Visualizing Mental Models: Understanding Cognitive Change to ...

Visualizing Mental Models: Understanding Cognitive Change to Support 

Teaching and Learning of Multimedia Design and Development 

Sara McNeil, smcneil@uh.edu 

Associate Professor, Instructional Technology 

University of Houston 

College of Education, Curriculum & Instruction 

256 Farish Hall 

Houston, Texas 77204-5027 

Keywords 

Visualization, Mental Models, Assessment of Cognitive Models 

Abstract 

Designing and developing multimedia software is a complex and sometimes confusing learning 

process for students. Often, students learn to use multimedia authoring programs and a collaborative 

instructional design model with little understanding of how the tools and the design process interrelate. In 

this study, teams of instructional technology graduate students in a two-semester, multimedia design and 

development course used an authoring program to create multimedia software for authentic clients. This 

study examined the cognitive changes that occurred when these students were immersed in a project- 

based, collaborative environment. The comparison of students’ visual representations of their mental 

models of multimedia design and development from the beginning and end of the course and in-depth 

interviews provided insight into these changes in their mental models. Students demonstrated significant 

transformations in their mental models from linear, individualistic, and skills-based models at the 

beginning of the course to recursive, collaborative, and team-oriented models at the end. 

"All our ideas and concepts are only internal pictures." 

Ludwig Boltzmann (1899)

Visualizing Mental Models: Understanding Cognitive Change to Support 

Teaching and Learning of Multimedia Design and Development 

This paper reports on the analysis of visual representations of students’ mental models in order to 

understand the cognitive changes that occurred during a collaborative and authentic multimedia design 

and development experience. Students were engaged in a two-semester graduate course that immersed 

them in a project-based learning environment designing software for authentic clients. The main objective 

of the course was to enable students to learn the collaborative design process in combination with 

authoring software and apply this knowledge in a real environment. The course focused on a practitioner 

model of instructional design (Seels & Glasgow, 1997), the application and use of specific authoring 

software (Authorware), and the development of workplace and teamwork skills. 

The workplaces of both today and tomorrow are demanding and dynamic, and require skills that 

are not merely exemplified as technological—logical, analytical, and technical, but also those represented 

as value skills—creativity, critical thinking, the ability to see the big picture, and working in a team (Datz, 

2004). Teaching multimedia design and development in isolated courses may decontextualize the 

learning experience for students. Situating the learning experience in a project-based approach allows 

students to develop strong technical skills and, at the same time, build value skills needed for careers in 

Educational Technology related jobs. 

Assessing students’ achievement of course objectives is critical, especially in this type of situated, 

collaborative environment. Instructors can measure students’ achievement of some course objectives 

through assessing the product developed. Often a rubric with categories such as content, audience 

consideration, and design qualities is used to evaluate multimedia products (Green & Brown, 2002; San 

Mateo County Office of Education, 2000). Other course objectives can be measured through discussion 

either online or face-to-face, through observation of behavior, and through the use of tests or quizzes of 

factual knowledge. However, the changes in ideas and perceptions about the team development process 

are more difficult to observe and measure. This study focused on understanding the cognitive changes 

that occurred as part of the experience through students’ reflective process of creating visual 

representations of mental models of multimedia design and development at the beginning and end of the

Visualizing Mental Models: Understanding Cognitive Change to Support Teaching and Learning of Multimedia Design and Development 

course. Along with in-depth interviews about their learning experiences, these visual representations 

provided a means of understanding the complex changes that occurred during this experience. 

This study was guided by two questions: 

Objectives of the Study 

1. What mental models do beginning designers and developers of multimedia software possess? 

2. How are these mental models changed after an exposure to a project-based, authentic learning 

environment in which the authoring software was used as a cognitive tool? 

My goal was to seek patterns in students’ visualizations of their mental models of multimedia 

design and development to determine whether the course objectives related to understanding 

collaboration in a team environment were met. In this study the mental models were used to judge the 

effectiveness of the invention, in other words, the effectiveness of the course in achieving the objectives. 

In addition, I wanted to understand not only the patterns but also the structure and organization of the 

mental model representations. 

Conceptual Framework 

Scottish psychologist, Kenneth Craik, is credited with first coining the term “mental model” in 1943. Craik’s 

definition of mental model was that of a thought process that provides a representation of some entity or 

system. Craik based his reasoning on the ability of humans to explore real and imaginary situations 

mentally, and he proposed the idea of thinking models that parallel reality: 

If the organism carries a small-scale model of external reality and its own possible 

actions within its head, it is able to try out various alternatives, conclude which is the best 

of them, react to future situations before they arise, utilize the knowledge of past events 

in dealing with the present and future, and in every way react to a much fuller, safer and 

more competent manner to emergencies which face it. 

