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Improved computation of individual ZPD in a distance learning system

机译:改进远程学习系统中单个ZPD的计算

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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:本文以社会建构主义领域的理论研究为基础。列夫·维果茨基(Lev Vygotsky)的近端发育区(ZPD)理论被认为是该研究领域的最伟大代表之一。我们的工作旨在将这一概念整合到计算机辅助学习系统的实践中。对于每个学习者,系统都会存储一个模型,该模型汇总了当前的学生知识(SK)。通过部署的内容,解决该问题所需的技能以及所获得的知识来指定每种教育活动,并通过为该任务估算的工作量来进一步注释。鉴于已经具备的能力,后者可能会从一个学生变成另一个学生。存储在SK中的学生技能的鲁棒性(确定性)的适当权重及其组合用于验证学生ZPD中是否包含学习活动。关于我们以前的工作,通过增强确定性加权策略,对用于计算单个学生的ZPD的算法进行了优化,并添加了ZPD的图形显示。多亏了后者,学生可以清楚地了解他/她目前可以解决的学习途径。这既有利于教育过程,又有助于发展元认知能力的自我评估。

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