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Research Synthesis Report
AI in Education: Key Impacts, Concerns, and Priorities
ANALYZER:Text Response Hub v.2.01
AI ENGINE:GPT-5-mini
REPORT DATE:Oct 21, 2025
Overview
Report Details:
Joel Vuolevi•
Text Response Hub
Text Response HubResearch Abstracts
English
Corpus:
Most topical and influential research abstracts on AI in teaching.
Number of abstracts: 95
Publication period: 2022 - 2025
Snapshot date: Oct 21, 2025
Keywords:
- AI in education
- generative AI
- teacher readiness
- ethical issues
- personalized learning
Key Themes (Synthesis)
Global insights extracted across all abstracts
98%
Integration of AI into teaching and learning practices
65%
Ethical concerns, academic integrity, bias, and privacy issues
55%
Teacher perceptions, readiness, and professional development needs
52%
AI enabling more efficient feedback, assessment, and administrative tasks
50%
Personalized/adaptive learning, tutoring systems, and learning analytics
48%
Technical limitations, infrastructure, usability, and resource constraints
47%
Need for AI literacy for students and teachers (skills and competencies)
45%
Generative AI (e.g., ChatGPT) as a disruptive tool and focus of debate
42%
Calls for institutional policies, guidelines, and governance frameworks
30%
Research gaps and need for further interdisciplinary studies
Percentages indicate the proportion of research abstracts that address each theme. Because a single study can cover multiple themes, totals across themes may exceed 100%.
Study Summaries (Evidence by study)
ID | Summary | Reference |
|---|---|---|
1 | LLMs like ChatGPT disrupt higher education pedagogy but can be leveraged to enhance teaching and assessment with proper instructional design. | Bronwyn Eager, Ryan Brunton (2023). Prompting Higher Education Towards AI-Augmented Teaching and Learning Practice. Journal of University Teaching and Learning Practice DOI link |
2 | AI enables anytime, personalized feedback and support in higher education while posing institutional and research challenges. | Satya Vir Singh, Kamal Kant Hiran (2022). The Impact of AI on Teaching and Learning in Higher Education Technology. Journal of Higher Education Theory and Practice DOI link |
3 | There is no consensus on GenAI use in higher education; systematic review identifies gaps and calls for interdisciplinary research and guidelines. | Bayode Ogunleye, Kudirat Ibilola Zakariyyah, Oluwaseun Ajao, Olakunle Olayinka, Hemlata Sharma (2024). A Systematic Review of Generative AI for Teaching and Learning Practice. Education Sciences DOI link |
4 | EFL teachers generally hold positive perceptions and intentions to use AI in middle school English instruction, influenced by UTAUT and TPACK factors. | Xin An, Ching Sing Chai, Yushun Li, Ying Zhou, Xi Shen, Chunping Zheng, Mengyuan Chen (2022). Modeling English teachers’ behavioral intention to use artificial intelligence in middle schools. Education and Information Technologies DOI link |
5 | Teachers viewed an AI-enhanced scaffolding system for STEM writing positively but raised concerns about changing teacher roles and AI transparency. | Nam Ju Kim, Min Kyu Kim (2022). Teacher’s Perceptions of Using an Artificial Intelligence-Based Educational Tool for Scientific Writing. Frontiers in Education DOI link |
6 | Higher education English instructors need familiarity, confidence, and tailored professional development to integrate generative AI effectively. | Lucas Kohnke, Benjamin Luke Moorhouse, Di Zou (2023). Exploring generative artificial intelligence preparedness among university language instructors: A case study. Computers and Education Artificial Intelligence DOI link |
7 | Integrating AI like ChatGPT should focus on pedagogy that promotes self-regulated learning through prompting, feedback, and personalization. | Daniel Chang, Michael Pin-Chuan Lin, Shiva Hajian, Quincy Q. Wang (2023). Educational Design Principles of Using AI Chatbot That Supports Self-Regulated Learning in Education: Goal Setting, Feedback, and Personalization. Sustainability DOI link |
8 | Applying AI in teaching requires improving teachers' AI literacy, with Applying AI driving gains in understanding, evaluation, and ethics. | Leilei Zhao, Xiaofan Wu, Heng Luo (2022). Developing AI Literacy for Primary and Middle School Teachers in China: Based on a Structural Equation Modeling Analysis. Sustainability DOI link |
9 | Students often trust ChatGPT in physics despite inaccuracies, highlighting misconceptions and the need for AI literacy in STEM. | Lu Ding, Tong Li, Shiyan Jiang, A. A. Gapud (2023). Students’ perceptions of using ChatGPT in a physics class as a virtual tutor. International Journal of Educational Technology in Higher Education DOI link |
