

importance of a high quality STEM labor force, the supply of the STEM workforce is shrinking

in recent years (Jobs for the Future, 2007). In response, the science community is preparing to

take its place in the national standards debate. Members of the engineering community and

others interested in the push for Science, Technology, Engineering, and Math (STEM) education

just integrated engineering and technology as a part of that movement (Committee on

Conceptual Framework for New Science Education Standards, 2010).

Research suggests that engaging younger children in the educational curricula of STEM

subjects would sustain the competitive edge of the United States to face the challenges in modern

times (Meeteren & Zan, 2010). Additional, prior results indicate that incorporating engineering

education into P-12 classrooms has several potential benefits: enhancing student learning and

achievement in related subjects such as science and mathematics (Wicklein, 2003; Katehi,

Pearson & Feder, 2009); increasing students' awareness of engineering and access to engineering

careers (Wicklein, 2003; Katehi et. al, 2009); increasing the technological literacy of all students

(Katehi et. al, 2009); and improving students’ problem-solving skills such as problem

formulation and assessing alternative solutions (Benenson, 2001).

Engineering is being integrated into P-12 curriculum across the nation in order to provide

students with meaningful contexts to apply math and science concepts (Tate, Chandler, Fontenot,


& Talkmitt, 2010). Engineering design in pre-college settings helps students understand these

abstract concepts by facilitating alternative mental models (Linn, diSessa, Pea, & Songer, 1994).

The Museum of Science, Boston has been a leader in the movement for P-12 engineering and

curriculum design for more than a decade and have created the Engineering is Elementary

curriculum (EiE), which is designed to be used in elementary schools (Lachapelle et al., 2008).

This work by the Museum of Science, Boston is the foundation for the instruction that is being

implemented at the school in which this study took place.

The EiE engineering design process (Cunningham, 2009; Hester & Cunningham, 2007)

includes five phases (see figure 1), which form a continuous circle around the design goal. In the

“Ask” phase, students identify design problems and clarify design limitations and requirements

by asking appropriate questions. In the “Imagine” phase they brainstorm design solutions and

choose the best one. In the “Plan” phase they draw a diagram and make lists of materials needed

for creating the design product. The students will then proceed to the “Create” phase to create

their design and test it out. After the design product is created, they will be in the “Improve”

phase talking about what works, what does not, and what could work better. Their attempt to

modify their design to make it better will led them going through a new round of the five phases.

Figure 1: The EiE engineering design process (adapted from Cunningham, 2009)


Particularly in the “Imagine” phase, as is illustrated above, elementary students will be

generating design ideas, and evaluating and screening design solutions. These activities

correspond to what occur in the conceptual design phase as defined by Howard, Culley &

Dekoninck (2008) and Jansson and Smith (1991). The conceptual design phase is of great

importance because “the behavior of the design is formed” in this phase (Howard, Culley &

Dekoninck, 2008, p. 164). This phase is crucial also in the sense that, although it takes up only a

relatively small amount of the total design time or efforts, “the leverage which early decisions

have on the entire process is very large” (Jansson and Smith, 1991). It is, therefore, reasonable

to believe that when elementary students are engaged in the “Imagine” phase, they are

performing activities that would have great impact on the whole design process.

Design fixation and design fixation effects

Despite the importance of the conceptual design phase, or the “Imagine” phase in the

case of elementary engineering education, design solutions born out of this phrase might be

misleading or of poor quality due to fixation, a very general phenomenon that occurs in a wide

variety of cognitive domains (Smith, Ward & Finke, 1995). Fixation may manifest itself in

sticking to the first idea coming to one’s mind (Nicholl & McLellan, 2007), in failing to see new

ways of using objects because of previous well learnt uses or object properties (Purcell & Gero,

1996), or drawing on a limited range of previous knowledge as information resources for idea

generation (Ward, 1995; Ward et al, 2002). According to Hatchuel, Le Masson, and Weil (2010),

design fixation can be observed during four processes: during the generation of alternatives, the

knowledge acquisition, the collaborative creativity, and the creativity process. These diverse

approaches of the fixation effect are related to the capacity of breaking the rules of previous


knowledge to create a number of different alternatives, individually or collaborative, and finally

develop a fixed solution of what designers perceive as a good idea (Hatchuel et al., 2010).

Jansson and Smith (1991) were among the first who adopted an experimental approach to

study design fixation in engineering. They define engineering design fixation as “a blind, and

sometimes counterproductive, adherence to a limited set of ideas in the design process” (Jansson

and Smith, 1991, p. 4). Their definition and their acknowledgement of the importance of the

conceptual design phase to the whole design process set up the paradigm of their study, that is, to

focus on the fixation related to the generation of design solutions in the conceptual design phase.

This research paradigm is adopted by many later studies on engineering design fixation (see for

instance Chrysikou and Weisberg, 2005; Linsey et al, 2010; Purcell & Gero, 1996; Purcell,

Williams, Gero, & Colbron, 1993; Smith, Ward & Schumacher, 1993). These studies revealed

that design fixation occurred during the conceptual design phrase and was related to the

instructions for a design problem and/or the presence of example solutions or designs.

Specifically, participants’ ideation and generation of design solutions were framed by the

problem instructions (Chrysikou and Weisberg, 2005) and the example designs or solutions

(Chrysikou and Weisberg, 2005; Jansson and Smith, 1991; Linsey et al, 2010; Purcell & Gero,

1996; Purcell, Williams, Gero, & Colbron, 1993; Smith, Ward & Schumacher, 1993), leading to

the production of a limited and repeated number of design features and solutions generated.

In terms of P-12 students, Nicholl & McLellan (2007) carried out a study to examine how

fixation applies to the idea generation process when pupils are solving design and technology

problems. The study found out that fixation was reoccurring among 11-16 year old students.

Pupils’ stereotypical design ideas predominantly reflected popular teenage culture and gender

patterns. The study also pointed out that pupils often felt annoyed that they were asked to think


of multiple ideas when they knew what they wanted to do right away. Pupils in the study tended

to stick to their first design idea, which often turned out to be stereotypical design ideas.

However, literally none of the study focuses on defixation instructional strategies toward pupils.

Findings from the above studies present strong evidence that design fixation in the

conceptual design phase were prevalent not only among undergraduate engineering students (see

for instance Jansson and Smith, 1991; Purcell & Gero, 1996) but among engineering design

researchers and educators as well (Linsey et al, 2010). Such evidence leads one to believe that

elementary students will very possibly experience design fixation in the “Imagine” phase of the

engineering design process. However, with little previous research into the corresponding area,

this belief will remain at best hypothetical and with very little data to know how exactly design

fixation presents itself.

As is suggested by previous research on design fixation on solution finding among adult

designers, an immediate effect of design fixation is that it limits designers’ abilities to find

alternative, more effective design solutions. Finding alternative solutions is an essential problem-

solving skill that needs to be developed in elementary students (Hester & Cunningham, 2007).

This need, together with the paucity of research into elementary students’ design fixation on

solution finding, justifies the present study’s focus on the “Imagine” phase in the engineering

design process of elementary design projects, and on the design fixation that might occur in this

phase when elementary students seek to find design solutions for their projects.

To overcome fixation, some authors have done research about working with fixations and

defixation examples (Chrysikou & Weisberg, 2005; Linsey et al., 2010; Purcell & Gero, 1996),

while others affirm that problems “must be both ambiguous and have an element of risk”

(McLellan & Nicholl, 2009, p. 89). Taking into account that design fixation is an important


barrier of engineering design goals (Chrysikou & Weisberg, 2005; Purcell & Gero, 1996), this

study will focus in understanding how a successful strategy, such as cooperative learning, can

help students to overcome this type of fixation.

