Personalized Programming Learning Support Method Based on Deep Learning Technology

2023 Fiscal Year Research-status Report

• Project/Area Number: 21K17865
• Research Institution: Ritsumeikan University
• Principal Investigator: YAN YU 立命館大学, 情報理工学部, 助教 (30875894)
• Project Period (FY): 2021-04-01 – 2025-03-31
• Keywords: Programming Education / NLP / Automatic Commenting / Automatic Grading / Machine Learning

Outline of Annual Research Achievements

In AY2023, the data collected from last year was analyzed in different ways. Feedbacks from ChatGPT students' programs were compared with human evaluations. The analysis results show that GhatGPT gives more positive feedback compared with human evaluations. These results also show that GhatGPT feedback can not give solutions to a defective student program. Several language processing models were explored to give better feedback. However, it is still ongoing.

Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

In AY2023, although there were no publishing outcomes from the research, the project ran smoothly and it is in the last stage now.

Strategy for Future Research Activity

In AY2024, I will find more collaborators to work with for the natural language processing part. In addition, I am planning to write a journal paper to publish the data analysis results and the neural network training results.

Causes of Carryover

The grant money for the next academic year (AY2024) will be used based on the following: 1. I am going to target a Journal to present the current experimental results. The money will be used to pay for the registration fee for the journal paper. 2. I am going to find more collaborators to work on the project. The grant will be used to pay for some technical support. 3. I am going to conduct one or two more experiments. The experiment results will be presented at an international conference. The money will be used to pay for the conference registration fee and travel.