Recommendation System Providing Similar Problems Instead ofw Model Answers to Programming Assignments

Ryoya Yoshimura, Kazunori Sakamoto, Hironori Washizaki, Yoshiaki Fukazawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Online judges are often used in programming education for beginners. Although they help improve coding skills, students may not obtain sufficient educational effects with much assignment difficulty. Instead of presenting a model answer to an assignment, we propose an approach to provide students contents of problems and answer source code similar to the assignment. We implemented the approach as a system and conducted an intervention experiment in a university lecture course to evaluate its effectiveness. There was a statistically significant improvement in the number of correct answers compared to the same course in another year without the proposed system. Therefore, it is suggested that the proposed approach can aid in the understanding of an assignment and improve the educational effect.

Original languageEnglish
Title of host publication5th IEEE Eurasian Conference on Educational Innovation 2022, ECEI 2022
EditorsTeen-Hang Meen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages229-232
Number of pages4
ISBN (Electronic)9781665433181
DOIs
Publication statusPublished - 2022
Event5th IEEE Eurasian Conference on Educational Innovation, ECEI 2022 - Taipei, Taiwan, Province of China
Duration: 2022 Feb 102022 Feb 12

Publication series

Name5th IEEE Eurasian Conference on Educational Innovation 2022, ECEI 2022

Conference

Conference5th IEEE Eurasian Conference on Educational Innovation, ECEI 2022
Country/TerritoryTaiwan, Province of China
CityTaipei
Period22/2/1022/2/12

Keywords

  • online judge
  • programming assignment
  • similar problem

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Media Technology
  • Education

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