Cooperative Learning

An instructional method that has been proven successful in nurturing the aforementioned

skills is that of cooperative learning. Cooperative learning has been utilized in the field of

education since the late 90’s (Johnson, Johnson, & Holubec, 1998; Johnson, Johnson, & Smith,

1991; Jacobson, Davis, & Licklider, 1998), although its’ roots are founded on the seminal works

of Deutsch’s social interdependence theory (1949a, 1949b), as well as Piaget’s (1952) and

Vygotsky’s (1962) work on cognitive development theory. Deutsch’s influence was the notion

that an individual is placed with a burden to contribute to group’s knowledge, causing positive

social interdependence (1949a, 1949b). Piaget (1952) focused on the individual’s curiosity for

discovery learning, and how the sharing of such knowledge among peer results in disequilibrium,

which causes the individual to sincerely consider the perspective of others. Vygotsky (1962),

although similar, centers on the social aspects of cognitive development, citing that the

cooperation to learn is what causes the zone of proximal development. Brown & Ciuffetelli

(2009) developed this further into five distinct essential elements of cooperative learning:

positive interdependence, face-to-face promotive interaction, individual accountability, social

skills, and group processing. As cooperative learning is a “deeply relationship-based

instructional strategy” (Kern, Moore, & Akillioglu, 2007, p. 2), it is highly appropriate to

stimulate a collaborative culture in preparation of the engineering field.

In engineering educational settings, cooperative learning is encouraged to make students

design learning process and scientific investigation with their peers (Haller et al., 2000;


Luechtefeld & Watkins, 2009). With an emphasis on social aspects (e.g., active communication)

from the perspective of constructivist theories of learning, cooperative learning such as project-

based learning is seen as a critical method in design classes. Cooperative learning can lead

directly to better decision-making as it requires students to communicate their personal values

and beliefs as well as explicitly asks them to consider the needs of different stakeholders when

searching for creative alternatives in a decision (Clemen & Hampton, 1994). As mentioned in the

above engineering design process, in the first and second steps of Ask and Imagine, students

need to consider questions like: What is the problem? What are some solutions? When

brainstorming ideas and choosing the best one, the student needs to explain his or her ideas to

peers and negotiate with them to locate the best alternative. According to the cognitive

elaboration perspective (Slavin, 1996), this process would probably deepen students’

understanding of the engineering design problem and accordingly improve their decision making

as a group. The majority of Engineering is Elementary design activities are done in small groups,

which can encourage students to generate a variety of ideas or solutions to develop the product

with their group members (Cunningham & Hester, 2007).

According to the literature on the comparison research between students working

individually and students working on well-functioning groups, students in teams not only

develop more positive attitude toward the class and project but also have greater confidence in

themselves (Felder & Brent, 2004). Project-based learning founded on cooperative learning is

usually adopted in engineering design class. Given a project each of students has an opportunity

to bring their own design and take a greater division of labor to group for the successful

completion of their projects. For example, Mourtos (1997) stated each group member is

responsible for their own design, and every member is also responsible for revising the designs


of their group members making suggestions for improvement. Moreover, cooperatively taught

students exhibit a tendency to have higher academic achievement, high-level reasoning and

critical thinking, better understanding of learning materials, encouraging relationships with peers

(Felder & Brent, 2001; Kaufman, Felder, & Fuller, 2000). As Linsey et al. state, students clarify

their ideas for helping others’ understanding. In the creativity step, novice group firstly generate

many different ideas and then select one idea to design (2010).

As shown above, design fixation is rife among young students while cooperative learning

strategies could benefit students in decision making in the engineering design process. Because

the lack of research examining the effect of cooperative learning strategies on design fixation in

K-12 classrooms, this study hopes to make a contribution herein.

Method

This study utilized a mixed methods approach by implementing a multiple case study

research design in order to identify variances across and within each case (Yin, 2003). The

participants were automatically divided into case studies via grade level (Merriam, 1998) and

also as groups. As analytical framework, the team used grounded theory, since the aim was to

create a new theory or to broaden an existing one (Creswell, 2008). Data collected in this study

included observation notes, student reflections, and photos of individual design solutions and

final group solutions, which were coded, categorized, and translated into quantitative parameters.

This method is focused on the process of codes’ identification through systematic procedures.

We included the four codification steps of grounded theory: identifying categories based on the

data collected, classifying properties of those categories, measuring dimensions of those

properties, and refining those elements (Creswell, 2008). Because one of the research questions

aimed at the understanding of what design fixation looks like, it is important to start with an open


codification that allows researchers to identify the complexity of the problem of design fixations,

since little research has been done in that field. The research group analyzed the Design Fixation

Protocol in order to identify general codes and then recognize properties and their dimensions

within the group interaction observed during the first two class sessions.

To assure high reliability despite the high number of researchers, the group completed a

round of codifications of one grade, discussed about the discrepancies in the codification, and

calibrated the categories and properties within each category. Two unique, independent methods

of analysis were performed on coded materials in order to provide validation for each.

Figure 2: Research Design

Participants

Participants (n=41) were selected from an existing engineering design class for students

in a private elementary school in a large city in the Midwest. Group and gender distribution is

shown in Table 1. The school offers a specialized program in which students participate in

engineering lessons taught by an instructor who is a doctoral student in the fields of engineering

education and high ability education. The instructor has over five years of elementary school


teaching experience, in addition to being skilled in teaching elementary school engineering and

conducting P-12 engineering teacher professional development and research.

Each class is comprised of 5 students from each of the 3 classes in the given grade;

students are in this classroom twice a week, usually on Tuesday and Fridays, for 50 minutes per

period. Each group of students participates in the engineering class for one quarter of the school

year.

Table 1 Participant Profile

Procedures

Content and Instruction. The instructor used a modified version of the Engineering is

Elementary (EIE) five-step engineering design process (EDP): Ask, Imagine, Plan, Create and

Improve (Duncan, Oware, Cox, & Diefes-Dux, 2007). The design challenge for the observations,

created by the instructor, involved each team designing one of four choices of duct tape products,

creating a prototype, and presenting the prototype to “clients” that would choose the best product

to take to production. The product choices were a wallet, folder, tote bag or water bottle holder.

The students were informed that their group design would be judged according to the following

rubric: 1) Task completion (Did the team meet the task specifications? 2) Attractiveness (Would

this item appeal to the public?) 3) Creativity (Was the team creative in their design?) 4)

Functionality (Is the team’s design functional? Can the user actually use it?) The students were

each given a rubric and list of specifications that must be met in order to satisfactorily complete

the project. The rubric was also to be used by the jury, which included two members of the


school administration, to determine prize winners for Client’s Choice and Overall Choice. The

instructor introduced the activity without the aid of examples and was careful not to provide any

extraneous information that might have influenced the students. The only exception withing the

classroom was a tote bag located behind the teacher’s desk, which students may have seen. The

lesson lasted over three days with the first day including the ask, imagine and plan stages of the

EDP from EIE; second day as the create prototype day; and third day as the day to present their

ideas to the client and complete a set of reflection questions that were provided by the instructor

as an instrument for this study.

Instruments

Cooperative Learning Observation Protocol. In order to systematically observe

elementary students’ behavior in the group engineering design project, the researchers adapted

the Cooperative Learning Observation Protocol (CLOP) (Kern, Moore & Akillioglu, 2007) for

evaluating the elements of cooperative learning and teaming in an engineering setting to guide

the observation. The CLOP is a mixed methods instrument recording frequency and evaluations

of observed instances of cooperative learning engagement through detailed field notes (Kern et.

al, 2007). We adapted the layout of CLOP in order to make it easier for observers to rate

participants’ behavior in terms of the five corresponding elements of cooperative learning

identified by Johnson, Johnson & Smith (2006): positive interdependence (P), individual

accountability (I), group processing (G), social skills (S) and promotive interaction (F). Each

item was allocated 10 points with the higher total score indicating a higher level of collaboration

and effectiveness in cooperative learning. The researchers recorded their observation with

extensive notes with the ratings.


Fixation observation protocol. The members of the research team created the design

fixation observation protocol to record instances of actions or discussion that would indicate

fixation. The five categories observed were discussion, novelty, value/critique, integration and

brainstorming, which were influenced by design fixation literature (Hatchuel et al, 2011: Jannson

& Smith, 1991; Chrysikou & Weisberg, 2005, Dix et al., 2006). This instrument measures

whether students are fixated to ideas which presented themselves through real-life experiences,

as well as the materials that the teacher demonstrates before design instructions or samples. The

protocol included ten major issues regarding design fixation for the observer to focus on and

required the observer to take detailed field notes.