10 | AI literacy for teachers is an emerging but underdeveloped area in teacher education, with gaps in practical and ethical knowledge. | Katarina Sperling, Carl-Johan Stenberg, Cormac McGrath, Anna Åkerfeldt, Fredrik Heintz, Linnéa Stenliden (2024). In search of artificial intelligence (AI) literacy in teacher education: A scoping review. Computers and Education Open DOI link |
11 | Educators believe generative AI will substantially impact teaching and assessment and call for curriculum and pedagogical changes emphasizing higher-order skills and ethics. | Matt Bower, Jodie Torrington, Jennifer W. M. Lai, Peter Petocz, Mark Alfano (2024). How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey. Education and Information Technologies DOI link |
12 | A case-based AI professional development program increased teachers' AI literacy, especially theoretical understanding, but application remained limited. | Ai-Chu Elisha Ding, Lehong Shi, Haotian Yang, Ikseon Choi (2024). Enhancing teacher AI literacy and integration through different types of cases in teacher professional development. Computers and Education Open DOI link |
13 | Most university lecturers are willing to accept AI for students, with acceptance influenced by experience, institutional support, and attitudes. | Kingsley Ofosu‐Ampong (2024). Beyond the hype: exploring faculty perceptions and acceptability of AI in teaching practices. Discover Education DOI link |
14 | AI tools aid Indonesian students' academic writing planning and drafting but need improved Indonesian language features and AI literacy training. | Santi Pratiwi Tri Utami, Andayani Andayani, Retno Winarni, Sumarwati Sumarwati (2023). Utilization of artificial intelligence technology in an academic writing class: How do Indonesian students perceive?. Contemporary Educational Technology DOI link |
15 | Mathematics teachers in Abu Dhabi see AI as beneficial for teaching and motivation but face workload and implementation challenges. | Mohammad A. Tashtoush, Yousef Wardat, Rommel AlAli, Shoeb Gamal Saleh (2024). Artificial Intelligence in Education: Mathematics Teachers’ Perspectives, Practices and Challenges. Iraqi Journal for Computer Science and Mathematics DOI link |
16 | Generative AI research in education centers on human-AI interaction, AI literacy, prompt engineering, and emotional intelligence as emerging priorities. | Aras Bozkurt (2023). Unleashing the Potential of Generative AI, Conversational Agents and Chatbots in Educational Praxis: A Systematic Review and Bibliometric Analysis of GenAI in Education. Open Praxis DOI link |
17 | Technochauvinism warns against assuming AI will inevitably improve education; evidence for transformative effects remains limited and uncertain. | Ben Williamson (2023). The Social life of AI in Education. International Journal of Artificial Intelligence in Education DOI link |
18 | Teachers perceive AI as threatening academic honesty in EFL student writing and call for training, detection strategies, and ethical guidelines. | Ebrahim Mohammadkarimi (2023). Teachers’ reflections on academic dishonesty in EFL students’ writings in the era of artificial intelligence. Journal of Applied Learning & Teaching DOI link |
19 | Generative AI-assisted professional development improved pre-service teachers' self-efficacy and higher-order thinking compared to traditional training. | Jijian Lu, Ruxin Zheng, Zikun Gong, Huifen Xu (2024). Supporting Teachers’ Professional Development With Generative AI: The Effects on Higher Order Thinking and Self-Efficacy. IEEE Transactions on Learning Technologies DOI link |
20 | AI integration in teaching and administration can revolutionize education by predicting learning outcomes and extracting behavioral insights from data. | Pravin R. Kshirsagar, D. B. V. Jagannadham, Hamed Alqahtani, Quadri Noorulhasan Naveed, Saiful Islam, M. Thangamani, Minilu Dejene (2022). Human Intelligence Analysis through Perception of AI in Teaching and Learning. Computational Intelligence and Neuroscience DOI link |
21 | AI in education positively influences teaching effectiveness, mediated by teachers' perceptions of educational technology and varying with AI use duration. | Hualiang Lin (2022). Influences of Artificial Intelligence in Education on Teaching Effectiveness. International Journal of Emerging Technologies in Learning (iJET) DOI link |
22 | Teachers' valuation and integration of genAI are driven by leadership support, professional growth striving, and change-related stress among other factors. | Rebecca J. Collie, Andrew J. Martin (2024). Teachers’ motivation and engagement to harness generative AI for teaching and learning: The role of contextual, occupational, and background factors. Computers and Education Artificial Intelligence DOI link |
