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Research Study Repository
Research synthesis is AI-generated, human reviewed. Updated 08/2026.
Showing 151 - 180 of 245 results
A systematic review of AI-driven intelligent tutoring systems (ITS) in K-12 education
Angélique Létourneau, Marion Deslandes Martineau, Patrick Charland, John Alexander Karran, Jared Boasen, Pierre Majorique L√©ger. (05/2025). npj Science of Learning.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – ComputationalMSA 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.
What is the application? Teaching – Assessment and Feedback
Who is the user?
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Numeracy
Study design: Technical – ComputationalTowards 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.
What is the application? Teaching – Professional Learning
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Implementation and Use, Technical – ComputationalVTutor for High-Impact Tutoring at Scale: Managing Engagement and Real-Time Multi-Screen Monitoring with P2P Connections
Eason Chen, Xinyi Tang, Aprille Xi, Chenyu Lin, Conrad Borchers, Jionghao Lin, Shivang Gupta, Kenneth R Koedinger. (05/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentMultimodal 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.
What is the application? Analyzing
Who is the user?
Which age? Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Social Emotional
Study design: Technical – Computational, Quantitative – OthersFrom Recall to Reasoning: Automated Question Generation for Deeper Math Learning through Large Language Models
Yongan Yu, Alexandre Krantz, Nikki G. Lobczowski. (05/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback
Who is the user? Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Durable Skills
Study design: Technical – Computational, Quantitative – OthersFrom 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.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Others
Which age? High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Technical – ComputationalEnhancing 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.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalAre 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.
What is the application? Learning – Student Support
Who is the user? Student
Which age? High School (9-12), Post-Secondary, Adult
Why use AI? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Durable Skills
Study design: Technical – ComputationalPedagogy-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.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning, Learning – Student Support, Analyzing
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Technical – ComputationalEduPlanner: 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.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – ComputationalCan Large Language Models Match Tutoring System Adaptivity? A Benchmarking Study
Conrad Borchers, Tianze Shou. (04/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Parent/Caregiver, Educator
Which age? Middle School (6-8)
Why use AI? Outcomes – Numeracy
Study design: Technical – ComputationalInclusive Education with AI: Supporting Special Needs and Tackling Language Barriers
Ricardo Fitas. (04/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support, Communicating / Social Tools, Organizing, Analyzing
Who is the user? Student, Parent/Caregiver, Educator, School Leader, Others
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional, Reimagined Schooling, Other
Study design: Descriptive – Implementation and Use, Descriptive – Product Development, Systematic ReviewAI for Accessible Education: Personalized Audio-Based Learning for Blind Students
Crystal Yang, Paul Taele. (04/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5)
Why use AI? Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product DevelopmentHow Do Teachers Create Pedagogical Chatbots?: Current Practices and Challenges
Minju Yoo, Hyoungwook Jin, Juho Kim. (03/2025). arXiv.
What is the application? Teaching – Instructional Materials, Analyzing
Who is the user? Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Descriptive – Implementation and UseThe Imitation Game for Educational AI
Shashank Sonkar, Naiming Liu, Xinghe Chen, Richard G. Baraniuk. (02/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation
Study design: Technical – ComputationalThe Advancement of Personalized Learning Potentially Accelerated by Generative AI
Yuang Wei, Yuan-Hao Jiang, Jiayi Liu, Changyong Qi, Linzhao Jia, Rui Jia. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Teaching – Professional Learning, Learning – Student Support, Communicating / Social Tools, Analyzing
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product Development, Systematic ReviewSET-PAIRED: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot
Hui-Ru Ho, Nitigya Kargeti, Ziqi Liu, Bilge Mutlu. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Parent/Caregiver
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Literacy, Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Social Emotional, Other
Study design: Descriptive – Product Development, Quantitative – OthersScaffolding Middle-School Mathematics Curricula With Large Language Models
Rizwaan Malik, Dorna Abdi, Rose Wang, Dorottya Demszky. (02/2025). British Journal of Educational Technology.
