Oct 2004 Index
Home Page


Editor’s Note
: Simulation and gaming have a special place in learning technologies because they are interactive and because they allow experimentation and discovery learning of multi-faceted skills in a close to real-world environment. Like most skill development, computer simulations benefit from preparation, guidance, coaching, and debriefing to optimize the learning experience. The ability to deliver these simulations online makes them a powerful alternative or supplement to work at a training site or educational institution.

Computer Simulations in Distance Education


Les M. Lunce

Keywords: Anchored instruction, distance education, experimental learning, feedback, interactive practice, problem solving, simulation, virtual reality.

Introduction

Distance education can incorporate many types of media and instructional methodologies, including computer simulations. Computer simulations can play a crucial role in distance education because they can provide a vehicle for “interactive practice” (Berge, 2002). “Interactive practice” can enable the student to respond to new and changing information in ways which closely approximate real-life situations. This type of instructional experience can produce a depth of learning which is difficult to achieve with other modalities.

The purpose of this paper is to explore the role that computer simulations can play in distance education. Specifically, the question of whether computer simulations can contribute to the learning experience will be investigated. To explore this question, seven cases from current research of computer simulations in distance education have been selected. All research presented was conducted by academic institutions in the United States, Europe and Taiwan between 1997 and 2002. The development tools employed in these research projects included Java applets, Asymetrix ToolBook© authoring software, virtual reality and video teleconferencing. The discussion presented here will focus on the design methodologies utilized in each project. Discussion or evaluation of the specific development tools is beyond the scope of this paper.

Details of the seven selected research projects are presented under “Current Research” below.

Definitions

The terms “computer simulations” and “distance education” are used throughout this paper. These terms are defined as follows:

Distance education. An institution-based formal education delivered in a setting or situation in which the instructor and learner are separated by distance, by time, or by both time and distance (Simonson, et. al., 2001). Further, “distance education employs media and technology”, often the World Wide Web (Web), to facilitate “two-way communication” between the teacher and the student (Ko & Rosen, 2001). Finally, “instruction tends to be focused on the needs of the individual student” rather than addressing students as a group (McIsaac & Gunawardena, 1996). In distance education, “the student controls”, to a large degree, location, time, and pace of learning (Evans & Fan, 2002).

Computer simulation. A computer model of a real-life system or process represented in an abstracted or scaled-down form (Heinich, et. al. 1999; Sternberg, 1999). Users of computer simulations may interact with other people or with elements of a simulated environment. Computer simulations can be powerful tools for analyzing, designing, and interacting with complex systems or processes. Well-designed computer simulations provide a model of those elements most relevant to the immediate learning objective. In addition, “they inform the instructor and the learner of aspects of the real-life system or process that have been simplified” or eliminated (Heinich, et. al., 1999; Sternberg, 1999). Effective computer simulations are built upon “mathematical models” in order to accurately depict the phenomena or process to be studied (Min, 2002). At the same time, “computer simulations have been found to be most effective for learning when unimportant aspects of the real-life situation or process are eliminated from the simulation” (Granland, et. al., 2000).

Why Computer Simulations?

Computer simulations provide a method for checking our understanding of the real world by modeling the structure and dynamics of a conceptual system or a real environment. They facilitate “interactive practice” of real-world skills by focusing on essential elements of a real problem or system (Heinich, et. al., 1999). Computer simulations can “communicate complex and technical scientific information” similar to interactive museum exhibits (Saul, 2001). A well-designed computer simulation can engage the learner in interaction by helping the learner to predict the course and results of certain actions, understand why observed events occur, explore the effects of modifying preliminary conclusions, evaluate ideas, gain insight and stimulate critical thinking. Computer simulations can also provide the learner with “feedback throughout the learning process” (Granland, et. al., 2000). Because “computer simulations are flexible and dynamic”, they can guide the learner in the achievement of specific learning goals (Gibbons, et. al., 1997). Finally, computer simulations permit the learner to experience or experiment with problems that would be too dangerous or expensive to explore in reality. The facility to “explore hypothetical scenarios and test hypothesis” makes computer simulations an important tool in science education (Forinash & Wisman, 2001). Through the use of “Java applets” computer simulations can now be delivered over the Web making them a viable component in the distance learning experience (Granland, et. al., 2000; Osciak & Milheim, 2001).