23 | The Pharmacy Academy should lead discussions on AI's technical, ethical, and educational implications for pharmacy education and practice. | Jeff Cain, Daniel R. Malcom, Timothy Dy Aungst (2023). The Role of Artificial Intelligence in the Future of Pharmacy Education. American Journal of Pharmaceutical Education DOI link |
24 | AI has potential to transform STEM higher education across pedagogy, curriculum, engagement, and assessment, warranting focused research and development. | B. Nagaraj, A. Kalaivani, Suraj Begum R, S Akila, Hemant Kumar Sachdev, N. K. Senthil Kumar (2023). The Emerging Role of Artificial Intelligence in STEM Higher Education: A Critical Review. International Research Journal of Multidisciplinary Technovation DOI link |
25 | Pre-service teachers' behavioral intention to design GenAI-assisted teaching is predicted by GenAI anxiety, social influence, and performance expectancy. | Kai Wang, Qianqian Ruan, Xiaoxuan Zhang, Chunhua Fu, Boyuan Duan (2024). Pre-Service Teachers’ GenAI Anxiety, Technology Self-Efficacy, and TPACK: Their Structural Relations with Behavioral Intention to Design GenAI-Assisted Teaching. Behavioral Sciences DOI link |
26 | Top U.S. universities' GenAI guidelines emphasize faculty-led, course-specific policies with positive sentiment but recurring concerns about integrity and privacy. | Yunjo An, Ji Hyun Yu, Shelley James (2025). Investigating the higher education institutions’ guidelines and policies regarding the use of generative AI in teaching, learning, research, and administration. International Journal of Educational Technology in Higher Education DOI link |
27 | A seven-month case study shows ChatGPT can meaningfully support an EFL teacher’s lesson planning and assessment when combined with AI competencies and critical judgment. | Manuela Mena Octavio, María Vicenta González Argüello, Joan‐Tomàs Pujolà (2024). ChatGPT as an AI L2 teaching support: A case study of an EFL teacher. Technology in Language Teaching & Learning DOI link |
28 | Generative AI enhances teaching performance by improving perceived usefulness, ease of learning, and enabling integration into learning materials and practice. | Heni Mulyani, Mohammad I. Azim, Elvia R. Shauki, Fitrina Kurniati, Hanifia Arlinda (2025). Transforming education: exploring the influence of generative AI on teaching performance. Cogent Education DOI link |
29 | AI-informed multimedia teaching materials were developed for Islamic education using ADDIE to support senior high school students' learning. | Sameera Alshorman (2024). THE READINESS TO USE AI IN TEACHING SCIENCE: SCIENCE TEACHERS' PERSPECTIVE. Journal of Baltic Science Education DOI link |
30 | The TEP-AITA scale measures teachers' efficacy perceptions of AI-based teaching across six factors, revealing strengths in cross-disciplinary and learner-demand domains and weaknesses in resource support. | S Syahrizal, Fifi Yasmi, Thomson Mary (2024). AI-Enhanced Teaching Materials for Education: A Shift Towards Digitalization. International Journal of Religion DOI link |
31 | A multi-agent AI system integrating optimization algorithms can improve intelligent integration of AI English teaching resources and information. | Chun-Mei Chou, Tsu-Chi Shen, Tsu-Chuan Shen, Chien-Hua Shen (2022). The level of perceived efficacy from teachers to access AI-based teaching applications. Research and Practice in Technology Enhanced Learning DOI link |
32 | AI chatbots improved students' speaking abilities in an EFL university setting, with mixed effects on pronunciation but positive attitudes toward chatbot use. | Minjuan Liu (2022). Intelligent Integration Method of AI English Teaching Resource Information under Multi-Agent Collaboration. Advances in Multimedia DOI link |
33 | AI-enhanced teaching strategies personalize learning, increase engagement, and provide data-driven insights while raising ethical and implementation challenges. | Zada Kemelbekova, Xeniya Degtyareva, Saule Yessenaman, D.T. Ismailova, Guldana Seidaliyeva (2024). AI in teaching English as a foreign language: Effectiveness and prospects in Kazakh higher education. XLinguae DOI link |
34 | AI is reshaping scientific practice and science education, prompting questions about aligning curricula and teacher education with AI-informed scientific methods. | Mr. Siddhant Mishra (2024). Revolutionizing Education: The Impact of AI-Enhanced Teaching Strategies. International Journal for Research in Applied Science and Engineering Technology DOI link |
35 | Research on AI in higher education shows imbalances across administration vs teaching, disciplines, nations, and highlights neglected topics needing interdisciplinary study. | Sibel Erduran, Olivia Levrini (2024). The impact of artificial intelligence on scientific practices: an emergent area of research for science education. International Journal of Science Education DOI link |
