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Post-Secondary
Research synthesis is AI-generated, human reviewed. Updated 05/2026.
Displaying 721 - 750 of 1108
Teaching at Scale: Leveraging AI to Evaluate and Elevate Engineering Education
J.-F. Chamberland, M. Carlisle, A. Jayaraman, K. R. Narayanan, S. Palsole, K. Watson. (08/2025). arXiv. http://arxiv.org/pdf/2508.02731v1
Automated Feedback on Student-Generated UML and ER Diagrams Using Large Language Models
Sebastian GŸrtl, Gloria Schimetta, David Kerschbaumer, Michael Liut, Alexander Steinmaurer. (07/2025). arXiv. http://arxiv.org/pdf/2507.23470v1
A ChatGPT-Based Approach For Questions Generation In Higher Education
Sinh Trong Vu, Huong Thu Truong, Oanh Tien Do, Tu Anh Le, Tai Tan Mai. (07/2025). arXiv. http://arxiv.org/pdf/2507.21174v2
Watermark in the Classroom: A Conformal Framework for Adaptive AI Usage Detection
Yangxinyu Xie, Xuyang Chen, Zhimei Ren, Weijie J. Su. (07/2025). arXiv. http://arxiv.org/pdf/2507.23113v1
AI Literacy as a Key Driver of User Experience in AI-Powered Assessment: Insights from Socratic Mind
Meryem Yilmaz Soylu, Jeonghyun Lee, Jui-Tse Hung, Christopher Zhang Cui, David A. Joyner. (07/2025). arXiv. http://arxiv.org/pdf/2507.21654v1
Decoding Instructional Dialogue: Human-AI Collaborative Analysis of Teacher Use of AI Tool at Scale
Alex Liu, Lief Esbenshade, Shawon Sarkar, Victor Tian, Zachary Zhang, Kevin He, Min Sun. (07/2025). arXiv. http://arxiv.org/pdf/2507.17985v2
A Comprehensive Review of AI-based Intelligent Tutoring Systems: Applications and Challenges
Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui. (07/2025). arXiv. http://arxiv.org/pdf/2507.18882v1
Students' Feedback Requests and Interactions with the SCRIPT Chatbot: Do They Get What They Ask For?
Andreas Scholl, Natalie Kiesler. (07/2025). arXiv. http://arxiv.org/pdf/2507.17258v1
Designing for Learning with Generative AI is a Wicked Problem: An Illustrative Longitudinal Qualitative Case Series
Clara Scalzer, Saurav Pokhrel, Sara Hunt, Greg L Nelson. (07/2025). arXiv. http://arxiv.org/pdf/2507.17230v1
AI, Expert or Peer? Examining the Impact of Perceived Feedback Source on Pre-Service Teachers Feedback Perception and Uptake
Lucas Jasper Jacobsen, Ute Mertens, Thorben Jansen, Kira Elena Weber. (07/2025). arXiv. http://arxiv.org/pdf/2507.16013v1
AI + LEARNING DIFFERENCES: Designing a Future with No Boundaries
Nneka J. McGee, Elizabeth Kozleski, Christopher J. Lemons, Isabelle C. Hau. (07/2025). Stanford Accelerator for Learning. https://acceleratelearning.stanford.edu/app/uploads/2025/07/AI-Learning-Differe…
EduThink4AI: Translating Educational Critical Thinking into Multi-Agent LLM Systems
Xinmeng Hou, Zhouquan Lu, Wenli Chen, Hai Hu, Qing Guo. (07/2025). arXiv. http://arxiv.org/pdf/2507.15015v1
LEKIA: A Framework for Architectural Alignment via Expert Knowledge Injection
Boning Zhao, Yutong Hu. (07/2025). arXiv. http://arxiv.org/pdf/2507.14944v1
Using LLMs to identify features of personal and professional skills in an open-response situational judgment test
Cole Walsh, Rodica Ivan, Muhammad Zafar Iqbal, Colleen Robb. (07/2025). arXiv. http://arxiv.org/pdf/2507.13881v1
