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Descriptive – Product Development
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 61 - 90 of 553
Towards Socraticode: Designing A Generative AI-Based Programming Tutor For K-12 Students Through A 4-Week Participatory Design Study
Cassandra Lucas, Anshul Bihani, Rohini Kukka, Chun-Hua Tsai, Jaydeb Sarker, Mia Mohammad Imran. (05/2026). arXiv. https://arxiv.org/abs/2605.17857v1
Beyond Model Readiness: Institutional Readiness For AI Deployment In Public Systems
Erika Fille Legara, Elmo Domino Jose, Paula Joy Martinez. (05/2026). arXiv. https://arxiv.org/abs/2605.17203v1
Promptdecipher: Supporting AI Tutor Authoring Through Editable Simulated Interactions
Miina Koyama, Ruiwei Xiao, John Stamper. (05/2026). arXiv. https://arxiv.org/abs/2605.16605v1
Adesua: Development And Feasibility Study Of An AI Whatsapp Bot For Science Learning In West Africa
George Boateng, Evans Atompoya, Philemon Badu, Samuel John, Samuel Ansah, Patrick Agyeman-Budu, and Victor Kumbol. (05/2026). arXiv. https://arxiv.org/abs/2605.15376v1
Mapping AI Programs In The U.S: A Status Report From Early 2026 And An Analysis Of AI Majors And Minors
Felix Muzny, Carolyn Jones, Carter Ithier, Hasnain Sikora, Hrutika Harshadbhai Patel, Carla E. Brodley. (05/2026). arXiv. https://arxiv.org/abs/2606.12428v1
Sycophancy Is An Educational Safety Risk: Why LLM Tutors Need Sycophancy Benchmarks
Enkelejda Kasneci, Gjergji Kasneci. (05/2026). arXiv. https://arxiv.org/abs/2605.14604v1
Agentic AI Ecosystems In Higher Education: A Perspective On AI Agents To Emerging Inclusive, Agentic Multi-Agent AI Framework For Learning, Teaching And Institutional Intelligence
Vidya K Sudarshan, Anushka Sisodia, Reshma A Ramachandra, Batra Sia, Josephine Chong Leng Leng. (05/2026). arXiv. https://arxiv.org/abs/2605.14266v1
Roboblockly Studio: Conversational Block Programming With Embodied Robot Feedback For Computational Thinking
Leyi Li, Chenyu Du, Jiafei Sun, Erick Purwanto, Qing Zhang. (05/2026). arXiv. https://arxiv.org/abs/2605.12059v1
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
An Explainable AI Assistant For Introductory Programming Education: Improving Feedback Reliability With Instructor-AI Collaboration
Muntasir Hoq, Griffin Pitts, Bradford Mott, Seung Lee, Jessica Vandenberg, Shuyin Jiao, Narges Norouzi, James Lester, and Bita Akram. (05/2026). arXiv. https://arxiv.org/abs/2606.12425v1
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 ‚àö√Ölvarez, Jorge Fernandez-Herrero, Diego Viejo, Rosabel Roig-Vila, Miguel Cazorla. (05/2026). arXiv. https://arxiv.org/abs/2502.20209v3
When Should Teachers Control AI Generation For Mathematics Visuals?
Zhengxu Li, Junling Wang, April Yi Wang. (05/2026). arXiv. https://arxiv.org/abs/2605.10672v1
First, Do No Harm: AI Supervisor Scaffolds Novice Growth In Counselor Education
Chen Xu, Zhenyu Lyu, Tian Lan, Yang Yi, Yu Ji, Luyao 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
Preparing Students For AI-Powered Materials Discovery: A Workflow-Aligned Framework For AI Literacy, Equity, And Scientific Judgment
Dongming Mei, Katherine Moore, Ben Sayler. (05/2026). arXiv. https://arxiv.org/abs/2605.09624v1
AI Expert Twin: Capturing Expert Cognition For Human-Centred, Practice-Based Learning
Annie Yuan, Xiaohua Chen, Kalina Yacef, Judy Kay. (05/2026). arXiv. https://arxiv.org/abs/2605.01401v2
Who Decides In AI-Mediated Learning?: The Agency Allocation Framework
Conrad Borchers, Olga Viberg, René F. Kizilcec. (05/2026). arXiv. https://arxiv.org/abs/2604.13534v2
Taklif.AI: LLM-Powered Platform For Interest-Based Personalized College Assignments
Zaki Kurdya, Mohammed Zuqlam, Salem Amassi, Shady Telbany, Motaz Saad. (05/2026). arXiv. https://arxiv.org/abs/2605.05842v1
From Surface Learning To Deep Understanding: A Grounded AI Tutoring System For Moodle
Anna Ostrowska, Michał Kukla, Gabriela Majstrak, Jan Opala, Sebastian Pergała, Jan Skwarek, Anna Wroblewska ´. (05/2026). arXiv. https://arxiv.org/abs/2605.06963v1
Who Designs The Designer? Behavioural Architecture For Genai In Education
Sepinoud Azimi. (05/2026). arXiv. https://arxiv.org/abs/2606.12416v1
The Pedagogy Of AI Mistakes: Fostering Higher-Order Thinking
Hadi Hosseini. (05/2026). arXiv. https://arxiv.org/abs/2605.05472v1
Alcofe: Implementation And Deployment Of An AI-Based Collaborative Feedback System For Higher Education
Alvaro Becerra, Alejandra Palma, Ruth Cobos. (05/2026). arXiv. https://arxiv.org/abs/2605.04740v1
Cognitive Twins: Investigating Personalized Thinking Model Building And Its Performance Enhancement With Human-In-The-Loop
Wu-Yuin Hwang, Nur Alif Ilyasa, Muhammad Irfan Luthfi, and Yuniar Indrihapsari. (05/2026). arXiv. https://arxiv.org/abs/2605.04761v1
Aissa: Implementation And Deployment Of An AI-Based Student Slides Analysis Tool For Academic Presentations
Alvaro Becerra, Diego Gomez and Ruth Cobos. (05/2026). arXiv. https://arxiv.org/abs/2605.04729v1
Lata: A Drop-In, Ferpa-Compliant Local-LLM Autograder For Upper-Division STEM Coursework
Jesse A. Rodríguez. (05/2026). arXiv. https://arxiv.org/abs/2605.05410v1
Dramaturgies Of Deception: AI Humanizers And The Performance Of Legitimacy In Higher Education Assessment: A Preprint
Jasper Roe, Mike Perkins, Peter Bannister, Leon Furze, James Wood. (05/2026). arXiv. https://arxiv.org/abs/2605.02649v1
Math Education Digital Shadows For Facilitating Learning With LLMs: Math Performance, Anxiety And Confidence In Simulated Students And Ais
Naomi Esposito, Anthony Tricarico, Luisa Porzio, Ali Aghazadeh Ardebili, and Massimo Stella. (04/2026). arXiv. https://arxiv.org/abs/2604.27618v1
What Don'T You Understand? Using Large Language Models To Identify And Characterize Student Misconceptions About Challenging Topics
Michael J. Parker, María G. Zavala-Cerna. (04/2026). arXiv. https://arxiv.org/abs/2605.00294v1
