From the arcade to the classroom: capitalizing on students’ sensory rich media preferences in disciplined-based learning

W. Gary Howard

The world of contemporary students is bombarded with noise, color, and action; even their entertainment is interactive and high tech. This new environment has impacted all levels of education; however, discipline-based studies capitalizing on this multimedia rich environment have been limited. Researchers have claimed that hypermedia as a learning methodology is in its infancy and called for additional study on its efficacy. This study explored if hypermedia can effectively capitalize on this contemporary sensory rich media environment and effectively employ multimedia effects to discipline-based learning. A pre-test, post-test case law study (n=183) was conducted using a modified hierarchical structure. Findings indicate that significant learning occurred among all class levels of students and for each of the learning styles defined by Kolb’s Learning Style Inventory. Student attitudes toward the learning experience were universally positive. Providing some learner control with structure seemed to accommodate the needs of varied learning styles in terms of achievement and interest.

Educators are confronted by a dilemma: Students have become so accustomed to technology that new means must be employed to retain their interest during the educational process. Even their toys and games involve interactive technology. In an environment of colorful 3-D graphics with elaborate lighting and music soundtracks, students role play on split screens designed for cooperative play. Sitting in front of televisions and computer monitors for hours, they create 3-D characters and settings, solve virtual mysteries, resolve virtual puzzles, or accomplish some virtual global phenomena. They travel through epochs of time making real-time tactical decisions about many events occurring simultaneously. Their virtual players even learn by experience, and their choices create reputations. The games come with tutorials and practice drills to enhance their characters’ skills. Contemporary students are bombarded by noise, color, and fast action in virtually every aspect of their lives.

This technological environment has saturated our communities. No longer is the world of interactive technology solely child’s play or the domain of teenage boys. Every demographic group has been impacted. A recent national survey found that the average age of video garners is now 29, and 64% of them are 18 years of age or older. Actually both men (38%) and women (26%) over 18 years outnumber boys (21%) 6 to 17 years of age ( /27/games.women.reut/index.html). What has been considered teenage boys’ dominion now includes a blend of every segment of society.

Thus has the influx of media in our society impacted students’ everyday lives and, therefore, learning. Because their surroundings and experiences are inundated with sights and sounds, contemporary students very quickly can become bored by slow-moving, traditional lectures and static textbooks; and effecting learning has become even more difficult. Educators, then, must find ways to exploit these “toys” and capitalize on technology in teaching.

Increasingly, educators search for new ways to accommodate today’s interactive, sensory world and to enhance the learning experience. With the increased use of computers in education and training, hypermedia has emerged as a delivery system which has the potential to meet these demands.

Stemler (1997) and Yang (1996) are two of many authors who proclaim the potential of hypermedia in learning environments–a potential, in fact, to revolutionize the way learning occurs. Hypermedia, a technology that is increasingly being used in the contemporary university, is a computer representation of information which may include text, graphics, sound, and video (Merrill, Hammon, Vincent, Reynolds, Christiansen, & Tolman, 1996). Kovalchick, Hrabe, Julian, and Kinzie (2003) cite that these features allow the ability to create real-world complexities and present simulated and authentic case evidence. Using hypermedia, instructors can tailor instruction to meet individual student needs and promote instructional effectiveness for a wide variety of students. Hypermedia also facilitates the amount of personal responsibility or influence an individual can exert in an instructional situation. Sterner continues, “with interactive multimedia programs the learning process becomes active, not passive, and it ensures that users are doing, not simply watching” (p. 340).

The unique characteristics of computer-based systems (e.g., hypertext) allows college professors to accommodate individual differences such as learning styles. Instruction created utilizing learner control precepts permits the learner to structure the learning experience (Jonassen, 1986). Increasingly, instructors are examining the individual differences of students that could influence performance when learning through hypermedia environments (Friend & Cole, 1990; Yoon, 1993-94; Reed, Ayersman, & Kraus, 1997).

While the variables of learning style and computer-based instruction have been experimentally combined, results have been unclear (Cordell, 1991; Yoder, 1994). For example, Ellis, Ford, and Wood (1993) and Dillon and Gabbard (1998) are among those who found that learning styles were a significant factor that influences learning in a hypertext environment; Paolucci (1998) and Ayersman (in Reed et al., 1997), on the other hand, found no significant differences. Yet many researchers have professed that hypermedia can make a significant contribution to education, and educators continuously search for ways to do a better job of meeting the varying learning needs of students.

