文章基本信息

标题：Practices of algorithm education based on discovery learning using a program visualization system
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作者：Koichi Yamashita ; Koichi Yamashita ; Ryota Fujioka 等
期刊名称：Research and Practice in Technology Enhanced Learning
电子版ISSN：1793-7078
出版年度：2016
卷号：11
期号：1
页码：1-19
DOI：10.1186/s41039-016-0041-5
语种：English
出版社：Springer
摘要：Abstract In this paper, we describe three practical exercises relating to algorithm education. The exercises are based on a learning support system that offers visualization of program behavior. Systems with the ability to visualize program behavior are effective to promote the understanding of algorithm behavior. The introduction of these systems into an algorithm course is expected to allow learners to cultivate a more thorough understanding. However, almost all existing systems cannot incorporate the teacher’s intent of instruction that may be necessary to accommodate learners with different abilities by using a different instructional approach. Based on these considerations, we conducted classroom practice sessions as part of an algorithm course by incorporating the visualization system we developed in our previous work. Our system visualizes the target domain world according to the visualization policy defined by the teacher. Our aim with the practical classes is to enable learners to understand the properties of algorithms, such as the number of comparisons and data exchanges. The contents of the course are structured such that the properties of an algorithm can be understood by discovery learning in the practical work. In this paper, we provide an overview of our educational practices and learners’ responses and show that the framework we use in our practices can be established in algorithm classes. Furthermore, we summarize the requirements for the inclusion of discovery learning in the algorithm classes as the knowledge obtained from our practices.
关键词：Algorithm education;Learning support system;Domain world model;Classroom practice;Discovery learning