Technical – Computational
Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 481 - 510 of 577
Are Large Language Models Good Essay Graders?
Kundu, Anindita, Barbosa, Denilson. (09/2024). arXiv. http://arxiv.org/pdf/2409.13120v1
Computational Language Analysis Reveals that Process-Oriented Thinking About Belonging Aids the College Transition
Dorottya Demszky, C. Lee Williams, Shannon T. Brady, Shashanka Subrahmanya, Eric Gaudiello, Gregory M. Walton, Johannes C. Eichstaedt. (09/2024). EdWorkingPapers. https://edworkingpapers.com/sites/default/files/ai24-1033.pdf
Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube
Kausik Lakkaraju, Vedant Khandelwal, Biplav Srivastava, Forest Agostinelli, Hengtao Tang, Prathamjeet Singh, Dezhi Wu, Matt Irvin, Ashish Kundu. (08/2024). arXiv. http://arxiv.org/pdf/2402.01760v2
New Curriculum, New Chance - Retrieval Augmented Generation for Lesson Planning in Ugandan Secondary Schools. Prototype Quality Evaluation.
Simon Kloker, Herbertson Bukoli, Twaha Kateete. (08/2024). arXiv. http://arxiv.org/pdf/2408.07542v1
Generative Language Models With Retrieval Augmented Generation for Automated Short Answer Scoring
Zifan Wang, Christopher Ormerod. (08/2024). arXiv. http://arxiv.org/pdf/2408.03811v1
The Feedback Prize: A Case Study in Assisted Writing Feedback Tools
Perpetual Baffour, Scott Crossley, Yu Tian, Alex Franklin, Natalie Rambis, Meg Benner, Ulrich Boser. (08/2024). The Learning Agency Lab. https://the-learning-agency-lab.com/wp-content/uploads/2023/08/TLA-Lab_Whitepap…
Automating Human Tutor-Style Programming Feedback: Leveraging GPT-4 Tutor Model for Hint Generation and GPT-3.5 Student Model for Hint Validation
Tung Phung, Victor-Alexandru Padurean, Anjali Singh, Christopher Brooks, Jose Cambronero, Sumit Gulwani, Adish Singla, Gustavo Soares. (08/2024). arXiv. http://arxiv.org/pdf/2310.03780v4
Dr.Academy: A Benchmark for Evaluating Questioning Capability in Education for Large Language Models
Yuyan Chen, Chenwei Wu, Songzhou Yan, Panjun Liu, Haoyu Zhou, Yanghua Xiao. (08/2024). arXiv. http://arxiv.org/pdf/2408.10947v1
Building a Domain-specific Guardrail Model in Production
Mohammad Niknazar, Paul V Haley, Latha Ramanan, Sang T. Truong, Yedendra Shrinivasan, Ayan Kumar Bhowmick, Prasenjit Dey, Ashish Jagmohan, Hema Maheshwari, Shom Ponoth, Robert Smith, Aditya Vempaty, Nick Haber, Sanmi Koyejo, Sharad Sundararajan. (07/2024). arXiv. http://arxiv.org/pdf/2408.01452v1
FairyLandAI: Personalized Fairy Tales utilizing ChatGPT and DALLE-3
Georgios Makridis, Athanasios Oikonomou, Vasileios Koukosa. (07/2024). arXiv. http://arxiv.org/pdf/2407.09467v1
Enhancing Computer Programming Education with LLMs: A Study On Effective Prompt Engineering for Python Code Generation
Tianyu Wang, Nianjun Zhou, Zhixiong Chen. (07/2024). arXiv. http://arxiv.org/pdf/2407.05437v1
Explainable Artificial Intelligence for Quantifying Interfering and High-Risk Behaviors in Autism Spectrum Disorder in a Real-World Classroom Environment Using Privacy-Preserving Video Analysis
Barun Das, Conor Anderson, Tania Villavicencio, Johanna Lantz, Jenny Foster, Theresa Hamlin, Ali Bahrami Rad, Gari D. Clifford, Hyeokhyen Kwon. (07/2024). arXiv. http://arxiv.org/pdf/2407.21691v1
COMET : "Cone of experience” enhanced large multimodal model for mathematical problem generation
