| Seller reputation or product presentation? An empirical investigation from cue utilization perspective Q Wang, X Cui, L Huang, Y Dai International Journal of Information Management 36 (3), 271-283, 2016 | 117 | 2016 |
| Course Content Analysis: An Initiative Step toward Learning Object Recommendation Systems for MOOC Learners. Y Dai, Y Asano, M Yoshikawa International Educational Data Mining Society, 2016 | 34 | 2016 |
| EXAIT: Educational eXplainable artificial intelligent tools for personalized learning H Ogata, B Flanagan, K Takami, Y Dai, R Nakamoto, K Takii Research and Practice in Technology Enhanced Learning 19, 2024 | 33 | 2024 |
| Educational explainable recommender usage and its effectiveness in high school summer vacation assignment K Takami, Y Dai, B Flanagan, H Ogata LAK22: 12th International Learning Analytics and Knowledge Conference, 458-464, 2022 | 28 | 2022 |
| EXAIT: A symbiotic explanation learning system B FLANAGAN, K TAKAMI, K TAKII, DAI Yiling, R MAJUMDAR International Conference on Computers in Education, 2021 | 16 | 2021 |
| Enhancing Automated Scoring of Math Self-Explanation Quality Using LLM-Generated Datasets: A Semi-Supervised Approach R Nakamoto, B Flanagan, T Yamauchi, Y Dai, K Takami, H Ogata Computers 12 (11), 217, 2023 | 12 | 2023 |
| Identifying students’ stuck points using self-explanations and pen stroke data in a mathematics quiz R Nakamoto, B Flanagan, K Takami, Y Dai, H Ogata ICCE 2021, 22-26, 2021 | 12 | 2021 |
| The influence of online product presentation and seller reputation on the consumers’ purchase intention across different involvement products Q Wang, Y Dai | 12 | 2013 |
| Toward educational explainable recommender system: explanation generation based on Bayesian knowledge tracing parameters K Takami, B Flanagan, DAI Yiling International Conference on Computers in Education, 2021 | 11 | 2021 |
| Design of a user-interpretable math quiz recommender system for Japanese high school students Y Dai, B Flanagan, K Takami, H Ogata Proceedings of the 4th workshop on predicting performance based on the …, 2022 | 10 | 2022 |
| Personality-based tailored explainable recommendation for trustworthy smart learning system in the age of artificial intelligence K Takami, B Flanagan, Y Dai, H Ogata Smart Learning Environments 10 (1), 65, 2023 | 8 | 2023 |
| Automated matching of exercises with knowledge components Z Tian, B Flanagan, Y Dai, H Ogata 30th International Conference on Computers in Education Conference …, 2022 | 8 | 2022 |
| Unsupervised techniques for generating a standard sample self-explanation answer with knowledge components in a math quiz R Nakamoto, B Flanagan, Y Dai, K Takami, H Ogata Research and Practice in Technology Enhanced Learning 19, 2024 | 6 | 2024 |
| Enhancing Self-Explanation Learning through a Real-Time Feedback System: An Empirical Evaluation Study R Nakamoto, B Flanagan, Y Dai, T Yamauchi, K Takami, H Ogata Sustainability 15 (21), 15577, 2023 | 6 | 2023 |
| Prerequisite-aware course ordering towards getting relevant job opportunities Y Dai, M Yoshikawa, K Sugiyama Expert Systems with Applications 183, 115233, 2021 | 6 | 2021 |
| Beyond recommendation acceptance: Explanation’s learning effects in a math recommender system Y Dai, K Takami, B Flanagan, H Ogata Research and Practice in Technology Enhanced Learning 19, 2024 | 4 | 2024 |
| Toward trustworthy explainable recommendation: personality based tailored explanation for improving e-learning engagements and motivation to learn K Takami, B Flanagan, Y Dai, H Ogata Companion Proceedings 13th International Conference on Learning Analytics …, 2022 | 4 | 2022 |
| Automated labeling of PDF mathematical exercises with word N-grams VSM classification T Yamauchi, B Flanagan, R Nakamoto, Y Dai, K Takami, H Ogata Smart Learning Environments 10 (1), 51, 2023 | 3 | 2023 |
| Investigation on practical effects of the explanation in a K-12 math recommender system DAI Yiling, K TAKAMI, B Flanagan, H Ogata International Conference on Computers in Education, 2022 | 3 | 2022 |
| An Automatic Self-explanation Sample Answer Generation with Knowledge Components in a Math Quiz R Nakamoto, B Flanagan, Y Dai, K Takami, H Ogata International Conference on Artificial Intelligence in Education, 254-258, 2022 | 3 | 2022 |
Brendan FlanaganAssociate Professor at Kyoto University, Japan確認したメール アドレス: kyoto-u.ac.jp