36 | Slovak pre-service EFL teachers show limited computational AI knowledge but generally positive attitudes toward AI in education and desire AI in curricula. | André Ullrich, Gergana Vladova, Felix Eigelshoven, André Renz (2022). Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions: a bibliometrics analysis and recommendation for future research. Discover Artificial Intelligence DOI link |
37 | AI usage in teaching enhances student creativity mediated by engagement, with AI literacy moderating the engagement effect. | Silvia Pokrivčáková (2023). Pre-service teachers’ attitudes towards artificial intelligence and its integration into EFL teaching and learning. Journal of language and cultural education DOI link |
38 | Math and science teachers use ChatGPT for examples, explanations, and test prep, finding benefits for engagement but concerns about accuracy and connectivity. | Min Zhou, Song Peng (2025). The Usage of AI in Teaching and Students’ Creativity: The Mediating Role of Learning Engagement and the Moderating Role of AI Literacy. Behavioral Sciences DOI link |
39 | Faculty at King Faisal University show average readiness to integrate AI, correlated with perceived benefits, attitudes, intentions, and facilitative conditions. | Osama Taani, Suzan Alabidi (2024). ChatGPT in education: benefits and challenges of ChatGPT for mathematics and science teaching practices. International Journal of Mathematical Education in Science and Technology DOI link |
40 | Pre-service life sciences teachers' intentions to adopt AI are shaped by attitudes, practical constraints, stakeholder norms, and resource issues. | Badiah N. M. Alnasib (2023). Factors Affecting Faculty Members’ Readiness to Integrate Artificial Intelligence into Their Teaching Practices: A Study from the Saudi Higher Education Context. International Journal of Learning Teaching and Educational Research DOI link |
41 | Teachers generally find AI educational tools useful and easy to use for AI literacy education but face gaps in AI content knowledge, infrastructure, and potential distractions. | Lindelani Mnguni (2024). A Qualitative Analysis of South African Pre-service Life Sciences Teachers’ Behavioral Intentions for Integrating AI in Teaching. Journal for STEM Education Research DOI link |
42 | AI-supported teaching in early childhood shows promise but faces limitations in data privacy, technical challenges, and ethical concerns. | Iris Heung Yue Yim, Rupert Wegerif (2024). Teachers' perceptions, attitudes, and acceptance of artificial intelligence (AI) educational learning tools: An exploratory study on AI literacy for young students. Future in Educational Research DOI link |
43 | Chatbot interaction frequency affects learning autonomy differently by user preference, with social presence mediating positive effects for companionship and undermining effects for knowledge seekers. | Carlos Díaz-Sánchez, Diego Chapinal-Heras (2023). Use of Open Access AI in teaching classical antiquity. A methodological proposal. The journal of classics teaching DOI link |
44 | AI can promote inclusive, personalized learning and accessibility, but careful implementation is needed to address quality, privacy, and equity concerns. | Lucrezia Crescenzi Lanna (2022). Literature review of the reciprocal value of artificial and human intelligence in early childhood education. Journal of Research on Technology in Education DOI link |
45 | Universities should foster transdisciplinary digital literacy to prepare students for AI-driven labor markets and promote critical engagement with generative AI. | Zehang Xie, Xinzhu Wu, Yunxiang Xie (2024). Can interaction with generative artificial intelligence enhance learning autonomy? A longitudinal study from comparative perspectives of virtual companionship and knowledge acquisition preferences. Journal of Computer Assisted Learning DOI link |
46 | AI-supported microteaching and avatar simulations offer scalable, immersive professional development opportunities for pre-service teachers. | Olabisi Oluwakemi Adeleye, Chima Abimbola Eden, Idowu Sulaimon Adeniyi (2024). Innovative teaching methodologies in the era of artificial intelligence: A review of inclusive educational practices. World Journal of Advanced Engineering Technology and Sciences DOI link |
47 | Some professors view ChatGPT as a tool to teach students how to engage with AI rather than ban it, emphasizing educator responsibility in assessment design. | Vera Dianova, Mario D. Schultz (2023). Discussing ChatGPT’s implications for industry and higher education: The case for transdisciplinarity and digital humanities. Industry and Higher Education DOI link |
48 | AI-based translation teaching using NMT and SMT improved translation accuracy and student performance, achieving high reported accuracy and teacher satisfaction. | Udan Kusmawan (2023). Redefining Teacher Training: The Promise of AI-Supported Teaching Practices. Journal of Advances in Education and Philosophy DOI link |
