| Vol-4006 urn:nbn:de:0074-4006-X Copyright © 2025 for the individual papers by the papers' authors. Copyright © 2025 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# EvalLAC 2025
Second Workshop on Automated Evaluation of Learning and Assessment Content

### Proceedings of the Second Workshop on Automated Evaluation of Learning and Assessment Content
co-located with 26th International Conference on Artificial Intelligence in Education (AIED 2025)

### Palermo, Italy, July 26, 2025.

Edited by

### Luca Benedetto *
Diana Galvan-Sosa *
George Dueñas **
Gabrielle Gaudeau *
Shiva Taslimipoor *
Andrew Caines *
Anastassia Loukina ***
Torsten Zesch ****

* University of Cambridge
** National Pedagogical University of Colombia
*** Grammarly Inc.
**** FernUniversität in Hagen

## Table of Contents

- Preface
  Summary: There were 23 papers submitted for peer-review to this workshop. Out of these, 9 papers were accepted for this volume, 7 as regular papers and 2 as short papers.

### Technical papers

- Leveraging AI Graders for Missing Score Imputation to Achieve Accurate Ability Estimation in Constructed-Response Tests
  Masaki Uto, Yuma Ito
- Domain-Adaptive Automated Essay Scoring with Topic Relevance Learning
  Sungjin Nam
- Automating Pedagogical Evaluation of LLM-based Conversational Agents
  Zaki Pauzi, Michael Dodman, Manolis Mavrikis
- Ordinality in Discrete-level Question Difficulty Estimation: Introducing Balanced DRPS and OrderedLogitNN
  Arthur Thuy, Ekaterina Loginova, Dries Benoit
- Open-Ended Questions Need Personalized Feedback: Analyzing LLM-Enabled Features with Student Data
  Rachel Van Campenhout, Jeffrey S. Dittel, Bill Jerome, Michelle W. Clark, Benny G. Johnson
- Enhancing Neural Automated Essay Scoring Accuracy by Removing Noisy Data Through Data Valuation
  Takumi Shibata, Yuto Tomikawa, Yuki Ito, Masaki Uto
- Fine-tuning for Better Few Shot Prompting: An Empirical Comparison for Short Answer Grading
  Joel Walsh, Siddarth Mamidanna, Benjamin Nye, Mark Core, Daniel Auerbach
- Comparing Human and LLM Evaluations on AI-Generated Critical Thinking Items: Implications for Valid Applications of Automatic Item Generation
  Euigyum Kim, Salah Khalil, Hyo Jeong Shin
- Leveraging the Intuitions of Lay People on Linguistic Complexity for Automatic Sentence Readability Assessment
  Ignatios Charalampidis, Xiaobin Chen

2025-07-24: submitted by Luca Benedetto, metadata incl. bibliographic data published under Creative Commons CC0
2025-08-05: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|