Table 2: Fixation Observation Protocol (Sources: Jansson & Smith [1991]; Chrysikou &

Weisberg [2005]; Dix, Ormerod, Twidale, Sas, Gomes & McKnight [2006]; Hatchuel, Masson

& Weil [2011]) Did the students:

point out features in the instructors’ example(s) to support their decision?

argue for ideas because they could lead something better than the instructor’s

example(s)?

present example(s) (objects or pictures) similar to the instructor’s example(s)?

mention example(s) they had seen before to support their decision?

refer to the design project instructions as their decision-making guidelines?

use ideas from different members of the group to create a new solution?

say anything like “I like it (idea or a design solution) because it’s new or better than the

example(s)”?

say anything like “I don’t like it (idea or a design solution) because it’s not like the

example(s) or because the instructions did not say so”?

go back and forth among their design solutions before reaching an agreement?

stick to one of their design solutions and reach an agreement quickly?

Fixation Code Sheet. For coding students’ design journals, the researchers developed

the “Fixation in the Engineering Design Project Code Sheet” (DFCS). The development began

with one group of researchers making the first iteration for the categorization by looking at the

main design elements of all the sketches. A second group of researchers chose three different and

representative artifacts complementing the design elements extracted by the first group of


researchers. After the group discussion, the rubric was updated in order to address fixation key

elements shown in the engineering design project. The final rubric consisted of four major

coding categories: general information (type of design, starred design, main shape, pattern, color),

features of straps, features of pockets and features of folds. This coding rubric was used to locate

the number of fixated features of each group as well as each individual student.

A design reflection report was utilized by the teacher in the classroom and responses

were provided for this study. The reflection report prompted students to identify which of their

four design ideas they chose to present to the group, identify possible sources for ideas, reflect on

the amount of personal contribution to the final product of the group artifact, and to list their own

ideas that were specifically found in the final product.

Observation procedures.

Four graduate student observers visited the classroom over the three days of instruction.

The time intervals were removed from the CLOPS after the first day as it was difficult for one

observer to report on two groups at a time. Photographs were taken of the students’ engineering

journals in order to record their brainstorming and planning. On day three, only field notes were

used to record pertinent statements and responses from the students during their group

presentations. Photographs of the final products and student reflections were also taken in order

for them to be compared to the sketches and statements throughout the process.

Role and background of researchers.

The research team consisted of three instructors and graduate students in an advanced

research methods class. The graduate students came from various fields of study (engineering

education, gifted education, learning design and technology, and science education). The team

determined the research questions, selected and created the observation protocols, as well as


coding scheme and scoring rubrics. Four of the graduate students, all experienced in classroom

instruction, traveled to the experiment site to collect the data artifacts. Each researcher was

briefed in each observation protocol, and due to the experiences from the first observation, the

design fixation and cooperative learning observation protocols were further adjusted to improve

the collection of data.

The primary qualitative analysis is based on one observer that visited the school on

multiple occasions preceding and during this study. This observer is also a researcher and student

in engineering education and gifted education, and took on the role of a qualitative instrument

(Patton, 2001), utilizing additional perceptivity developed from designing similar activities,

teaching students, and training teachers.

Data Analysis

For further analysis of the coded raw data, the research team employed two distinctly

different analysis models referenced as Model A and Model B. The reason for employing two

different models was to (a) provide not just a triangulation of data points but a triangulation of

analysis methods as well and (b) to highlight nuances which one analysis method was better in

detecting than the other.

In both models, data were analyzed through content analysis, multiple regression analysis,

and ANCOVA to answer the two major research questions. Content analysis is broadly defined

as “any technique for making inferences by objectively and systematically identifying specified

characteristics of messages" (Holsti, 1969. p14), so the researchers applied it to analyzing

participants’ design journals and the field notes of class observation, in order to sift through large

volumes of data with relative ease in a systematic fashion (Gao, 1996). The team used emergent


and priori coding (Stemler, 2001) and categorizing of the data (Weber, 1990) to describe what

design fixation looks like and recognize its patterns among the participants.

Coding of design journals. First, participants’ design journals recording their individual

designs as well as the selected final group design were coded according to the DFCS developed

by the researchers based on previous literature on design fixation. This instrument containing

priori coding aimed to identify the different types of design fixation manifesting in both the

individual and group design solutions. Secondly, the field notes accompanying the Fixation

Observation Protocol were coded and categorized to identify the themes of elementary

engineering design fixation. In addition, participants’ reflections on their individual design idea

generation and group design selection were also analyzed to triangulate the patterns and themes

identified through researchers in the first two steps. Lastly, the field notes accompanying the

CLOP instrument were coded and categorized to provide a qualitative analysis of the cooperative

learning strategies adopted by the participants while they worked in their engineering teams.

The basis for both analysis models was the coding of the raw data.

Analysis Model A

Analyis Model A is inspired by Linsey et al.’s (2010) metric to analyze fixation based on

“redundant ideas vs. non-redundant ideas (p.5).”

Design Fixation Rubric. In Model A, the Design Fixation Rubric was used to determine

levels of fixation for groups and individuals throughout the design process. An Imagine Rank

was calculated for groups to determine the level of creative ideas during the individual

imagination stage. This score was based on an average ranking of each group’s total number of

ideas, number of different ideas and the percentage of different ideas to total ideas. A Plan Rank

was calculated for groups to determine the level of change during the collaborative planning


stage. This score was calculated by averaging the rankings of each group’s number of ideas that

were present in the group plan and the percentage of original ideas that were found in the group

plan. An FX Rank was calculated to determine the level of change during the plan and create

stages. This score was calculated based on an average of the rankings of the scores described

below that followed the imagination stage. A total score was then calculated to determine the

overall level of fixation and creativity. This score was an average of all of the rankings.

In order to calculate the rankings in Model A, the imagine sketches, plan sketches and

final artifacts were coded and those codes were compared to determine the level of change of

each individual and groups designs. Twenty aspects were coded in four main categories: 1)

General Information such as shape, pattern, and color; 2) Information about straps and handles

including number, location, design and size; 3) Characteristics of pockets such as shape, number,

size, location, pattern, open or closed; and 4) Aspects related to folds such as number, location, if

there are flaps and if the item rolls up.

When comparing the data, calculations were made to capture the quantity of ideas and to

measure their impact on the group planning and artifact creation stages. The following five areas

were tabulated:

Ideas = Total number of ideas expressed in sketches, plan and artifact (e.g., for pocket

location, one student fourteen characteristics coded throughout his or her four sketches).

Dif = Number of different ideas expressed in sketch, plan or artifact (e.g., of those

fourteen characteristics, six of them were unique or not repeated by the individual in the sketch,

plan or artifact).


Plan = Number of these individual ideas that were expressed in the group plan (e.g., of

the fourteen ideas, eight of those appeared in the group plan). In cases where some aspects of

individual plans differed from the group consensus, the consensus was used.

Art = Number of these individual ideas that were identified in the artifact (e.g., of the

fourteen ideas, three were identified in the group artifact).

XCT = Number of ideas that were exactly found in the artifact (e.g., another student

specifically sketched a pocket on the lower left of the front of the item; the three codes were

found identically on the artifact (lower, left, outside) therefore, the ideas were counted as exact;

the codes had to match exactly, such as 1, 2, 4, 5 being coded in the student sketch and being the

coding for the artifact.).

These numbers were totaled for each student and for each group in order to find averages.

Due to the fact that some items and coding had different numbers of codes, the scores were

adjusted (e.g., a wallet had eight elements coded, so each individual total was divided by the

number of elements in that item). These are noted in the data tables by the word Adjusted.

Additionally, the following ratios were calculated:

XCT/ID= Exact elements/Total Ideas: Percentage of unique ideas that were exactly found

in the artifact.

Dif/ID = Different ideas/Total Ideas: Percentage of ideas that were unique.