49 | Bibliometric analysis shows rapid growth and collaboration in research on AI and teaching, with trending topics including ChatGPT, machine learning, and emotion recognition. | Chun-Mei Chou, Tsu-Chi Shen, Tsu-Chuan Shen, Chien-Hua Shen (2024). Developing and validating an AI-supported teaching applications’ self-efficacy scale. Research and Practice in Technology Enhanced Learning DOI link |
50 | An AI-based TPACK program improved pre-service teachers' AI-convergence teaching capabilities, notably PCK and overall TPACK. | Michael Singh (2023). Maintaining the integrity of the South African university: The impact of ChatGPT on plagiarism and scholarly writing. South African Journal of Higher Education DOI link |
51 | An AI system for intraoperative landmark identification improved surgeons' annotations and confidence, potentially reducing bile duct injury risk. | Yu Yuxiu (2024). Application of translation technology based on AI in translation teaching. Systems and Soft Computing DOI link |
52 | Teachers' trust in AI-based teaching analysis systems increases perceived usefulness and willingness to use them, while evaluation anxiety reduces ease of use and adoption. | Malinka Ivanova, Gabriela Grosseck, Carmen Holotescu (2024). Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching. Informatics DOI link |
53 | An AI-embedded architectural teaching model positively affected student learning, innovation, and efficiency, though students used AI fragmentedly. | Seong-Won Kim (2024). Development of a TPACK Educational Program to Enhance Pre-service Teachers’ Teaching Expertise in Artificial Intelligence Convergence Education. International Journal on Advanced Science Engineering and Information Technology DOI link |
54 | AI enables personalized, immersive educational resources and multilingual accessibility but raises concerns about data quality, privacy, and equitable access. | Giselle Ferreira, Márcio Silveira Lemgruber, Thiago Cabrera (2023). From Didachography to AI: Metaphors Teaching is Automated by. Journal of Interactive Media in Education DOI link |
55 | AI and training can improve MRI image quality assessment in prostate cancer diagnostics, supporting implementation of quality initiatives along the diagnostic pathway. | Yuichi Endo, Tatsushi Tokuyasu, Yasuhisa Mori, Koji Asai, Akiko Umezawa, Masahiro Kawamura, Atsuro Fujinaga, Aika Ejima, MISAKO KIMURA, Masafumi Inomata (2023). Impact of AI system on recognition for anatomical landmarks related to reducing bile duct injury during laparoscopic cholecystectomy. Surgical Endoscopy DOI link |
56 | ESL engineering students generally view AI-assisted English learning positively but report issues with app quality, calling for further research into classroom use. | Mengke Wang, Zengzhao Chen, Qinxue Liu, Xian Peng, Taotao Long, Yawen Shi (2024). Understanding teachers’ willingness to use artificial intelligence-based teaching analysis system: extending TAM model with teaching efficacy, goal orientation, anxiety, and trust. Interactive Learning Environments DOI link |
57 | AI offers personalized, adaptive teaching and assessment opportunities but requires ethical, equitable, and human-centered implementation to realize benefits. | Shitao Jin, Huijun Tu, Jiangfeng Li, Yuwei Fang, Qu Zhang, Fan Xu, Kun Liu, Yiquan Lin (2024). Enhancing Architectural Education through Artificial Intelligence: A Case Study of an AI-Assisted Architectural Programming and Design Course. Buildings DOI link |
58 | Integrating AI into technical higher education can enhance power supply fundamentals teaching through simulations and adaptive systems to prepare a skilled workforce. | Carlos Alberto Gómez Cano, Ana Lucía Colala Troya (2023). Artificial Intelligence applied to teaching and learning processes. LatIA DOI link |
59 | Combining IoT and AI in college physical education can improve teaching efficiency and quality through optimized neural network models. | Alexandre Woernle, Cameron Englman, Louise Dickinson, Alex Kirkham, Shonit Punwani, Aiman Haider, Alex Freeman, Veeru Kasivisivanathan, Mark Emberton, John Hines, Caroline M. Moore, Clare Allen, Francesco Giganti (2023). Picture Perfect: The Status of Image Quality in Prostate MRI. Journal of Magnetic Resonance Imaging DOI link |
60 | AI integration in power mechanical engineering teaching needs a dedicated platform and improved teacher knowledge to drive classroom reform. | N Moulieswaran, Prasantha Kumar N S (2023). Investigating ESL Learners’ Perception and Problem towards Artificial Intelligence (AI) -Assisted English Language Learning and Teaching. World Journal of English Language DOI link |
