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Improved computation of individual ZPD in a distance learning system

机译:改进了远程学习系统中单个ZpD的计算

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摘要

This paper builds upon theoretical studies in the field of social constructivism. Lev Vygotsky is considered one of the greatest representatives of this research line, with his theory of the Zone of Proximal Development (ZPD). Our work aims at integrating this concept in the practice of a computer-assisted learning system. For each learner, the system stores a model summarizing the current Student Knowledge (SK). Each educational activity is specified through the deployed content, the skills required to tackle it, and those acquired, and is further annotated by the effort estimated for the task. The latter may change from one student to another, given the already achieved competence. A suitable weighting of the robustness (certainty) of student’s skills, stored in SK, and their combination are used to verify the inclusion of a learning activity in the student’s ZPD. With respect to our previous work, the algorithm for the calculation of the ZPD of the individual student has been optimized, by enhancing the certainty weighting policy, and a graphical display of the ZPD has been added. Thanks to the latter, the student can get a clear vision of the learning paths that he/she can presently tackle. This both facilitates the educational process, and helps developing the metacognitive ability self-assessment.
机译:本文建立在社会建构主义领域的理论研究。 Lev Vygotsky被认为是本研究系列最大的代表之一,他的近端发展区域(ZPD)的理论。我们的工作旨在将这种概念集成在计算机辅助学习系统的实践中。对于每个学习者,系统存储总结当前学生知识(SK)的型号。每个教育活动都是通过部署的内容指定的,解决它所需的技能以及所获得的技能,并通过估计任务的努力进一步注释。后者可能从一个学生改变给另一个学生,给出了已经取得的能力。储存在SK中的学生技能的鲁棒性(确定性)的合适加权用于验证学生ZPD中的学习活动。关于我们以前的工作,通过增强确定性加权策略,已经优化了用于计算各个学生ZPD的算法,并添加了ZPD的图形显示。由于后者,学生可以清楚地了解他/她目前可以解决的学习路径。这两者都促进了教育过程,并有助于制定元认知能力自我评估。

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