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Research Synthesis Report
AI in Learning: Trends, Applications, Benefits, and Key Concerns
ANALYZER:Text Response Hub v.2.01
AI ENGINE:GPT-5-mini
REPORT DATE:Oct 22, 2025
Overview
Report Details:
Joel Vuolevi•
Text Response Hub
Text Response HubResearch Abstracts
English
Corpus:
Most topical and influential research abstracts on AI in learning.
Number of abstracts: 86
Publication period: 2022 - 2025
Snapshot date: Oct 22, 2025
Keywords:
- artificial intelligence
- adaptive learning
- concerns for AI
- learning analytics
- personalization
Key Themes (Synthesis)
Global insights extracted across all abstracts
47%
AI in education: applications, tools, and pedagogical integration across K-12, higher education, teacher training and lifelong learning
33%
Personalized and adaptive learning enabled by AI (tutors, adaptive pathways, learning analytics)
30%
Ethics, bias, privacy, trust and governance concerns for AI deployments
18%
Generative AI and ChatGPT: impacts, opportunities and challenges for writing, assessment and instruction
18%
AI in medicine and healthcare: diagnostics, clinical decision support, pathology and clinical workflows
16%
Assessment, academic integrity and trustworthy evaluation with AI (proctoring, detection, redesigning assessments)
15%
AI applied to networks, industry and infrastructure (6G, Industry 4.0/5.0, IoT, digital twins)
12%
Explainability, interpretability and XAI techniques to increase transparency and adoption
10%
AI for language learning and NLP-powered speaking/writing tools
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 | Proposes a common language and frameworks (detect-diagnose-act; six levels of automation) to guide interdisciplinary, stakeholder-inclusive AI integration in education focusing on augmentation and hybrid intelligence. | Inge Molenaar (2022). Towards hybrid <scp>human‐AI</scp> learning technologies. European Journal of Education DOI link |
2 | Reviews AI language learning tools, highlighting personalization, efficiency, and future integration with VR/AR while noting needs for human interaction and large data. | Roxana Rebolledo Font de la Vall, Fabián Avelino González Araya (2023). Exploring the Benefits and Challenges of AI-Language Learning Tools. The International Journal of Social Sciences and Humanities Invention DOI link |
3 | Analyzes adoption of AI-based learning outcomes in Saudi higher education, finding nascent but transformative potential and a need for faculty technical upskilling to meet Vision 2030. | Nayef Shaie Alotaibi, Awad Hajran Alshehri (2023). Prospers and Obstacles in Using Artificial Intelligence in Saudi Arabia Higher Education Institutions—The Potential of AI-Based Learning Outcomes. Sustainability DOI link |
4 | Identifies factors from UTAUT and perceived risk influencing college students' willingness to accept AI-assisted learning, with expectancy and social influence positive and psychological risk negative. | Wentao Wu, Ben Zhang, Shuting Li, Hehai Liu (2022). Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory. Frontiers in Psychology DOI link |
5 | Highlights ethical concerns and multiple sources of bias in medical/pathology AI-ML systems and calls for comprehensive evaluation from development to deployment to ensure fairness and transparency. | Matthew G. Hanna, Liron Pantanowitz, Brian Jackson, Octavia M. Peck Palmer, Shyam Visweswaran, Joshua Pantanowitz, Mustafa Deebajah, Hooman H. Rashidi (2024). Ethical and Bias Considerations in Artificial Intelligence (AI)/Machine Learning. Modern Pathology DOI link |
6 | Systematic review finds ChatGPT can enhance academic and librarian tasks in higher education but raises ethical concerns and potential impacts on critical thinking and job roles. | Alfonso Renato Vargas-Murillo, Ilda Nadia Monica de la Asunción Pari-Bedoya, Francisco de Jesús Guevara-Soto (2023). Challenges and Opportunities of AI-Assisted Learning: A Systematic Literature Review on the Impact of ChatGPT Usage in Higher Education. International Journal of Learning Teaching and Educational Research DOI link |
7 | Argues for integrating mobility, interactivity, AI, and immersive technologies into a mobile-interactive pedagogical paradigm centered on intelligent tutoring systems for democratized, personalized learning. | Ashraf Alam, Atasi Mohanty (2023). Educational technology: Exploring the convergence of technology and pedagogy through mobility, interactivity, AI, and learning tools. Cogent Engineering DOI link |
8 | Pilots ChatGPT writing an academic paper, showing efficiency and coherence, and argues education should shift toward creativity and critical thinking with AI-involved learning tasks and new assessments. | Shanaka Kristombu Baduge, P.S.M. Thilakarathna, Jude Shalitha Perera, Mehrdad Arashpour, P. Sharafi, Bertrand Teodosio, Ankit Shringi, Priyan Mendis (2022). Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications. Automation in Construction DOI link |
9 | Develops an AI-based learning style prediction and collaborative filtering recommender for primary students, improving material matching and learning performance with satisfactory RMSE. | Xiaoming Zhaı (2022). ChatGPT User Experience: Implications for Education. SSRN Electronic Journal DOI link |
10 | Discusses ChatGPT and large language models as potential virtual teaching assistants in medical education, urging research on impacts, ethics, curriculum and assessment integration. | Bens Pardamean, Teddy Suparyanto, Tjeng Wawan Cenggoro, Digdo Sudigyo, Andri Anugrahana (2022). AI-Based Learning Style Prediction in Online Learning for Primary Education. IEEE Access DOI link |
