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Outcomes – Numeracy
Research synthesis is AI-generated, human reviewed. Updated 09/2025.
Displaying 181 - 197 of 197
Math Education With Large Language Models: Peril or Promise?
Harsh Kumar, David M. Rothschild, Daniel G. Goldstein, Jake M. Hofman. (11/2023). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4641653
Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference
Zachary Levonian, Chenglu Li, Wangda Zhu, Anoushka Gade, Owen Henkel, Millie-Ellen Postle, Wanli Xing. (11/2023). arXiv. http://arxiv.org/pdf/2310.03184v2
Exploring User Perspectives on ChatGPT: Applications, Perceptions, and Implications for AI-Integrated Education
Reza Hadi Mogavi, Chao Deng, Justin Juho Kim, Pengyuan Zhou, Young D. Kwon, Ahmed Hosny Saleh Metwally, Ahmed Tlili, Simone Bassanelli, Antonio Bucchiarone, Sujit Gujar, Lennart E. Nacke, Pan Hui. (11/2023). arXiv. https://arxiv.org/pdf/2305.13114
"Mistakes Help Us Grow”: Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms
Kunal Handa, Margaret Clapper, Jessica Boyle, Rose E Wang, Diyi Yang, David S Yeager, Dorottya Demszky. (10/2023). arXiv. https://arxiv.org/pdf/2310.10637
The NCTE Transcripts: A Dataset of Elementary Math Classroom Transcripts
Dorottya Demszky, Heather Hill. (10/2023). arXiv. https://arxiv.org/pdf/2211.11772
Data-Driven Artificial Intelligence in Education: A Comprehensive Review
Kashif Ahmad, Waleed Iqbal, Ammar El-Hassan, Junaid Qadir, Driss Benhaddou, Moussa Ayyash, Ala Al-Fuqaha. (09/2023). IEEE. https://ieeexplore.ieee.org/document/10247566
Let's Have a Chat! A Conversation with ChatGPT: Technology, Applications, and Limitations
Sakib Shahriar, Kadhim Hayawi. (08/2023). arXiv. http://arxiv.org/pdf/2302.13817v4
Towards Applying Powerful Large AI Models in Classroom Teaching: Opportunities, Challenges and Prospects
Kehui Tan, Tianqi Pang, Chenyou Fan, Song Yu. (06/2023). arXiv. http://arxiv.org/pdf/2305.03433v2
Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction
Rose Wang, Dorottya Demszky. (06/2023). arXiv. http://arxiv.org/pdf/2306.03090v1
Interpretable Math Word Problem Solution Generation Via Step-by-step Planning
Mengxue Zhang, Zichao Wang, Zhichao Yang, Weiqi Feng, Andrew Lan. (06/2023). arXiv. http://arxiv.org/pdf/2306.00784v1
Inspecting Spoken Language Understanding from Kids for Basic Math Learning at Home
Eda Okur, Saurav Sahay, Roddy Fuentes Alba, Lama Nachman. (06/2023). arXiv. http://arxiv.org/pdf/2306.00482v1
Let GPT be a Math Tutor: Teaching Math Word Problem Solvers with Customized Exercise Generation
Zhenwen Liang, Wenhao Yu, Tanmay Rajpurohit, Peter Clark, Xiangliang Zhang, Ashwin Kaylan. (05/2023). arXiv. http://arxiv.org/pdf/2305.14386v1
Solving math word problems with process- and outcome-based feedback
Jonathan Uesato, Nate Kushman, Ramana Kumar, Francis Song, Noah Siegel, Lisa Wang, Antonia Creswell, Geoffrey Irving and Irina Higgins. (11/2022). arXiv. http://arxiv.org/pdf/2211.14275v1
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Anais Tack, Chris Piech. (05/2022). arXiv. http://arxiv.org/pdf/2205.07540v1
Artificial Intelligence Applications in K-12 Education: A Systematic Literature Review
Mostafa Zafari, Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi. (05/2022). IEEE. https://ieeexplore.ieee.org/document/9785805
Home-Tutoring Services Assisted with Technology: Investigating the Role of Artificial Intelligence Using a Randomized Field Experiment
Jun Hyung Kim, Minki Kim, Do Won Kwak, Sol Lee. (09/2021). Sage. https://journals.sagepub.com/doi/full/10.1177/00222437211050351
Student Learning Benefits Of A Mixed-Reality Teacher Awareness Tool In AI-Enhanced Classrooms
Kenneth Holstein, Bruce M. McLaren, Vincent Aleven. (06/2018). International Conference on Artificial Intelligence in Education. https://link.springer.com/chapter/10.1007/978-3-319-93843-1_12