Computer simulations do have distinct disadvantages compared with other modalities. First, because computer simulations are often used with “problem-based learning” methods, they stimulate learners to immerse themselves in a problematic situation and experiment with different approaches (Heinich, et. al., 1999). This type of learning may require significantly more time than other methods of instruction. Second, research has shown that, without coaching, the learner gains little from “discovery learning” from computer simulations (Min, 2001; Heinich, et. al., 1999). Third, constructivists argue that computer simulations “oversimplify the complexities of real-life situations”, giving the learner a “false understanding” of a real life problem or system (Heinich, et. al., 1999). Finally, development of computer simulations may involve extensive planning and require significant investment of labor and financial resources.

Current Research

The use of computer simulations in distance education is a relatively new phenomena and research in this area is limited. Even so there are ongoing efforts towards developing and studying the use of computer simulations in distance education illustrated by seven simulation projects:

1. Open Software Solutions

Sharp and Hall (2000) reported on a case study of a software engineering course offered through the Open University in the United Kingdom (UK). Students enrolled in the course interacted with a “multimedia computer simulation” of a software publishing house. The object of the simulation was to give students a feel for participating in a software development team in a realistic workplace setting. The computer simulation allowed students to make choices based on incomplete information and to see the consequences of their choices. The learning objective of the simulation was “anchored instruction”, resulting in a self-motivated and relevant learning experience (Heinich, et. al., 1999). The materials presented in the computer simulation were supported and supplemented by a course pack of printed materials sent to each student. The course pack contained basic information while the computer simulation provided challenging applications of basic knowledge and skills. In addition, each student was assigned to a tutor / coach who offered support and guidance by email or telephone.

Feedback is an essential element in any learning experience (Gagne, et. al., 1992). In the case of the software publishing house computer simulation, a significant feedback element was provided by the simulation software itself. This feedback was presented to the student in the form of suggested solutions to sample problems.

To gauge the effectiveness of the simulation, the authors collected user feedback through questionnaires and usability studies. Although results were mixed, in general students viewed the computer simulation as engaging and easy to use. Positive responses to the simulation focused on the inclusion of real-world case studies. Negative responses addressed the relevance of the simulation’s multimedia interface to the course and the amount of time required to work through the course pack.

The distance education course discussed by Sharp and Hall (2000) is the subject of ongoing study. The efficacy of computer simulations in distance education courses is supported by data indicating that students recognized and valued the real-world learning experience facilitated by the simulation.

2. A VR-enhanced Computer Simulation

Some researchers and educational practitioners have explored the use of virtual reality (VR) in distance education as a means of facilitating constructivist learning activities (Briggs, May, 2002; Miettinen, 2002). Sung and Ou (2001) reported on a Web-based computer graphics course in which VR technology was incorporated into a computer simulation. The goal was to increase learning effectiveness. The computer graphics course was offered through the Department of Electrical Engineering, National Central University, Chung-Li, Taiwan. http://www.ncu.edu.tw/English/. The authors asserted that learning acquired by students through a VR-enhanced computer simulation was more meaningful because it was derived from the student’s own exploration of the simulation environment (McLellan, 1994).

Preliminary analysis of the effectiveness of the VR-enhanced computer simulation was determined by administering a pre-test and post-test both to students who used the simulation and students who used more traditional learning systems. Test results indicated that students who used the VR-enhanced computer simulation scored higher on practical examinations (post-test). The authors also observed that students who had access to the VR-enhanced computer simulation returned frequently to the course Web site to refresh their skills. In addition, these students were observed to retain a higher level of cognitive knowledge than students who had not used the simulation. Students reported that using the VR-enhanced computer simulation was a rewarding and positive experience. Further, students viewed the simulation more as a computer game with instructional value than as a homework assignment. As a result, students were willing to devote more time working in the VR-enhanced computer simulation than they would have allocated to more traditional study.

