Machine learning / AI

Studies tagged with AI from their full text or abstract; see each study for details.

Showing 31 - 60 of 347 studies

Context-Aware Prediction Of Student Quiz Performance With Multimodal Textbook Features

Samin Khan. (05/2026). arXiv. https://arxiv.org/abs/2606.24770v1
Access Timing As Scaffolding: A Reinforcement Learning Approach To Genai In Education

Janne Rotter, Pau Benazet i Montobbio, Davinia Hernandez-Leo. (05/2026). arXiv. https://arxiv.org/abs/2605.15850v2
Prediction Model Of Motivators And Demotivators Of Integrating Large Language Models In Software Engineering Education: An Empirical Study

Maryam Khan, Muhammad Azeem Akbar, Jussi Kasurinen, Estefanía Martín-Barroso. (05/2026). arXiv. https://arxiv.org/abs/2605.09393v3
ChatGPT Vs Teachers Vs Students: Large-Scale Analysis Of Generative AI Discourse In Education Communities On Reddit

Pelin Yuce, Xiangruo Dai, Rebecca Owens, Tugrulcan Elmas. (05/2026). arXiv. https://arxiv.org/abs/2605.17712v1
Simulating Students Or Sycophantic Problem Solving? On Misconception Faithfulness Of LLM Simulators

Heejin Do, Shashank Sonkar, Mrinmaya Sachan. (05/2026). arXiv. https://arxiv.org/abs/2605.12748v1
Generative AI For Visualizing Highway Construction Hazards Through Synthetic Images And Temporal Sequences

Trevor Neece, Mason Smetana, and Lev Khazanovich. (05/2026). arXiv. https://arxiv.org/abs/2605.11276v1
Dipser: A Dataset For In-Person Student Engagement Recognition In The Wild

Luis Marquez-Carpintero, Sergio Suescun-Ferrandiz, Carolina Lorenzo Álvarez, Jorge Fernandez-Herrero, Diego Viejo, Rosabel Roig-Vila, Miguel Cazorla. (05/2026). arXiv. https://arxiv.org/abs/2502.20209v3
First, Do No Harm: AI Supervisor Scaffolds Novice Growth In Counselor Education

Chen Xu, Zhenyu Lyu, Tian Lan, Yang Yi, Yu Ji, Yu Ji, Jian Shen, Zhihua Wang, Leyang Cui, Jieshuo Zhang, Xiaohua Wan, Qunxi Dong, Minqiang Yang, Juan Wang, Xiuling Liu, Bin Hu. (05/2026). arXiv. https://arxiv.org/abs/2508.09042v3
Can Providing Feedback On Gaze And Mental-Effort Synchrony Improve Pair Programming Performance?

Anahita Golrang, Kshitij Sharma. (05/2026). arXiv. https://arxiv.org/abs/2605.05836v1
Automatic Reflection Level Classification In Hungarian Student Essays

Zsolt Csibi, Kristian Fenech, Mónika Sándor, Mónika Serfőző, Kinga Gyöngy. (05/2026). arXiv. https://arxiv.org/abs/2605.02402v1
Pedagogical Promise And Peril Of AI: A Text Mining Analysis Of ChatGPT Research Discussions In Programming Education

Juvy Cruz Grume, John Paul P. Miranda, Aileen P. De Leon, Jordan Lansang Salenga, Hilene E. Hernandez, Mark Anthony A. Castro, Vernon Grace M. Maniago, Joel D. Canlas, Joel B. Quiambao. (05/2026). arXiv. https://arxiv.org/abs/2605.00361v1
From Test-Taking To Cognitive Scaffolding: A Pedagogical Diagnostic Benchmark For LLMs On English Standardized Tests

Luoxi Tang, Tharunya Sundar, Yuqiao Meng, Shuai Yang, Ankita Patra, Lakshmi Manohar Chippada, Jiqian Zhao, Yi Li, Weicheng Ma, Zhaohan Xi. (04/2026). arXiv. https://arxiv.org/abs/2505.17056v2
Your Students Don't Use LLMs Like You Wish They Did

Sebastian Kobler, Matthew Clemson, Angela Sun, Jonathan K. Kummerfeld. (04/2026). arXiv. https://arxiv.org/abs/2604.23486v1
Applications Of The Transformer Architecture In AI-Assisted English Reading Comprehension

Ping Li. (04/2026). arXiv. https://arxiv.org/abs/2604.23615v1
Artificial Intelligence As A Real Game To Enlighten Science Education For Disabled Students In Rural New Mexico