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(Craik, 1943)


Similar to pictures in Wittgenstein’s (1922) "picture" theory of the meaning of language, mental models 

have a structure that is the equivalent of the structure they represent. Mental models are similar in 

structure to architects’ scale models of buildings, to biologists’ models of complex DNA, and to physicists’ 

diagrams of particle interactions. A person must have a working model of the phenomenon in his or her 

mind in order to understand a real-world phenomenon. Take, for example, individual mental models of 

how cars operate. Although each person’s model would be different, each would be based on a similar 

structure and contain elements that mimic reality – gasoline, pistons, combustion, and exhaust. There are 

differences in novice and expert models, but each model reflects the individual’s understanding at that 

point in time. Although mental models are simpler and less complicated than real-world phenomena, they 

are similar in structure. This similarity allows the holder of the model to make mental inferences about the 

phenomenon that is also true in the real world. 

A learner’s mental model is highly individualized and constantly changing as more input and 

learning take place. Lambert and Walker (1995, p.1) stated that a mental model is, “an individual's 

existing understanding and interpretation of a given concept, which is formed and reformed on the basis 

of experiences, beliefs, values, socio-cultural histories, and prior perceptions. Our mental models (or 

schemas) affect how we interpret new concepts and events.” Nersessian (2007) proposed that mental 

models are “organized units of mental representation of knowledge employed in various cognitive tasks 

including reasoning, problem solving, and discourse comprehension.” (p. 9) 

Donald Norman (1988) gave a current definition of mental models: "…the models people have of 

themselves, others, the environment, or things with which they interact. People form mental models 

through experience, training and instruction." Norman also noted, “To gain control over a technical system 

humans try to build internal mental models of the things with which they are interacting. These models 

provide predictive and explanatory power for understanding.” Cognitive science researchers and 

scientists propose that the mind constructs mental models as a result of perception, imagination and 

knowledge, and the understanding of discourse. 

Mental models have become known as a summation of all of a person's thoughts and 

understandings on a subject. More than just isolated bits of information, a mental model can become a 

system with which exploratory inputs can be fed and observed for its resultant behavior (Carroll & Olson, 

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1988.) Mental models are incomplete, unstable, easily confused, and based on superstition instead of 

scientific fact. Despite these limitations, mental models play a very important role in understanding human 

cognitive change. 

Learners construct new knowledge and modify existing knowledge as they experience situations, 

problems, circumstances, and other events in learning settings (Tzeng & Schwen, 2003). One way to 

measure this learning is to examine the mental models of learners since they can reflect the type and 

level of construction that has occurred. Although mental models are different for novices and experts, the 

models of both continue to change as more knowledge is gained. Authentic project-based learning 

environments have the potential to provide an environment that allows students to experience learning in 

situated contexts, and these experiences enrich and change their mental models. 

In project-based learning, instruction and learning occur within the context of a challenging project 

(Thomas, 2000). Using a project with real-world clients analogous to complicated tasks encountered in 

today’s workplaces, can act as a focus and catalyst for learning. Normally, projects extend over time to 

act as interactive channels to help students acquire, new necessary knowledge, and skills. This approach 

is learner centered and encompasses multiple learning communities—peers, clients, users, instructors, 

and experts. 

Mental Models and Other Visual Techniques of Knowledge Representation 

In a paper discussed on ITFORUM this fall, Mauri Ahlberg (2008) discussed different methods of 

graphically representing knowledge structures. Two methods of creating these representations that she 

discussed are significant to the current study: mind mapping and concept mapping. 

Mind Mapping 

Ahlberg (2008) noted that mind mapping was developed by Buzan (1974), a British psychologist, 

in the early 1970s, and he subsequently registered the term, Mind Map ®. Mind maps closely resemble 

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an aerial view of a tree and are used to represent words, ideas, tasks, or other items. Sub-ideas are 

arranged in a branch-like, organic manner around the central key word or graphic that represents the 

main idea, problem or issue. In addition to the use of color as an organizing tool, small icons and 

drawings are often used to enhance the words and meaning in a mind map. Brinkmann (2003) noted that 

a mind map allows creators to use both sides of their brain which work together and “connects 

imagination with structure and pictures with logic.” 

Buzan’s company has developed software that facilitates the creation of mind maps called 

iMindMap (http://www.imindmap.com/). On the iMindMap website, there is a video under the education 

link about using mind maps for pre- and post-course assessment. The video states: 

…it (mind mapping) encourages students to think metaphorically. This type of thinking 

has been proven to be a useful means of interpreting and expressing complex ideas and 

concepts… Mind mapping provides visual and kinesthetic learners with a better chance 

of expressing their knowledge than traditional assessment techniques…Mind maps 

provide a more realistic representation of knowledge. The method that a mind map uses 

to bring together students’ knowledge moves away from the traditional linear ‘yes-no’ 

assessment and allows their understanding to be more transparent. This provides a more 

realistic representation of their knowledge. 