Plan/ID = Elements found in group plan/Total Ideas: Percentage of initial ideas that were

found in the group plans.

Pln/Art= Percentage of initial ideas in the group plan that were found in the artifact.

Art/ID = Percentage of initial ideas found in the group artifact.


Cooperative Learning Observation Protocol. The team averaged the values from the two

days of observations using the CLOPS by finding the mean value for each total per group over

the two days, a total value per day and a total mean for the two days.

Observation Notes. In the qualitative analysis, Model A utilized the observation notes

from the first two days of the activity to determine trends in behaviors and signs of cooperative

learning strategies. Notes from the third day activity, the sales pitch day, have also been

examined to add insight into the group processes and creative/fixation levels. Model A did not

quantify the field notes.

Statistical Analysis. Grade level comparisons were made in the fixation scores and

CLOPS averages. Pearson Correlations were used to determine correlation between the various

types of data.

Analysis Model B

Model B utilized a correlation analysis. Quantification of the data for the correlation

analysis included frequencies of elements of cooperative learning, as well as of design fixation.

Besides the frequency, the quantification also included the level of cooperation and fixation

occurrences. For instance, using a rectangle form is more common than using a triangle form,

therefore the level of fixation is higher when using a rectangle instead of a triangle, when the

requirements does not address any requirement for the artifact’s shape.

The final stage of the analysis of the data had a quantitative approach, making a

correlation between fixation levels and cooperative interactions levels. Although the number of

groups was small, the complementary analysis of qualitative key elements permitted to

triangulate the information of the correlation results with representative cases of cooperation and

fixation in the three grades.


Design Fixation Rubric. Model B analyzed the level of fixation in each group and grade

first by looking at the frequencies when a student chose his or her first, second, third, or fourth

idea to the group. If the student or the group sticks with the same idea, regardless of the

requirements, the group may be fixated in that alternative. The rubric was then used to analyze

primary shapes of the designs and compared to existing or popular known designs for each item.

The type of product each group chose to design was also examined. Finally, similar to Model A,

numbers of changes by each group throughout the design process were tabulated and compared.

Student Design Reflections. Model B used the student design reflection reports to

quantify student reflections on the origin of their own designs. For instance, some students

mentioned specific stimuli for their ideas such as previously viewed similar objects or references

to popular culture. These numbers were then used in a cross-analysis with student perceptions of

their contribution to the overall plan and final artifacts.

Observation Protocols. Model B combined the information from the two observation

protocols that were utilized in this study. Two types of information were collected, levels of

cooperative learning and levels of design fixation. Both utilized quantitative and qualitative data.

Qualitative data were gathered by documenting the conversations and interactions between kids.

Qualitative data were calculated from the codification in fixation, while the observers of

cooperative learning established quantification. Data from both protocols was then compared.

Results

Results of Analysis Model A

An example of the tabulation of the coding from the design fixation rubric for one group

(Grade Three, Group One) from Analysis Model A is shown (Table 3) to demonstrate the

calculation process utilized. Unique ideas (Dif/ID) were determined by finding the percentage of


ideas in the individual brainstorming that were unique or not repeated. Similarly, percentages

were calculated for the other ratio categories.

Table 3: Individual and group ratings based on the design fixation rubric using Analysis Model

A

Third Grade

Adju

st

Adju

st

Adju

st

Adju

st

Adju

st

Student Ideas Dif

Dif/I

D Plan Art XCT

XCT/I

D

Plan/I

D

Pln/A

rt

Art/I

D

311.0 5.5 1.9 35.0 4.5 3.7 2.6 48.3 81.7 119.5 68.4

312.0 5.2 1.9 36.8 3.9 3.5 2.3 43.9 75.5 113.2 66.6

313.0 4.8 1.8 37.7 4.0 3.3 2.5 50.9 83.0 122.2 67.8

314.0 4.6 2.1 45.1 2.6 2.3 1.7 37.3 56.9 116.0 48.9

Grp 1

Average 5.0 1.9 38.5 3.8 3.2 2.3 45.3 74.7 117.9 63.3

Class Ave 4.5 1.6 35.0 3.4 3.2 2.9 66.1 75.9 104.5 72.9

Group comparison in Model A utilized in-class comparisons of data from the design

fixation rubric. The rankings for Imagine (IMG Rank), Planning (Plan Rank), Plan-to-Artifact

(Plan/Art) and overall Fixation (FX Rank) were calculated by calculating the means of the sub-

rankings then ranking accordingly (Table 4). The sub-rankings were: Image Rank = Ideas, Dif

and Dif/ID; Plan Rank = Plan and Plan/ID; Plan-to-Artifact = Art, XCT and XCT/ID; Overall

Fixation = IMG Rank, Plan Rank, Plan/Art and Art/ID. Table 5 shows that Group 1 had the least

overall fixation bolstered by low fixation in the individual imagine stage as well as during the

Plan-to-Artifact stage.

Table 4 Group rankings based on individual ratings from the design fixation rubric using Model

A

Third Grade

GR

P Ideas Dif

Dif/I

D

IM

GRa

nk Plan

Plan

/ID

Plan

Ran

k Art

XC

T

XCT/

ID

Pln/A

rt

Art/

ID

FX

Rank

4 4.13

1.43

33.63

3 3.32

79.43

2.5 3.11

3.13

75.73

104.92

75.

73

2.4

3 4.72

1.82

38.42

2 3.11

65.41

1 3.33

2.92

61.22

93.04

70.

32

2.1


2 4.04

1.24

29.54

4 3.43

84.04

3.5 3.33

3.34

82.14

102.23

82.

34

3.6

1 5.01

1.91

38.51

1 3.84

74.72

3 3.22

2.31

45.31

117.91

63.

31

1.7

Cla

ss 4.5 1.6 35.0 3.4 75.9

3.2 2.9 66.1 104.5

72.

9

Grade level totals were calculated in Model A using means for each stage of the design process

and again for total fixation (Table 5). The fifth grade means show the least fixation in the

imagine stage (I), the second least in the plan stage (P), the least in the Planning-to-Artifact stage

and second overall (FX). Overall, the fourth grade had the least fixation, followed by the fifth

grade then the third grade.

Table 5: Grade Comparison of Fixation Scores using Model A

Grad

e

Idea

s Dif

Dif/I

D I

Pla

n

Plan/I

D P Art

XC

T

XCT/I

D

Pln/Ar

t

Art/I

D FX

5th 4.71

1.71

35.92

1.

3 3.32

69.52

2

2.82

2.42

52.22

124.11

64.92

1.

9

4th 4.23

1.62

37.81

2 2.71

63.41

1

2.71

2.21

50.51

112.82

63.51

1.

1

3rd 4.52

1.62

35.03

2.

3 3.43

75.93

3

3.23

2.93

66.13

104.53

72.93

3

Analysis Model B

As demonstrated in Figure III, the first design idea was chosen to be participants’ favorite

picture to share with the group members for 14 times, which was the most frequently chosen one

out of the four design ideas. The second, third and fourth design ideas were chosen 11, 6, and 10

times respectively. Since the sample size was 41, the researcher argued that the effect size of the

first design idea might be larger with a larger sample. The typical reason given by participants to

choose the first design idea is “I chose that idea because it looked easiest.”


Figure 3: Number of students fixated on each design idea

Table 6 exposes how the majority of the students, especially older students, selected the

first sketch to show to the group.

