R&D: Developing Science Problem-Solving Skills and Engagement Through Intelligent Game-Based Learning Environments

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• 批准号: 0822200
• 负责人: James Lester
• 金额: $ 252.33万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0822200&HistoricalAwards=false
• 关键词: R& Developing; Science; Problem; Solving

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.

该项目以早期开发的水晶岛为基础，利用智能辅导和以叙事为中心的学习技术，为小学高年级理科学生创造了一套基于游戏的智能学习环境。这些游戏明确地模拟学生的知识和问题解决，并根据需要动态定制反馈、建议和解释。与其前身不同，该平台是多用户的，因此它可以支持协作；提供动态生成的反馈、建议和解释；并提供生成学生进度报告的教学仪表板。学生通过参与叙事来导航丰富的故事世界设置，与游戏中的大量角色互动，并在解决问题的过程中操纵环境中的人工制品。他们正在进入一个智能的、基于游戏的学习环境，这是一个实验室，研究人员可以在这里调查各种方法，通过这些方法可以最有效地获得复杂的问题解决技能。由于这样的环境包括多人交互和语音通信，研究人员可以在协作解决问题的背景下研究复杂的通信。通过多名学生协调他们的努力来解决问题，基于游戏的智能学习环境创造了需要有效协作技能的情景。通过这些研究，还研究了敬业度，包括动机、情景兴趣、在场、心流、目标定向和自我效能。