Richard Van Eck


Richard Van Eck is Associate Professor and Graduate Director of the Instructional Design & Technology program at the University of North Dakota (UND). He received his M.A. in English from UND, and his Ph.D. in instructional design and development from the University of South Alabama. He was on the instructional design faculty at the University of Memphis for 5 years, where he was also a member of the Institute for Intelligent Systems and the committee chair for the Center for Multimedia Arts in the FedEx Institute of Technology. His work in digital game-based learning includes 4 refereed journal publications, 4 refereed conference presentations, 11 conference presentations, 1 invited publication (Educause Review) and 6 invited presentations and keynotes, most recently as a featured speaker at the Educause ELI conference, and he has created several serious games, including a game to promote transfer of mathematics skills in middle school students which he created for his dissertation. He has taught a graduate course on instructional simulations and games every year since 2001, and has several other publications on authoring tools, intelligent tutoring systems, pedagogical agents, and help systems (advisement) in computer-based instruction.



Where do we go from here? Ten critical areas to guide future research in DGBL.

Digital Game-based Learning (DGBL) has reached a crossroads in its development as a field of study. We must now move from change agency to research and prescription, and we must establish the focus and rigor that will be required of us. If we do not, we will soon go the way of the movements of media in the schools (the 1960s & 1970s) and computers in the schools (the 1980s and 1990s). This workshop will outline what I see as 10 areas that can help focus DGBL on the questions we must answer if we are to become a field instead of a fad.

1.Artificial Intelligence
Pedagogical agents, intelligent tutoring systems, and discourse analysis hold tremendous promise for DGBL, but little research is being done to find ways to modify and blend these technologies.

2.New models for discourse and distributed learning
Artificial Intelligence in the learning sciences often involves discourse analysis (the study of conversation, including tutoring). Discourse is typically conceptualized as dyadic, yet games (and the modern workplace) require situated, scenario-driven conversational interaction amongst multiple Non-Player Characters (NPCs) and Player Characters (PCs). Discourse theory remains a powerful set of strategies for learning and game advancement, but must be adapted to and validated for distributed environments such as multi-player games.

3.Blended taxonomies of games and learning
Gagné's seminal book, the Conditions of Learning, distinguishes between 5 types or "varieties" of learning. He further breaks one type, intellectual skills, into 5 sub-categories. Just as this taxonomy has allowed designers to generate more effective learning, taxonomies of games allow us to design games that meet different needs and criteria. It is reasonable to suggest that these taxonomies can be blended to help guide the development of DGBL.

4.Games and problem-solving/critical thinking
Anecdotal evidence abounds for the power of games to stimulate problem-solving and critical thinking in learning, but little research exists to document this. Longitudinal studies should be conducted with different domains, games, and populations to begin to address this.

5.Twitch games, and visual processing as it relates to specific fields of study
Studies have shown that visual processing can be increased through the use of "twitch" games (e.g., Green & Bavalier, 2003). This has specific application to multiple fields (e.g., air traffic controllers, athletes, aerospace, law enforcement, industrial safety, etc.). We need to conduct discipline-specific application studies of this and other DGBL research.

6.Development and evaluation of tools for game analysis
Researchers like James Gee have laid the groundwork for discussing the specific mechanism by which games accomplish what they do. In order to extend this research, we need tools that help us analyze and evaluate individual games using common frameworks and taxonomies.

7.Move beyond what games males and females like to what themes, strategies, and interactions each like (with validation)
Traditional wisdom about game preferences by gender is based on research that is out of date. Preferred interaction strategies and themes, the subject of current research, are more relevant than taxonomic game preferences and will help us focus on what works for both audiences.

8.Development of Authoring Tools and EPSSs for instructional content integration with games
We need tools to structure and support the integration of content into digital games without adversely impacting the game play, compromising the instruction, or requiring game developers to master pedagogy and educators to master game development. Authoring tools and Electronic Performance Support Systems (EPSSs) have been developed to solve this issue in other fields and should be developed for games.

9.Development of new interdisciplinary models
Game designers will never become pedagogical experts, nor will educators become expert game developers. Likewise, no single approach or instructional theory is likely to work for all content, all games, and all learners. DGBL requires an interdisciplinary approach combining psychology, education, instructional design, human performance technology, game design, and the arts. Models for games that draw upon all of these areas are most likely to be successful.

10.International/Cultural differentiation of gameplay, preferences, and learning
Just as games and learning are not all alike, the audiences who play them are not alike. Research in all of the above areas should be combined with attention to the cultural and individual differences in game play and game preference. Validation studies should be conducted with multiple cultures to establish heuristics for DGBL in global environments.

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