The authors concluded by stating that VR-enhanced computer simulations provided students with “experiential learning” (Sung & Ou, 2001). This type of high-level learning was possible because the simulation involved the student in active completion of specific tasks and complex operations. Research has shown that students involved in “experiential learning” tend to remember 90% of what they encounter in the course of the learning activity (Heinich, et. al., 1999). If VR-enhanced computer simulations can provide this type of learning experience over the Web, then they may have a place in distance education (Ryhme, 2002).

3. Java Applet-based Micro Worlds

A variety of technologies may be used to deliver computer simulations through distance education. Min (2001) reported on an ambitious project conducted at the University of Twente in the Netherlands, http://www.utwente.nl/en/, in which Java applets were used to deploy computer simulations to students in an array of distance settings. These Java applet-based computer simulations, referred to as, “micro worlds”, were designed to be downloaded over the Web (Min, 2001).

The computer simulations developed by Min and colleagues were strongly grounded in constructivist learning theory and Vygotsky’s “Zone of Proximal Development” (ZPD) concept (Sternberg, 1999; Miettinen, 2002). Min stated that these were model-driven stand-alone simulations as distinguished from instructional or tutorial courseware. The computer simulations were designed to fulfill the rolls of in-class demonstration, coached learning, individual discovery learning, interactive practice, and assessment. Of equal importance, the computer simulations provided a vehicle for evaluating whether students successfully applied what they had learned to practical problems. Min also stressed the vital role computer simulations played as a feedback channel for the instructor.

Min stated that successful application of computer simulations demanded “coached learning, two-way communication, feedback, demonstrated ability of the student to form sound hypotheses, access to appropriate manuals, written assignments and well-designed printed materials”. Without these elements, the computer simulations could not have achieved their instructional goals. Min observed that the more time students spent working in the computer simulations the more the students learned. However, Min also noted that if the student used the computer simulations without coaching, the result was often ineffective practice. Further, if the student interacted with the simulations without first mastering the appropriate problem related skills, the interactive practice often resulted in null or incorrect learning.

The computer simulations developed by Min and colleagues supported discovery learning through the use of cases and scientific experiments. Each case was presented to the student in print format with the essential dynamic elements of the case portrayed by computer simulations. The student was directed to construct and test a hypothesis, and manipulate one or more parameters of the computer simulation until the simulation model behaved normally. Scientific experiments were designed to resemble vocational practicums in which the student measured specific variables with the goal of attaining a certain insight. Results of the experiment were recorded by the student in an electronic or paper worksheet. The student then constructed charts or used other graphic representations to visualize the results of the experiments. Finally, the student evaluated the resulting visual representations with the goal of gaining insight into a real-world phenomenon.

While Min did not report quantitative data on use of Java applet-based computer simulations in distance education courses, the potential of the technology is clear. Given the relatively small file sizes of Java applets and the ease with which they can be accessed through the Web, the Java applet computer simulations described by Min may be applicable to a wide range of distance education situations.

4. “Chernobyl”, “C3 Fire” and “ERCIS”

The Web may prove to be the most functional vehicle for “delivering computer simulations to students at a distance” (Simonson, et. al., 2001). Granland, Bergland and Eriksson (2000) reported on the development of three Web-based computer simulations for distance education, conducted in the Department of Computer and Information Science, Linköping University, Linköping, Sweden. The authors focused on the relationships between Web-based computer simulations and instructional strategies appropriate to simulation-based learning environments. A number of learning methodologies for which computer simulations may provide optimal learning outcomes were presented. These methodologies included problem-solving, demonstration, experimentation, exploration and hypotheses testing.

The three computer simulations presented by Granland, Bergland and Eriksson were named, “Chernobyl”, “C3 Fire” and “ERCIS”. All three computer simulations were implemented using Java applets. The “Chernobyl” computer simulation was designed to teach basic operations of a nuclear power plant as well as rule-based modeling. The simulation introduced plant operations and allowed the student to deal with certain malfunctions which can occur during the course of normal plant operation. The “Chernobyl” simulation included three prewritten cases and one random case in which events were not determined in advance. While the simplified physics model on which the simulation was built was inaccurate, the simulation did familiarize the student with the dynamics of a real-world situation.

