Outcomes – Differentiation
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 301 - 330 of 673
Detecting Struggling Student Programmers using Proficiency Taxonomies
Noga Schwartz, Roy Fairstein, Avi Segal, Kobi Gal. (08/2025). arXiv. http://arxiv.org/pdf/2508.17353v1
ZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities
Wenhan Dong, Zhen Sun, Yuemeng Zhao, Zifan Peng, Jun Wu, Jingyi Zheng, Yule Liu, Xinlei He*, Yu Wang, Ruiming Wang, Xinyi Huang, Lei Mo*. (08/2025). arXiv. http://arxiv.org/pdf/2508.14377v2
RoboBuddy in the Classroom: Exploring LLM-Powered Social Robots for Storytelling in Learning and Integration Activities
Daniel Tozadore, Nur Ertug, Yasmine Chaker and Mortadha Abderrahim. (08/2025). arXiv. http://arxiv.org/pdf/2508.16706v1
AI-Supported Mini-Labs: Combining Smartphone-Based Experiments and Multimodal AI
Jochen Kuhn, David J. Rakestraw, Stefan Stefan KŸchemann, Patrik Vogt. (08/2025). arXiv. http://arxiv.org/pdf/2508.16320v1
Explainable AI for Predicting and Understanding Mathematics Achievement: A Cross-National Analysis of PISA 2018
Liu Liu, Dai Rui. (08/2025). arXiv. http://arxiv.org/pdf/2508.16747v1
Sociotechnical Imaginaries of ChatGPT in Higher Education: The Evolving Media Discourse
Yinan Sun, Ali Unlu, Aditya Johri. (08/2025). arXiv. http://arxiv.org/pdf/2508.14692v1
Reliable generation of isomorphic physics problems using ChatGPT with prompt-chaining and tool use
Zhongzhou Chen. (08/2025). arXiv. http://arxiv.org/pdf/2508.14755v1
Enabling Multi-Agent Systems as Learning Designers: Applying Learning Sciences to AI Instructional Design
Jiayi Wang, Ruiwei Xiao, Xinying Hou, John Stamper. (08/2025). arXiv. http://arxiv.org/pdf/2508.16659v1
Teaching Introduction to Programming in the Times of AI: A Case Study of a Course Redesign
Nikolaos Avouris, Kyriakos Sgarbas, George Caridakis, Christos Sintoris. (08/2025). arXiv. http://arxiv.org/pdf/2508.06572v2
Cognitive Structure Generation: From Educational Priors to Policy Optimization
Hengnian Gu, Zhifu Chen, Yuxin Chen, Jin Peng Zhou, Dongdai Zhou. (08/2025). arXiv. http://arxiv.org/pdf/2508.12647v1
PAPPL: Personalized AI-Powered Progressive Learning Platform
Shayan Bafandkar, Sungyong Chung, Homa Khosravian, Alireza Talebpour. (08/2025). arXiv. http://arxiv.org/pdf/2508.14109v1
CoGrader: Transforming Instructors' Assessment of Project Reports through Collaborative LLM Integration
Zixin Chen, Jiachen Wang, Yumeng Li, Haobo Li, Chuhan Shi, Rong Zhang, Huamin Qu. (08/2025). arXiv. http://arxiv.org/pdf/2507.20655v2
RPKT: Learning What You Don't Know - Recursive Prerequisite Knowledge Tracing in Conversational AI Tutors for Personalized Learning
Jinwen Tang, Qiming Guo, Zhicheng Tang. (08/2025). arXiv. http://arxiv.org/pdf/2508.11892v1
LEARN: A Story-Driven Layout-to-Image Generation Framework for STEM Instruction
Maoquan Zhang, Bisser Raytchev, Xiujuan Sun. (08/2025). arXiv. http://arxiv.org/pdf/2508.11153v1
From Misunderstandings To Learning Opportunities: Leveraging Generative AI In Discussion Forums To Support Student Learning