Nelson Uloma Egondu, Gil Gallegos. (04/2026). arXiv. https://arxiv.org/abs/2606.00034v1
Arguagent: AI-Supported Real-Time Grouping For Productive Argumentation In STEM Classrooms

Jennifer Kleiman, Yizhu Gao, Xin Xia, Zhaoji Wang, Zipei Zhu, Jongchan Park, Xiaoming Zhai. (04/2026). arXiv. https://arxiv.org/abs/2604.23449v1
Pedagogical Safety In Educational Reinforcement Learning: Formalizing And Detecting Reward Hacking In AI Tutoring Systems

Oluseyi Olukola, Nick Rahimi. (04/2026). arXiv. https://arxiv.org/abs/2604.04237v1
Evaluating Vision-Language And Large Language Models For Automated Student Assessment In Indonesian Classrooms

Nurul Aisyah, Muhammad Dehan Al Kautsar, Arif Hidayat, Raqib Chowdhury, Fajri Koto. (04/2026). arXiv. https://arxiv.org/abs/2506.04822v3
Understanding Teacher Revisions Of Large Language Model-Generated Feedback

Conrad Borchers, Luiz Rodrigues, Newarney Torrezao da Costa, Cleon Xavier, Rafael Ferreira Mello. (03/2026). arXiv. https://arxiv.org/abs/2603.27806v1
From Slides To Chatbots: Enhancing Large Language Models With University Course Materials

Tu Anh Dinh, Philipp Nicolas Schumacher, Jan Niehues. (03/2026). arXiv. https://arxiv.org/abs/2510.22272v2
Criterion-Referenceability Determines LLM-As-A-Judge Validity Across Physics Assessment Formats

Will Yeadon, Tom Hardy, Paul Mackay, and Elise Agra. (03/2026). arXiv. https://arxiv.org/abs/2603.14732v1
Effective Personalized AI Tutors Via Llm-Guided Reinforcement Learning

Angel Tsai-Hsuan Chung, Botong Zhang, Ling-Chieh Kung, Hamsa Bastani, Osbert Bastani. (03/2026). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6423358
Scalable Classification Of Course Information Sheets Using Large Language Models: A Reusable Institutional Method For Academic Quality Assurance

Brecht Verbeken, Joke Van den Broeck, Inge De Cleyn, Steven Van Luchene, Nadine Engels, Andres Algaba, Vincent Ginis. (03/2026). arXiv. https://arxiv.org/abs/2603.13562v1
Heal: Hindsight Entropy-Assisted Learning For Reasoning Distillation

Wenjing Zhang, Jiangze Yan, Jieyun Huang, Yi Shen, Shuming Shi, Ping Chen, Ning Wang, Zhaoxiang Liu, Kai Wang, Shiguo Lian. (03/2026). arXiv. https://arxiv.org/abs/2603.10359v1
The Studychat Dataset: Analyzing Student Dialogues With Chatgpt In An Artificial Intelligence Course

Hunter McNichols, Fareya Ikram, Andrew Lan. (03/2026). arXiv. https://arxiv.org/pdf/2503.07928v4
Prefdisco: Benchmarking Proactive Personalized Reasoning

Shuyue Stella Li, Avinandan Bose, Faeze Brahman, Simon Shaolei Du, Pang Wei Koh, Maryam Fazel, Yulia Tsvetkov. (03/2026). arXiv. https://arxiv.org/pdf/2510.00177v2
Chatbot Conversations In Physics Education: Using Artificial Intelligence To Analyze Student Reasoning Through Computational Grounded Theory

Atharva Dange, Ramón López. (03/2026). arXiv. https://arxiv.org/pdf/2603.04616v1
When Shallow Wins: Silent Failures And The Depth-Accuracy Paradox In Latent Reasoning

Subramanyam Sahoo, Aman Chadha, Vinija Jain, Divya Chaudhary. (03/2026). arXiv. https://arxiv.org/pdf/2603.03475v1
Faster, Cheaper, More Accurate: Specialised Knowledge Tracing Models Outperform Llms

Prarthana Bhattacharyya, Joshua Mitton, Simon Woodhead, Ralph Abboud. (03/2026). arXiv. https://arxiv.org/pdf/2603.02830v1
Uniskill: A Dataset For Matching University Curricula To Professional Competencies

Nurlan Musazade, Joszef Mezei, Mike Zhang. (03/2026). arXiv. https://arxiv.org/pdf/2603.03134v1