(transcribed from Pre and Post Assessment in the Classroom video, 

iMindMap website) 

Neither the video nor the iMindMap website provides any citations or evidence to support these 

claims. Ahlberg (2008) noted that there is little empirical research on the efficacy of the mind mapping 

technique and cited a study by Farrand, Hussain, and Hennessey (2002) that suggested that using a 

mind mapping technique could improve recall of factual information by up to 10% over conventional study 

methods. On the iMindMap website, there are 12 articles dealing with the techniques and value of using 

mind maps, but all are clearly promotional material; none are research studies. 

See other examples of mind maps here: 

http://www.12manage.com/methods_mind_mapping.html. 

Concept Mapping 

Concept maps were developed in 1970s by Joseph Novak at Cornell University in his research in 

understanding changes in children’s knowledge of science (Novak & Musonda, 1991). Concept mapping 

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is defined as “a technique of graphically representing concepts and their hierarchical interrelations along 

two dimensions” (Beyerbach, 1988). Concept maps are used to graphically represent knowledge and 

feelings and are composed of concepts that are labeled in circles or boxes. The relationships between 

two concepts are shown by a connecting line that links both concepts. Words are written on this line that 

specifies the relationship between the two concepts. The unit composed of two concepts and the linking 

word is called a proposition. Although the relationships are usually hierarchical, multiple linkages are 

possible (Jonassen, Beissner, & Yacci, 1993). 

Concept mapping is one technique for assessing students’ mental models of complex concepts. 

Concept maps are useful tools in instruction and reflection as well as evaluation of students’ learning. 

Studies involving concept maps have been conducted with a variety of students as young as third grade 

through higher education. In addition to measuring changes in cognitive knowledge, concept maps have 

been used to show attitudinal changes as well. A concept map is a useful tool for obtaining information on 

how the learner organizes information, what key concepts are included, and what types of relationships 

exist between the concepts. 

Novak and Cañas (2008) noted that concept maps may also be used for the assessment of 

student understanding. In the latest versions of CmapTools, a concept mapping software, there is an 

option to compare an “expert” concept map for a topic with maps constructed by students, and all similar 

or different concepts and propositions are shown in color. However, Novak and Cañas state that there is 

no data available about this use. 

Drawbacks Using Mind Mapping and Concept Mapping 

Brinkmann (2003) described a set of rules for using mind maps that she derived from a list of 

sources including Buzan. These rules are very specific and include, “Use a large sheet of paper without 

lines in a landscape format” and “The topic of the mind map should be displayed in an eye-catching way, 

preferably by a coloured image.” (p. 36) There are also rules for creating concept maps. Novak and 

Cañas (2008) stated: 

Given a selected domain and a defined question or problem in this domain, the next step 

is to identify the key concepts that apply to this domain. Usually 15 to 25 concepts will 

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suffice. These concepts could be listed, and then from this list a rank ordered list should 

be established from the most general, most inclusive concept, for this particular problem 

or situation at the top of the list, to the most specific, least general concept at the bottom 

of the list. Although this rank order may be only approximate, it helps to begin the 

process of map construction. We refer to the list of concepts as a parking lot, since we 

will move these concepts into the concept map as we determine where they fit in. Some 

concepts may remain in the parking lot as the map is completed if the mapmaker sees no 

good connection for these with other concepts in the map. 

Both mind maps and concept maps provide structures for creating visual representations of 

knowledge, but because of their predetermined structure and rules, I felt that they may hinder the natural 

expression of a mental model. In this study, students were not given a defined structure to use for their 

mental model representations so that the representations could be as genuine and spontaneous as 

possible. No directions were given about how the representations should be drawn except for the paper 

and tools to be used. Some students had previous knowledge about concept maps, but few of the 

representations they created had qualities of either mind maps or concept maps. 

The Project-Based Learning Experience 

This study was situated in a two-semester, graduate course focused on advanced instructional 

design principles, the application and use of a specific authoring program (Authorware) to create 

software for an actual client, and the development of workplace and team skills needed for optimal 

interaction and collaboration. 

On the first night of class, students completed an initial assessment of computer skills, multimedia 

skills, and team strategies. Students were presented with brief descriptions of the proposed projects and 

asked to rank their first, second, and third choices. The second week of class, students were assigned to 

four different teams based on a combination of factors: the skills assessments, instructor’s knowledge of 

each student’s abilities and background, and student preference. Most students received their first or 

second choice. Clients included the Children’s Museum, the Museum of Fine Arts, Houston, and the 

Franz Meyer Museum of Mexico City. 

During the first part of the course (mid-August through mid-December), the teams identified 

instructional needs, formulated objectives, wrote content, and created storyboards for the project. In the 

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second part of the course (mid-January through mid-May), the teams designed the interface and 

graphical elements, used Authorware to develop the project, and evaluated the software with target 

users. Throughout the design and development of the software, the teams worked closely with their 

clients in an iterative and recursive process which provided for a meaningful situated context for their 

learning experience. 

Over the nine month experience, the role of the instructor in this course changed from information 

provider to facilitator to observer as teams assumed increasing responsibility for both their learning 

process and their product. 

