Learning Analytics
Real-time Analytics
Real-time analytics enables teachers to understand students' activities even during a lecture period. The fundamental methodologies such as collection, aggregation and analysis of a large scale of learning logs are developed.
Journals (Peer-reviewed)
- Atsushi Shimada, Shin’ichi Konomi, Hiroaki Ogata
Real-Time Learning Analytics System for Improvement of On-Site Lectures
Interactive Technology and Smart Education, Vol.15, No.4, pp.314-331, 2018.12
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Summarization of Learning Materials
Summarized learning materials enhance the pre-understanding of contents via preview. Image processing and natural language processing are utilized to select important pages, and optimization function is solved to generate a digest version of original learning material.
Journals (Peer-reviewed)
- Atsushi Shimada, Fumiya Okubo, Chengjiu Yin, Hiroaki Ogata
Automatic Summarization of Lecture Slides for Enhanced Student Preview -Technical Report and User Study-
IEEE Transactions on Learning Technologies, Vol.11, No.2, pp.165-178, 2017.03
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Performance Prediction
Academic performance prediction is helpful for both of teachers and students to understand the current learning status and how it will relate to the final performance. A large scale of learning logs is utilized to make a prediction model.
International Conferences (Peer-reviewed)
- Fumiya Okubo, Takayoshi Yamashita, Atsushi Shimada, Yuta Taniguchi, Shin'ichi Konomi
On the Prediction of Students’ Quiz Score by Recurrent Neural Network
Multimodal Learning Analytics Across Spaces Workshop (CrossMMLA), 2018.03
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Recommendation
Recommendation of related learning materials is helpful for students to understand the contents more deeply and/or to extend the knowledge about the contents. Page-wise recommendation is realized through the analytics of learning materials.
International Conferences (Peer-reviewed)
- Keita Nakayama, Masanori Yamada, Atsushi Shimada, Tsubasa Minematsu, Rin-ichiro Taniguchi
Learning Support System for Providing Page-wise Recommendation in e-Textbooks
Society for Information Technology & Teacher Education International Conference 2019, 2019.03
BibTeX
Knowledge Map Analytics
Knowledge map enables teachers and students to understand the situation of knowledge acquisition. Analytics methodologies to integrate multiple knowledge maps, to explore similar knowledge maps, to visualize the analytics results are developed.
International Conferences (Peer-reviewed)
- Akira Onoue, Masanori Yamada, Atsushi Shimada, Rin-ichiro Taniguchi
The Integrated Knowledge Map for Surveying Students’ Learning
The Society for Information Technology and Teacher Education (SITE), 2019.03
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