What is the application? Teaching – Instructional Materials
Who is the user? Educator
Which age? Middle School (6-8)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersMindCraft: Revolutionizing Education through AI-Powered Personalized Learning and Mentorship for Rural India
Arihant Bardia, Aayush Agrawal. (02/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student, Educator, Others
Which age? Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Social Emotional, Outcomes – Durable Skills, Reimagined Schooling
Study design: Descriptive – Product DevelopmentOne Size doesn't Fit All: A Personalized Conversational Tutoring Agent for Mathematics Instruction
Ben Liu, Jihai Zhang, Fangquan Lin, Xu Jia, Min Peng. (02/2025). arXiv.
What is the application? Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Technical – ComputationalFrom Correctness to Comprehension: AI Agents for Personalized Error Diagnosis in Education
Yi-Fan Zhang, Hang Li, Dingjie Song, Lichao Sun, Tianlong Xu, Qingsong Wen. (02/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Analyzing
Who is the user? Educator
Which age? Elementary (PK5)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalAutograding Mathematical Induction Proofs with Natural Language Processing
Chenyan Zhao, Mariana Silva, Seth Poulsen. (02/2025). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user? Student
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy
Study design: Impact – Quasi–experimental, Technical – ComputationalUnifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors
Kaushal Kumar Maurya, KV Aditya Srivatsa, Kseniia Petukhova and Ekaterina Kochmar. (02/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – ComputationalIntelliChain: An Integrated Framework for Enhanced Socratic Method Dialogue with LLMs and Knowledge Graphs
Changyong Qi, Linzhao Jia, Yuang Wei, Yuan-Hao Jiang, Xiaoqing Gu. (01/2025). arXiv.
What is the application? Teaching – Instructional Materials, Learning – Student Support
Who is the user? Student, Educator
Which age? Elementary (PK5), Middle School (6-8), High School (9-12), Post-Secondary
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersA Study on Educational Data Analysis and Personalized Feedback Report Generation Based on Tags and ChatGPT*
Yizhou Zhou, Mengqiao Zhang, Yuan-Hao Jiang, Xinyu Gao, Naijie Liu, Bo Jiang. (01/2025). arXiv.
What is the application? Teaching – Assessment and Feedback, Analyzing
Who is the user? Educator
Which age? Elementary (PK5)
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Differentiation
Study design: Descriptive – Product Development, Technical – Computational, Quantitative – OthersPredicting Long-Term Student Outcomes from Short-Term EdTech Log Data
Ge Gao, Amelia Leon, Andrea Jetten, Jasmine Turner, Husni Almoubayyed, Stephen Fancsali, Emma Brunskill. (01/2025). arXiv.
What is the application? Analyzing
Who is the user? Student
Which age? Elementary (PK5), Middle School (6-8)
Why use AI? Outcomes – Literacy, Outcomes – Numeracy
Study design: Quantitative – OthersImproving the Validity of Automatically Generated Feedback via Reinforcement Learning
Alexander Scarlatos, Digory Smith, Simon Woodhead, Andrew Lan. (12/2024). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user?
Which age? Middle School (6-8)
Why use AI? Outcomes – Numeracy
Study design: Technical – ComputationalA Benchmark for Math Misconceptions: Bridging Gaps in Middle School Algebra with AI-Supported Instruction
Nancy Otero, Stefania Druga and Andrew Lan. (12/2024). arXiv.
What is the application? Teaching – Assessment and Feedback
Who is the user?
Which age? Middle School (6-8)
Why use AI? Outcomes – Numeracy, Outcomes – Differentiation
Study design: Technical – ComputationalScaffold or Crutch? Examining College Students' Use and Views of Generative AI Tools for STEM Education
Karen D. Wang, Zhangyang Wu, L'Nard Tufts II, Carl Wieman, Shima Salehi, Nick Haber. (12/2024). arXiv.
What is the application? Teaching – Instructional Materials, Teaching – Assessment and Feedback, Learning – Student Support
Who is the user? Student, Educator
Which age? Post-Secondary
Why use AI? Efficiency, Outcomes – Numeracy, Outcomes – Other Academic, Outcomes – Differentiation, Outcomes – Durable Skills
Study design: Descriptive – Implementation and Use