Table 6: Percentage of students selecting first sketch

Table 7 displays the shape used for the main element of the artifact. The majority of the

ideas included rectangle or rounded shapes, which are very commonly used or seen in existing

designs. Fourth grade used the less common shapes in their sketches. However, the final product

0

2

4

6

8

10

12

14

1st Design

Idea

2nd Design

Idea

3rd Design

Idea

4th Design

Idea

14

11

6

10

Number of Students Fixated on Each Design Idea

First Second Third Fourth Total Observations

T1G3 4 0% 50% 25% 25% 100%

T2G3 2 50% 50% 0% 0% 100%

T3G3 4 50% 75% 0% 0% 125% S3 chose two

T4G3 2 0% 0% 0% 100% 100%

T1G4 4 75% 25% 0% 0% 100%

T2G4 3 33% 33% 0% 33% 100%

T3G4 4 0% 25% 25% 50% 100%

T4G4 3 33% 0% 67% 0% 100%

T1G5 4 50% 25% 0% 25% 100%

T2G5 4 25% 0% 50% 25% 100%

T3G5 4 75% 0% 0% 25% 100%

T4G5 3 0% 33% 0% 33% 67% S1 didn't choose any

G3 12 25% 50% 8% 25% 108%

G4 14 36% 21% 21% 21% 100%

G5 15 40% 13% 13% 27% 93%

Individually 41 34% 27% 15% 24% 100%

Starred Picture


has common shape in almost every group. Some of the unique shapes for the first sketches of the

design were animals, hearts, and flowers.

Table 7: Shapes used in the design

Table 8: Group decision on artifact to design

Rectangular Triangle Rounded Unique

T1G3 80% 0% 0% 20%

T2G3 0% 0% 70% 10%

T3G3 95% 0% 0% 5%

T4G3 40% 0% 30% 30%

T1G4 55% 0% 35% 10%

T2G4 60% 0% 13% 27%

T3G4 30% 0% 55% 15%

T4G4 53% 0% 13% 33%

T1G5 55% 0% 25% 20%

T2G5 85% 0% 0% 15%

T3G5 100% 0% 0% 0%

T4G5 47% 20% 13% 20%

G3 65% 0% 17% 15%

G4 49% 0% 31% 20%

G5 73% 4% 9% 13%

Individually 62% 1% 19% 16%

Shape Used

Wallet Tote Bag

Water

Boter

Holder

School

Folder

T1G3 100% 0% 0% 0%

T2G3 0% 0% 80% 0%

T3G3 100% 0% 0% 0%

T4G3 0% 100% 0% 0%

T1G4 0% 100% 0% 0%

T2G4 100% 0% 0% 0%

T3G4 0% 100% 0% 0%

T4G4 0% 100% 0% 0%

T1G5 0% 100% 0% 0%

T2G5 0% 0% 0% 100%

T3G5 5% 0% 0% 95%

T4G5 100% 0% 0% 0%

G3 67% 17% 13% 0%

G4 21% 79% 0% 0%

G5 21% 27% 0% 52%

Individually 35% 41% 4% 19%

Type of Design


Table 8 shows how each group decided to design one type of artifact. The type of artifact

varies between groups within the same grade, although the group had to decide the type of

artifact they were design before drawing the four initial ideas. It is noteworthy how just one

groups of third grade was the only one deciding to design a water bottle holder, despite the

teacher briefly made a connection with an example of this type of design.

Table 9 shows levels of fixated designs for the plan and artifact in each group. The table

displays greener cells for the groups with more changes between initial ideas and plans or

artifacts. The yellow cells show higher levels of fixed designs during the plan and creation of

artifact; that means that groups with yellow cells remained with one or more initial ideas during

the whole design process.


Table 9: Level of fixated design - consolidated

DESIGN FIXATION RUBRIC ‐ CONSOLIDATED

Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix Fix

General

Shape 0.75 0.75 0 0.875 0.75 1 0.125 0.5 0.4375 0.4375 0.5 0.5 0.4375 0.375 0.4167 0.4167 0.4375 0.4375 0.8125 0.8125 1 1 0.0833 0.1667

Pattern 0.5 0.0625 0 1 0.2857 0 0.8333 0 0.4286 0 1 0 0 0 0.1111 0.7778 0.0714 0.5714 0.7333 0 0.3125 0.3125 0.4167 0.0833

Straps

Location NA NA 0.125 0.125 NA NA 1 1 0.0667 0.9333 NA NA 0.9286 0.1429 0.6667 0 1 1 NA NA 0.4375 0.8125 NA NA

Relat. Loc. NA NA 0.375 0.875 NA NA 0.8571 0.8571 1 1 NA NA 1 1 0.6667 0 1 1 NA NA NA NA NA NA

Shape NA NA 1 1 NA NA 1 1 0.25 0.8125 NA NA 0.875 0.875 0.4167 0.5 0.875 0.875 NA NA 0.375 0.8125 NA NA

Size NA NA 0.625 0.625 NA NA 0.125 0.125 0.875 0.875 NA NA 0.5625 0.5625 0.4167 0.6667 0.9333 0.5333 NA NA 0.4375 0.8125 NA NA

Pockets

Shape 1 1 1 1 1 1 1 1 0.1429 1 0.6667 0.6667 0.5 0.5 0.5833 0.5833 0.75 0.75 0.75 0.75 1 1 NA NA

Location 0 0 1 1 0 0.125 1 1 0.1429 1 1 1 1 1 1 1 0.4286 1 NA NA NA NA 0.8333 0.8333

Open 1 1 1 1 0 0.9333 1 1 1 1 1 1 0.2143 0.7857 0.8333 0.1667 0.4286 0.8571 1 1 1 0 0.1667 0.25

Size 0.6875 0.6875 1 1 0 0.2727 1 1 0.1429 1 0.8 0.8 0.875 0.875 1 1 0.4286 1 0.5333 0 0.2308 0.2308 1 1

Folds

Location 0.375 0.375 NA NA 0.9375 0.9375 NA NA NA NA 0.3333 0.3333 NA NA NA NA NA NA 0.1875 0.0625 0.9375 0.9375 0.5833 0.5833

Rolls NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0.5833 0.5833

Flaps NA NA NA NA 0.1875 0.8125 NA NA NA NA NA NA NA NA NA NA NA NA 0.125 0.875 NA NA NA NA

T1G4T1G3 T2G3 T3G3 T4G3Artifact

T2G4 T3G4 T4G4 T1G5 T2G5 T4G5ArtifactPlanArtifactPlan

T3G5Artifact PlanArtifactPlanArtifactPlanArtifactPlan

GENERAL

STRAPS

POCKETS

FOLD

SPlanArtifactPlanArtifactPlanArtifact PlanArtifactPlanArtifactPlan


Table 10: Group scores from the CLOPS Protocol

CLOPS - Cooperative Learning Observation Protocol

Group Day P

Rating

I

Rating

G

Rating

F

Rating

S

Rating Mean

3Group 1 1 4 3 4 3 3 3.4

3Group 1 2 6 7 8 5 6 6.4

Mean 5 5 6 4 4.5 4.9

3Group 2 1 8 6 8 10 10 8.4

3Group 2 2 1 2 0 4 2 1.8

Mean 4.5 4 4 7 6 5.1

3Group 3 1 4 5 6 7 6 5.6

3Group 3 2 4 6 2 5 6 4.6

Mean 4 5.5 4 6 6 5.1

3Group 4 1 5 6 6 6 5 5.6

3Group 4 2 10 10 10 7 7 8.8

Mean 7.5 8 8 6.5 6 7.2

Grade 5.25 5.625 5.5 5.875 5.625 5.575

P = Positive Interdependence, I = Individual Accountability, G = Group

Process, F = Promotive Interaction, S = Social Skills

Table 11 and Figure 4 below demonstrate each group’s mean score of the two-day cooperative

designing of engineering products based on the CLOPS instrument. The highest mean among the

five cooperative learning elements is individual accountability (MeanI=6.33) while the lowest

mean is promotive interaction (MeanF=5.88).