Methods and Data Sources 

Using a multifaceted approach, data collection included eliciting pre- and post-course visual 

representations of students’ mental models of multimedia design and development as well as conducting 

in-depth interviews, and examining peer-evaluations of team performance, weekly individual and team 

reflections of progress, and evaluating the actual software that was developed. Participants in this study 

were graduate (masters and doctoral level) instructional technology students who had completed 

introductory courses in instructional design and courseware authoring. 

Data collection began in the first class meeting with collecting students’ initial mental models of 

multimedia design and development. Students were asked to create this visual representation on a single 

piece of paper using pencils, pens, or color markers. Technology applications such as Inspiration were 

not used because I felt that they would filter students’ representations through a pre-determined format, 

and they would require prior knowledge of the tools. In addition, I did not ask students to use the structure 

of either mind mapping or concept mapping since I wanted students to express their initial 

representations as easily and as simply as possible. At the end of the course, students were once again 

asked to visually represent their mental models of multimedia design and development using the same 

parameters as the first. Students did not see or discuss their pre-course maps after creating them. 

Other techniques were also used to gather data. Interviews were conducted by another 

researcher and were taped and transcribed. The objective for the interviews was to gain access to 

students’ understandings, feelings, and attitudes about their design and development process in the 

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collaborative project-based environment. Two peer-evaluations were conducted for each team member at 

the middle (December) and end (May) of the courses. Peer evaluations used a Likert scale and open 

ended responses to questions about team performance, member roles, and achievement of course 

objectives. Finally, both individual and team reports that students posted as documentation of weekly 

progress were collected using an on-line form and database. 

All these forms of data from multiple sources collected using different methods were examined for 

significant themes that documented the changes in students’ mental models of multimedia design and 

development. The process included looking for themes and patterns in the data as well as examining the 

structure and organization of the visual representations of the mental models (Gentner & Stevens, 1983; 

Johnson-Laird, 1983). 

Organizing and Measuring Mental Models 

Doyle, Radzicki, and Trees (2008) noted that there are a variety of formal techniques used by 

researchers to organize and represent mental model information. These include systems flow diagrams, 

causal loop diagrams, influence diagrams, hexagons, and social fabric matrices. The problem with using 

one of these techniques is that these techniques were designed to facilitate change in mental models not 

to measure change. Doyle et al. (2008) stated “…the very features that make them valuable for changing 

mental models …simultaneously make them unsuitable for measuring that change in an accurate and 

unbiased way.” These researchers proposed that any method for measuring mental models should have 

eight goals: (1) attain a high degree of experimental control; (2) separate measurement and 

improvement; (3) collect data from individuals in isolation; (4) collect detailed data from the memory of 

each individual; (5) measure change rather than perceived change; (6) obtain quantitative measures of 

characteristics of mental models; (7) employ a naturalistic task and response format; and (8) obtain 

sufficient statistical power. Studies by Vennix (1990) and Doyle et al. (2007) using these goals relied on 

detailed content analysis of written essays and did not use any form of visual representation. The present 

study applied this same approach but used the analysis and interpretation of visual models. 

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Semiotic Analysis 

Measuring learners’ cognitive change is a complex task, and many types of data may be used to 

assess and analyze mental models. In this study, changes in the mental models of learners were studied 

using semiotic analysis of the pre- and post-course visual representations. Semiotics is a philosophical 

approach that seeks to interpret messages in terms of their signs and patterns of symbolism. As a field of 

study, semiotics offers a framework for understanding visual representations of concepts and provides a 

way to understand and compare different representations. As a mode of analysis, semiotics attempts to 

uncover the rules and principles that account for patterns of behavior as well as to interpret 

communication patterns through the use of metaphors. “A metaphor substitutes one expression for 

another in order to produce an expansion (or a ‘condensation’) of knowledge at the semantic level.” (Eco, 

1990). 

Kress and van Leeuwen (1996) proposed a vocabulary for visual semiotics that provides a 

descriptive framework for analysis: (1) representational meaning, how the image and its parts represent 

the world; (2) interactive meaning, the interaction that the image contains or represents; and (3) 

compositional meaning, how the layout, placement and salience of the image combine to provide the total 

composition. Representational meaning is further classified into one of two visual syntactic patterns: 

narrative structures that contain vectors that either directly or subconsciously connect parts and direct the 

gaze of the viewer, and conceptual structures that visually define, analyze or classify parts (Jewitt & 

Oyama, 2001). Interactive meaning is divided into three parts: (a) contact, making contact with the viewer 

to establish a relationship; (b) distance, the framing of an image to be close or far; and (c) point of view, 

the perspective from which the image is taken. Compositional meaning is divided into four parts: (a) 

information value, where the elements are placed in a composition; (b) framing, how the elements in a 

composition are ‘connected’ or ‘disconnected’ from one another; (c) salience, making some elements 

stand out more than others; and (d) modality, the form of the visual itself. For this study, only 

representational meaning and compositional meaning were used to structure the analysis since the 

visuals were drawings, and interactive meaning was difficult to determine. 