The “C3 Fire” computer simulation was designed to present “Command, Control and Communication” (C3 Fire) problems in a Web-based learning environment. The goal of the simulation was to let the student experiment with various strategies for team training, coordination and situation-awareness. The metaphor for the simulation was fighting forest fires and included fire fighting units, vegetation, houses and other simulated agents. Fire-fighting was used merely as a vehicle to demonstrate the problem solving principles inherent in team management. “C3 Fire” was designed to allow the learner to experience some of the dynamics present in a real-world emergency situation. To facilitate this, the fire-fighting scenario played out by the simulation changed autonomously and in response to the learner’s actions. The simulation maintained a detailed log of the learner’s actions and reactions to the changing scenario. This log was later used by the instructor to evaluate the learner’s performance.

“ERCIS” and “C3 Fire” both utilized a team distance learning environment as opposed to a single user simulation demonstrated in “Chernobyl”. “ERCIS” (group distance exERCISe) simulated certain key aspects of the RBS-70 unit of Swedish Anti-Aircraft Defense. The goal of “ERCIS” was to provide “training” with equipment and procedures related to the RBS-70 unit (Noble, 2002). The simulation abstracted some aspects of the RBS-70 technology, focusing rather on key functions and operation parameters relevant to group activity in a real-world combat setting.

All three simulations presented by Granland, Bergland and Eriksson shared the goal of helping the learner distinguish between conceptual and operational knowledge. Subsequent to observation and evolution of the simulations, the authors concluded that the “Chernobyl” simulation provided the learner with a good understanding of the underlying model upon which the simulation is built. The “C3 Fire” simulation allowed the student to learn about various aspects of a dynamic situation where the model underlying the simulation was not the focus of instruction. The “ERCIS” simulation facilitated mastery of operational knowledge in a situation where the concepts and user interface of the simulation model closely resembled a real-world setting. All three simulations focused on discovery learning in which the student explored the simulation environment, collected data, analyzed information, and made informed decisions in order to acquire knowledge. Further, the simulations were designed to emphasize affective learning, incorporating as much motivation appeal as possible.

Although all three computer simulations were designed for use over the Web in a distance education setting, the authors stressed the need for teacher-guided learning and instructional feedback (Nator, et. al., 2002). While the authors presented no data in support of their research, they asserted that Web-based computer simulations have two key advantages for distance education. The first and most obvious advantage is that computer simulations built with Java applets are easily and widely accessible to any student with Internet access. Java applets can provide the flexibility to “address different learning styles and provide access to a variety of media elements” (Roccetti & Salomoni, 2001). Second, and more importantly, computer simulations can present the learner with opportunities to experience dynamic and interactive environments. The value of “experiential learning” has been well documented in the literature (Heinich, et. al., 1999). If well-designed, model-based computer simulations can be made available over the Web, students in distance settings can engage in “real-world problem-based learning” (Notar, et. al., 2002).

5. “MODEM”

Hensgens, et al, (1998) reported on the “MODEM” project (Multimedia Optimisation [sic] and Demonstration for Education in MicroElectronics) http://www.ecotec.com/sharedtetriss/projects/files/modem.html, an effort to support active learning through the use of computer simulations in a distance learning setting. “MODEM” was developed at the Research Institute for Knowledge Systems(RIKS bv), Maastricht, The Netherlands. The goal of the “MODEM” project was to allow students to acquire complex knowledge and skills relevant to the microelectronics industry through experience with professional microelectronics modeling software tools. Through hands-on experience with real-world tools in a simulated work environment, students were able to explore and experience the key concepts of microelectronics modeling.

The “MODEM” simulation incorporated access to real-world software tools which ran on a server. This was facilitated by a software bridge which connected desktop PCs at a distance to a UNIX server using the PC-X-server, HCLeXceed. Multimedia and hypermedia were extensively utilized throughout the “MODEM” simulation to support constructivist learning, interactivity and maximum learner control. The simulation promoted learning by doing; students were free to make mistakes and acquire knowledge from solutions they developed. Further, the “MODEM” computer simulation motivated students to build and test their own hypothesis acquiring high-level knowledge through development of complex problem-solving skills. Finally, because the “MODEM” simulation was delivered over the Web, it eliminated the same-time same-place constraint present in more traditional microelectronics instruction.

