Programming Learning Support System based on Programmed Visual Contents Comparison (PVCC)
Research Overview
Our research focuses on enhancing programming education through the innovative PVCC (Programmed Visual Contents Comparison) methodology. This approach combines visual learning with collaborative techniques to improve programming comprehension and skills assessment. The system has been successfully implemented and tested in various educational contexts, demonstrating significant improvements in student engagement and learning outcomes.
System Introduction
PAT (Programming Learning Support System) is a comprehensive web-based platform that implements the PVCC methodology. The system provides interactive code testing environments, real-time feedback mechanisms, and collaborative learning features. It supports multiple programming languages and visualization engines, making it versatile for different educational needs and skill levels.
Research Publications
- Hidenari Kiyomitsu, Thanh Ha Nguyen, Kazuhiro Ohtsuki, Dick Martinez Carderon, Shuai Shao and Kento Shigyo, "Question Authoring for Learning Programming Skills based on the Programmed Visual Content Comparison Method," 2019 IEEE International Conference on Engineering, Technology and Education (TALE), Yogyakarta, Indonesia, 2019, pp. 1-6, doi: 10.1109/TALE48000.2019.9225958.
- Thanh Ha Nguyen, Hidenari Kiyomitsu, Kazuhiro Ohtsuki, "Trial of Collaborative Learning in Programming Education with the Programed Visual Contents Comparison Method," JSiSE Research Report, Vol. 37, No. 7, March 2023, pp. 66-72. www.jsise.org
- Thanh Ha Nguyen, Hidenari Kiyomitsu, Yi Sun, Takeshi Nishida, Kazuhiro Ohtsuki, "Collaborative Learning in Programming Education with the Programmed Visual Contents Comparison Method," 2024 ICIET, pp. 467-471, doi: 10.1109/ICIET60671.2024.10542766.
- Thanh Ha Nguyen, Yi Sun, Takeshi Nishida, Xiaonan Wang, Kazuhiro Ohtsuki, Hidenari Kiyomitsu, "Effectiveness of the Programmed Visual Contents Comparison Method for Two Phase Collaborative Learning in Computer Programming Education: A Case Study," Database Systems for Advanced Applications. DASFAA 2024 International Workshops. DASFAA 2024. Lecture Notes in Computer Science, vol 14667, pp 203–210, doi: 10.1007/978-981-96-0914-7_14
可視化コンテンツ比較法(PVCC)によるプログラミング学習支援システム
研究概要
本研究は、PVCC（プログラムビジュアルコンテンツ比較）法を用いたプログラミング教育の向上に焦点を当てています。この手法は、視覚的学習と協調的な技術を組み合わせることで、プログラミングの理解とスキル評価を改善します。このシステムは様々な教育環境で実装・検証され、学生の参加度と学習成果の大幅な向上を示しています。
システム紹介
PAT（プログラミング学習支援システム）は、PVCC方法を実装した総合的なWebベースプラットフォームです。システムは、インタラクティブなコードテスト環境、リアルタイムフィードバック機能、協調学習機能を提供します。複数のプログラミング言語と視覚化エンジンをサポートし、様々な教育ニーズとスキルレベルに対応できる柔軟性を備えています。
研究論文
- 清光英成, Thanh Ha Nguyen, 大月一弘, Dick Martinez Carderon, Shuai Shao and Kento Shigyo, "Question Authoring for Learning Programming Skills based on the Programmed Visual Content Comparison Method," 2019 IEEE International Conference on Engineering, Technology and Education (TALE), Yogyakarta, Indonesia, 2019, pp. 1-6, doi: 10.1109/TALE48000.2019.9225958.
- Thanh Ha Nguyen, 清光英成, 大月一弘, "プログラムビジュアルコンテンツ比較方式を用いたプログラミング教育における協調学習の試み," 教育システム情報学会研究報告, 第37巻, 第7号, 2023年3月, pp. 66-72. www.jsise.org
- Thanh Ha Nguyen, 清光英成, 孫 一, 西田健志, 大月一弘, "Collaborative Learning in Programming Education with the Programmed Visual Contents Comparison Method," 2024 ICIET, pp. 467-471, doi: 10.1109/ICIET60671.2024.10542766.
- Thanh Ha Nguyen, 孫 一, 西田健志, Xiaonan Wang, 大月一弘, 清光英成, "Effectiveness of the Programmed Visual Contents Comparison Method for Two Phase Collaborative Learning in Computer Programming Education: A Case Study," Database Systems for Advanced Applications. DASFAA 2024 International Workshops. DASFAA 2024. Lecture Notes in Computer Science, vol 14667, pp 203–210, doi: 10.1007/978-981-96-0914-7_14