61 | A multimodal generative AI clinical narrative boosted medical students' engagement and short-term retention in pharmacology compared to traditional cases. | Dr Seema Yadav (2024). NAVIGATING THE LANDSCAPE OF AI INTEGRATION IN EDUCATION: OPPORTUNITIES, CHALLENGES, AND ETHICAL CONSIDERATIONS FOR HARNESSING THE POTENTIAL OF ARTIFICIAL INTELLIGENCE (AI) FOR TEACHING AND LEARNING. BSSS Journal of Computer DOI link |
62 | Teachers report pedagogical benefits from AI tools but face technical, resource, and readiness challenges requiring professional development and supportive policies. | Numon N. Niyozov, Salamat Saburov, Shaxruz Ganiyev, Shirinboy Sharofovich Olimov (2023). AI-powered learning: revolutionizing technical higher education institutions through advanced power supply fundamentals. E3S Web of Conferences DOI link |
63 | Training with AI software did not significantly improve dental students' proximal caries detection overall, and tooth overlap reduces detection accuracy. | Hongtao Yu, Yang Mi (2023). Application Model for Innovative Sports Practice Teaching in Colleges Using Internet of Things and Artificial Intelligence. Electronics DOI link |
64 | AI automated feedback tools can be reframed to develop students' feedback literacy and foster partnerships between students and teachers. | James C. Liao (2022). Teaching Methods of Power Mechanical Engineering Based on Artificial Intelligence. Kinetic Mechanical Engineering DOI link |
65 | AI language models can transform education through content creation and personalization but raise ethical, bias, transparency, and privacy concerns that require institutional strategies. | Tyler Bland (2024). Enhancing Medical Student Engagement Through Cinematic Clinical Narratives: A Multimodal Generative AI-Based Teaching Method (Preprint). JMIR Medical Education DOI link |
66 | AI can enhance college English listening and speaking courses by enabling personalized, interactive learning that boosts engagement and outcomes. | Neda Arvin, Masuod Hoseinabady, Bita Bayat, Esmat Zahmatkesh (2023). Teacher Experiences with AI-based Educational Tools DOI link |
67 | A learning circle increased librarians' AI knowledge and confidence to teach AI topics, highlighting opportunities and concerns about AI's impact on libraries. | Lars Schropp, Anders Peter Sejersdal Sørensen, Hugh Devlin, Louise Hauge Matzen (2023). Use of artificial intelligence software in dental education: A study on assisted proximal caries assessment in bitewing radiographs. European Journal Of Dental Education DOI link |
68 | AI use in teaching positively affects students' innovative behavior and well-being via positive emotions, moderated by students' trust in AI. | Laura Tubino, Chie Adachi (2022). Developing feedback literacy capabilities through an AI automated feedback tool. ASCILITE Publications DOI link |
69 | Stefan Popenici argues universities must adapt curricula and digital literacy to critically engage with AI's societal and labor-market impacts. | Amal Alrayes, Tara Henari, Dalal Abdulkarim Ahmed (2024). ChatGPT in Education – Understanding the Bahraini Academics Perspective. The Electronic Journal of e-Learning DOI link |
70 | Case studies of 'centaur' teachers show generative AI augments teacher labor for planning, instruction, and assessment but raises privacy and integrity concerns. | Yun Luo (2024). Innovative research on AI-assisted teaching models for college English listening and speaking courses. Applied and Computational Engineering DOI link |
71 | AI tools like ChatGPT, MathGPT, and Wolfram Alpha can act as virtual tutors to improve calculus understanding and problem-solving through iterative prompting. | Karolina Andersdotter (2023). Artificial intelligence literacy in libraries. Journal of Information Literacy DOI link |
72 | Vietnamese middle school teachers are aware of AI-based instructional technology but actual implementation is low, needing infrastructure and teacher training. | Ke Ma, Yan Zhang, Bei-He Hui (2024). How Does AI Affect College? The Impact of AI Usage in College Teaching on Students’ Innovative Behavior and Well-Being. Behavioral Sciences DOI link |
73 | Systematic review finds teacher training for AI is hampered by low motivation; effective programs should be motivating, customized, and hands-on with current technologies. | Ştefan Popenici, Jürgen Rudolph, Shannon Tan, Samson Tan (2023). A critical perspective on generative AI and learning futures. An interview with Stefan Popenici. Journal of Applied Learning & Teaching DOI link |
74 | AI trainers can reduce gender bias in teaching outcomes by providing nondiscriminatory, interactive instruction that narrows gender gaps. | William J. Fassbender (2024). “I can almost recognize its voice”: AI and its impact on ethical teacher-centaur labor. English Teaching Practice & Critique DOI link |
