Mathattack: Attacking large language models towards math solving ability

Z Zhou, Q Wang, M **, J Yao, J Ye, W Liu… - Proceedings of the …, 2024 - ojs.aaai.org
With the boom of Large Language Models (LLMs), the research of solving Math Word
Problem (MWP) has recently made great progress. However, there are few studies to …

Bridging the novice-expert gap via models of decision-making: A case study on remediating math mistakes

RE Wang, Q Zhang, C Robinson, S Loeb… - arxiv preprint arxiv …, 2023 - arxiv.org
Scaling high-quality tutoring remains a major challenge in education. Due to growing
demand, many platforms employ novice tutors who, unlike experienced educators, struggle …

More than model documentation: uncovering teachers' bespoke information needs for informed classroom integration of ChatGPT

M Tan, H Subramonyam - Proceedings of the 2024 CHI Conference on …, 2024 - dl.acm.org
ChatGPT has entered classrooms, circumventing typical training and vetting procedures.
Unlike other educational technologies, it placed teachers in direct contact with the versatility …

Pedagogical alignment of large language models (llm) for personalized learning: a survey, trends and challenges

MA Razafinirina, WG Dimbisoa, T Mahatody - Journal of Intelligent …, 2024 - scirp.org
This survey paper investigates how personalized learning offered by Large Language
Models (LLMs) could transform educational experiences. We explore Knowledge Editing …

Supporting self-reflection at scale with large language models: Insights from randomized field experiments in classrooms

H Kumar, R **ao, B Lawson, I Musabirov, J Shi… - Proceedings of the …, 2024 - dl.acm.org
Self-reflection on learning experiences constitutes a fundamental cognitive process,
essential for consolidating knowledge and enhancing learning efficacy. However, traditional …

Disclosures & Disclaimers: Investigating the Impact of Transparency Disclosures and Reliability Disclaimers on Learner-LLM Interactions

JY Bo, H Kumar, M Liut, A Anderson - Proceedings of the AAAI …, 2024 - ojs.aaai.org
Abstract Large Language Models (LLMs) are increasingly being used in educational
settings to assist students with assignments and learning new concepts. For LLMs to be …

Enhancing Tutoring Effectiveness Through Automated Feedback: Preliminary Findings from a Pilot Randomized Controlled Trial on SAT Tutoring

J Yun, Y Hicke, M Olson, D Demszky - Proceedings of the Eleventh ACM …, 2024 - dl.acm.org
To address educational inequities, high-quality SAT tutoring is crucial for students who need
support. Many tutors, however, are novices and require coaching to be effective. To examine …

Prompting as Panacea? A Case Study of In-Context Learning Performance for Qualitative Coding of Classroom Dialog

A Ganesh, C Ch, S D'Mello, M Palmer, K Kann - 2024 - par.nsf.gov
One of the areas where Large Language Models (LLMs) show promise is for automated
qualitative coding, typically framed as a text classification task in natural language …

Revolutionizing teaching economics online with AI: leveraging LLMs for enhanced communication, creativity, and efficiency in education

SD Halliday, JE Tierney - Teaching Economics Online, 2024 - elgaronline.com
In the ever-evolving landscape of technology, Artificial Intelligence (AI) has emerged as a
force for increasing firm productivity (Czarnitzki et al. 2023), exposing jobs to automation …