OCTAL: online course tool for adaptive learning

Daniel Armendariz, Zachary MacHardy, Daniel D. Garcia
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引用次数: 10

Abstract

The Online Course Tool for Adaptive Learning (OCTAL) is an adaptive exercise system that customizes the progression of question topics to each student. By creating a concept dependency graph of topics in a course and modeling a student's knowledge state, the tool presents questions that test knowledge within a student's zone of proximal development. We intend OCTAL to be a formative assessment tool that is not tied to any specific course by providing language-agnostic questions on computer science concepts. While the tool will be generalizable for many courses, our first prototype includes a concept map and question set for UC Berkeley's introductory computer science course, CS10: The Beauty and Joy of Computing. Using the tool, we will launch an experiment in the spring to investigate metacognitive improvements in the identification of knowledge gaps by presenting online course material in a nonlinear fashion.
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OCTAL:适应学习的在线课程工具
自适应学习在线课程工具(OCTAL)是一个自适应练习系统,可以为每个学生定制问题主题的进度。通过创建课程主题的概念依赖图并对学生的知识状态进行建模,该工具提出了测试学生最近发展区域内知识的问题。我们希望OCTAL成为一种形成性的评估工具,通过提供与语言无关的计算机科学概念问题,它与任何特定课程无关。虽然这个工具可以推广到许多课程,但我们的第一个原型包括一个概念图和加州大学伯克利分校计算机科学入门课程CS10的问题集:计算的美丽和乐趣。使用这个工具,我们将在春季启动一项实验,通过以非线性方式呈现在线课程材料来研究元认知在识别知识差距方面的改进。
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