75 | Designing a 'Turing Teacher' for K-12 must address stakeholder needs, collaboration with human teachers, adaptability, and bridging the digital divide. | Roberto Carlos Torres-Peña, Darwin Peña González, Ellery Chacuto-López, Edwan Anderson Ariza Echeverri, Diego Vergara (2024). Updating Calculus Teaching with AI: A Classroom Experience. Education Sciences DOI link |
76 | AI supports inclusive education by improving performance and accessibility but faces technical, pedagogical, and data limitations requiring policy responses. | Nguyen Minh Giam, Nam Nguyen, Nguyễn Thị Hương Giang (2022). Situation and Proposals for Implementing Artificial Intelligence-based Instructional Technology in Vietnamese Secondary Schools. International Journal of Emerging Technologies in Learning (iJET) DOI link |
77 | Integrating the metaverse and AI in education can create immersive, personalized learning environments that enhance comprehension across disciplines. | Yousef Aljemely (2024). Challenges and best practices in training teachers to utilize artificial intelligence: a systematic review. Frontiers in Education DOI link |
78 | A FT-CNN-LSTM-AM AI method with optimizer is proposed to predict and improve primary students' math performance using AI and VR tools. | Leo Bao, Difang Huang, Chen Lin (2024). Can Artificial Intelligence Improve Gender Equality? Evidence from a Natural Experiment. Management Science DOI link |
79 | Systematic review of 99 papers synthesizes psychological perspectives on responses, attitudes, and behaviors toward GenAI in higher education classrooms. | Alexander Pelaez, Amal Jacobson, Kara Trias, Elaine R. Winston (2022). The Turing Teacher: Identifying core attributes for AI learning in K-12. Frontiers in Artificial Intelligence DOI link |
80 | Intelligent tutoring systems generally produce positive learning effects in K-12 but require longer, larger, and more diverse studies and ethical evaluation. | Gabriel Julien (2024). How Artificial Intelligence (AI) impacts inclusive education. Educational Research and Reviews DOI link |
81 | A Kantian analysis suggests intelligent tutoring systems and ChatGPT may threaten student maturity, while AI research tools can support mature learning if used responsibly. | Khalid Almeman, Faycel El Ayeb, Mouhebeddine Berrima, Brahim Issaoui, Hamdy Morsy (2025). The Integration of AI and Metaverse in Education: A Systematic Literature Review. Applied Sciences DOI link |
82 | Training with synthetic generative AI retinal images markedly improved trainee diagnostic accuracy, demonstrating synthetic data's value in medical education. | Yaping Qiu, Junjie Pan, Nor Asniza Ishak (2022). Effectiveness of Artificial Intelligence (AI) in Improving Pupils’ Deep Learning in Primary School Mathematics Teaching in Fujian Province. Computational Intelligence and Neuroscience DOI link |
83 | Lecturers in Nigerian arts faculties show moderate AI awareness and strong interest in discipline-tailored training but face technical and resource constraints. | Fan Wu, Yang Dang, Manli Li (2025). A Systematic Review of Responses, Attitudes, and Utilization Behaviors on Generative AI for Teaching and Learning in Higher Education. Behavioral Sciences DOI link |
84 | Social science fiction is a valuable creative method to imagine and critique future AIED scenarios, surfacing hopes and concerns from researchers. | Angélique Létourneau, Marion Deslandes-Martineau, Patrick Charland, Alexander-John Karran, Jared Boasen, Pierre‐Majorique Léger (2025). A systematic review of AI-driven intelligent tutoring systems (ITS) in K-12 education. npj Science of Learning DOI link |
85 | Mixed-methods analysis suggests AI implementation can increase engagement, GPA, and innovation metrics, but longitudinal and ethical research is needed. | Alice Watanabe (2024). Have Courage to Use your Own Mind, with or without AI: The Relevance of Kant's Enlightenment to Higher Education in the Age of Artificial Intelligence. The Electronic Journal of e-Learning DOI link |
86 | An AI-assisted English teaching system preserved or improved student grades and correlated engagement with learning gains, supporting its effectiveness. | Hitoshi Tabuchi, Justin Engelmann, Fumiatsu Maeda, Ryo Nishikawa, Toshihiko Nagasawa, Tomofusa Yamauchi, Mao Tanabe, Masahiro Akada, Keita Kihara, Yasuyuki Nakae, Yoshiaki Kiuchi, Miguel O. Bernabéu (2024). Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images. British Journal of Ophthalmology DOI link |
87 | Voice recognition devices like Alexa can support deep language learning and engagement in EFL contexts, warranting further statistical research. | Abdulrahman Burour Ibrahim (2024). Assessing the Knowledge and Perception of Artificial Intelligence for Teaching and Research among Lecturers in the Faculties of Arts in Nigeria. Journal of Global Research in Education and Social Science DOI link |