While hypermedia materials have become increasingly popular in education, research needs to be conducted to ascertain just how effective hypermedia is. Alessi and Trollip (2001) claim that hypermedia is still in its infancy as a learning methodology and considerable ground must be covered before it realizes its full potential. Researchers continue to solicit additional study in this area (Farmer, 1989; Kinzie & Berdel, 1990; Yoon, 1993-94; Song, 2002). Beasley and Waugh (1996) suggest, “the solid empirical research base necessary for guiding the design of effective hypermedia systems is lagging far behind advances in the capabilities of the technology itself” (p. 272). Wells and McKinney (1997) call for instruction to be designed to combine predominate learning abilities of students with appropriate teaching methodologies and media to maximize learning; yet discipline-based studies have been limited, and the need for “further research is warranted …” (p. 13). Song (2002) writes that there is a demand for research on interaction between learners and hypermedia and, “perhaps the most important and challenging is the issue of designing hypermedia that appropriately consider individual learning skills differences” (p. 437).

With such possibilities in mind, the authors of this study set out to see how effectively hypermedia can be employed to teaching and learning in the sensory rich technology environment of the new millennium. In evaluating hypermedia as a teaching tool for student learning, the following three hypotheses were tested:

Hyphothesis One There will be significant learning among all class

levels of students.

Hyphothesis Two There will be no significant difference in learning

between levels of students.

Hyphothesis Three There will be no significant difference in learning

between learning styles.


To determine how successfully students learned using hypermedia, we conducted a pre-test/post-test study (n = 183). Undergraduate students were administered an in-class pre-test to assess prior knowledge of the lesson topic–case law. Two groups were included in the study: a control group which did not receive hypermedia treatment and a group which did complete the hypermedia module. After a two-week period during which students completed a hypermedia lesson, an in-class post-test was administered to measure performance. The pre-test and post-test included questions from various levels of learning which spanned a continuum from concrete to abstract.

The hypermedia treatment, which included text, audio, and graphic segments, was created using a modified hierarchy with associative structures. Students were able to link to related information and menu screens as they progressed through the module much like a concept map links concepts. The learner in this type of environment, thus, experiences moderate learner control.

Design. Since C. C. Langdell introduced it at Harvard in the 1800s, case law has been the predominate method of teaching law in numerous disciplines such as business, communications, education, and political science. Students of law are required to brief a case and to be able to decipher issues and rules of law from incidental information; yet many times the acquaintance with how to accomplish this very important task is derived from a short lecture or a brief handout. These methods lack interaction, and often the professor discovers too late that the students concentrate on facts and not the rule when they cannot apply the principle of law to new situations. The purpose of this study was to ascertain the applicability of hypermedia to deliver this method of teaching legal concepts to college students in an alternative multimedia, interactive setting.

The computer-generated, self-paced module was designed to move the students from general information to more specific information. There are two sections (Components of a Legal Case and Briefing a Legal Case), each with a main menu designed to permit students to choose the element they desired to review. Each of the main menus is similar to stages of a virtual video game, and each of the major steps of a case is like a different screen of a game.

The module is introduced with a movie screen containing title and credits–a familiar scene to the university student. Students receive instruction on how to navigate from screen to screen. For appeal, each screen appears and disappears by fading in and fading out, an effective mechanism for enhancing presentation and viewer interest.

A virtual judge, who is employed as a mentor, delivers a dialogue summarizing the content for each section. The judge also presents an introduction to each of the major steps and summarizes its importance in the judicial process. Additionally, a repository of photos of actual justices with audio clips is used state issues from landmark cases. These scenes are analogous to drills or exercises to sharpen the skills of a player in a video game. Thus, the students benefit from practice in looking beyond the facts of the cases to discern the higher level issues. This technique also acquaints the student with historical justices as it explains where to find and how to distinguish pertinent issues. When students complete the lesson, a screen appears congratulating them on their success.

This multimedia rich, simulation environment captures the interest of students beyond its game-like appeal. It also motivates them by capitalizing on individual learning preferences. Auditory learners concentrate on the audio; visual learners focus on the graphics; and the clips add variety for all learners.

