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Middle School (6-8)
Research synthesis is AI-generated, human reviewed. Updated 03/2025.
Displaying 91 - 120 of 187
Generative AI and Digital Neocolonialism in Global Education: Towards an Equitable Framework
Matthew Nyaaba, Alyson Wright, Gyu Lim Choi. (06/2024). arXiv. http://arxiv.org/pdf/2406.02966v3
Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AI
Gyeong-Geon Lee, Xiaoming Zhai. (05/2024). arXiv. https://arxiv.org/abs/2405.07163
Towards Educator-Driven Tutor Authoring: Generative AI Approaches for Creating Intelligent Tutor Interfaces
Tommaso Calo, Christopher J. MacLellan. (05/2024). arXiv. https://arxiv.org/abs/2405.14713
Rethinking the A in STEAM: Insights from and for AI Literacy Education
Pekka Mertala, Janne Fagerlund, Tomi Slotte Dufva. (05/2024). arXiv. https://arxiv.org/abs/2405.18179
Math Multiple Choice Question Generation via Human-Large Language Model Collaboration
Jaewook Lee, Digory Smith, Simon Woodhead, Andrew Lan. (05/2024). arXiv. http://arxiv.org/pdf/2405.00864v1
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
Effective and Scalable Math Support: Experimental Evidence on the Impact of an AI- Math Tutor in Ghana
Owen Henkel, Hannah Horne-Robinson, Nessie Kozhakhmetova, Amanda Lee. (05/2024). arXiv. https://arxiv.org/pdf/2402.09809
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
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
Artificial Intelligence and Educational Measurement: Opportunities and Threats
Andrew D. Ho. (05/2024). DASH Harvard. https://dash.harvard.edu/bitstream/handle/1/37379195/AI%20and%20Educational%20M…
Generating A Crowdsourced Conversation Dataset to Combat Cybergrooming
Xinyi Zhang, Pamela J. Wisniewski, Jin-Hee Cho, Lifu Huang, Sang Won Lee. (05/2024). arXiv. http://arxiv.org/pdf/2405.13154v1
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
An Automatic Question Usability Evaluation Toolkit
Steven Moore, Eamon Costello, Huy A. Nguyen, John Stamper. (05/2024). arXiv. http://arxiv.org/pdf/2405.20529v1
Improving Teaching at Scale: Can AI Be Incorporated Into Professional Development to Create Interactive, Personalized Learning for Teachers?
Yasemin Copur-Gencturk, Jingxian Li, Sebnem Atabas. (05/2024). American Educational Research Journal. https://journals.sagepub.com/doi/full/10.3102/00028312241248514
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
AI and personalized learning: Bridging the gap with modern educational goals
Kristjan-Julius Laak, Jaan Aru. (04/2024). arXiv. https://arxiv.org/abs/2404.02798
Pros and Cons of Artificial Intelligence–ChatGPT Adoption in Education Settings: A Literature Review and Future Research Agendas
Idria Maita, Saide Saide, Afifah Mesha Putri, Didi Muwardi. (04/2024). IEEE. https://ieeexplore.ieee.org/document/10510580
Large Language Models for Education: A Survey and Outlook
Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen. (04/2024). arXiv. http://arxiv.org/pdf/2403.18105v2
Instructors as Innovators: a Future-focused Approach to New AI Learning Opportunities, With Prompts
Ethan R. Mollick, Lilach Mollick. (04/2024). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4802463
Designing Child-Centric AI Learning Environments: Insights from LLM-Enhanced Creative Project-Based Learning
Siyu Zha, Yuehan Qiao, Qingyu Hua, Zhongsheng Li, Jiangtao Gong, Yingqing Xu. (04/2024). arXiv. http://arxiv.org/pdf/2403.16159v2
Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges
Qingyao Li, Lingyue Fu, Weiming Zhang, Xianyu Chen, Jingwei Yu, Wei Xia, Weinan Zhang, Ruiming Tang, Yong Yu. (04/2024). arXiv. http://arxiv.org/pdf/2401.08664v3
Remote Possibilities: Where There Is a WIL, Is There a Way? AI Education for Remote Learners in a New Era of Work-Integrated-Learning
Derek Jacoby, Saiph Savage, Yvonne Coady. (04/2024). arXiv. http://arxiv.org/pdf/2402.12667v2
AI and Machine Learning for Next Generation Science Assessments
Xiaoming Zhai. (04/2024). arXiv. http://arxiv.org/pdf/2405.06660v1
Clue-Instruct: Text-Based Clue Generation for Educational Crossword Puzzles
Andrea Zugarini, Kamyar Zeinalipour, Surya Sai Kadali, Marco Maggini, Marco Gori, Leonardo Rigutini. (04/2024). arXiv. http://arxiv.org/pdf/2404.06186v1
Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform
Dorottya Demszky, Rose E. Wang, Sean Geraghty, Carol Yu. (03/2024). ACM Digital Library. https://dl.acm.org/doi/10.1145/3636555.3636924
Developing and Deploying Industry Standards for Artificial Intelligence in Education (AIED): Challenges, Strategies, and Future Directions
Richard Tong, Haoyang Li, Joleen Liang, and Qingsong Wen. (03/2024). arXiv. http://arxiv.org/pdf/2403.14689v2
AGI: Artificial General Intelligence for Education
Ehsan Latif, Gengchen Mai, Matthew Nyaaba, Xuansheng Wu, Ninghao Liu, Guoyu Lu, Sheng Li, Tianming Liu and Xiaoming Zhai. (03/2024). arXiv. http://arxiv.org/pdf/2304.12479v5
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation
Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg Stephen E. Fancsali, Vincent Aleven, Lee Branstetter, Emma Brunskill, Kenneth R. Koedinger. (03/2024). Association for Computing Machinery. https://dl.acm.org/doi/pdf/10.1145/3636555.3636896
Survey of Natural Language Processing for Education: Taxonomy, Systematic Review, and Future Trends
Yunshi Lan, Xinyuan Li, Hanyue Du, Xuesong Lu, Ming Gao, Weining Qian and Aoying Zhou. (03/2024). arXiv. http://arxiv.org/pdf/2401.07518v3