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Practices of algorithm education based on discovery learning using a program visualization system.
Koichi Yamashita1, Ryota Fujioka2, Satoru Kogure3
11Faculty of Business Administration, Tokoha University, 1230 Miyakoda, Kita-ku, Hamamatsu, Shizuoka 431-2102 Japan.
Research and Practice in Technology Enhanced Learning
|January 8, 2019
Summary
This study introduces practical algorithm education exercises using a visualization system. The system helps students understand algorithm properties through discovery learning, enhancing comprehension in algorithm courses.
Area of Science:
- Computer Science Education
- Algorithm Analysis
Background:
- Traditional algorithm education struggles to adapt instruction for diverse learners.
- Existing visualization systems lack teacher-defined instructional policies.
Purpose of the Study:
- To develop and evaluate practical algorithm education exercises using a novel visualization system.
- To enhance student understanding of algorithm properties through discovery learning.
- To investigate the integration of teacher-defined visualization policies in algorithm courses.
Main Methods:
- Developed a learning support system for algorithm visualization with teacher-defined policies.
- Conducted classroom practice sessions within an algorithm course.
- Structured course content to facilitate discovery learning of algorithm properties.
Main Results:
- The developed visualization system was successfully integrated into algorithm classes.
- Learners demonstrated an improved understanding of algorithm properties like comparisons and data exchanges.
- The framework proved effective for establishing discovery learning in algorithm education.
Conclusions:
- The visualization system and discovery learning approach are viable for algorithm education.
- Teacher-defined visualization policies are crucial for accommodating diverse learning needs.
- Key requirements for integrating discovery learning in algorithm classes were identified.
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