Learning style. To determine the effect of learning type or style, Kolb’s Learning Style Inventory was administered (Kolb, 1981; Smith & Kolb, 1986). While many classifications of learning styles exist, Kolb was selected because it is an inventory that is used predominantly for adult learners. This theory is based on two bipolar dimensions: perception (abstract-concrete) and processing (reflective-active).

According to Kolb, perception and processing form the two dimensions that comprise the basis for understanding how learning styles influence the learning process. The dimensions are based upon the notion that there are competing abilities within each dimension of perception and process. The continuum between each pole allows for gradations in the levels of preference for each dimension. The choice of one ability or another is the basis of the learning styles preference.

Perception reflects how individuals perceive information. For example, abstract learners approach learning analytically and logically; they learn best in instructor-led, impersonal situations that emphasize theory and systematic analysis. These learners tend to be frustrated by unstructured learning experiences. Concrete learners, on the other hand, learn most effectively through specific examples. They benefit from interaction with others, especially learners with similar abilities.

Processing refers to how individuals process information. Reflective learners, for instance, tend to be introverts, and they prefer to observe before making judgments; they favor lecture-type learning situations. Active learners, on the other hand, are more often extraverts, and they display tendencies toward experimentation; they learn best when they participate in projects, homework, and small group discussions (Smith & Kolb, 1986).

Studies have demonstrated that student performance improves when learning styles are considered (Dunn, 1986; Matthews, 1991). Research also support the notion that learning styles interact with other variables, such as learner control and instructional delivery, to variably influence performance (Yoder, 1994).

Statistical tests employed to investigate these effects on achievement and learning styles were paired t-tests, one-way ANOVAs, and ANCOVAs. All tests were conducted at the .05 level of significance.


Hypothesis One dealt with whether or not significant learning occurred among students employing the hypermedia. The total group completing the hypermedia module was composed of students of various class levels and learning styles. The control group had no significant gains (t=1.63, p<. 132); however, significant learning did occur among the hypermedia group. Table 1 displays the learning results for all class levels of students using the hypermedia module.

Learning did occur among all groups of students who completed the hypermedia module, represented by an overall gain for the students of 4.35 items. Using a paired t-test, the results indicate significance at the .0001 level. Table 1 also summarizes the test scores of lower and upper division students and demonstrates that each class level accomplished significant gains in learning. Therefore, Hypothesis One is supported.

Hypothesis Two related to significant learning with the levels of students. The student population included both lower division and upper division students. Were the achievement levels of upper division students significantly different than those of lower division students? The mean gain for lower division students was 5.98 items; it was 4.01 for upper division students. Yet, the mean scores on the post-test were essentially the same. Further analysis was performed using one-way ANOVAs. Results reported in Table 2 indicate support for Hypothesis Two. Significant differences in scores for both pre-test and gain occurred in both groups with lower division students scoring significantly lower on the pre-test and higher on overall gain. However, there was no significant difference on post-test results based on class. Hypothesis Two is supported.

Hypothesis Three proposed that there would be no significant difference in learning between type or style using Kolb’s model. To examine the effect of Kolb’s characteristics on achievement, we ran analyses of covariance for each of the learning styles. Both process (active and reflective) and perception (concrete and abstract) styles were analyzed with the pretest as a covariant and the post-test as the dependent variable. In neither style were the associated p-values significant at the .05 level: active/reflective (F = .457, p = .999) and abstract/concrete (F = 1.195, p = .222); neither process nor perception dimensions of learning styles varied significantly with the hypermedia treatment. Even though significant learning occurred, no significant differences in achievement were observed within any of Kolb’s classifications. Based upon these data, one can conclude that, while learning occurs via hypermedia, learning styles do not necessarily affect how well that learning occurs. Thus, Hypothesis Three–there would be no significant difference between learning styles and achievement levels—is retained.


Maximizing student performance through individualization is one goal of using hypermedia in educational environments. In this study, there was a significant change in performance after the instructional hypermedia treatment. Of more interest, however, is the notion that incorporating learning structures that account for individual learning styles may be an effective way to enhance student performance.

