EvalLAC 2024
Automated Evaluation of Learning and Assessment Content

Table of Contents

• Preface
  Summary: There were 10 papers submitted for peer-review to this workshop. Out of these, 10 papers were accepted for this volume, 7 as regular papers and 3 as short papers.

Technical papers

• Question Difficulty Prediction Based on Virtual Test-Takers and Item Response Theory
  Masaki Uto , Yuto Tomikawa , Ayaka Suzuki
• Can LLMs Evaluate Items Measuring Collaborative Problem-Solving?
  Ella Anghel , Yu Wang , Madhumitha Gopalakrishnan , Pranali Mansukhani , Yoav Bergner
• Enhancing Cross-prompt Automated Essay Scoring by Selecting Training Data Based on Reinforcement Learning
  Takumi Shibata , Masaki Uto
• Exploring Large Language Models for Evaluating Automatically Generated Questions
  Jeffrey S. Dittel , Michelle W. Clark , Rachel Van Campenhout , Benny G. Johnson
• Large Language Models for Learner Assistance in Massive Open Online Courses: Challenges, Tools, and Approaches
  Jesus-Angel del-Hoyo-Gabaldon , Eva Garcia-Lopez , Antonio Garcia-Cabot , David de-Fitero-Dominguez , Mary-Ellen Wiltrout , Jessica Sandland , Ana Bell
• Evaluation with Language Models in Non-formal Education: Understanding Student’s Persuasion Style in Competitive Debating
  Ali Al-Zawqari , Mohamed Ahmed , Gerd Vandersteen
• Towards Automatic Evaluation of Questions Generated from Ontologies
  Samah Alkhuzaey , Floriana Grasso , Terry R. Payne , Valentina Tamma
• Difficulty of Items – Predictions on Linguistic Features
  Anna Winklerová
• Evaluating LLMs’ Performance At Automatic Short-Answer Grading
  Rositsa V. Ivanova , Siegfried Handschuh