The “MODEM” simulation software was developed using Asymetrix ToolBook © authoring tool http://www.asymetrix.com/en/toolbook/index.asp and designed to run in either Netscape or Internet Explorer Web browsers. Synchronous communication among students and between students and teachers were facilitated with Microsoft’s NetMeeting© software http://www.microsoft.com/windows/netmeeting/. The whiteboard functions of NetMeeting were used extensively for feedback and collaborative work. While the “MODEM” simulation was designed to provide the learner with full control over the course materials, extensive feedback and coaching were provided through NetMeeting. The authors stressed that coaching and guidance were essential to prevent the learner from becoming lost in the simulation.

Evaluation of the “MODEM” computer simulation was conducted at the University of Leeds and the University of Twente. Data was collected by administering usability questionnaires to a small group of software testers. The authors reported an overall positive response to the simulation, although no quantitative data were provided. Subsequent testing was carried out with students, all of whom were experienced computer users. Upon completion of the microelectronics course, the students were asked to complete the same usability questionnaires previously presented to the software testers. Once again, the authors reported very positive student response to the simulation, but provided no supporting data. In particular, students commented most favorably about instructor feedback made possible by the NetMeeting software. Although some technical communication problems did arise during the course, students worked around these difficulties and did not consider them a negative aspect of their experience with the “MODEM” simulation.

The authors emphasized that the “MODEM” simulation was unique because it incorporated access to real-world resources and was built partially around existing software, i.e. NetMeeting. That part of the simulation constructed with ToolBook was designed to bring the preexisting software packages together under a coherent user interface, provide consistent and relevant feedback, and give students complete access to all course materials. The ToolBook user interface also facilitated note taking and collaborative work. The authors stated that “MODEM” represented a viable and cost effective approach to the development of computer simulations.

6. Computer Simulation Using Video Teleconferencing

Computer simulations can be incorporated into a wide variety of distance education situations. The medical education community has investigated the use of computer simulations incorporating “video teleconferencing” to supplement traditional face-to-face instruction (Heinich, et. al., 1999; Jacobs & Rodgers, 1997). These efforts have been motivated by the constantly expanding curriculum of most medical training programs. At the same time, educators have investigated ways of getting medical students more actively involved in their own learning (Levison & Straumanis, 2002).

Cooper, et. al., (2000) reported on a realistic medical simulation project conducted by the Center for Medical Simulations, Boston, MA. The first phase of the project was carried out at Massachusetts General Hospital on May 22, 1997. The project consisted of several two-way, interactive seminars in which medical cases were presented to large audiences at widely dispersed locations. Although the primary information delivery medium in this project was video teleconferencing, computer simulation was used for medical telemetry.

According to the authors, these medical simulations were focused on the goals of allowing students to see the effects of their actions in real-time, to enhance learning by facilitating concurrent presentation and discussion and to facilitate student participation at a distance. The simulations made it possible for students to conduct hypotheses testing in real-time and discover cause-and-effect relationships which more traditional instructional methods might have rendered less apparent. An added benefit was that students were able to “observe and interact with medical equipment which was in limited supply or inaccessible for viewing by large groups” (Forinash & Wisman, 2001).

Although the authors did not conduct a large-scale assessment of the simulation project, a survey instrument was administered to one of the largest audience groups to assess user reactions to the methodology. Survey responses were generally enthusiastic with regard to the technology, although some respondents questioned the cost-benefit ratio.

Further experimentation with this type of simulation has been held back due to the high bandwidth requirements of video teleconferencing. However, the development of streaming video may facilitate future research projects of this type. The authors stressed the need for development of additional simulations so that more comprehensive data could be collected as to the methodology’s efficacy.

 

7. Assessment Instrument for Computer Simulations in Distance Education

A number of research projects have been presented in which computer simulations have been incorporated into open or distance-learning venues. Although the authors of these projects have attested to their success, their claims have not been supported with quantitative data. The need for reliable assessment instruments for evaluation of computer simulations is warranted.