The data support other conclusions in the literature–students can and do learn by hypermedia. Significant learning occurred for all levels of students (from freshman to senior) and for each of the learning styles defined by Kolb. More importantly, perhaps, is the relatively short amount of time that students needed to overcome the prior knowledge of other students. One might assume that upper division students would score higher on the pre-test because of prior knowledge. While upper division students usually had some knowledge of case law prior to completing the hypermedia module, freshmen with no background were able to score as well on the post-test as juniors and seniors. Prior knowledge was overcome using only one hypermedia application, as indicated by the fact that the mean post-test score was essentially the same for both groups.

Not only did students achieve significant gains, hypermedia provided other advantages. For example, the modified hierarchical format allowed learners some degree of control; they were able to manage the pace at which they proceeded through the lesson and select the sequence of the information presentation. They could return to specific sections for review, and they could access additional information. With the click of a mouse, students could explore primary sources through both text, audio, and graphic sequences. Textual, auditory, and graphical instruction allowed for visual and auditory learning preferences and facilitated learning for visual or hearing impaired students.

While some studies suggest that there is an interaction between learning styles and achievement level, this study did not support that notion. Perhaps one explanation for the disparity in findings relates to the principle of learner control. Learner control has been touted as one of the most important advantages of hypermedia. Depending upon a lesson’s design, students are free to create and control their own study paths and to assume more responsibility for learning because of the non-linear nature of hypermedia (Ambrose, 1991). Thus, students accommodate the lesson to their own styles and preferences. There are some concerns about the effectiveness of learner control (Park, 1991); some researchers proffer that since students do not have sufficient knowledge about the content, they cannot make appropriate decisions about learning strategies.

Assessing student attitudes toward the learning experience, we found their responses to the hypermedia were universally positive. They used words like “outstanding,” “beneficial,” “entertaining,” and “worthwhile” to describe the experience. They particularly liked the multimedia effect and the ability to control the pace. In addition, the novelty of the experience may have added to their motivation in the learning experience, enhancing their performance.

In summary, the hypermedia treatment using a modified hierarchy with associated structures allows each of the learning styles to achieve equally well. Through branching, no single established sequence for linking instructional nodes is forced on learners, and learners create their own meaning and knowledge by navigating through the instruction. Too much learner control seems to frustrate some learners while too much structure causes others to feel inhibited. Some students do not have enough content background to know how to employ the non-linear format, while others feel the need to explore many paths. The modified hierarchical structure seems to accommodate the needs of both perception and process styles in terms of achievement and interest. Indications are that this format is a good middle ground.


Educators are ever aware of the need for more effective instructional tools for teaching; they continue to search for ways to maximize the student’s learning experience. Designing hypermedia learning modules has become increasingly popular among educational and instructional researchers; however, the number of hypermedia studies in traditional liberal arts fields has been limited. The purpose of this study was to ascertain the applicability of hypermedia to the major way of studying law (i.e., briefing cases) in the contemporary world of interactive technology. The relationship of learning style was a major component.

This study’s findings indicate a knowledge gain for students completing the hypermedia module. The modified hierarchical model seems to provide a solution to the difference in learning style. Providing some learner control with structure allowed for the preferences of both dimensions as defined by Kolb.

The results of this study support the assertion that hypermedia with its video, audio, and graphics media is a tool that can be applied to the study of case law. The implication is that now the professor can be freed to guide students to explore the impact of a subject rather than the fundamental facts. For those who have been reticent to utilize the computer and hypermedia for fear that students might not learn, these findings provide some assurance that significant learning can and does occur with their use.

In the quest for those universal tools of education, there much remains to discovered. And educators continue to search for modes of instruction to enhance pedagogy. Hypermedia allows an environment wherein students are not just passive viewers of predetermined, sequential presentations. In the contemporary student’s world of bright lights and action, instructors can capitalize on multimedia and technology to promote learning. Having a variety of senses stimulated, students of diverse learning styles can now hypernavigate through learning experiences. Add another technique to the teaching portfolio.

Table 1.

Test Results for Groups Completing Hypermedia Module

Pre-Test Means Post-Test Means t p value

Total Group 7.22 11.56 17.63 .0001

Lower Division 5.28 11.24 11.04 .0001

Upper Division 7.62 11.63 14.26 .0001

Table 2.

