DC in LAK 2022
Proceedings of the 4th Workshop on Predicting Performance Based on the Analysis of Reading Behavior

Table of Contents

• Preface
  Brendan Flanagan, Rwitajit Majumdar, Huiyong Li, Atsushi Shimada, Fumiya Okubo, Hiroaki Ogata

Summary: Each paper submitted to the workshop underwent a rigorous double-blind review by at least two reviewers. Each paper was evaluated with respect to four criteria: 1) quality of content, 2) significance for theory and practice, 3) originality and level of innovativeness, 4) fitting to the workshop theme. The review results of each paper were subsequently discussed by the six workshop chairs resulting in a decision of acceptance or rejection. There were 6 papers submitted for peer-review to this workshop. Out of these, 6 papers were accepted as regular papers for this volume.

Research Papers

• Exploring the Use of Probabilistic Latent Representations to Encode the Students' Reading Characteristics 1-10
  Erwin D. Lopez Z., Tsubasa Minematsu, Taniguchi Yuta, Fumiya Okubo, Atsushi Shimada
• Predicting Student Performance based on Lecture Materials Data using Neural Network Models 11-20
  Sukrit Leelaluk, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Atsushi Shimada
• Preliminary Personal Trait Prediction from High School Summer Vacation e-learning Behavior 21-29
  Kyosuke Takami, Brendan Flanagan, Rwitajit Majumdar, Hiroaki Ogata
• Design of a User-Interpretable Math Quiz Recommender System for Japanese High School Students 30-38
  Yiling Dai, Brendan Flanagan, Kyosuke Takami, Hiroaki Ogata
• An Analysis of Reading Process based on Real-time Eye-tracking Data with Web-camera--Focus on English Reading at Higher Education Level 39-48
  Xiu Guan, Chaojing Lei, Yingfen Huang, Yu Chen, Hanyue Du, Shuowen Zhang, Xiang Feng
• A Preliminary Study on Student Classroom Reading vs Digital Reading Pattern Behavior Analysis during Pandemic 49-58
  Divanshi Priyadarshni Wangoo, S.R.N Reddy