Dean and Webster (2000) examined an interactive computer simulation in the context of a distance education business degree course. Their goals were to develop an instrument to assess whether computer simulations motivate “high quality learning”, and to determine whether computer simulations impact student’s ability to transfer knowledge to the real-world. High quality learning is essential for moving the student to a state of “metacognition” where the student takes responsibility for his/her own learning (Sternberg, 1999). The authors asserted that the variable and inconclusive results obtained with existing assessment instruments pointed to the need for new assessment tools geared toward computer simulations in distance settings. Because computer simulations tend to focus on the student-centered learning, the authors stated that any new assessment instrument needed to be more focused on student-related factors.

The computer simulation used in this study was designed to support development of cognitive models, provide interactive practice, encourage hypothesis formation, hypothesis testing, experimentation and mastery of concepts through application of knowledge to real-world problems. The simulation involved the student in theory-and-practice exercises with the goal of enabling the student to apply acquired knowledge to realistic work environments. The simulation software was built on a decision support system and tutorial which encouraged the student to apply acquired knowledge to work-based decision making. Interactive practice was achieved by allowing students to make their own decisions through a series of scenarios presented by the simulation. Students received feedback about their decisions and guidance with regard to factors not considered. Direct face-to-face interaction with instructors or other students was very limited during the study. Most feedback came to the student through the simulation.

The authors conducted an assessment by distributing survey instrument to 150 students who had completed the business course using the computer simulation. Detailed quantitative results presented by the authors indicated that current computer simulations do not promote transfer of knowledge to a greater degree than other methodologies. In short, computer simulations as currently constructed for distance education do not appear to facilitate transfer learning of acquired knowledge to real-world situations. At the same time, survey results indicated that students responded positively to the high degree of interactivity. In this regard, computer simulations do appear to have a positive impact on students’ motivation to study.

The authors encouraged others to develop similar instruments for assessment of computer simulations delivered to students at a distance. However, the authors cautioned that such instruments should be carefully crafted to focus on student-related factors as well as factors pertaining to cognition, transfer learning and motivation.

Conclusions

The goal of this paper has been to investigate current developments in the use of computer simulations in distance education. Seven research projects have been discussed to ascertain whether computer simulation may constitute a viable component in distance education. The tools utilized by these research projects for the development of computer simulations included Java applets, Asymetrix ToolBook© authoring software, virtual reality and video teleconferencing. For the purpose of this paper, discussion of these research projects has focused on the design methodologies employed rather than the specific development tools. Further, while a variety of media were presented for “delivery of computer simulations”, a comprehensive inventory of delivery options was not attempted (Evans, & Fan, November 4, 2002).

Seven applications of computer simulations in distance education settings have been presented. Sharp and Hall (2000) reported that students in an engineering course offered via distance education responded positively to a computer simulation of a software publishing company. Students found real-world case studies presented through simulation engaging and easy to use.

In another distance education setting, Sung and Ou (2001) administered a pre-test and post-test to students in a computer graphics course to gauge the effectiveness of a VR-enhanced simulation. Test results indicated that students who used the VR-enhanced computer simulation scored higher on practical examinations (post-test). The authors also observed that students who made frequent use of VR-enhanced computer simulation retained a higher level of cognitive knowledge than students who did not use the simulation. Finally, the authors reported that student response to the VR-enhanced computer simulation was positive as demonstrated by willingness to devote more time working in the simulation than to more traditional study methods.

Min (2001) discussed Java-applet-based computer simulations which supported discovery learning through the use of cases and scientific experiments. These applets were designed to facilitate experiential learning and the application of knowledge to real-word problems. The applets also augmented feedback and assessment of student performance. While no data were reported, the author made a solid case for the efficacy of Java-applet-based computer simulations in distance education.

Granland, Bergland and Eriksson (2000) reported on three Web-based computer simulations for distance education. These simulations facilitated discovery learning in which the student explored the simulation environment, collected data, analyzed information, and made informed decisions in order to acquire knowledge. The authors asserted that well-designed, Web-accessible, model-based computer simulations can allow students in distance settings to engage in real-world problem-based learning.

Hensgens, et al, (1998) presented “MODEM”, a microelectronics course computer simulation for distance education which incorporated access to real-world resources and was built partially around existing software. The simulation was evaluated by collecting data from usability questionnaires administered to software testers, and subsequently to students. The authors reported an overall positive response to the simulation, but provided no detailed data.

