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Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 61 - 90 of 195
Analyzing Undergraduate Problem-Solving in Physics Through Interaction With an AI Chatbot
Syed Furqan Abbas Hashmi, N. Sanjay Rebello. (08/2025). arXiv. http://arxiv.org/pdf/2508.14778v1
PAPPL: Personalized AI-Powered Progressive Learning Platform
Shayan Bafandkar, Sungyong Chung, Homa Khosravian, Alireza Talebpour. (08/2025). arXiv. http://arxiv.org/pdf/2508.14109v1
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
Exploring the Application of Visual Question Answering (VQA) for Classroom Activity Monitoring
Sinh Trong Vu, Hieu Trung Pham, Dung Manh Nguyen, Hieu Minh Hoang, Nhu Hoang Le, Thu Ha Pham, Tai Tan Mai. (08/2025). arXiv. http://arxiv.org/pdf/2507.22369v2
The Boiling-Frog Problem of Physics Education
Gerd Kortemeyer. (08/2025). arXiv. http://arxiv.org/pdf/2508.08842v1
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
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
Dean of LLM Tutors: Exploring Comprehensive and Automated Evaluation of LLM-generated Educational Feedback via LLM Feedback Evaluators
Keyang Qian, Yixin Cheng, Rui Guan, Wei Dai, Flora Jin, Kaixun Yang, Sadia Nawaz, Zachari Swiecki, Guanliang Chen, Lixiang Yan, Dragan Ga_evic. (08/2025). arXiv. http://arxiv.org/pdf/2508.05952v1
Learning in Focus: Detecting Behavioral and Collaborative Engagement Using Vision Transformers
Sindhuja Penchala, Saketh Reddy Kontham, Prachi Bhattacharjee, Sareh Karami, Mehdi Ghahremani, Noorbakhsh Amiri Golilarz, Shahram Rahimi. (08/2025). arXiv. http://arxiv.org/pdf/2508.15782v1
A Mixed User-Centered Approach to Enable Augmented Intelligence in Intelligent Tutoring Systems: The Case of MathAlde app
Guilherme Guerino, Luiz Rodrigues, Luana Bianchini, Mariana Alves, Marcelo Marinho, Thomaz Veloso, Valmir Macario, Diego Dermeval, Thales Vieira, Ig Bittencourt, Seiji Isotani. (08/2025). arXiv. http://arxiv.org/pdf/2508.00103v2
Explainable AI and Machine Learning for Exam-based Student Evaluation: Causal and Predictive Analysis of Socio-academic and Economic Factors
Bushra Akter, Md Biplob Hosen, Sabbir Ahmed, Mehrin Anannya, Md. Farhad Hossain. (08/2025). arXiv. http://arxiv.org/pdf/2508.00785v1
Transparent Adaptive Learning via Data-Centric Multimodal Explainable AI
MARYAM MOSLEH, MARIE DEVLIN, ELLIS SOLAIMAN. (08/2025). arXiv. http://arxiv.org/pdf/2508.00665v1
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 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
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…
Bridging MOOCs, Smart Teaching, and AI: A Decade of Evolution Toward a Unified Pedagogy
Bo Yuan, Jiazi Hu. (07/2025). arXiv. http://arxiv.org/pdf/2507.14266v1
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
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
Exploring LLMs for Predicting Tutor Strategy and Student Outcomes in Dialogues
Fareya Ikram, Alexander Scarlatos, Andrew Lan. (07/2025). arXiv. http://arxiv.org/pdf/2507.06910v1
Detection of Disengagement from Voluntary Quizzes: An Explainable Machine Learning Approach in Higher Distance Education
Behnam Parsaeifard, Christof Imhof, Tansu Pancar, Ioan-Sorin Comsa, Martin Hlosta, Nicole Bergamin and Per Bergamin. (07/2025). arXiv. http://arxiv.org/pdf/2507.02681v2
Autonomous AI Surveillance: Multimodal Deep Learning for Cognitive and Behavioral Monitoring
Ameer Hamza, Zuhaib Hussain But, Umar Arif, Samiya, M. Abdullah Asad, Muhammad Naeem. (07/2025). arXiv. http://arxiv.org/pdf/2507.01590v1
Research on Comprehensive Classroom Evaluation System Based on Multiple AI Models
Xie Cong, Yang Li, Wang Daben, Xiao Jing. (06/2025). arXiv. http://arxiv.org/pdf/2506.23079v1
Detecting LLM-Generated Short Answers and Effects on Learner Performance
Shambhavi Bhushan, Danielle R. Thomas, Conrad Borchers, Isha Raghuvanshi, Ralph Abboud, Erin Gatz, Shivang Gupta, Kenneth R. Koedinger. (06/2025). arXiv. http://arxiv.org/pdf/2506.17196v1
Feeling Machines: Ethics, Culture, and the Rise of Emotional AI
Vivek Chavan, Arsen Cenaj, Shuyuan Shen, Ariane Bar, Srishti Binwani, Tommaso Del Becaro, Marius Funk, Lynn Greschner, Roberto Hung, Stina Klein, Romina Kleiner, Stefanie Krause, Sylwia Olbrych, Vishvapalsinhji Parmar, Jaleh Sarafraz, Daria Soroko, Daksitha Withanage Don, Chang Zhou, Hoang Thuy Duong Vu, Parastoo Semnani, Daniel Weinhardt, Elisabeth Andre, Jorg Kruger, Xavier Fresquet. (06/2025). arXiv. http://arxiv.org/pdf/2506.12437v1
RETUYT-INCO at BEA 2025 Shared Task: How Far Can Lightweight Models Go in AI-powered Tutor Evaluation?
Santiago G—ngora, Ignacio Sastre, Santiago Robaina, Ignacio Remersaro, Luis Chiruzzo, Aiala Ros‡. (06/2025). arXiv. http://arxiv.org/pdf/2506.11243v1
Combining Log Data and Collaborative Dialogue Features to Predict Project Quality in Middle School AI Education
Conrad Borchers, Xiaoyi Tian, Kristy Elizabeth Boyer, Maya Israel. (06/2025). arXiv. http://arxiv.org/pdf/2506.11326v1
Exploring Effective Strategies for Building a Customised GPT Agent for Coding Classroom Dialogues
Luwei Bai, Dongkeun Han, Sara Hennessy. (06/2025). arXiv. http://arxiv.org/pdf/2506.07194v1
Sentiment Analysis in Learning Management Systems Understanding Student Feedback at Scale
Mohammed Almatauri. (06/2025). arXiv. http://arxiv.org/pdf/2506.05490v1