ANOVA on the Test Scores Varying by Class Level of Learners

F p value

Pre-Test 17.15 .0001

Post-Test .35 .557

Gain 9.51 .002


Alessi, S. M., & Trollip, S. R. (2001). Multimedia for learning: Methods and development (3rd ed.). Boston: Allyn and Bacon.

Ambrose, D. W. (1991). The effects of hypermedia on learning: A literature review. Educational Technology, 31(12), 51-55.

Beasley, R. E., & Waugh, M.L. (1996). The effects of content-structure focusing on learner structural knowledge acquisition, retention, and disorientation in a hypermedia environment. Journal of Research on Computing in Education, (Spring), 271-281. (2003, August 27). Study: Female gamers outnumber boys. Retrieved August 27, 2003, from games/08/27/games.women.reut/index.html.

Cordell, B. J. (1991). A study of learning styles and computer-assisted instruction. Computers in Education, 16(2), 195-183.

Dillon, A., & Gabbard, R. (1998). Hypermedia as an educational technology: A review of the quantitative research literature on learner comprehension, control, and style. Review of Educational Research, 68(3), 322-349.

Dunn, R. (1986). Learning style: State of the science. Theory into Practice, 24(1), 10-19.

Ellis, D., Ford, N., & Wood, F. (1993). Hypertext and learning styles. The Electronic Library, 11(1), 13-18.

Farmer, L. (1989). Hypertext: Links, nodes, and associations. CLJ, 46(4), 235-238.

Friend, C.L. & Cole, C.L. (1990). Learner control in computer-based instruction: A current literature review. Educational Technology, 30(11), 47-49.

Jonassen, D.H. (1986). Hypertext principles for text and courseware design. Educational Psychologist, 21(4), 269-292.

Kinzie, M.B. & Berdel, R.L. (1990). Design and use of a hypermedia system. ETR&D, 38(3), 61-68.

Kolb, D.A. (1981). Learning styles and disciplinary differences. In A.W. Chickering (Ed.), The Modern American College. (pp. 232-255). San Francisco: Jossey-Bass.

Kolvalchick, A., Hrabe, M. E., Julian, M. F., & Kinzie, M. B. (2003). Constructing ID case studies for use via the world wide web. In P. A. Ertmer and J. Quinn (Eds.), The ID casebook. (pp. 230-238). Upper Saddle River, NJ: Pearson Education, Inc.

Matthews, D.B. (1991). The effects of learning style on grades of first-year college students. Research in Higher Education, 32(3): 253-268.

Merrill, P.E., Hammon, K., Vincent, B.R., Reynolds, P.L., Christiansen, L., & Tolman, M.N. (1996). Computers in Education. Boston: Allyn and Bacon.

Paolucci, R. (1998). The effects of cognitive style and knowledge structure on performance using a hypermedia learning system. Journal of Educational Multimedia and Hypermedia, 7(2/3), 123-150.

Park, O. (1991). Hypermedia: Functional features and research issues. Educational Technology, 31(8), 24-31.

Reed, W.M., Ayersman, D.J. & Kraus, L.A. (1997). The effects of learning style and task type of hypermedia-based mental models. Journal of Educational Multimedia and Hypermedia, 6(3/4), 305-320.

Smith, D.M. & Kolb, D.A. (1986). LSI User’s Guide. Boston: McBer & Company.

Song, C. (2002). Literature review for hypermedia study from an individual learning differences perspective. British Journal of Educational Technology, 33(4), 435-447.

Stemler, L.K. (1997). Educational characteristics of multimedia: A literature review. Journal of Educational Multimedia and Hypermedia, 6(3/4): 339-359.

Wells, J.B. & McKinney, M.K. (1997). Assessing criminal justice student learning styles for multimedia instruction. Journal of Criminal Justice Education, 8(1), 1-18.

Yang, S.C. (1996). Designing instructional applications using constructive hypermedia. Educational Technology, 36(6), 45-50.

Yoder, M.E. (1994). Preferred learning style and educational technology: Linear vs. interactive video. Nursing & Health Care, 15(3), 128-132.

Yoon, G.S. (1993-94). The effects of instructional control, cognitive style, and prior knowledge on learning of computer-assisted instruction. Journal of Educational Technology Systems, 22(4), 357-370.




University of West Florida

COPYRIGHT 2004 Project Innovation (Alabama)

COPYRIGHT 2004 Gale Group

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