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Outcomes – Differentiation
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 1 - 30 of 822
Calibrating LLM Tutor Initiation to Learner Expertise: Proactive and Reactive Support for Computational Thinking
Arun Rai, Liwei Chen, Balasubramaniam Ramesh, Cynthia Breazeal, Yuan Long, Benjamin M. Ampel, Andrea Aria. (11/2026). SSRN. https://bampel.com/uploads/calibrating-llm-tutor-initiation.pdf
Not Faster, But Better: Generative AI And Teacher Skill In Peru
Carla Z. Glave, Carolina Lopez, Ezequiel Molina, Roman Andres Zarate. (10/2026). World Bank. http://documents.worldbank.org/curated/en/099309210012625906
Teacher-Mediated Multimodal Platform And Math Achievement: Evidence From Goblins' Yearlong District Implementation
Anika Alam, Nicolas Dominguez-Mel, Jing Liu. (10/2026). EdWorking Papers. https://edworkingpapers.com/ai26-1611
The Effects Of Course-Integrated AI Tutoring On Student Performance And Engagement: A Randomized University Trial
Jing Liu, Tracy Sweet, Marty Haoyuan Chen, Jonathan Engelberg, Megan C. Masters, Martyn Clark, Axel Persaud, Alia Lancaster, Jeffrey K. Hollingsworth, Jennifer King Rice. (10/2026). EdWorking Papers. https://edworkingpapers.com/ai26-1598
How University Disability Services Professionals Write Image Descriptions For Hci Figures Using Generative AI
Muhammad Raees, Yugo Iwamoto, Konstantinos Papangelis, Jamison Heard, Garreth W. Tigwell. (09/2026). arXiv. https://arxiv.org/abs/2602.08937v2
When Evaluators Cry Wolf: Lessons From Production LLM-As-Judge Evaluation In Educational AI
Chris Rohlfs, Rodrigo Vergara Bosse, Priscilla Rain Hopper, Keanon O'Keefe, Patrick Russell. (09/2026). arXiv. https://arxiv.org/abs/2609.28478v2
Fairness Theatre: Evaluating Post-Hoc Fairness Interventions In Vendor-Controlled Early Warning Systems
Kelly McConvey, Angelina Zhai, Rebecca Li, Shion Guha. (09/2026). arXiv. https://arxiv.org/abs/2609.38552v1
Critical Thinking With Generative AI: A Constraint-First Design Pilot Of A Thinking-Partner Intervention
Fatima Tuz Zahra, Jiangen He, David M. Bowers, Wei Wang. (09/2026). arXiv. https://arxiv.org/abs/2609.38029v1
Characterizing LLM-Based Family Education Through The Lens Of Activity Theory: A Scoping Review Of The Hci Literature
Lan Luo, Yuqi Liang, Jie Cai, Anqi Wang, Dongyijie Primo Pan, Muzhi Zhou, Chun Yu, Pan Hui. (09/2026). arXiv. https://arxiv.org/abs/2609.28886v1
Judgment-Centred Software Engineering Education: A Post-Hype Review And Framework For AI-Augmented Learning
Qusay H. Mahmoud. (09/2026). arXiv. https://arxiv.org/abs/2609.29473v1
Studentbench: AI And Human Tutoring Yield Equivalent Gre Learning Gains
Curtis Northcutt, Inaara Hasmani, Kevin Feng, Trevor Khangi, Andreas Plesner, Jonas Mueller. (09/2026). arXiv. https://arxiv.org/abs/2609.28470?utm_source=chatgpt.com
"We'Ll Fix It Later": Education, AI, And The Deferral Of Privacy In EdTech
Meghna Manoj Nair, Rachel Greenstadt. (09/2026). arXiv. https://arxiv.org/abs/2609.28137v1
AI-Assisted Social Story Intervention For Special Education: The Design Of Adapted Stories
Buyankhishig Enkhjargal, Himanshi Lalwani, Hanan Salam. (09/2026). arXiv. https://arxiv.org/abs/2609.24245v1
