Technical – Computational
Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 361 - 390 of 577
Automated evaluation of children's speech fluency for low-resource languages
Bowen Zhang, Nur Afiqah Abdul Latiff, Justin Kan, Rong Tong, Donny Soh, Xiaoxiao Miao, Ian McLoughlin. (05/2025). arXiv. http://arxiv.org/pdf/2505.19671v1
Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval-Augmented Generation Across Learning Styles
Debdeep Sanyal, Agniva Maiti, Umakanta Maharana, Dhruv Kumar, Ankur Mali, C. Lee Giles, Murari Mandal. (05/2025). arXiv. http://arxiv.org/pdf/2505.19173v1
Predicting Student Dropout Risk With A Dual-Modal Abrupt Behavioral Changes Approach
Jiabei Cheng, Zhen-Qun Yang, Jiannong Cao, Yu Yang, Xinzhe Zheng. (05/2025). arXiv. http://arxiv.org/pdf/2505.11119v1
Illusions of Intimacy: Emotional Attachment and Emerging Psychological Risks in Human-AI Relationships
Minh Duc Chu, Patrick Gerard, Kshitij Pawar, Charles Bickham, Kristina Lerman. (05/2025). arXiv. http://arxiv.org/pdf/2505.11649v2
Human-AI Collaboration or Academic Misconduct? Measuring AI Use in Student Writing Through Stylometric Evidence
Eduardo Araujo Oliveira, Madhavi Mohoni, Sonsoles L¬ópez-Pernas, Mohammed Saqr. (05/2025). arXiv. http://arxiv.org/pdf/2505.08828v1
Multimodal Assessment of Classroom Discourse Quality: A Text-Centered Attention-Based Multi-Task Learning Approach
Ruikun Hou, Babette BŸhler, Tim FŸtterer, Efe Bozkir, Peter Gerjets, Ulrich Trautwein, Enkelejda Kasneci. (05/2025). arXiv. http://arxiv.org/pdf/2505.07902v1
LECTOR: Summarizing E-book Reading Content for Personalized Student Support
Erwin L—pez, Cheng Tang, Valdemar Sv‡bensky, Fumiya Okubo, Atsushi Shimada. (05/2025). arXiv. http://arxiv.org/pdf/2505.07898v1
SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models
Peichao Lai, Kexuan Zhang, Yi Lin, Linyihan Zhang, Feiyang Ye, Jinhao Yan, Yanwei Xu, Conghui He, Yilei Wang, Wentao Zhang, Bin Cui. (05/2025). arXiv. http://arxiv.org/pdf/2505.07247v2
Towards Actionable Pedagogical Feedback: A Multi-Perspective Analysis of Mathematics Teaching and Tutoring Dialogue
Jannatun Naim, Jie Cao, Fareen Tasneem, Jennifer Jacobs, Brent Milne, Tamara Sumner, James Martin. (05/2025). arXiv. http://arxiv.org/pdf/2505.07161v1
VTutor: An Animated Pedagogical Agent SDK that Provide Real Time Multi-Model Feedback
Eason Chen, Chenyu Lin, Yu-Kai Huang, Xinyi Tang, Aprille Xi, Jionghao Lin, Kenneth Koedinger. (05/2025). arXiv. http://arxiv.org/pdf/2505.06676v1
KCluster: An LLM-based Clustering Approach to Knowledge Component Discovery
Yumou Wei, Paulo Carvalho, John Stamper. (05/2025). arXiv. http://arxiv.org/pdf/2505.06469v1
From First Draft to Final Insight: A Multi-Agent Approach for Feedback Generation
Jie Cao, Chloe Qianhui Zhao, Xian Chen, Shuman Wang, Christian Schunn, Kenneth R. Koedinger, Jionghao Lin. (05/2025). arXiv. http://arxiv.org/pdf/2505.04869v1
MSA at BEA 2025 Shared Task: Disagreement-Aware Instruction Tuning for Multi-Dimensional Evaluation of LLMs as Math Tutors
Baraa Hikal, Mohamed Basem, Islam Oshallah, Ali Hamdi. (05/2025). arXiv. http://arxiv.org/pdf/2505.18549v1
CAFES: A Collaborative Multi-Agent Framework for Multi-Granular Multimodal Essay Scoring
Jiamin Su, Yibo Yan, Zhuoran Gao, Han Zhang, Xiang Liu, Xuming Hu. (05/2025). arXiv. http://arxiv.org/pdf/2505.13965v1
