The project builds on the earlier developed Crystal Island and draws upon intelligent tutoring and narrative-centered learning technologies to produce a suite of intelligent game-based learning environments for upper elementary school science students. The games explicitly model student knowledge and problem solving and dynamically customize feedback, advice, and explanation as appropriate. Unlike its predecessor, the platform is multi-user so it can support collaboration; offer dynamically generated feedback, advice, and explanation; and provide a pedagogical dashboard that generates student progress reports.
Students navigate rich storyworlds setup by engaging narratives, interact with a large cast of characters in the game, and manipulate artifacts in the environment in the course of solving problems. They are entering an intelligent, game-based learning environment that is a laboratory where researchers can investigating various approaches through which complex problem-solving skills can be most effectively acquired. Because such environments include multiplayer interaction and voice communication, research can study complex communication in the context of collaborative problem solving. With multiple students coordinating their efforts to solve problems, intelligent game-based learning environments create situations that require effective collaboration skills. Through these, engagement is also studied, which includes motivation, situational interest, presence, flow, goal-orientation, and self-efficacy.
There has been significant development in game-based learning in the past decade. Of particular interest is the potential that game-based learning environments have for integrating effective problem-solving episodes with highly engaging learning experiences. Recent advances include theoretical developments, the creation of game-based learning environments for a broad range of curricula, and the emergence of technically advanced game-based learning environments for both education and training. In the course of the project, the research team designed, developed, and iteratively refined a game-based learning environment for upper elementary science education. The project’s intelligent game-based learning environment research investigated problem solving, engagement, and STEM education by targeting the following two objectives: 1. Designing a suite of intelligent game-based learning environment technologies for elementary science education. To promote effective science learning, we created intelligent game-based learning environment technologies that leverage the rich interactive 3D game environments provided by commercial game engines and the inferential capabilities of intelligent tutoring systems. Building on our experience in these two areas, we developed Crystal Island: Uncharted Discovery, an engaging intelligent game-based learning environment for fifth grade science education. This sophisticated gaming environment offers goal-based problem scenarios dynamically tailored to students’ abilities that model students’ problem-solving progress and provide customized explanations and feedback. The environment features an immersive 3D storyworld with an expansive cast of characters. 2. Provide a cognitive account of elementary students’ problem-solving processes and engagement with STEM content as they interact with intelligent game-based learning environments. To understand the cognitive mechanisms by which learning occurs, we took a mixed method approach to investigating science learning with the Crystal Island: Uncharted Discovery learning environment for fifth grade science. These studies investigated the central issues of problem solving and engagement with respect to achievement as measured by both science content knowledge and transfer. Emphasizing content connections to the North Carolina Standard Course of Study and building on our experience with school-based research, all studies were conducted onsite at the project’s partner elementary schools. With diverse student populations drawn from urban, suburban, and rural settings, the studies determined which technologies and conditions contribute most effectively to learning processes and outcomes.
