EXAIT: A Symbiotic Explanation Learning System. - Brendan Flanagan; Kyosuke Takami; Kensuke Takii; Yiling Dai; Rwitajit Majumdar (ICCE, 2021)

Identifying Students' Stuck Points Using Self-Explanations and Pen Stroke Data in a Mathematics Quiz. - Ryousuke Namamoto; Brendan Flanagan; Kyosuke Takami (ICCE, 2021)

Toward Educational Explainable Recommender System: Explanation Generation based on Bayesian Knowledge Tracing Parameters. - Kyosuke Takami; Brendan Flanagan; Yiling Dai (ICCE, 2021)

An Automatic Self-explanation Sample Answer Generation with Knowledge Components in a Math Quiz. - Ryosuke Nakamoto; Brendan Flanagan; Yiling Dai; Kyosuke Takami; Hiroaki Ogata (AIED (2), 2022)

Investigation on Practical Effects of the Explanation in a K-12 Math Recommender System. - Yiling Dai; Kyosuke Takami; Brendan Flanagan; Hiroaki Ogata (ICCE, 2022)

Automated Test Set Quiz Maker Optimizing Solving Time and Parameters of Bayesian Knowledge Tracing Model Extracted from Learning Log. - Kyosuke Takami; Gou Miyabe; Brendan Flanagan; Hiroaki Ogata (ICCE, 2022)

Nudge Messages for E-Learning Engagement and Student's Personality Traits: Effects and Implication for Personalization. - Taisei Yamauchi; Kyosuke Takami; Brendan Flanagan; Hiroaki Ogata (ICCE, 2022)

Design of a User-Interpretable Math Quiz Recommender System for Japanese High School Students. - Yiling Dai; Brendan Flanagan; Kyosuke Takami; Hiroaki Ogata (LAK (Data Challenge), 2022)

Educational Explainable Recommender Usage and its Effectiveness in High School Summer Vacation Assignment. - Kyosuke Takami; Yiling Dai; Brendan Flanagan; Hiroaki Ogata (LAK, 2022)

Preliminary Personal Trait Prediction from High School Summer Vacation e-learning Behavior. - Kyosuke Takami; Brendan Flanagan; Rwitajit Majumdar; Hiroaki Ogata (LAK (Data Challenge), 2022)

Learning with Explainable AI-Recommendations at School: Extracting Patterns of Self-Directed Learning from Learning Logs. - Rwitajit Majumdar; Kyosuke Takami; Hiroaki Ogata (ICALT, 2023)

Improved Automated Labeling of Mathematical Exercises in Japanese. - Taisei Yamauchi; Ryosuke Nakamoto; Yiling Dai; Kyosuke Takami; Brendan Flanagan; Hiroaki Ogata (ICCE, 2023)

Matching Intervention Messages Considering Complex Personality Types of High School Students. - Taisei Yamauchi; Yuta Nakamizo; Kyosuke Takami; Rwitajit Majumdar; Hiroaki Ogata (ICCE, 2023)

Enhancing Automated Scoring of Math Self-Explanation Quality Using LLM-Generated Datasets: A Semi-Supervised Approach. - Ryosuke Nakamoto; Brendan Flanagan; Taisei Yamauchi; Yiling Dai; Kyosuke Takami; Hiroaki Ogata (Comput., 2023)

Personality-based tailored explainable recommendation for trustworthy smart learning system in the age of artificial intelligence. - Kyosuke Takami; Brendan Flanagan; Yiling Dai; Hiroaki Ogata (Smart Learn. Environ., 2023)

Automated labeling of PDF mathematical exercises with word N-grams VSM classification. - Taisei Yamauchi; Brendan Flanagan; Ryosuke Nakamoto; Yiling Dai; Kyosuke Takami; Hiroaki Ogata (Smart Learn. Environ., 2023)

An Automated Impasse Detection System Based on the Analysis of Self-Explanations in Mathematics. - Ryosuke Nakamoto; Brendan Flanagan; Yiling Dai; Kyosuke Takami; Hiroaki Ogata (ICALT, 2024)

Auto-Scoring of Math Self-Explanations by Combining Visual and Language Analysis. - Ryosuke Nakamoto; Brendan Flanagan; Yiling Dai; Kyosuke Takami; Hiroaki Ogata (ICALT, 2024)

Utilization of Japanese Public Educational Data by Retrieval Augmented Generation for Policy Research. - Kyosuke Takami (ICCE, 2024)

LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs. - Akiko Aizawa; Eiji Aramaki; Bowen Chen; Fei Cheng 002; Hiroyuki Deguchi 002; Rintaro Enomoto; Kazuki Fujii; Kensuke Fukumoto; Takuya Fukushima; Namgi Han; Yuto Harada; Chikara Hashimoto; et al. (CoRR, 2024)

Evaluating the Effectiveness of Bayesian Knowledge Tracing Model-Based Explainable Recommender. - Kyosuke Takami; Brendan Flanagan; Yiling Dai; Hiroaki Ogata (Int. J. Distance Educ. Technol., 2024)

Unsupervised techniques for generating a standard sample self-explanation answer with knowledge components in a math quiz. - Ryosuke Nakamoto; Brendan Flanagan; Yiling Dai; Kyosuke Takami; Hiroaki Ogata (Res. Pract. Technol. Enhanc. Learn., 2024)

Integrating self-explanation and operational data for impasse detection in mathematical learning. - Ryosuke Nakamoto; Brendan Flanagan; Yiling Dai; Taisei Yamauchi; Kyosuke Takami; Hiroaki Ogata (Res. Pract. Technol. Enhanc. Learn., 2024)

EXAIT: Educational eXplainable Artificial Intelligent Tools for personalized learning. - Hiroaki Ogata; Brendan Flanagan; Kyosuke Takami; Yiling Dai; Ryosuke Nakamoto; Kensuke Takii (Res. Pract. Technol. Enhanc. Learn., 2024)

Beyond recommendation acceptance: explanation's learning effects in a math recommender system. - Yiling Dai; Kyosuke Takami; Brendan Flanagan; Hiroaki Ogata (Res. Pract. Technol. Enhanc. Learn., 2024)

Do personal recommendations need to be personalized? Investigating the relationships between student differences and educational recommendations. - Yiling Dai; Heinz Ulrich Hoppe; Brendan Flanagan; Kyosuke Takami; Hiroaki Ogata (Smart Learn. Environ., 2024)

Social and Emotional Modes of Learning Within Digital Ecosystems: Emerging Research Agendas. - Ola Erstad; Miroslava Cernochová; Gerald Knezek; Takahisa Furuta; Kyosuke Takami; Changhao Liang (Technol. Knowl. Learn., 2024)

Co-designing Data-Driven Educational Technology and Practice: Reflections from the Japanese Context. - Hiroaki Ogata; Changhao Liang; Yuko Toyokawa; Chia-Yu Hsu 002; Kohei Nakamura; Taisei Yamauchi; Brendan Flanagan; Yiling Dai; Kyosuke Takami; Izumi Horikoshi; Rwitajit Majumdar (Technol. Knowl. Learn., 2024)

Evaluating Local LLMs on Japanese National University Entrance Examination Dataset in Comparison with Student Performance. - Kyosuke Takami; Satoshi Sekine; Yusuke Miyao (EDM, 2025)