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Changes in Mental Models 

Participants in this study demonstrated significant changes in their mental models over the two- 

semester period. Three major themes emerged from the comparison of pre- and post-course 

representations of their mental models. The themes indicated change from a linear, individualistic, and 

skills-based model to a recursive, collaborative, and team-oriented model. 

The themes were: 

1. Structure and Organization of the mental models changed from isolated and individualistic 

representations to collaborative and team oriented processes. 

2. The Mindset and Attitudes of the students changed from skills in isolation to teamwork and 

collaboration. 

3. Knowledge Constructs in the representations changed from a focus on small, isolated units or 

the individual parts to the whole, a cognitive model that included the big picture. 

In order to develop these themes, I looked for patterns in the students’ representations, 

interviews, and journals that indicated change and organized the emerging patterns in tables. Analysis 

was aided by discussion with other researchers of the emerging patterns and furthered by repeatedly 

reading and seeking for confirming and disconfirming membership of these patterns under possible 

categories. This process resulted in the development of the final themes summarized in Table 1. The 

differences noted here may be indicative of students’ changes in their mental models of multimedia 

design and development. 

It is important to note that the post representations of mental models are distinct from the pre- 

course representations, perhaps as expected. What makes these findings interesting is the display of 

specific emphasis on collaborative teamwork and the importance of both technical and value skills in the 

final representations. I believe that this is not merely a happy coincidence, but a result of the carefully 

designed and implemented two-semester long course experience that was perceived as authentic and as 

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close to a real-world experience as possible in an academic setting. The project-based learning 

experience itself, not merely technical skills or theoretical learning (e.g., instructional design theory) 

influenced the students’ construction of a mental model that reflected the inherent complexity of the 

process of multimedia design and development. 

Table 1. Changes in Students’ Mental Models Grouped by Theme 

PRE POST 

Theme 1. Structure and Organization 

Each step of the multimedia design and 

development process is carefully contained in its 

own space. 

Process is represented as linear and directional 

(indicated by one way arrows). 

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Phases of the multimedia design and 

development process are overlapping, 

intermingled, and recursive. 

Process is largely represented as overlapping, 

circular, and spiral (represented by multidirectional, 

often circular movement). 

Process has fewer steps. Process has multiple interactive processes. 

Job titles such as designer, developer, client, user, 

are largely isolated from each other. 

Job titles are not a strong focus; instead the 

focus is on the output of that phase. 

Process is ordered, separated, and regimented. Less structured, more dynamic and interrelated. 

Theme 2. Mindset, Attitudes 

Individualistic mindset is primary in the 

representations. (What do I need to know? What can 

I do?) 

Collaborative mindset is central in the 

representation. (What does the team do?) 

If used, the team is only a part of the whole process. The team is an all-encompassing part of the 

entire process. 

Little appreciation of the value of the team is 

demonstrated. 

The focus on the team is well demonstrated. 

Few value skills are represented. Many value skills (e.g., creativity, critical 

Emphasis on hands-on abilities such as using a 

specific application is noted in the representations. 

thinking, and communication) are represented. 

Emphasis on cognitive skills such as 

theoretical planning and knowledge of process 

is noted in the representations. 

Theme 3. Knowledge Constructs 

Less content is shown in the representation. Dense content is shown in the representation.


Focus of the content is on technical skills. Focus of the content is on multiple skills 

(including both technical and value skills) and 

how they relate. 

If used, teamwork is isolated and is a small part. Teamwork is usually at the center and is a 

large part. 

Concepts described in the content are simple and 

lacking continuity. 

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Concepts described in the content are complex 

and cohesive. 

Instructional design ideas depicted are largely that of Instructional design ideas depicted are more 

a simple systematic model. 

complex and originate from a need, rather than 

a stepwise model. 

In addition to using semiotic framework to analyze the mental models, I also used the following 

four key objectives of the course as lenses through which to further analyze the representations: (1) 

Multimedia, (2) Authoring Software, (3) Design and Development in Collaborative Teams, and (4) 

Instructional Design. These key aspects are intrinsic to the multimedia design and development process 

and were used by the instructor to build the course outcomes and structure the learners’ experiences. I 

applied this approach to understand the changes in students’ mental models of multimedia design and 

development for each student by analyzing that student’s data as a separate case. These analyses 

demonstrated that what may have seemed like isolated and discrete notions about multimedia design and 

development gathered from prior experiences clearly evolved to show richer and more complex 

understandings of the process. 

Two students’ visualizations of their mental models prior to and at the end of the two-semester 

experience are shared here to illustrate the changes in mental models. While participants’ pre-course 

mental models differed, they were all clearly influenced by their prior experiences and knowledge of 

computer and multimedia skills, and team strategies. In the post-course representations, the participants’ 

mental models all showed an increase in the importance of collaboration, teamwork, and value skills. 

Student 1


Student 1 Pre-Course Representation Student 1 Post-Course Representation 

Figure 1. Student 1 - PRE 

The visual representation of Student 1’s pre-course mental model is presented in Figure 1. 

