面向大规模适应学习者:整合MOOC和智能辅导框架

V. Aleven, J. Sewall, J. M. Andres, R. Sottilare, Rodney A. Long, R. Baker
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引用次数: 17

摘要

适应个别学习者特点的教学往往比把所有学习者都一视同仁的教学更有效。让mooc适应学习者的一个实际方法可能是整合智能辅导系统(ITSs)框架。使用学习工具互操作性标准(LTI),我们将两个智能辅导框架(GIFT和CTAT)集成到edX中。我们在宾夕法尼亚大学MOOC课程“大数据与教育”中描述了我们对四种适应性教学模式的初步探索。这项工作说明了大规模适应的一条途径。
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Towards adapting to learners at scale: integrating MOOC and intelligent tutoring frameworks
Instruction that adapts to individual learner characteristics is often more effective than instruction that treats all learners as the same. A practical approach to making MOOCs adapt to learners may be by integrating frameworks for intelligent tutoring systems (ITSs). Using the Learning Tools Interoperability standard (LTI), we integrated two intelligent tutoring frameworks (GIFT and CTAT) into edX. We describe our initial explorations of four adaptive instructional patterns in the PennX MOOC "Big Data and Education." The work illustrates one route to adaptivity at scale.
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