Table 11: Cooperative learning score based on CLOPS

Figure 4: Chart of CLOPS means bygrade

Observation Notes

Table 12: Observation notes from Day 1 and Day 2

Day G3_1 G3_2 G3_3 G3_4

1

All present ideas,

one interrupted,

rock paper scissors,

negotiating for

votes

Whispering, guarded,

pointing at each other's

papers, drawing on

each other's papers

Difficulty deciding on

item, two leaders and

two passive

Working together, one

member missing, quick

agreement but then

change item, share ideas

P I G F S

3rd Grade Group 1 Mean 5 5 6 4 4.5

Group 2 Mean 4.5 4 4 7 6

Group 3 Mean 4 5.5 4 6 6

Group 4 Mean 7.5 8 8 6.5 6

4th Grade Group 1 Mean 7 6.5 6 6.5 6.5

Group 2 Mean 7.5 7 6 4 6.5

Group 3 Mean 5.5 6 8 8 7

Group 4 Mean 6 7.5 4.5 5 4

5th Grade Group 1 Mean 4.5 5.5 5 4 5.5

Group 2 Mean 9 8.5 9 8.5 9.5

Group 3 Mean 6.5 7 5.5 6.5 6.5

Group 4 Mean 5 5.5 7 4.5 5

6.00 6.33 6.08 5.88 6.08

1.52 1.32 1.64 1.57 1.40

Mean

Standard Deviation

5.3 5.6 5.5

5.9 5.6

4.9

6.5 6.8 6.1 5.9 6.0

5.5

6.3 6.6 6.6

5.9

6.6

5.6

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

P Rating I Rating G Rating F Rating S Rating Total

CLOPS Means by Grade

Grade 3

Grade 4

Grade 5


2

One student does

most work, all help

when he is

confused, one more

concerned with

decoration but does

prepare tape

One does most of the

work, another cuts

tape but is not paying

attention, ran out of

time, group unhappy

Working together as

team, two working at

first, third inactive until

progress being made then

jumps in to help and

encourage, mediate

disagreement

Team working together,

all participating, helping,

directing each other

Design Reflection Elementary school students’ design ideas also reflected popular teenage

culture. The following are some quotations of students’ answers to the sources of their design

ideas: “From Justin Biebers birthday”; “Lady Gaga because I thought out of the box in designed

and technique”. Some of their design ideas also reflected gender stereotypes. Girls’ designs

tented to be more decorated such as using heart-shape, drawing flower patterns, emphasizing the

use of colors; and adding straps/handles to the wallet design. For example, two girls mentioned

that “I like the shape of the flower and when I was drawing the roses”; “I came up with this

because I love flowers and I like we made it the colors of the flowers”. One girl explicitly

mentioned in the reflection that she got the idea from “Vera Bradley totes,” which is a feminine

brand.

Table 13: Responses from reflection questions

Group Q1 Q2 Q3 Q4 Q6

3_1 1,2,3,3 design, color, shape,

size, function, best,

cool, function

Lady Gaga, brain,

imagined, wallet

0,55,

35,0

It was __'s idea,

money pocket, all

of it, camo tape

3_2 O, 1 changed mind, thick other holder, thickness

and length

35,50 color, handle

3_3 1,2,1 awesome, best, best,

colorful

XXX, purse, real

wallet, other thing I

saw

50,95

,35,6

0

color, credit card

slot, pockets,

smiley faces

3_4 4,4 built and structure,

shape

flowers, flowers 38,1 colors, handle


Table 14 shows students’ perceptions about the level of integration (inclusion of their own idea)

into the final design. This information illustrates how some groups such as T3G4 were diverse in

the appreciation of the integration, while groups such as T2G5 though similarly (in this case not

integration at all).

Table 14: Progression from Previous Ideas to Integration of Ideas

Table 15: Observation notes from Day 3

Sales Pitch Notes (Day Three)

Group Item Functions noted Issues Changes

3_1 Wallet Non-flammable,

child-safe, great for

Veteran's Day

(camo)

tape in wrong spot,

disagreement, not

serious until last

minute, decorations

bigger pocket,

more cats, zipper

3_2 Water

Bottle

Holder

had trouble with the

tape

make it bigger

3_3 Wallet size, looks, like a

wallet sized-purse

with flaps cut off,

put phone in, stands

up

won't fit in pocket

3_4 Tote

Bag?

colors, shape, her idea, book won't

stay, no time to test

taller, longer

handle

Existing New Not mentioned

T1G3 4 50% 50% 0%

T2G3 2 50% 0% 50%

T3G3 4 100% 0% 0%

T4G3 3 0% 67% 33%

T1G4 4 50% 0% 50%

T2G4 4 75% 0% 25%

T3G4 4 75% 25% 0%

T4G4 3 67% 33% 0%

T1G5 4 75% 25% 0%

T2G5 4 25% 50% 0%

T3G5 4 100% 0% 0%

T4G5 3 0% 0% 67%

G3 13 54% 31% 15%

G4 15 67% 13% 20%

G5 15 53% 20% 13%

Individually 43 58% 21% 16%

Previous Ideas

0%‐20% 25%‐40% 45%‐60% 65%‐80% 85%‐100% To

T1G3 4 50% 25% 25% 0% 0% 100%

T2G3 2 0% 50% 50% 0% 0% 100%

T3G3 4 0% 25% 50% 0% 25% 100%

T4G3 3 33% 33% 0% 0% 33% 100%

T1G4 4 25% 0% 0% 50% 25% 100%

T2G4 4 50% 25% 0% 25% 0% 100%

T3G4 4 25% 25% 0% 25% 25% 100%

T4G4 3 33% 67% 0% 0% 0% 100%

T1G5 4 75% 0% 0% 25% 0% 100%

T2G5 4 75% 0% 0% 0% 0%

T3G5 4 0% 0% 50% 50% 0% 100%

T4G5 3 0% 33% 33% 0% 0%

G3 13 23% 31% 31% 0% 15% 100%

G4 15 33% 27% 0% 27% 13% 100%

G5 15 40% 7% 20% 20% 0%

Individually 43 33% 21% 16% 16% 9%

Integration of ideas (approximated values)


Table 16: Pearson Correlations for Third Grade

Correlations

IMG_Rank Plan_Rank Ideas Total Clops FX_Rank XCTID DifID XCT

Clops Pearson

Correlation

.321 -.028 -.530 .150 1 .017 .455 -.250 .420

Sig. (2-

tailed)

.679 .972 .470 .850

.983 .545 .750 .580

N 4 4 4 4 4 4 4 4 4

XCTID Pearson

Correlation

.985* .243 -

.845**

.937 .455 .876 1 -

.757**

.937**

Sig. (2-

tailed)

.015 .757 .000 .063 .545 .124

.001 .000

N 4 4 16 4 4 4 16 16 16

DifID Pearson

Correlation

-.949 -.634 .628**

-.961* -.250 -.951

* -.757

** 1 -

.668**

Sig. (2-

tailed)

.051 .366 .009 .039 .750 .049 .001

.005

N 4 4 16 4 4 4 16 16 16

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

Table 17: Pearson Correlations for all three grades

Correlations

CLOPS Total FX Plan IMG Group Grade

CLOPS Pearson Correlation 1 -.292 -.359 .014 -.058 .033 .011

Sig. (1-tailed) .179 .126 .483 .429 .460 .487

N 12 12 12 12 12 12 12

Total Pearson Correlation -.292 1 .960**

.498* .815

** -.001 .000

Sig. (1-tailed) .179 .000 .050 .001 .498 .500

N 12 12 12 12 12 12 12

FX Pearson Correlation -.359 .960**

1 .609* .621

* .023 .012

Sig. (1-tailed) .126 .000 .018 .016 .472 .485

N 12 12 12 12 12 12 12

Plan Pearson Correlation .014 .498* .609

* 1 .150 -.005 .000

Sig. (1-tailed) .483 .050 .018 .321 .494 .500

N 12 12 12 12 12 12 12

IMG Pearson Correlation -.058 .815**

.621* .150 1 -.028 .000

Sig. (1-tailed) .429 .001 .016 .321 .466 .500

N 12 12 12 12 12 12 12

Group Pearson Correlation .033 -.001 .023 -.005 -.028 1 .991**

Sig. (1-tailed) .460 .498 .472 .494 .466 .000

N 12 12 12 12 12 12 12

Grade Pearson Correlation .011 .000 .012 .000 .000 .991**

1


Sig. (1-tailed) .487 .500 .485 .500 .500 .000

N 12 12 12 12 12 12 12

**. Correlation is significant at the 0.01 level (1-tailed).

*. Correlation is significant at the 0.05 level (1-tailed).