Sannyuya Liu, Jintian Feng, Zongkai Yang, Yawei Luo, Qian Wan, Xiaoxuan Shen, Jianwen Sun. (07/2024). arXiv. http://arxiv.org/pdf/2407.11315v1
CourseAssist: Pedagogically Appropriate AI Tutor for Computer Science Education
Ty Feng, Sa Liu, Dipak Ghosal. (07/2024). arXiv. https://arxiv.org/pdf/2407.10246
Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors
Nico Daheim, Jakub Macina, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan. (07/2024). arXiv. http://arxiv.org/pdf/2407.09136v1
RAMO: Retrieval-Augmented Generation for Enhancing MOOCs Recommendations
Jiarui Rao, Jionghao Lin. (07/2024). arXiv. http://arxiv.org/pdf/2407.04925v1
Encouraging Responsible Use of Generative AI in Education: A Reward-Based Learning Approach
Aditi Singh, Abul Ehtesham, Saket Kumar, Gaurav Gupta, Tala Talaei Khoei. (06/2024). arXiv. https://arxiv.org/pdf/2407.15022
How Effective is GPT-4 Turbo in Generating School-Level Questions from Textbooks Based on Bloom's Revised Taxonomy?
Subhankar Maity, Aniket Deroy, Sudeshna Sarkar. (06/2024). arXiv. http://arxiv.org/pdf/2406.15211v1
AI AGENTS AND EDUCATION: SIMULATED PRACTICE AT SCALE
Ethan Mollick, Lilach Mollick, Natalie Bach, LJ Ciccarelli, Ben Przystanski, Daniel Ravipinto. (06/2024). arXiv. https://arxiv.org/pdf/2407.12796
Knowledge Distillation of LLMs for Automatic Scoring of Science Assessments
Ehsan Latif, Luyang Fang, Ping Ma, Xiaoming Zhai. (06/2024). arXiv. http://arxiv.org/pdf/2312.15842v3
Generative AI for Enhancing Active Learning in Education: A Comparative Study of GPT-3.5 and GPT-4 in Crafting Customized Test Questions
Hamidreza Rouzegar, Masoud Makrehchit. (06/2024). arXiv. https://arxiv.org/pdf/2406.13903
Human-AI Collaborative Essay Scoring: A Dual-Process Framework with LLMs
Changrong Xiao, Wenxing Ma, Qingping Song, Sean Xin Xu, Kunpeng Zhang, Yufang Wang, Qi Fu. (06/2024). arXiv. https://arxiv.org/pdf/2401.06431
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
Joykirat Singh, Akshay Nambi, Vibhav Vineet. (06/2024). arXiv. http://arxiv.org/pdf/2406.10834v1
JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models
Kun Zhou, Beichen Zhang, Jiapeng Wang, Zhipeng Chen, Wayne Xin Zhao, Jing Sha, Zhichao Sheng, Shijin Wang, Ji-Rong Wen. (05/2024). arXiv. http://arxiv.org/pdf/2405.14365v1
LLMs can Find Mathematical Reasoning Mistakes by Pedagogical Chain-of-Thought
Zhuoxuan Jiang, Haoyuan Peng, Shanshan Feng, Fan Li, Dongsheng Li. (05/2024). arXiv. http://arxiv.org/pdf/2405.06705v1
Large Language Models for Education: A Survey
Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu and Philip S. Yu. (05/2024). arXiv. http://arxiv.org/pdf/2405.13001v1
Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming
Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla. (05/2024). arXiv. http://arxiv.org/pdf/2310.10690v3
Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability to Mark Short Answer Questions in K-12 Education
Owen Henkel, Libby Hills, Adam Boxer, Bill Roberts, Zach Levonian. (05/2024). ACM Digital Library. https://dl.acm.org/doi/pdf/10.1145/3657604.3664693
Evaluating and Optimizing Educational Content with Large Language Model Judgments
Joy He-Yueya, Noah D. Goodman, Emma Brunskill. (05/2024). arXiv. http://arxiv.org/pdf/2403.02795v2