Cooper, et. al., (2000) reported on a medical simulation project which incorporated video teleconferencing. The goal of the project was to help motivate medical students to take a more active role in their own learning. The simulation permitted students at a distance to conduct hypotheses testing in real-time and discover cause-and-effect relationships. A survey instrument was administered to one group of distance students to gauge reactions to the simulation. The authors reported that student responses were generally positive.

Dean and Webster (2000) examined an interactive computer simulation in the context of a distance education business course with the goal of developing an assessment instrument. The instrument was designed to measure the degree to which computer simulations motivate high quality learning, and to determine whether computer simulations impact student’s ability to transfer knowledge to the real-world. The authors reported detailed results obtained from a survey instrument distributed to 150 students. Data indicated that use of computer simulations in distance education do not promote transfer of knowledge to a greater degree than other methodologies. However, data did appear to support the author’s claim that computer simulations can have a positive impact on students’ motivation to study.

Granland, Bergland and Eriksson (2000) reported no data on the simulation they discussed. However, authors of the other six projects reported positive responses to the computer simulations they studied. Such positive responses from students indicate that computer simulations can contribute to the learning experience in distance education. Further data collection, observation and assessment are essential for determining the best use of computer simulations in distance education.

The application of computer simulations in distance education is a new area of study which seems to hold the promise of high-quality learning. While innovative and intriguing research is currently ongoing, future research efforts should be focused on several specific areas.

First, there is an apparent lack of quantitative data on the efficacy of computer simulations in distance education settings. Further studies need to be conducted using larger treatment and control groups.

Second, the functionality of various development tools should be investigated.

Third, development of computer simulations can be expensive and time-consuming. Knowing which tools can provide the shortest development cycle while still resulting in the highest quality simulations will be important.

Fourth, the development of computer simulations in the humanities or social sciences distance education should be documented.

Finally, more effort should be devoted to developing assessment instruments that accurately measure the efficacy of computer simulations in distance education.

The benefits of “high-quality learning”, which simulations can provide to the student, are well documented in the literature (Forinash, & Wisman, September, 2001). However, further research will be essential in ascertaining the degree to which the instructional benefits of computer simulations may be extended to distance education.

References

Berge, Z. L. (Summer, 2002). Active, Interactive and Reflective eLearning. Quarterly Review of Distance Education, 3(2), 181-90.

Briggs, J. C. (May, 2002). Virtual Reality is Getting Real: Prepare to Meet Your Clone. Futurist, 36(3), 34-42.

Cooper, J. B., Baron, D., Blum, R., Davison, K., Feinstein, D., Halasz, J., et. al. (May, 2000). Video Teleconferencing with Realistic Simulation for Medical Education. Journal of Clinical Anesthesia, 12, 256-261.

Dean, A. M. & Webster, L. (2000). Simulation in Distance Education: Progress towards an Evaluation Instrument. Distance Education, 21(2), 344-360.

Evans, C. & Fan, F. P. (November 4, 2002). Lifelong Learning through the Virtual University. Campus-Wide Information Systems, 19(4), 127-134.

Forinash, K. & Wisman, R. (September, 2001). The Viability of Distance Education Science Laboratories. T H E Journal (Technological Horizons in Education), 29(2), 38.

Gagne, R. M., Briggs, L. J. & Wager, W. W. (1992). Principles of Instructional Design. (4th ed). (pp. 196-197). Fort Worth, Texas: Holt, Rinehart & Winston.

Gibbons, A. S., Fairweather, P. G., Anderson, T. A., & Merrill, M. D. (1997). Simulation and computer-based instruction: A future view. In C. R. Dills and A. J. Romiszowski (Eds.) Instructional Development: State of the Art. (pp. 772-783). Englewood Cliffs, New Jersey: Instructional Technology Publications.

Granland R., Bergland, E., & Eriksson, H. (2000). Designing Web-based Simulation for Learning. Future Generation Computer Systems, 17, 171-185.

Heinich, R., Molenda, M., Russell, J., & Smaldino, S. (1999). Instructional Media and Technologies for Learning. (6th ed). (pp. 14-15, 21, 213-214, 290-291, 319-324). Upper Saddle River, New Jersey: Prentice-Hall.

