Follow
Yiling Dai
Yiling Dai
Researcher, Kyoto University
Verified email at kyoto-u.ac.jp
Title
Cited by
Cited by
Year
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
952016
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
312016
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
222022
Toward educational explainable recommender system: explanation generation based on Bayesian knowledge tracing parameters
K Takami, B Flanagan, Y Dai, H Ogata
29th International Conference on Computers in Education Conference …, 2021
102021
The influence of online product presentation and seller reputation on the consumers’ purchase intention across different involvement products
Q Wang, Y Dai
102013
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
92024
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
82022
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
82021
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
32024
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
22024
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
22023
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
22022
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
12023
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
12023
Automated matching of exercises with knowledge components
Z Tian, B Flanagan, Y Dai, H Ogata
30th International Conference on Computers in Education Conference …, 2022
12022
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
12022
Prerequisite-aware course ordering towards getting relevant job opportunities
Y Dai, M Yoshikawa, K Sugiyama
Expert Systems with Applications 183, 115233, 2021
12021
Estimating Knowledge Category Coverage by Courses Based on Centrality in Taxonomy
Y Dai, M Yoshikawa, Y Asano
IEICE TRANSACTIONS on Information and Systems 103 (5), 928-938, 2020
12020
Evaluating the Effectiveness of Bayesian Knowledge Tracing Model-Based Explainable Recommender
K Takami, B Flanagan, Y Dai, H Ogata
International Journal of Distance Education Technologies (IJDET) 22 (1), 1-23, 2024
2024
A human-in-the-loop system for labeling knowledge components in Japanese mathematics exercises.
B Flanagan, Z Tian, T Yamauchi, Y Dai, H Ogata
Research & Practice in Technology Enhanced Learning 19, 2024
2024
The system can't perform the operation now. Try again later.
Articles 1–20