Student 1 - PRE contains 17 items and has four streams coming off of one main concept at the center of 

the representation: technical skills. The four streams are: applications, choice of application, learning 

curve, and implementation. Applications is divided into four subtopics: graphics, video, voice, and 

Authorware. Choice of application is divided into three subtopics: Why?, Where?, and When? Learning 

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curve is divided into three subtopics: book resources, tutoring, and time. The fourth stream, 

implementation, is divided into two subtopics: objective of the project and team work. 


Representational meaning: The representation of Student 1’s PRE mental model is similar to a 

concept map and contains solid lines that are used to connect the streams to the main topic and dotted 

lines that are used to indicate connections between subtopics. It is substantially different from a concept 

map in that it does not contain words that specify the relationship between the two concepts. 

Compositional meaning. The placement of elements in the PRE model emphasizes technical 

skills since the oval that contains those words is larger and centered. The elements are all connected with 

a line, but each element ‘stands alone’ in a separate oval that doesn’t directly touch another. Four dotted 

lines connect learning curve and implementation, learning curve and applications, choice of application 

and implementation, and choice of application and applications. Color is used to further classify elements 

into groups, but it doesn’t appear to serve any other purpose. The shapes are all organic, but similar. Size 

of the ovals and placement indicate importance of each element. There is an open space at the lower 

right side of the model that makes it seem incomplete and lop-sided as if another stream was to be 

placed there. 

Course Objectives Analysis 

Multimedia. Student 1 - PRE presents a techno-centric view of multimedia. With technical skills at 

the center of the representation, there seems to be an emphasis on hands-on abilities rather than 

cognitive skills such as knowledge of the whole process or an instructional design model. The student 

does show four aspects of multimedia: the authoring software, video, voice and graphics. 

Authoring Software. Student 1 – PRE has a stream that lists applications for authoring software 

and includes several different types of media. Instead of listing generic applications for the authoring 

program, Student 1 – PRE lists the specific software used for the projects. 

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Design and Development in Collaborative Teams. Student 1 – PRE lists one item related to 

design teams: team work. No characteristic or skill associated with working in a team is shown. 

Instructional Design. Student 1 – PRE provides one item related to instructional design: objective 

of project. Although all students had a knowledge of a generic instructional design model through 

previous coursework, individual steps of an ID model were rarely used in the PRE representations. 

Figure 2. Student 1 – POST 

Student 1- POST contains 38 items and has interlocking circles around one main concept at the 

center: Goal: Multimedia Product. There are not clear streams; instead the circles, with the word skill at 

each juncture of the circles, seem to be connected and interrelated. In comparison to the student’s first 

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visual representation, it shows a much richer view of multimedia and the surrounding factors. In addition, 

the interrelatedness of the items begins to show the complexity of the cognitive model and the 

relationships of the items. Many skills, rather than merely technical skills, are a part of the complex 

process. 


Representational meaning. This image does not contain vectors; instead, the conceptual 

structures, circles, are joined and interconnected like a ring with no beginning and end. The meaning is 

clear that the creator meant for the elements to be seen as interrelated as well as having shared 

boundaries much like a Venn diagram. 

Compositional meaning. The elements are placed significantly in the composition with 

overlapping edges and mutual boundaries providing a connected, cohesive framing. It is significant that 

no element stands out more than others with the exception of the center label, Goal: Multimedia Product. 


Multimedia. Student 1 - POST presents a very different view of multimedia than Student 1 - PRE. 

Multimedia is integrated into the center of the representation, and there is less focus on the software 

application (Authorware) and more emphasis on the collaborative product. 

Authoring Software. Student 1 – POST integrates authoring skills throughout the representation 

with such items as Audio, Interface Layout, Graphics, Animation, and Authorware. 

Design and Development in Collaborative Teams. Student 1 – POST contains several items 

related to team qualities in addition to the one item, Team, that was used in the PRE representation. 

Items related to design teams include: Cooperation, Shared Responsibility, Written Communication, and 

Oral Communication, all important aspects of value skills. 

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Instructional Design. Student 1 – POST provides one item: instructional design. At first glance, 

this omission seemed negative. However, this could be indicative that the student had internalized core 

tenets of instructional design into the entire process. One of the objectives of the course was that the final 

product demonstrates the participants’ knowledge of a collaborative instructional design model. The 

absence of specific steps in the instructional design process in the final mental model representation 

supports that this internalization may have occurred. Other evidence I used to make this assertion was a 

careful evaluation of the final multimedia product, by the students, instructors and clients, as well as a 

group of target users. Additional contributing indicators of this internalization included observations of the 

team’s application of the instructional design process as well as individual and team journals. 

The interview data also supports the changes demonstrated in the visual representations 

of Student 1’s mental models. She described how her attitude has changed from an isolated 

teacher designing materials alone to working with other teachers in a collaborative environment. 

