Publication Date

5-2012

Type of Culminating Activity

Dissertation

Degree Title

Doctor of Education in Curriculum and Instruction

Department

Curriculum, Instruction, and Foundational Studies

Supervisory Committee Chair

Jennifer Snow, Ph.D.

Abstract

Critics of the American education system point to student boredom, lack of personalized and relevant instruction, and a deficit of 21st century skills as challenges to producing productive citizens of a modern, digital society (Barab et al., 2009; Eccles & Wingfield, 2002; Ketelhut, 2007; U.S. Department of Education Office of Educational Technology, 2010). Digital learning, including game-based approaches, offers opportunities to bring about meaningful, engaging, individualized learning (Barab & Dede, 2007; Gee, 2005; Squire, 2003). Quest-based learning is an instructional design theory of game-based learning that focuses on student activity choice within the curriculum, which offers promising pedagogical possibilities in the area. This study expands upon current research of video game characteristics and variables of attractiveness in learner choice. Identifying these attractive characteristics in game-based educational design can increase engagement (Barab et al., 2009), educational effectiveness (Sullivan & Mateas, 2009), and impact instructional design decisions.

Quests were coded and tagged to identify features and attributes. An educational quest taxonomy was developed building on Merrill’s Knowled ge Object (Redeker, 2003; Wiley, 2000) classification and expanded to include current digital tools and thinking. Electronically collected decision data from a quest-based learning management system was analyzed using descriptive statistical analysis and data mining techniques. Educational quests were differentiated by a number of data points and identified as more or less attractive using an initial interest score and a completion score. User rating was also considered for descriptive purposes. Data mining and text mining highlighted the specific characteristics of attractive quests including clusters of characteristics identified as most attractive as well as their significance. Suggestions for future attractive quest-based learning design are suggested. (Keywords: Quests, quest-based learning, game-based learning, 3D GameLab, play styles, learner preferences, rewards, badges, gamification, MMORPGs, virtual environments, informal learning.)

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