An Automated Explainable Educational Assessment System Built on LLMs
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Abstract (arXiv)
In this demo, we present AERA Chat, an automated and explainable educational assessment system designed for interactive and visual evaluations of student responses. This system leverages large language models (LLMs) to generate automated marking and rationale explanations, addressing the challenge of limited explainability in automated educational assessment and the high costs associated with annotation. Our system allows users to input questions and student answers, providing educators and researchers with insights into assessment accuracy and the quality of LLM-assessed rationales. Additionally, it offers advanced visualization and robust evaluation tools, enhancing the usability for educational assessment and facilitating efficient rationale verification. Our demo video can be found at https://youtu.be/qUSjz-sxlBc.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 12 of its 21 references that are in the map. First posted on arXiv 17 Dec 2024.
Builds on
12 of 21 references.
References · 12
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2022Training language models to follow instructions with human feedbackcited by 15,712
- 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
- 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
- 2018e-SNLI: Natural Language Inference with Natural Language Explanationscited by 468
- 2021Few-Shot Self-Rationalization with Natural Language Promptscited by 83
- 2023The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysiscited by 34
- 2024Eliminating Biased Length Reliance of Direct Preference Optimization via Down-Sampled KL Divergencecited by 29
- 2023Rationalization for Explainable NLP: A Surveycited by 22
- 2023Distilling ChatGPT for Explainable Automated Student Answer Assessmentcited by 14
- 2024Calibrating LLMs with Preference Optimization on Thought Trees for Generating Rationale in Science Question Scoringcited by 8
- 2024AERA Chat: An Interactive Platform for Automated Explainable Student Answer Assessmentcited by 1
Built on by
Citing papers per year: 2025: 4; 2026: 1.
5 papers.
- 2025Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Researchcited by 9
- 2025Two Heads Are Better Than One: Dual-Model Verbal Reflection at Inference-Timecited by 8
- 2025Sparse Activation Editing for Reliable Instruction Following in Narrativescited by 3
- 2025Interpretability from the Ground Up: Stakeholder-Centric Design of Automated Scoring in Educational Assessmentscited by 1
- 2026CoLearn: An Agentic Tutor that Learns its Learner in a Human--AI Co-Learning Loopcited by 0
- 2026CoLearn: An Agentic Tutor that Learns its Learner in a Human--AI Co-Learning Loop17 Sep 2026
- 2025Interpretability from the Ground Up: Stakeholder-Centric Design of Automated Scoring in Educational Assessments21 Nov 2025
- 2025Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Research2 Jun 2025
- 2025Sparse Activation Editing for Reliable Instruction Following in Narratives22 May 2025
- 2025Two Heads Are Better Than One: Dual-Model Verbal Reflection at Inference-Time26 Feb 2025