From Content Generation To Learning Support: Pedagogy-Guided Generative Video Tutors For STEM Learning
Xinchen Ma, Shuimu Wang, Gaole He, Yanbin Zhang, Chunyang Wang, Yunshi Lan, Weining Qian. (09/2026). arXiv. https://arxiv.org/abs/2609.24083v1
When AI Tutors Speak: Evidence From A Randomized Field Experiment
Shihao Yang, Marshall Van Alstyne, Chrysanthos Dellarocas. (09/2026). arXiv. https://arxiv.org/abs/2609.23958v1
A Course Intelligence Platform For Higher Education: Lessons From AI-Assisted Course Evaluation
Bo Yuan, Jiazi Hu, Haimei Zhao. (09/2026). arXiv. https://arxiv.org/abs/2411.02455v3
Instructional Objectives Completed And Skill-Specific Early Reading Growth In A Digital Reading Tutor
Nicholas A. Gage. (09/2026). EdArXiv. https://osf.io/preprints/edarxiv/47pzq_v1
Dose, Not Access: Digital Reading Tutor Use And Early Reading Growth
Nicholas A. Gage. (09/2026). EdArXiv. https://osf.io/preprints/edarxiv/4a6sk_v1
Artificial Intelligence Driven Physics Assignments Using Context Prompts
Miguel Rodriguez, Peter Wulff. (09/2026). arXiv. https://arxiv.org/abs/2609.22578v1
The Role Of Implicit And Explicit Demographic Signals In Large Language Model-Based Student Assessment
Donya Rooein, Luca Benedetto, Dirk Hovy. (09/2026). arXiv. https://arxiv.org/abs/2609.16993v1
Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study On Cooking Recipes
Paola Mejia-Domenzain, Jibril Frej, Seyed Parsa Neshaei, Luca Mouchel, Tanya Nazaretsky, Thiemo Wambsganss, Antoine Bosselut, Tanja Kaser. (09/2026). arXiv. https://arxiv.org/abs/2609.17118v1
Evaluating AI Tutoring At The Speed Of Innovation: Practitioner-Led Micro-Randomised Trials Of An AI Tutoring Platform In Gcse Science
Wayne Harrison, Rahil Khowaja, Emma Dobson, Germaine Uwimpuhwe, Steve Higgins. (09/2026). arXiv. https://arxiv.org/abs/2609.14789v1
Generative AI Assisted Workflows In Architectural Conceptual Design: Performance, Creative Self-Efficacy, And Cognitive Load
Yao Xiao, Han Jiang, Rachel Hurley, Shichao Liu. (09/2026). arXiv. https://arxiv.org/abs/2601.10696v2
An Emancipatory Vision For Designing (Generative) AI For Learner Flourishing
Luis P. Prieto, Yannis Dimitriadis. (09/2026). arXiv. https://arxiv.org/abs/2609.07715v1
Flawed But Memorable: Student Critical Reception Of Interest-Personalized Genai Analogies In Computing Education
Seth Bernstein, Naaz Sibia. (09/2026). arXiv. https://arxiv.org/abs/2609.06095v1
From Misconceptions To Evidence: What Science Teachers Make Visible When Co-Designing Agentic Learning Apps
Nizam Kadir, Liow Wei Ting, Sumbul Khan, Ang Lay Kee. (09/2026). arXiv. https://arxiv.org/abs/2609.03917v1
A Prompt-Engineering Approach To Develop Scalable, Flexible, And Real-Time Hybrid Micro-Level Personalization In A General Purpose AI Teaching Assistant
Saptarshi Basu, Sandeep Kakar, Ashok Goel. (09/2026). arXiv. https://arxiv.org/abs/2609.03402v1
Beyond Helpfulness: A Teaching-Over-Solving Diagnostic For Measuring Educational Impact In LLM Tutors
Junyi Yao, Zihao Zheng, Baichuan Li. (08/2026). arXiv. https://arxiv.org/abs/2606.16206v2
Learning To Prompt: Improving Student Engagement With Adaptive LLM-Based High-School Tutoring
Po-Chin Chang, Nicholas Hogan, Aske Plaat, Michiel T. van der Meer. (08/2026). arXiv. https://arxiv.org/abs/2606.20138v2
