Kyosuke Takami

According to our database, Kyosuke Takami authored at least 12 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

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., September, 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

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

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

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., December, 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., December, 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., October, 2023

Learning with Explainable AI-Recommendations at School: Extracting Patterns of Self-Directed Learning from Learning Logs.

Rwitajit Majumdar, Kyosuke Takami, Hiroaki Ogata

Proceedings of the IEEE International Conference on Advanced Learning Technologies, 2023

2022

Preliminary Personal Trait Prediction from High School Summer Vacation e-learning Behavior.

Kyosuke Takami, Brendan Flanagan, Rwitajit Majumdar, Hiroaki Ogata

Proceedings of the 4th Workshop on Predicting Performance Based on the Analysis of Reading Behavior, 2022

Educational Explainable Recommender Usage and its Effectiveness in High School Summer Vacation Assignment.

Kyosuke Takami, Yiling Dai, Brendan Flanagan, Hiroaki Ogata

Proceedings of the LAK 2022: 12th International Learning Analytics and Knowledge Conference, Online Event, USA, March 21, 2022

Design of a User-Interpretable Math Quiz Recommender System for Japanese High School Students.

Yiling Dai, Brendan Flanagan, Kyosuke Takami, Hiroaki Ogata

Proceedings of the 4th Workshop on Predicting Performance Based on the Analysis of Reading Behavior, 2022

An Automatic Self-explanation Sample Answer Generation with Knowledge Components in a Math Quiz.

Ryosuke Nakamoto, Brendan Flanagan, Yiling Dai, Kyosuke Takami, Hiroaki Ogata

Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium, 2022