| Presentation | 2023-01-20 A System for Estimating Adaptive Solution Based on Transition of Each Learner's Source Codes Soichiro Sato, Yoshiki Sato, Shoichi Nakamura, Youzou Miyadera, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Analyses of source codes created by learners are often used to support teaching in programming classes. However, most studies aim to estimate the learners' understanding and identify those who need help. The purpose of this study is to develop a system that automatically estimates a solution method (source code) from the transition of source codes submitted by a learner who has had difficulty with the programming tasks in the past. The estimated source code should be easy for the learners to understand, and teachers can use it to provide adaptive solution support. An approach to developing this system is to compile source codes and generate abstract syntax trees and then convert to token columns and weights. These are classified for each solution by clustering and then labeled. After inputting the transition of labeled source codes, a machine learning model is created to output the labeled source code (solution method). In the development of machine learning models, clustering results have a significant effect on estimation accuracy, therefor we compared and examined the clustering threshold value for each task to estimate the solution. The machine learning model created in this study was evaluated using an existing machine learning evaluation method, and the results suggested that our developed model can automatically estimate the solution that is easy for learners to understand with high AUC. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Programming Learning / Solution Estimation / Machine Learning / Source Code History / Educational Support |
| Paper # | ET2022-57 |
| Date of Issue | 2023-01-13 (ET) |
| Conference Information | |
| Committee | ET |
|---|---|
| Conference Date | 2023/1/20(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hyogo College of Medicine and Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Embodies Knowledge and Skill Education, etc. |
| Chair | Kenji Watanabe(Hiroshimai Univ.) |
| Vice Chair | Hisayoshi Kunimune(Chiba Inst. of Tech.) |
| Secretary | Hisayoshi Kunimune(Mejiro Univ.) |
| Assistant | Kazuaki Yoshihara(Kinki Univ.) / Toru Kano(Tokyo University of Science) |
| Paper Information | |
| Registration To | Technical Committee on Educational Technology |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A System for Estimating Adaptive Solution Based on Transition of Each Learner's Source Codes |
| Sub Title (in English) | |
| Keyword(1) | Programming Learning |
| Keyword(2) | Solution Estimation |
| Keyword(3) | Machine Learning |
| Keyword(4) | Source Code History |
| Keyword(5) | Educational Support |
| 1st Author's Name | Soichiro Sato |
| 1st Author's Affiliation | Tokyo Gakugei University(Tokyo Gakugei Univ.) |
| 2nd Author's Name | Yoshiki Sato |
| 2nd Author's Affiliation | Tokyo Gakugei University(Tokyo Gakugei Univ.) |
| 3rd Author's Name | Shoichi Nakamura |
| 3rd Author's Affiliation | Fukushima University(Fukushima Univ.) |
| 4th Author's Name | Youzou Miyadera |
| 4th Author's Affiliation | Tokyo Gakugei University(Tokyo Gakugei Univ.) |
| Date | 2023-01-20 |
| Paper # | ET2022-57 |
| Volume (vol) | vol.122 |
| Number (no) | ET-348 |
| Page | pp.pp.5-10(ET), |
| #Pages | 6 |
| Date of Issue | 2023-01-13 (ET) |