Active Learning is About More Than Hands-On: A Mixed-Reality AI System to Support STEM Education
Active Learning is About More Than Hands-On: A Mixed-Reality AI System to Support STEM Education
复制标题
主动学习不仅仅是动手：支持 STEM 教育的混合现实人工智能系统
DOI：
10.1007/s40593-020-00194-3
复制
发表时间：
2020
影响因子：
4.9
通讯作者：
Koedinger, Kenneth R.
中科院分区：
文献类型：
--
作者：
Yannier, Nesra;Hudson, Scott E.;Koedinger, Kenneth R.
尽管人们对主动学习的力量达成了广泛共识，但其基本要素却缺乏精确性。新的教育技术为系统地探索支持主动学习的替代技术的好处提供了工具。我们引入了一种新型智能科学站技术，该技术利用人工智能 (AI) 支持儿童通过在现实世界中做科学来学习科学。我们在一项随机对照试验中使用该系统，调查主动学习在以指导性刻意练习、建设性“动手”活动或两者结合的形式实施时是否最好。我们开发了一种专门的人工智能计算机视觉算法，可以实现自动化的反应性引导，该算法用于跟踪孩子们在使用物理对象进行实验和发现时在物理环境中所做的事情。结果支持刻意练习，并表明，与单独的探索性构建相比，基于有效学习机制（例如自我解释、对比案例和个性化互动反馈）的引导发现可以产生更稳健的学习。通过引导发现进行学习的儿童比仅通过动手构建进行学习的儿童能够更好地理解科学原理（测试前后的进步提高了 4 倍）。重要的是，引导发现和实践构建条件相结合可以更好地学习实践构建技能，而实践构建技能是实践建设性学习条件的唯一焦点（前后改进>10倍）。这些结果提出了实现科学和工程的强大主动学习的方法，超越了将实践活动与有效学习等同的普遍诱惑。
Along with substantial consensus around the power of active learning, comes some lack of precision in what its essential ingredients are. New educational technologies offer vehicles for systematically exploring benefits of alternative techniques for supporting active learning. We introduce a new genre of Intelligent Science Station technology that uses Artificial Intelligence (AI) to support children in learning science by doing science in the real world. We use this system in a randomized controlled trial that investigates whether active learning is best when it is implemented as guided deliberate practice, as constructive “hands-on” activity, or as a combination of both. Automated, reactive guidance is made possible by a specialized AI computer vision algorithm we developed to track what children are doing in the physical environment as they do experiments and discoveries with physical objects. The results support deliberate practice and indicate that having some guided discovery based on effective learning mechanism such as self-explanation, contrasting cases and personalized interactive feedback produces more robust learning compared to exploratory construction alone. Children learning through guided discovery achieve greater understanding of the scientific principles than children learning through hands-on construction alone (4 times more pre-to-post test improvement). Importantly, a combined guided discovery and hands-on construction condition leads to better learning of the very hands-on construction skills that are the sole focus of the hands-on constructive learning condition (>10 times more pre-to-post improvement). These results suggest ways to achieve powerful active learning of science and engineering that go beyond the widespread temptation to equate hands-on activity with effective learning.
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DOI：
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发表时间：
2008
期刊：
2008 IEEE International Symposium on Parallel and Distributed Processing with Applications
影响因子：
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DOI：
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发表时间：
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期刊：
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作者：
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影响因子：
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DOI：
10.1145/258549.258797
发表时间：
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期刊：
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影响因子：
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作者：
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