Hensgens, J, van Rosmalen, P. & Hanu, B. (1998). Microelectronics Simulation-based Training on a Virtual Campus. Displays, 18, 221-229.

Jacobs, G. & Rodgers, C. (December, 1997). Remote Teaching with Digital Video: A Trans-National Experience. British Journal of Educational Technology, 28(4), 292-304.

Ko, S. & Rossen, S. (2001). Teaching Online: A Practical Guide. (pp. 2, 17-18, 51, 112-123, 197). New York: Houghton Mifflin Company.

Levison, S. P. & Straumanis, J. (Sep./Oct. 2002). FIPSE: Changing Medical Education Forever. Change, 34( 5), 18-26.

McIssac, M. S., & Gunawardena, C. N. (1996). Distance education. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 403-437). New York: Simon & Schuster Macmillan.

McLellan, H. (1996). Virtual Realities. In D. H. Jonassen (Ed.), Handbook of Research for Educational Communications and Technology: A Project of the Association for Educational Communications and Technology, (pp. 457-487). New York, NY: Macmillan.

Miettinen, R. (2002). Varieties of Constructivism in Education: Where Do We Stand? Lifelong Learning in Europe, 7(1), 41-48.

Min, R. (2001). Designing Dynamical Learning Environments for Simulation: Micro-Worlds Applets on the World Wide Web. 6th Proceedings of EARLI, SIG, June 27-29, 2002, in Erfurt, Germany.

Min, R. (2001). Simulation and Discovery Learning in an Age of Zapping & Searching: Learning Models. Retrieved February 24, 2002, from: http://projects.edte.utwente.nl/pi/Papers/DiscLearning.html.

Noble, D. F. (2002). Digital Diploma Mills: The Automation of Higher Education. (pp. 2). New York. Monthly Review Press.

Notar, C. E., Wilson, J. D. & Ross, K. G. (Summer 2002). Distant Learning for the Development of Higher-level Cognitive Skills. Education, 122(4), 642-648.

Osciak, S. Y. & Milheim, W. D. (Winter, 2001). Multiple Intelligence and the Design of Web-based Instruction. International Journal of Instructional Media, 28(4), 355-362.

Rhyne, T. (July, 2002). Computer Games and Scientific Visualization: How Should Scientists Approach the Innovations in Visualization--rendering Systems Increasingly Derived from Computer Game Tools, Interfaces, Navigation Techniques, and Plot Lines? Communications of the ACM, 45(7), 40-45.

Roccetti, M. & Salomoni, P. (2001). A Web-based Synchronized Multimedia System for Distance Education. ACM, 94-98.

Saul, C. (February, 2001). Modeling Information for Three-dimensional Space: Lessons Learned from Museum Exhibit Design. Technical Communications, 48(1), 66-81.

Sharp, H. & Hall, P. (2000). An Interactive Multimedia Software House Simulation for Postgraduate Software Engineers. ICSE, 688-691.

Simonson, M., Smaldino, S., Albright, M. & Zvacek, S. (2001). Teaching and Learning at a Distance. (2nd ed.). (pp. 7-9, 87-88, 253-257). Upper Saddle River, New Jersey: Pearson Education, Inc.

Sternberg, R. J. Cognitive Psychology. (1999). (2nd ed.). (pp. 17, 186, 446-449). Fort Worth, Texas: Harcourt Brace College Publications.

Sung, W. & Ou, S. (2001). Application of Web-based Learning in Sculpture Curves and Surfaces. IEEE, 121-122.

About the Author

Les Lunce

Les Lunce has over 20 years experience in information technology. His background includes programming, Web content developer, multimedia courseware developer, computer lab manager, instructor, technical support and administrator.

Currently he is employed by North Lake College, Irving, Texas, teaching Internet-based courses in Flash, JavaScript and Microsoft FrontPage. In May of 2003 he completed his MS in Computer Education and Cognitive Systems through the College of Education (COE) at the University of North Texas (UNT). Currently he is pursing a Doctorate in Educational Computing through COE at UNT.

His research area is the use of immersive and non-immersive virtual worlds for instructional simulations. His major professor is Dr. Mark Mortensen, 940-565-4130, markmort@unt.edu

 

go top
Oct 2004 Index
Home Page