Automated Bias Assessment in AI-Generated Educational Content Using CEAT Framework
Jingyang Peng, Wenyuan Shen, Jiarui Rao, Jionghao Lin. (05/2025). arXiv. http://arxiv.org/pdf/2505.12718v1
Supporting Preschool Emotional Development with AI-Powered Robots
Santiago Berrezueta-Guzman, Mar’a Dol—n-Poza, Stefan Wagner. (05/2025). arXiv. http://arxiv.org/pdf/2505.18661v1
Pedagogy-R1: Pedagogically-Aligned Reasoning Model with Balanced Educational Benchmark
Unggi Lee, Jaeyong Lee, Jiyeong Bae, Yeil Jeong, Junbo Koh, Gyeonggeon Lee, Gunho Lee, Taekyung Ahn, Hyeoncheol Kim. (05/2025). arXiv. http://arxiv.org/pdf/2505.18467v1
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, Namrata Srivastava, Menton Deweese, Angela Eeds, Gautam Biswas. (05/2025). arXiv. http://arxiv.org/pdf/2505.17238v1
LLM Access Shield: Domain-Specific LLM Framework for Privacy Policy Compliance
Yu Wang, Cailing Cai, Zhihua Xiao and Peifung E. Lam. (05/2025). arXiv. http://arxiv.org/pdf/2505.17145v1
Are LLMs Ready for English Standardized Tests? A Benchmarking and Elicitation Perspective
Luoxi Tang, Tharunya Sundar, Shuai Yang, Ankita Patra, Manohar Chippada, Giqi Zhao, Yi Li, Riteng Zhang, Tunan Zhao, Ting Yang, Yuqiao Meng, Weicheng Ma, Zhaohan Xi. (05/2025). arXiv. http://arxiv.org/pdf/2505.17056v1
Enhancing Mathematics Learning for Hard-of-Hearing Students Through Real-Time Palestinian Sign Language Recognition: A New Dataset
Fidaa khandaqji, Huthaifa I. Ashqar, Abdelrahem Atawnih. (05/2025). arXiv. http://arxiv.org/pdf/2505.17055v1
Towards Robust Evaluation of STEM Education: Leveraging MLLMs in Project-Based Learning
Yanhao Jia, Xinyi Wu, Qinglin Zhang, Yiran Qin, Luwei Xiao, Shuai Zhao. (05/2025). arXiv. http://arxiv.org/pdf/2505.17050v1
From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Pedagogical Visualization
Haonian Ji, Shi Qiu, Siyang Xin, Siwei Han, Zhaorun Chen, Dake Zhang, Hongyi Wang, Huaxiu Yao. (05/2025). arXiv. http://arxiv.org/pdf/2505.16832v1
From Recall to Reasoning: Automated Question Generation for Deeper Math Learning through Large Language Models
Yongan Yu, Alexandre Krantz, Nikki G. Lobczowski. (05/2025). arXiv. http://arxiv.org/pdf/2505.11899v1
Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering
Hessa Alawwad, Usman Naseem, Areej Alhothali, Ali Alkhathlan, Amani Jamal. (05/2025). arXiv. http://arxiv.org/pdf/2505.13520v1
STRIVE: A Think & Improve Approach with Iterative Refinement for Enhancing Question Quality Estimation
Aniket Deroy, Subhankar Maity. (04/2025). arXiv. https://arxiv.org/pdf/2504.05693v1
EducationQ: Evaluating LLMs' Teaching Capabilities Through Multi-Agent Dialogue Framework
Yao Shi, Rongkeng Liang, Yong Xu. (04/2025). arXiv. https://arxiv.org/pdf/2504.14928v1
EduPlanner: LLM-Based Multi-Agent Systems for Customized and Intelligent Instructional Design
Xueqiao Zhang, Chao Zhang, Jianwen Sun, Jun Xiao, Yi Yang, Yawei Luo. (04/2025). arXiv. https://arxiv.org/pdf/2504.05370v1
Can Large Language Models Match Tutoring System Adaptivity? A Benchmarking Study
Conrad Borchers, Tianze Shou. (04/2025). arXiv. https://arxiv.org/pdf/2504.05570v1
Single-Agent vs. Multi-Agent LLM Strategies for Automated Student Reflection Assessment
Gen Li, Li Chen, Cheng Tang, Valdemar Svabensky, Daisuke Deguchi, Takayoshi Yamashita, Atsushi Shimada. (04/2025). arXiv. https://arxiv.org/pdf/2504.05716v1