… as a teacher – a secondary teacher – we are often alone, isolated. And we’re 

totally responsible for our students, our content, what we teach. And we don’t have that 

opportunity unless we make the effort, after school, weekends, evenings, to meet with 

someone else and share and do something together. During the day there’s no time. 

And so I always think I’m going to work together with other people, do projects 

together. And I started doing a lot of that in the last two years that I taught, but it wasn’t 

really with other teachers it was people outside like at the public library, or – I did a lot of 

work with different libraries. And so I never got to do that sharing or working together as 

a team. I always ended up being responsible for doing things by myself. 

And so what I really thought was great about this is that we were all teachers, 

and we got to work together. And so for me I realized, hey, you know, what? Teachers 

can work together. So it was a great experience even though we’re – none of us are 

really teaching. I mean, I guess I’m the closest to the teaching. But it was a great 

experience, you know, for working together. And I think – I realize that, you know, I can 

work in a team. I can work together and get a project completed. You know, so it was 

reaffirming in that way. 

18


Student 2 

Student 2 Pre-Course Representation Student 2 Post-Course Representation 

The visual representation of Student 2’s pre-course mental model is presented in Figure 3. 

Student 2 - PRE emphasizes skills – the main topic noted in the center circle. The representation contains 

32 items and has five streams coming off of one main concept at the center of the representation: skills 

for CUIN 7327 (the name of the course). It is interesting to note that this representation has words 

immediately above each subtopic that create more meaning; these words are shown below in brackets. 

The five streams are: technical skills, instructional design skills, public relations skills, knowledge 

acquisition skills, and teamwork skills. Technical skills is divided into six subtopics: [learn] program, 

[create method of] navigation, [add] applications, [test &] troubleshoot, [adapt to different] levels, and 

[gain skills in] programming. Instructional design skills is divided into five subtopics: [add] graphics, 

[decide on] sequence, [make it] user-friendly, [appeal to audience], and [create] layout. Public relations 

skills with client is divided into four subtopics: [assess] needs, [produce] presentations, [good] 

communication, and [present] ideas. The fourth stream, knowledge acquisition skills is divided into six 

subtopics: [research] topic, [gather] information [from client], [align] content [with objectives], [write] 

19


content, [edit] content, and [establish] assessment. Teamwork skills is divided into six subtopics: [set 

aside] time, [equal] participation, [be] flexible, trust, [open] communication, and [build upon] strength. 

Figure 3. Student 2 - PRE 


20


Representational meaning. This image does not contain obvious vectors; instead, the conceptual 

elements, shapes like flower petals, are arranged around the center circle. The placement of the shapes 

is very structured, and no shape touches another. Each subtopic is carefully, but invisibly, joined to the 

corresponding topic. 

Compositional meaning. The elements share no boundaries. Each of the streams is roughly equal 

size, and each of the subtopics is approximately the shape and dimensions. No element stands out more 

than others with the exception of the center circle, skills for CUIN 7327. The composition is carefully 

balanced, unlike Student 1’s PRE lopsided representation, and each element is positioned precisely so 

nothing feels random or haphazard. The modality of the image is decorative and resembles a poster or 

graphic rather than a representation of a mental model. 


Multimedia. Student 2 - PRE also emphasizes skills but only one, [add] graphics under the 

stream, instructional design skills, recognizes the multimedia aspect of the course. There is no mention of 

any other feature of multimedia such as audio, video, animation, interactivity, or non-linear navigation. 

Authoring Software. Student 2 – PRE has stream for technical skills that contains [learn] program 

and [gain skills in] programming, but no mention is made of the particular software program used. The 

emphasis is on programming, not authoring. 

Design and Development in Collaborative Teams. Student 2 – PRE created a stream called 

teamwork skills, noting needs of the team to [set aside] time, have [equal] participation, to [be] flexible, to 

trust, to have [open] communication, and to [build upon] strengths. 

Instructional Design. Student 1 – PRE provides several subtopics related to instructional design, 

but interestingly enough they are scattered in other streams as well as the one labeled instructional 

design skills. For example, [establish] assessment is under knowledge acquisition skills, and [assess] 

needs in under public relations skills with client. The items listed under instructional design skills are a bit 

21


unusual as well. Three items, [add] graphics, [create] layout and [make it] user friendly are more graphic 

design skills rather than instructional design skills. 

Overall, Student 2’s PRE mental model representation is unusual because each item is carefully 

segmented and roughly equidistant from each other. The shapes are self-contained and stylized, and 

they are not connected with a mechanical means like a line. The interconnectedness of the items and 

their relationship to each other, except for falling under a particular stream, is not demonstrated. As far as 

size of the elements, each of the five main streams is the same size and the subtopics are the same size; 

size is not used to emphasize any subtopic. 

Student 2 - POST 

Student 2- POST contains 20 items and is composed of very organic, freeform shapes that seem 

to fit into one another like puzzle pieces. Like Student 1’s POST representation, all of the components 

seem to be connected and interrelated. Similar to the differences between Student 1’s PRE and POST 

representations, Student 2’s POST visual representation shows a much richer and deeper view of 

multimedia and the surrounding factors. The interrelatedness of the items also shows the complexity of 

the cognitive model and the relationships of the items. The largest shape, Teamwork, plays a dominant 

role in the representation. 

