PASTEL: Evidence-based Learning Engineering Method to Create Intelligent Online Textbook at Scale. - Noboru Matsuda; Machi Shimmei (iTextbooks@AIED, 2019)

Evidence-Based Recommendation for Content Improvement Using Reinforcement Learning. - Machi Shimmei; Noboru Matsuda (AIED (2), 2019)

Learning a Policy Primes Quality Control: Towards Evidence-Based Automation of Learning Engineering. - Machi Shimmei; Noboru Matsuda (EDM, 2020)

Learning Association Between Learning Objectives and Key Concepts to Generate Pedagogically Valuable Questions. - Machi Shimmei; Noboru Matsuda (AIED (2), 2021)

Automatic Question Generation for Evidence-based Online Courseware Engineering. - Machi Shimmei; Noboru Matsuda (iTextbooks@AIED, 2022)

Machine-Generated Questions Attract Instructors When Acquainted with Learning Objectives. - Machi Shimmei; Norman L. Bier; Noboru Matsuda (AIED, 2023)

Can't Inflate Data? Let the Models Unite and Vote: Data-agnostic Method to Avoid Overfit with Small Data. - Machi Shimmei; Noboru Matsuda (EDM, 2023)

Leveraging Prompts in LLMs to Overcome Imbalances in Complex Educational Text Data. - Jeanne McClure; Machi Shimmei; Noboru Matsuda; Shiyan Jiang (CoRR, 2024)

Tell Me Who Your Students Are: GPT Can Generate Valid Multiple-Choice Questions When Students' (Mis)Understanding Is Hinted. - Machi Shimmei; Masaki Uto; Yuichiroh Matsubayashi; Kentaro Inui; Aditi Mallavarapu; Noboru Matsuda (CoRR, 2025)