Findings of MEGA: Maths Explanation with LLMs using the Socratic Method for Active Learning
Tosin Adewumi, Foteini Simistira Liwicki, Marcus Liwicki, Viktor Gardelli, Lama Alkhaled, Hamam Mokayed. (07/2025). arXiv. http://arxiv.org/pdf/2507.12079v1
AI-Powered Math Tutoring: Platform for Personalized and Adaptive Education
Jaros_aw A. Chudziak, Adam Kostka. (07/2025). arXiv. http://arxiv.org/pdf/2507.12484v1
Natural Language-based Assessment of L2 Oral Proficiency using LLMs
Stefano Banno, Rao Ma, Mengjie Qian, Siyuan Tang, Kate Knill, Mark Gales. (07/2025). arXiv. http://arxiv.org/pdf/2507.10200v1
SentiDrop: A Multi-Modal Machine Learning model for Predicting Dropout in Distance Learning
Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui. (07/2025). arXiv. http://arxiv.org/pdf/2507.10421v1
On the development of an AI performance and behavioural measures for teaching and classroom management
Andreea I.Niculescu, Jochen Ehnes, Chen Yi, Du Jiawei, Tay Chiat Pin, Joey Tianyi Zhou, Vigneshwaran Subbaraju, Teh Kah Kuan, Tran Huy Dat, Gi Soong Chee, Kenneth Kwok. (07/2025). arXiv. http://arxiv.org/pdf/2506.11143v2
Beyond Classical And Contemporary Models: A Transformative Ai Framework For Student Dropout Prediction In Distance Learning Using RAG, Prompt Engineering, And Cross-Modal Fusion
Miloud Mihoubi, Meriem Zerkouk, Belkacem Chikhaoui. (07/2025). arXiv. http://arxiv.org/pdf/2507.05285v2
Enhancing Essay Cohesion Assessment: A Novel Item Response Theory Approach
Bruno Alexandre Rosa, Hil‡rio Oliveira, Luiz Rodrigues, Eduardo Araujo Oliveira, Rafael Ferreira Mello. (07/2025). arXiv. http://arxiv.org/pdf/2507.08487v1
Findings of the BEA 2025 Shared Task on Pedagogical Ability Assessment of AI-powered Tutors
Ekaterina Kochmar, Kaushal Kumar Maurya, Kseniia Petukhova, KV Aditya Srivatsa, Ana¯s Tack, Justin Vasselli. (07/2025). arXiv. http://arxiv.org/pdf/2507.10579v1
Short-Term Gains, Long-Term Gaps: The Impact Of GenAI and Search Technologies On Retention
Mahir Akgun, Sacip Toker. (07/2025). arXiv. http://arxiv.org/pdf/2507.07357v1
Do AI tutors empower or enslave learners? Toward a critical use of AI in education
Lucile Favero, Juan Antonio PŽrez-Ortiz, Tanja K‡sser and Nuria Oliver. (07/2025). arXiv. http://arxiv.org/pdf/2507.06878v1
Assessing the Prevalence of AI-assisted Cheating in Programming Courses: A Pilot Study
KalŽu Delphino. (07/2025). arXiv. http://arxiv.org/pdf/2507.06438v1
Creating a customisable freely-accessible Socratic AI physics tutor
Eugenio Tufino, Bor Gregorcic. (07/2025). arXiv. http://arxiv.org/pdf/2507.05795v1
Conversational Education at Scale: A Multi-LLM Agent Workflow for Procedural Learning and Pedagogic Quality Assessment
Jiahuan Pei, Fanghua Ye, Xin Sun, Wentao Deng, Koen Hindriks, Junxiao Wang. (07/2025). arXiv. http://arxiv.org/pdf/2507.05528v1
AGACCI : Affiliated Grading Agents for Criteria-Centric Interface in Educational Coding Contexts
Kwangsuk Park, Jiwoong Yang. (07/2025). arXiv. http://arxiv.org/pdf/2507.05321v1
Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools
Lorenzo Lee Solano, Charles Koutcheme, Juho Leinonen, Alexandra Vassar, Jake Renzella. (07/2025). arXiv. http://arxiv.org/pdf/2507.05305v1
