2025
ACL
ACL 2025
NLIP at BEA 2025 Shared Task: Evaluation of Pedagogical Ability of AI Tutors
Abstract
AbstractThis paper describes the system created for the BEA 2025 Shared Task on Pedagogical Ability Assessment of AI-powered Tutors. The task aims to assess how well AI tutors identify and locate errors made by students, provide guidance and ensure actionability, among other features of their responses in educational dialogues. Transformer-based models, especially DeBERTa and RoBERTa, are improved by multitask learning, threshold tweaking, ordinal regression, and oversampling. The efficiency of pedagogically driven training methods and bespoke transformer models for evaluating AI tutor quality is demonstrated by the high performance of their best systems across all evaluation tracks.
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Machine Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Classification
Machine Learning > Learning Types > Weakly Supervised Learning
Natural Language Processing > Applications > Text Classification
Machine Learning > Learning Types > Multi-Task Learning
Artificial Intelligence > Core AI > Large Language Models
Machine Learning > Core Methods > Multi-Task Learning
Deep Learning > Learning Types > Multi-Task Learning
Artificial Intelligence > Core AI > Natural Language Processing