Stanislav Pozdniakov, Jonathan Brazil, Oleksandra Poquet, Stephan Krusche, Santiago Berrezueta-Guzman, Shazia Sadiq, Hassan Khosravi. (08/2025). arXiv. http://arxiv.org/pdf/2508.11150v1
Mathematical Computation and Reasoning Errors by Large Language Models
Liang Zhang, Edith Aurora Graf. (08/2025). arXiv. http://arxiv.org/pdf/2508.09932v2
Navigating the New Landscape: A Conceptual Model for Project-Based Assessment (PBA) in the Age of GenAI
Rajan Kadel, Samar Shailendra, Urvashi Rahul Saxena. (08/2025). arXiv. http://arxiv.org/pdf/2508.11709v1
Human-in-the-Loop Systems for Adaptive Learning Using Generative AI
Bhavishya Tarun, Haoze Du, Dinesh Kannan, Dr. Edward F. Gehringer. (08/2025). arXiv. http://arxiv.org/pdf/2508.11062v1
Aryabhata: An exam-focused language model for JEE Math
Ritvik Rastogi, Sachin Dharashivkar, Sandeep Varma. (08/2025). arXiv. http://arxiv.org/pdf/2508.08665v2
From Self-Crafted to Engineered Prompts: Student Evaluations of AI-Generated Feedback in Introductory Physics
Amogh Sirnoorkar, N. Sanjay Rebello. (08/2025). arXiv. http://arxiv.org/pdf/2508.09825v1
Next-Gen Education: Enhancing AI for Microlearning
Saha, S., Rahbari, F., Sadique, F., Velamakanni, S. K. C., Farooque, M., Rothwell, W. J.. (08/2025). arXiv. http://arxiv.org/pdf/2508.11704v1
Designing a Feedback-Driven Decision Support System for Dynamic Student Intervention
Timothy Oluwapelumi Adeyemi, Nadiah Fahad AlOtaibi. (08/2025). arXiv. http://arxiv.org/pdf/2508.07107v2
Securing Educational LLMs: A Generalised Taxonomy of Attacks on LLMs and DREAD Risk Assessment
Farzana Zahid, Anjalika Sewwandi, Lee Brandon, Vimal Kumar, Roopak Sinha. (08/2025). arXiv. http://arxiv.org/pdf/2508.08629v1
CODAE: Adapting Large Language Models for Education via Chain-of-Thought Data Augmentation
Shuzhou Yuan, William LaCroix, Hardik Ghoshal, Ercong Nie, Michael FŠrber. (08/2025). arXiv. http://arxiv.org/pdf/2508.08386v1
Assessing the Quality of AI-Generated Exams: A Large-Scale Field Study
Calvin Isley, Joshua Gilbert, Evangelos Kassos, Michaela Kocher, Allen Nie, Emma Brunskill, Ben Domingue, Jake Hofman, Joscha Legewie, Teddy Svoronos, Charlotte Tuminelli, Sharad Goel. (08/2025). arXiv. http://arxiv.org/pdf/2508.08314v1
A Fuzzy Logic Prompting Framework for Large Language Models in Adaptive and Uncertain Tasks
Vanessa Figueiredo. (08/2025). arXiv. http://arxiv.org/pdf/2508.06754v1
Discerning Minds Or Generic Tutors? Evaluating Instructional Guidance Capabilities In Socratic LLMS
Ying Liu, Can Li, Ting Zhang, Mei Wang, Qiannan Zhu, Jian Li, Hua Huang. (08/2025). arXiv. http://arxiv.org/pdf/2508.06583v1
Beyond Automation: Socratic AI, Epistemic Agency, and the Implications of the Emergence of Orchestrated Multi-Agent Learning Architectures
Peer-Benedikt Degen, Igor Asanov. (08/2025). arXiv. http://arxiv.org/pdf/2508.05116v1
Al Conversational Tutors in Foreign Language Learning: A Mixed-Methods Evaluation Study
Nikolaos Avouris. (08/2025). arXiv. http://arxiv.org/pdf/2508.05156v1
InqEduAgent: Adaptive AI Learning Partners with Gaussian Process Augmentation
Tian-Fang Zhao, Wen-Xi Yang, Guan Liu, Liang Yang. (08/2025). arXiv. http://arxiv.org/pdf/2508.03174v2