Multiple regression analysis on fixation and the five elements of cooperative learning. As

this study aims to explore whether cooperative learning has any effect on elementary engineering

design fixation, a multiple regression analysis (Figure 5) was conducted. Before conducting the

analysis, we used the residual plot and QQplot to make sure the data met the constant variance

and normality assumptions. The fixation score (Table III) was regressed on the five elements of

cooperative learning (Table II). Although the R-square of 0.6039 is rather satisfactory, the

overall F test indicated that we cannot use the full model containing elements of positive

interdependence, individual accountability, group processing, social skills or promotive

interaction to effectively predict the design fixation among 3rd

, 4th

and 5th

graders in the

engineering design project (F0.05, 5,6=1.83, P=0.2414). Nevertheless when examining the T-tests

closer, the variable of S was marginally significant at α level of 0.05 even with P, I G and F

already in the model. The Variance Inflation Factor (VIF) values which exceeded 2.5 indicated

that multicollinearity might be a cause for concern (VIFp=6.85; VIFI=4.66; VIFS=3.72). As

shown in Figure 6, the model only contained the variables of F, S and I nearly reached

significance at α level of 0.05 (F0.05, 3, 8=3.62, P=0.0646). The small sample size might be the

reason why the P-value was not lower. Therefore such results indicated that promotive

interaction, social skills and individual accountability in cooperative learning are significant in

predicting design fixation. The parameter estimate for individual accountability (βI=0.60)

indicated that when individual accountability is increased by one unit while holding other

elements constant, the predicted unit change in the fixation level is smaller than 1, which means


individual accountability helps reduce the fixation level. In the same sense the parameter

estimate for social skills (βS=-1.72) indicated that when social skills is increased by one unit

while holding other elements constant, the predicted unit change in the fixation level is less than

zero, which means fixation level will be greatly decreased with more social skills.

Figure 5: Multiple regression analysis on fixation and the five factors of cooperative learning

Figure 6: Multiple regression analysis on fixation and the "I, F, S" factors of cooperative

learning

Source DF Sum of

Squares

Mean

Square

F Value P-Value

Model 5 28.33235 5.66647 1.83 0.2414

Error 6 18.58432 3.09739

Corrected

Total

11 46.91667

Variable Parameter

Estimate

t Value P-Value Variance

Inflation

Intercept 5.74131 1.8 0.1212 0

P -0.37257 -0.41 0.6972 6.85198

I 0.79012 0.91 0.3978 4.66245

G 0.27063 0.59 0.5748 1.97726

F 0.97913 1.87 0.1106 2.39415

S -1.72471 -2.35 0.0571 3.72453

Source DF Sum of

Suares

Mean

Square

F Value P-Value

Model 3 27.02208 9.00736 3.62 0.0646

Error 8 19.89459 2.48682

Corrected

Total

11 46.91667

Variable Parameter

Estimate

t Value P-Value

Intercept 6.23899 2.35 0.0463

I 0.60494 1.51 0.1705

F 1.04245 2.3 0.0504

S -1.77173 -3.27 0.0113


Analysis of ANCOVA on grade and fixation. In order to investigate the difference of

design fixation level among students of 3rd

, 4th

and 5th

grades, an ANCOVA analysis on grade

and fixation taking cooperative learning score as the covariate was done. The SAS output below

shows that with P-value=0.9028, there is no significant difference between the grade level and

fixation.

Table 18: Analysis of ANCOVA on grade and fixation

Discussion

According to Piaget’s theory of cognitive development stages of children (Driscoll,

2005), 7 to 11 years old belong to the concrete operational period, during when children

overcome egocentrism and demonstrate logically integrated thought to solve concrete problems;

however they still have difficulty thinking hypothetically and systematically. As the participants

in this study were roughly 9 to 11 years old, who belonged to the same cognitive development

stage, this may be the reason why there was no significant difference between grade level and

fixation level. According to the observation notes of CLOP, the students had demonstrated

certain abilities to solve concrete problems in a logical fashion with their group members to

solve problems. For example, at the beginning of the project, they brainstormed on which one of

the four products they would like to do and then voted. However, the 3rd, 4th and 5th graders

could not think about all aspects of a problem at this age level, in this case in spite of group

Source DF Sum of

Squares

Mean

Square

F Value P-Value

Model 3 3.063081 1.021027 0.19 0.9028

Error 8 43.85359 5.481698

Corrected

Total

11 46.91667


sharing they were still largely fixated on their previous knowledge of certain things and the

teenage culture when designing engineering products.

The qualitative data of the study indicated that many students failed to generate novel

ideas in the engineering design project, and that fixation is predictable in the elementary

engineering design project. As mentioned in the literature review, when the individual does not

know about a particular knowledge or technique, he or she is likely to be fixated (Smith, 1995).

To this end, students will draw on existing knowledge that is most accessible to them in design

work (Ward et al., 2002). This may explain why the students seemed to be fixated on the features

of things that first came to their mind. The results indicated that students relied on popular

culture that they attached to the most to derive design ideas, which is in line with Nicholl &

McLellan (2007)’s finding that design idea generation clearly reflects the hobbies and interests

of students of certain age groups. The common reliance on their personal items to generate

design solutions among students may be explained by Ward, Patterson, Sifonis, Dodds, &

Saunders (2002, p. 203)’s path-of-least resistance model in the idea generation, which means

“items that come to mind more quickly and to more people are the ones most likely to be used as

sources of information for the development of new ideas.” As Nicholl & McLellan (2007)

argued that design fixation is the result of the subconscious, automatic and normative cognitive

processes of students, participants in this study had a tendency to generate the design solutions

with little self-awareness.

The third grade scored the lowest across the board in cooperative learning strategies, yet

the Pearson correlation above shows that grade level is insignificant in this sample (r =.011) of

twelve groups. Similarly, the CLOPS appears to be insignificant in regards to this sample of

twelve groups in the imagine rank, plan rank, fixation rank and total score. The cooperation


amongst this group may not be represented in the CLOPS but it does reflect the literature that

indicates cooperative groups work together for a common goal or reward (D. W. Johnson et al.,

1984). This group would appear to fit the description of a cooperative base group as they have a

long term relationship through friendships and sports (D. W. Johnson et al., 1984).

Comparing the grades shows that the grade 4 had the least overall fixation (1.5) with

grade 5 close behind (1.7) and grade 3 the most (2.8) Grade 5 had the best score (1.3) for the

individual imagination stage with grade 4 (2) and grade 3 (2.3) trailing. Grade 4 scored better

during the group planning stage (1), with grade 5 (2) and grade 3 (3) behind. Again, grade

difference was statistically insignificant.

The fixation measures constructed as part of this research appear to be supported by the

data as the fixation ranking and total score are highly correlated with several other scores and

ratios. The fixation ranking significantly correlates with the plan ranking and the imagine

ranking. The total score is almost perfectly correlated with the fixation ranking, which is an

indication that the fixation ranking and total score comprised of too many similar scores.

However, it is a positive sign that the fixation, planning and imagining scores may be valuable

due to the fact that the measures are based on independent factors.

The quantitative analysis in this study demonstrated that the cooperative learning

elements of promotive interaction, social skills and individual accountability are significant in

predicting design fixation. The students in this study were informed at the beginning of this

engineering design project that they would work in groups to compete in a design competition.

They would present their final products to the “clients” and be awarded a certificate if they win.

This instructional design stimulated the individual accountability (Mean=6.33, SD=1.32,

βI=0.60). The students expected each other’s participation in the groupwork, for instance, they


checked each other’s progress in generating individual design solutions. Kern et. al (2007)

argued that social skills (Mean=6.08, SD=1.40, βS=-1.77)that contribute to cooperative learning

include asking clarification, praising, paraphrasing, mediating conflicts and so on and the

students in this study evidenced a number of such skills. For example, the students gave

feedback to each other like “It’s a good/cool idea”; “I like it”; “Isn't it so shiny, we did a good

job” and so on. They asked their group members for clarification such as the size requirement of

the product or their work progress. When they had divergences such as the color or size

selection, they would negotiate through conversations. These observations are in line with the

literature review that the group work can encourage students to generate more solutions in

engineering design activities so that fixation is diminished.