22


Figure 4. Student 2 – POST 

23



Representational meaning.. While the shapes in Student 2’s PRE representation were very crisp 

and singular, the shapes in the POST representation almost seem to be growing and moving like living 

organisms. These amorphous figures, while still not physically touching, seem to be invisibly connected to 

one another because of the way they are drawn in mirror edges – each edge the reverse of the one next 

to it. 

Compositional meaning. Two techniques, color and size, are used deliberately and play an 

important part in understanding Student 2’s POST representation. Color is used to show relationships and 

hierarchy as well as to indicate categories. Size is used to show importance. The top shape, Multimedia 

design skills, is made up of a combination of colors – green, yellow, red, blue and purple – suggesting 

that this topic may be the combination of all of the subtopics. Formative evaluation on the top left is solid 

red, and summative evaluation on the top right is solid yellow. The next shape, which is also the largest, 

is Teamwork and it directly reflects the four main colors of the shapes directly below it, green, blue, 

purple, and red, which could indicate that it is composed of these subtopics. 

The color in these subtopics is equally descriptive. The first subtopic under Teamwork and on the 

left side is labeled Time & Effort. Below it, in shades of green ranging from dark green to light green, are 

the subtopics of Determination and Dedication. The next shape, labeled Graphic skills, is colored in blue, 

and below, in shades from dark to light blue, are shapes labeled Layout, Design, Artwork, and Sound. 

The shape labeled Authorware programming skills is purple, and the shapes below are Knowledge of 

icons, Variables & functions, and Navigation. Again, each shape ranges from dark purple for the top icon 

to light purple for the bottom icon. Finally, a red shape labeled Organization is shown on the far right with 

the shapes below labeled Timeline, Communication, and Focus in shades of dark to light red. 


24


Multimedia. Student 2 - POST presents a very different view of multimedia than Student 2 - PRE. 

Multimedia Design Skills is at the top of the model and is integrated into the center of the representation. 

The shape resembles a person, and there is emphasis on formative and summative evaluation. 

Authoring Software. Student 2 – POST contains a subtopic called Authorware programming skills 

with other components of knowledge of icons, variables & functions, and navigation. 

Design and Development in Collaborative Teams. Student 2 – POST emphasizes teamwork with 

a large shape labeled teamwork skills that is located directly under multimedia design skills and above the 

four other subtopics. 

Instructional Design. Like Student 1’s POST representation, Student 2 – POST does not provide 

specific references to steps in the instructional design process. I believe this is supporting evidence that 

this student, like Student 1, had internalized the core tenets of instructional design into the entire process. 

Conclusion 

The comparison of students’ representations of their mental models of multimedia design and 

development from the beginning and end of the course, and in-depth interviews provided a case-by-case 

understanding of changes in mental models. This process of analyzing changes in each student’s mental 

models made it possible to gain a better understanding of student needs, and facilitating the learning of 

multimedia design and development. 

In conclusion, I found that students demonstrated a more coherent visual representation of their 

mental models and these representations were structurally more cohesive. All final representations 

showed significant changes from linear, individualistic, and skills-based models to recursive, 

collaborative, and team-oriented models. 

25


Educational Significance 

Graduate students in instructional technology take many isolated courses in learning theory, 

instructional design and technology applications. The very nature of an academic environment that 

segments knowledge into separate courses, contributes to students’ perception of skills and knowledge in 

isolation. As evidenced in the pre-course representations, students’ prior knowledge is often ill-defined. A 

critical factor therefore is the careful, planned integration and practice of all three of these strands: 

learning theory, instructional design and technology applications. Capstone courses such as the one 

described in this study, may provide this type of integration in an authentic context. It is important to 

determine however, whether students have actually achieved the objectives of this experience. The 

visualization of cognitive models and the change that occurs after this type of experience can help us 

understand what’s inside the learner’s head in relation to thinking, knowing, and learning. This 

understanding can help us improve and support teaching and learning experiences in multimedia design 

and development. 

Instructors of multimedia design and development who are more aware of the role that mental 

models play in learning ill-structured knowledge are more likely to succeed in supporting learners’ 

experiences (Eckert & Bell, 2005). Visualization of mental models can help both instructors and students 

understand the knowledge building process (Yehezkel, Ben-Ari, & Dreyfus, 2005). 

Acknowledgements 

I would like to thank a former colleague, Dr. Tirupalavanam G. Ganesh, now at Arizona State University, 

who collaborated with me on an earlier version of this paper. I also appreciate the help of a doctoral 

student, Nancy Barnhart, in organizing information about mental model research. A recent graduate of the 

IT Program at the University of Houston, Dr. Larry Butts, used the interviews collected in this study for his 

26


dissertation and provide insights into mental model development. 

27


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