Personalized Programming Learning Support Method Based on Deep Learning Technology

基于深度学习技术的个性化编程学习支持方法

• 批准号: 21K17865
• 负责人: YAN YU
• 金额: $ 2.33万
• 依托单位: Ritsumeikan University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Early-Career Scientists
• 财政年份: 2021
• 资助国家: 日本
• 起止时间: 2021-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-21K17865/
• 关键词: Programming Education; NLP; Automatic Commenting; Automatic Grading; Machine Learning; Recurrent Neural Network; Random Forest; E-learning; Programming education; Deep Learning

In 2022, the following achievements were reached:1. The data with students' programs and corresponding grading results and comments for each has been collected. It is from two registered class homework assignments in the author's university.2. A software engineer (Victor KHAUSTOV) was hired for about six months to process the data mentioned in "1". The processed data has been anonymized with the students' names and ID numbers. Additionally, a machine-learning environment has been set for data training.3. The paper ("A Model to Automatically Evaluate Beginners Programs Based on Syntactic Knowledge Point and Deep Learning Technology") has been published in an international conference proceeding ("2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems").

2022年，取得了以下成果：1.收集了学生的课程和相应的评分结果和评论的数据。它来自作者所在大学的两个注册的班级作业。雇佣了一名软件工程师(Victor KHAUSTOV)，时间约为6个月，负责处理“1”中提到的数据。处理后的数据已与学生的姓名和身份证号码一起匿名。此外，还为数据培训设置了机器学习环境。论文《基于句法知识点和深度学习技术的初学者自动评估模型》已在国际会议论文集(《2022年第12届软计算与智能系统国际会议暨第23届先进智能系统国际研讨会》)上发表。

项目成果

A Model to Automatically Evaluate Beginners’ Programs Based on Syntactic Knowledge Point and Deep Learning Technology

• DOI: 10.1109/scisisis55246.2022.10001960
• 发表时间: 2022-11
• 期刊: 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS)
• 作者: Yumo Yan;Hirokuni Kurokawa