At the same time it should be noted that in the cooperative learning process, several

problems exist as well. According to the filed notes of CLOP, some dominant or most capable

members of a group took over leadership roles at the expense of others. For example, one student

boasted “I'm the best fashion designer in Indianapolis and I guarantee it.” On the other hand, the

introverted or the less capable students withdrew from group discussion and this is social

matching, which is a tendency to conform to peers (Asch, 1951). Some other students took the

advantage of group work without working to their full potential. This was social loafing

(Latane´, Williams & Harkins, 1979), as the design responsibility is diffused among the group

members in group work. These problems were likely to reduce the engagement and cohesiveness

among the group in cooperative learning. This may explain why the element of positive

interdependence had a relatively low score in this study (Mean=6.0, SD=1.52). The group

processing asks for a team to pause every once in a while to see what they had completed up to

that point and adjust their plan for future work (Kern et. al, 2007). As participants in this study


belonged to concrete operational period, they were unable to solve problems systematically and

constant reflective activities involved in group processing were probably beyond their capacities.

Our data showed that there were a couple of outlying groups who outperformed the others with a

larger standard deviation (Mean=6.08, SD=1.64). In addition, although after finishing drawing

their individual design solutions, several groups chose to make in-group presentations; however,

due to the above mentioned problems such as dominance, social loafing and social matching,

group members did not receive much constructive feedback from their peers. This may explain

why the parameter estimate for fixation on the predictor of promotive interaction is relatively

large (βF=1.04). The problems occurring in the group process might have offset certain benefits

of cooperative learning and even lead to more fixation on the group design. For example, there

were a couple of groups who fixed on one member’s design idea and finally chose it as their

group design solution without making any additional changes.

Fixated on common features of things. In this study, elementary school students tended to

come up with their design solutions based on commonly seen features of certain things. For

example, when designing a wallet, the predominantly majority of students chose the most

common shape of rectangular to be their main shape, rather than trying some more unique shapes

such as circle, triangle or crescent. Moreover, 34% of the participants in the study did not

explicitly explain where they got their ideas in the imagination process. Some quotations of

students’ responses in the reflections are “I got my ideas from my brain”; “In my head about a

folder”; “when I see bags I think that.” Some fifth graders attempted to give more reasonable but

still somehow vague answers: “I saw something and changed it a little. I also thought about the

constraint”; “From recent events.”

Conclusion


The fixation scores based on the imagination and planning rankings appear to have

potential for future use but this small population and limited setting added to the absence of

reliability and validity data require that they need to be investigated further. They do align with

the literature that shows that creativity is a factor of fixation (McLellan & Nicholl, 2009) and are

created based on the notion that fixation is the resistance or inability to change ideas, think of

new ideas or abandon old ideas (Dix et al., 2006).

One limitation present in the study was caused by the instructor. One aspect of fixation

for students is becoming fixated on teacher examples whether it is showing items or verbal clues

(Linsey, et al., 2010). This instructor was very careful and deliberate, a skill that has been

developed through experience in teaching this type of curriculum, to not offer any examples that

would add to the student fixation. Based on anecdotal evidence and experience in teaching

similar lessons, it would be safe to assume that not many instructors could avoid this with such

skill.

The limitations of the study render the answer to the research question, “How does

cooperation and age contribute to overcoming fixation?” to be inconclusive. The effectiveness of

the CLOPS is not supported by the data. The high creativity and low cooperation exhibited by

this group reflects the very insignificant correlations between the CLOPS protocol and all of the

other factors. One reason for this could be that the CLOPS was designed to be used in a college

design setting. Another reason could be the fact that the instrument had not been validated and

the only statistical support revealed by the creators of the rubric was a high inter-rater reliability,

which says nothing about the validity of the measure. Also, the CLOPS was intended to be used

in limited settings where groups worked for only twenty minutes at a time and one observer was

used per group, rather than one observer for two to four groups as happened in this study (Kern,


Moore, & Akillioglu, 2007). The addition of a second observation paper made it nearly

impossible to keep up with all of the recording and caused some observers to abandon them in

favor of written field notes.

As design fixation is shown to be rife and predictable among students, teachers need to

look for or develop pedagogical strategies to help students overcome it. According to the

quantitative findings in this study, incorporating the instruction that aims at creating a sense of

individual accountability and encouraging students to adopt more social skills in the group work

may play a significant role in reducing the design fixation level among students. Instructors

could establish clearly defined rules and criteria for grading, which includes points for individual

contribution to the group work. The individual contribution can be assessed using average

peering ratings by other group members in completing assigned tasks in group process.

Instructors may also incorporate some non-competitive, cooperative games which will enhance

social skills in class. For example, they can adopt some role-play games in which students’ skills

in solving conflicts, decision making, consulting others, making observations and so on could be

fostered.

The main limitation of the study is that results are not conclusive. Although a trend has

been found in the relation between design fixation and cooperative learning, the results are not

significant. This can be caused because of the small sample of groups in the study. Since this

research was a first approach of how design fixation and cooperative learning are related, was

adequate to conduct it with a small but relevant sample of students. However, for future research

is important to confirm the relation found, with a larger amount of participants.

Likewise, it is important to conduct further qualitative research about how the relation

between design fixation and cooperative learning is, because cooperative learning has different


elements that can be stronger related with design fixation. In addition, further research may

address questions about the type of the relation. For instance, cooperative learning may promote

overcoming fixation, but also fixation may be the cause of lower levels of cooperative learning.

The following are some possible future research questions. Which of cooperative learning

or design fixation affects the other? Which elements of cooperative learning have a stronger

influence on overcoming design fixation? Does individual design fixation is related with group

design fixation? If so, how this relation can predict levels of cooperation within groups?

Educational Implications

The results of this study show that fixation does exist and the literature supports that

particular classroom environments that promote creativity can help to overcome fixation.

Therefore, it would be wise to use instruction that promotes individual creativity and that helps

children learn creative strategies such as brainstorming. The notion that examples can stifle

creativity lie in stark contrast to those people that say that busy atmospheres, such as decorated

rooms, promote imagination. It would almost seem that from the literature, that a classroom with

little to know visual stimuli would be the most conducive to imagination and brainstorming. One

student was believed to have come up with the most creative idea, a wallet shaped like a Dorito,

revealed that she looked around the classroom for ideas and saw shapes so decided to make her

four sketches all with different shapes. Making a triangle into a Dorito was creative but that was

attributed to the fact that she was hungry.

In regards to the particular curriculum being used in the engineering classroom, I think

this study does reinforce the importance of assuring that students do have the time to imagine

individually. Also, the importance of proper sharing and presentation skills is supported as

design teams can’t integrate each other’s ideas without being able to present or hear them. They


first need to have the opportunity to think and brainstorm on their own in order to spark that

creativity.

Another interesting idea comes from (Dix et al., 2006) in the “Why Bad Ideas are a Good

Idea,” in which the authors propose methods of intentionally presenting bad ideas in creative

settings. While they and other researchers note that bad examples can have a great affect on

fixation, these authors suggest a set of steps that will have students looking at bad ideas to make

them into good ideas. The first step is to analyze the bad idea to determine what is bad about it

and what is good about it. The next step involves three options that can facilitate turning the bad

idea around and are thinking of opposite ideas, changing the context or using role play in which

the bad idea is played out to an extreme. They go on to encourage instructors to facilitate

conversations about bad ideas and have competitions of bad ideas.

Although extreme, these bad ideas activities are one way of meeting Howard-Jones’

(2002) suggestion that providing stimulus for creative thinking is an effective way of avoiding

fixation but cautions against showing examples because they cause fixation. Jones’ research on a

dual model of creative cognition also reveals other strategies to encourage creativity and avoid

fixation. Asking students to perform self-evaluations too early in the design process can be

similar to criticizing ideas shared during brainstorming. He also wrote that extrinsic motivators

such as rewards and competition promote fixation due to the goal-seeking acting as cognitive

block that outweighs the motivation of the goal. Non-competitive and relaxed atmospheres

should promote creativity (Howard-Jones, 2002).


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