Using Self-Explanation and Ontology for Providing Proper Feedbacks in a Programming Environment

Cheng Wei Yen, Tzone I. Wang

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

1 Citation (Scopus)

Abstract

To help programmer gaining sound concepts of a programming language and boost their problem solving ability, this study constructs a programming environment, which, based on the self-explanation strategy, gives proper feedbacks for the programmers of C++language. The embedded self-explanation strategy guides the environment which, when programmers gets compilation errors, gives extended examples for the programmers and ask them for self-explanations on the inference of the error after they study the examples. An algorithm developed in this study compares the self-explanation sentence from a programmer with base strings, established and organized into an ontology by programing experts, and finds possible errors on the explanation, which lead to his/her possible misconceptions. Based on the results, the environment manages to feedback proper learning material and extended examples for programmers to correct their possible misconceptions. This study builds an ontology of C++ concepts class hierarchy with class properties and instances being possible misconceptions and the learning material feedbacks. The possible misconceptions are collected from actual programming practices in several pilot experiments joined by programmers of college students. The final experiment involves 13 college students who use the system for actual programming. The environment records students programming activities, analyzes their self-explanations on errors, and gives proper feedbacks, which, after verified by programming experts, reaches an average accuracy of 84.7%. The distinctive feature of this study is the open question style self-explanation sentence requirement, a rare research of its kind. All the schemes and algorithms developed in this study can be used as a methodology for establishing system with self-explanation learning strategy in other fields.

Original languageEnglish
Title of host publicationProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
EditorsKiyota Hashimoto, Naoki Fukuta, Tokuro Matsuo, Sachio Hirokawa, Masao Mori, Masao Mori
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages585-590
Number of pages6
ISBN (Electronic)9781538606216
DOIs
Publication statusPublished - 2017 Nov 15
Event6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 - Hamamatsu, Shizuoka, Japan
Duration: 2017 Jul 9 → …

Publication series

NameProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017

Other

Other6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
CountryJapan
CityHamamatsu, Shizuoka
Period17-07-09 → …

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

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  • Cite this

    Yen, C. W., & Wang, T. I. (2017). Using Self-Explanation and Ontology for Providing Proper Feedbacks in a Programming Environment. In K. Hashimoto, N. Fukuta, T. Matsuo, S. Hirokawa, M. Mori, & M. Mori (Eds.), Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 (pp. 585-590). [8113313] (Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IIAI-AAI.2017.136