88 | AI algorithms applied to online PE teaching are underutilized in higher education, resulting in inefficient instruction and low student motivation. | Iosif Gidiotis, Stefan Hrastinski (2024). Imagining the future of artificial intelligence in education: a review of social science fiction. Learning Media and Technology DOI link |
89 | AI has transformative potential for STEM education through personalized tutoring and analytics but faces evidence, equity, and training challenges. | Mark Treve (2024). Integrating Artificial Intelligence in Education: Impacts on Student Learning and Innovation. International Journal of Vocational Education and Training Research DOI link |
90 | AI detection tools risk false positives; educators should adopt growth-oriented responses and use detection cautiously due to uncertainty in identification. | Junli Yu, Lirong Wang (2024). Research on the Integration Path and Practice of AI Intelligent Technology and English Teaching Reform in Higher Vocational Colleges and Universities. Applied Mathematics and Nonlinear Sciences DOI link |
91 | Teachers adopt different pedagogical orientations with an AI-enabled inquiry ITS, affecting feature use and perceptions of AI as support versus collaborator. | Iman Oraif (2023). Natural Language Processing (NLP) and EFL Learning: A Case Study Based on Deep Learning. Journal of Language Teaching and Research DOI link |
92 | Students use ChatGPT mainly for information gathering motivated by convenience and can identify unethical academic uses, informing AI policy development. | Yujia Wang (2023). Exploration on the Operation Status and Optimization Strategy of Networked Teaching of Physical Education Curriculum Based on AI Algorithm. International Journal of Information Technologies and Systems Approach DOI link |
93 | AI has potential to address South African higher education challenges but requires infrastructure, skills, equity, and ethical safeguards for effective adoption. | Mohammad Aniq Bin Amdan, Naldo Janius, Mohd Aidil Hazidi Bin Kasdiah (2024). Concept paper: Efficiency of Artificial Intelligence (AI) tools For STEM Education In Malaysia. International Journal of Science and Research Archive DOI link |
94 | Among private school teachers in Azerbaijan, perceived usefulness, institutional policy, colleague use, and younger age predict AI adoption more than ease of use or innovativeness. | Gary D. Fisk (2024). AI or Human? Finding and Responding to Artificial Intelligence in Student Work. Teaching of Psychology DOI link |
95 | AI impacts online assessments and teaching by offering adaptive methods and real-time feedback but raises concerns about privacy, bias, and fairness requiring pedagogical integration. | Lehong Shi, Ai-Chu Elisha Ding, Ikseon Choi (2024). Investigating Teachers’ Use of an AI-Enabled System and Their Perceptions of AI Integration in Science Classrooms: A Case Study. Education Sciences DOI link |
Method
We queried OpenAlex for English-language journal articles matching the phrase AI in teaching in titles or abstracts published between 2022 and 2025. Articles with fewer than 5 citations or flagged as paratexts (e.g., editorials, corrections, retractions) were first excluded. From the remaining set, the 100 most topical and influential abstracts were selected using a hybrid scoring scheme with α = 0.50, assigning equal weight to textual relevance and citation influence.
Abstracts were taken from OpenAlex when available and enriched via Europe PMC or Crossref where necessary. Texts were normalized—for example, removing a leading “Abstract”—and records without usable abstracts were discarded.
The remaining abstracts were embedded in a semantic space, clustered to identify global themes, and labeled by a large language model (LLM). The approach is multi-label, allowing one abstract to belong to several themes. The percentages shown in this report represent the share of abstracts mentioning each theme.
For each theme, LLMs were deployed to compute a topical relevance score between the theme and every abstract. Abstracts with zero relevance to a given theme were omitted from that theme’s list, and abstracts scoring below the midpoint across all theme scores were excluded entirely to remove off-topic material (for example, papers using “AI in teaching” in unrelated contexts).
After filtering, the final dataset included 95 abstracts most substantively related to AI in teaching. These form the basis for the key themes and relevance-ranked study summaries presented in this report.
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Metadata
Version: Text Response Hub v.2.01 • AI Engine: GPT-5-mini • Snapshot date: Oct 21, 2025
Disclaimer
This analysis extracts patterns in research abstracts using AI methods and may miss nuance; interpretations are subjective. Results are provided “as is,” without warranties, and should be evaluated alongside other evidence. See Method for scope, assumptions, and limitations.