Technical – Computational
Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 301 - 330 of 577
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
SimStep: Chain-of-Abstractions for Incremental Specification and Debugging of AI-Generated Interactive Simulations
Zoe Kaputa, Anika Rajaram, Vryan Almanon Feliciano, Zhuoyue Lyu, Maneesh Agrawala, Hari Subramonyam. (07/2025). arXiv. http://arxiv.org/pdf/2507.09664v1
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
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
Can LLMs Reliably Simulate Real Students' Abilities in Mathematics and Reading Comprehension?
KV Aditya Srivatsa, Kaushal Kumar Maurya, Ekaterina Kochmar. (07/2025). arXiv. http://arxiv.org/pdf/2507.08232v1
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
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
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
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
From Query to Explanation: Uni-RAG for Multi-Modal Retrieval-Augmented Learning in STEM
Xinyi Wu, Yanhao Jia, Luwei Xiao, Shuai Zhao, Fengkuang Chiang, Erik Cambria. (07/2025). arXiv. http://arxiv.org/pdf/2507.03868v1
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
Benchmarking the Pedagogical Knowledge of Large Language Models
Maxime Lelievre, Amy Waldock, Meng Liu, Natalia Valdes Aspillaga, Alasdair Mackintosh, Mar’a JosŽ Ogando Portela, Jared Lee, Paul Atherton, Robin A. A. Ince, Oliver G. B. Garrod. (07/2025). arXiv. http://arxiv.org/pdf/2506.18710v3
Designing an Adaptive Storytelling Platform to Promote Civic Education in Politically Polarized Learning Environments
Christopher M. Wegemer, Edward Halim, Jeff Burke. (06/2025). arXiv. http://arxiv.org/pdf/2507.00161v1
Leveraging a Multi-Agent LLM-Based System to Educate Teachers in Hate Incidents Management
Ewelina Gajewska, Michal Wawer, Katarzyna Budzynska, Jaroslaw A. Chudziak. (06/2025). arXiv. http://arxiv.org/pdf/2506.23774v1
Computer Vision for Objects used in Group Work: Challenges and Opportunities
Changsoo Jung, Sheikh Mannan, Jack Fitzgerald, Nathaniel Blanchard. (06/2025). arXiv. http://arxiv.org/pdf/2507.00224v1
Quantifying Student Success with Generative AI: A Monte Carlo Simulation Informed by Systematic Review
Seyma Yaman Kayadibi. (06/2025). arXiv. http://arxiv.org/pdf/2507.01062v1
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
FEAT: A Preference Feedback Dataset through a Cost-Effective Auto-Generation and Labeling Framework for English AI Tutoring
Hyein Seo, Taewook Hwang, Yohan Lee, Sangkeun Jung. (06/2025). arXiv. http://arxiv.org/pdf/2506.19325v2
CogGen: A Learner-Centered Generative AI Architecture for Intelligent Tutoring with Programming Videos
Wengxi Li, Roy Pea, Nick Haber, Hariharan Subramonyam. (06/2025). arXiv. http://arxiv.org/pdf/2506.20600v1
Leveraging AI Graders for Missing Score Imputation to Achieve Accurate Ability Estimation in Constructed-Response Tests
Masaki Uto, Yuma Ito. (06/2025). arXiv. http://arxiv.org/pdf/2506.20119v1
Confucius3-Math: A Lightweight High-Performance Reasoning LLM for Chinese K-12 Mathematics Learning
Lixin Wu, Na Cai, Qiao Cheng, Jiachen Wang, Yitao Duan. (06/2025). arXiv. http://arxiv.org/pdf/2506.18330v2
Deciphering Emotions In Children Storybooks: A Comparative Analysis Of Multimodal Llms In Educational Applications
Bushra Asseri, Estabraq Abdelaziz, Maha Al Mogren, Tayef Alhefdhi, Areej Al-Wabil. (06/2025). arXiv. http://arxiv.org/pdf/2506.18201v1
Language Bottleneck Models: A Framework for Interpretable Knowledge Tracing and Beyond
Antonin Berthon, Mihaela van der Schaar. (06/2025). arXiv. http://arxiv.org/pdf/2506.16982v1
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
Personalizing Student-Agent Interactions Using Log-Contextualized Retrieval-Augmented Generation (RAG)
Clayton Cohn, Surya Rayala, Caitlin Snyder, Joyce Horn Fonteles, Shruti Jain, Naveeduddin Mohammed, Umesh Timalsina, Sarah K. Burriss, Ashwin T S, Namrata Srivastava, Menton Deweese, Angela Eeds, Gautam Biswas. (06/2025). arXiv. http://arxiv.org/pdf/2505.17238v2
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
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
LLM-Driven Personalized Answer Generation and Evaluation
Mohammadreza Molavi, Mohammadreza Tavakoli, Mohammad Moein, Abdolali Faraji, Gabor Kismihok. (06/2025). arXiv. http://arxiv.org/pdf/2506.10829v1
