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
• Conceptual Map Assessment Through Structure Classification
  Laís P. V. Vossen, Isabela Gasparini, Elaine H. T. Oliveira, Lukas Menzel, Sebastian Gombert, Knut Neumann, Hendrik Drachsler
• 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