Active Learners: Redesigning an Intelligent Tutoring System to Support Self-regulated Learning
Active Learners: Redesigning an Intelligent Tutoring System to Support Self-regulated Learning
复制标题
主动学习者：重新设计智能辅导系统以支持自我调节学习
DOI：
10.1007/978-3-642-40814-4_44
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
V. Aleven
中科院分区：
文献类型：
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作者：
Yanjin Long;V. Aleven
支持学生自主学习SRL是学习科学中的一个重要课题。 SRL 涉及的两个关键过程是自我评估和研究选择。智能辅导系统 ITS 已被证明可以通过指导问题解决实践有效支持学生的领域级学习，但它们如何有效支持 SRL 流程，同时保持甚至增强其在领域级的有效性，仍然是一个悬而未决的问题。我们结合以用户为中心的设计技术和实验课堂研究来重新设计和评估用于线性方程求解的 ITS，使其支持自我评估和研究选择。我们在导师的开放学习者模型OLM中添加了三个功能，可以支撑学生的自我评估自我评估提示，延迟学生进度条的更新，并提供问题类型级别的进度信息。我们还设计了一个问题选择屏幕，具有共享的学生/系统控制和类似游戏的功能。我们进行了两次设计迭代，并对当地 160 名中学生进行了两次对照实验，以评估新功能的有效性。评估表明，具有自我评估支持的新 OLM 促进了学生的学习过程，并显着提高了他们的学习成果。然而，由于问题选择功能，我们没有发现显着的学习收益。这项工作为支持 SRL 的未来 ITS 的设计提供了信息。
Supporting students' self-regulated learning SRL is an important topic in the learning sciences. Two critical processes involved in SRL are self-assessment and study choice. Intelligent tutoring systems ITSs have been shown to be effective in supporting students' domain-level learning through guided problem-solving practice, but it is an open question how they can support SRL processes effectively, while maintaining or even enhancing their effectiveness at the domain level. We used a combination of user-centered design techniques and experimental classroom research to redesign and evaluate an ITS for linear equation solving so it supports self-assessment and study choice. We added three features to the tutor' Open Learner Model OLM that may scaffold students' self-assessment self-assessment prompts, delaying the update of students' progress bars, and providing progress information on the problem type level. We also designed a problem selection screen with shared student/system control and game-like features. We went through two iterations of design and conducted two controlled experiments with 160 local middle school students to evaluate the effectiveness of the new features. The evaluations reveal that the new OLM with self-assessment support facilitates students' learning processes, and enhances their learning outcomes significantly. However, we did not find significant learning gains due to the problem selection feature. This work informs the design of future ITS that supports SRL.