11 | Critical review finds vague definitions and two dominant discourses (imperative change; altering authority) in AI literature in higher education and calls for research on social implications and accountability. | Hyunsu Lee (2023). The rise of <scp>ChatGPT</scp>: Exploring its potential in medical education. Anatomical Sciences Education DOI link |
12 | Systematic review of Deepfake detection methods (2018–2020) groups approaches and finds deep learning methods outperform others while discussing datasets and challenges. | Mohsen Soori, Behrooz Arezoo, Roza Dastres (2023). Artificial intelligence, machine learning and deep learning in advanced robotics, a review. Cognitive Robotics DOI link |
13 | Scoping review of AI in early childhood education finds limited but positive studies showing AI can improve childrens' AI concepts, creativity, collaboration, and computational thinking, with future research directions. | Annamma Joy, Ying Zhu, Camilo Peña, Myriam Brouard (2022). Digital future of luxury brands: Metaverse, digital fashion, and non‐fungible tokens. Strategic Change DOI link |
14 | Reviews how CADD combined with AI/ML/DL accelerates drug discovery, detailing in silico tools, ML/DL applications, and stages from target ID to clinical trial design. | Margaret Bearman, Juliana Ryan, Rola Ajjawi (2022). Discourses of artificial intelligence in higher education: a critical literature review. Higher Education DOI link |
15 | Mixed-methods study finds ChatGPT-assisted instruction improved Chinese EFL students' writing skills and motivation, with qualitative concerns about accuracy and over-reliance. | Md. Shohel Rana, Mohammad Nur Nobi, Beddhu Murali, Andrew H. Sung (2022). Deepfake Detection: A Systematic Literature Review. IEEE Access DOI link |
16 | Proposes an AI pipeline that auto-generates narrative fragments (overviews and reflection quizzes) using semantic models and GPT-2 to increase engagement and adaptability in learning pathways. | Jiahong Su, Weipeng Yang (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education Artificial Intelligence DOI link |
17 | Systematic review of AI and learning analytics in teacher education finds focus on teacher behaviors and competencies, prevalent use of ML, limited ethical clearance reporting, and varied data sources. | Fan Ouyang, Mian Wu, Luyi Zheng, Liyin Zhang, Pengcheng Jiao (2023). Integration of artificial intelligence performance prediction and learning analytics to improve student learning in online engineering course. International Journal of Educational Technology in Higher Education DOI link |
18 | Qualitative content analysis of social media finds early adopters use ChatGPT across education sectors, noting themes of productivity and ethics and mixed attitudes about dependence and critical thinking. | Divya Vemula, Perka Jayasurya, Varthiya Sushmitha, Yethirajula Naveen Kumar, Vasundhra Bhandari (2022). CADD, AI and ML in drug discovery: A comprehensive review. European Journal of Pharmaceutical Sciences DOI link |
19 | Editorial notes image generation by Midjourney and ChatGPT screenshot and discloses contributors and affiliations. | Cuiping Song, Yanping Song (2023). Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in Psychology DOI link |
20 | Narrative review highlights potential clinical and public health applications of AI in infection management but notes limited real-world validation and ethical, transparency, and bias concerns. | Chaitali Diwan, Srinath Srinivasa, Gandharv Suri, Saksham Agarwal, Ram Prasad (2022). AI-based learning content generation and learning pathway augmentation to increase learner engagement. Computers and Education Artificial Intelligence DOI link |
21 | Reviews AI-enabled routing and learning-based protocols for UAV networks, emphasizing topology prediction, self-adaptation, datasets, and challenges in connectivity, security, and energy efficiency. | Sdenka Zobeida Salas‐Pilco, Kejiang Xiao, Xinyun Hu (2022). Artificial Intelligence and Learning Analytics in Teacher Education: A Systematic Review. Education Sciences DOI link |
22 | Introduces a special issue on empowering learners for the age of AI, identifying themes like explainability, assessment, design, ethics, data ownership, and AI literacies in education research and policy. | Li‐Tao Zhu, Xizhong Chen, Bo Ouyang, Wei‐Cheng Yan, He Lei, Zhe Chen, Zheng‐Hong Luo (2022). Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors. Industrial & Engineering Chemistry Research DOI link |
23 | Large-scale RCT on AI assistance in peer feedback suggests students rely on AI rather than learn from it; self-regulation helps fill gaps but is less effective than AI, raising concerns about student agency. | 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 (2023). ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions. Computers in Human Behavior Artificial Humans DOI link |
24 | Reviews 6G vision, enabling technologies (AI, THz, VLC, blockchain, post-quantum crypto) and security/privacy challenges, proposing architecture and trustworthiness solutions. | Jonathan B. Singer, Johanna Creswell Báez, Juan A. Rios (2023). AI Creates the Message: Integrating AI Language Learning Models into Social Work Education and Practice. Journal of Social Work Education DOI link |
25 | Reviews AI adoption in dentistry, mainly for image-based diagnosis, and discusses data constraints, relationship with evidence-based dentistry, and potential to assist clinical workflows. | Anastasia A Theodosiou, Robert C. Read (2023). Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician. Journal of Infection DOI link |
26 | Qualitative descriptive study reports strong student agreement on AI's importance and potential as virtual tutors but most students disagree that AI can replace teachers. | Arnau Rovira-Sugranes, Abolfazl Razi, Fatemeh Afghah, Jacob Chakareski (2022). A review of AI-enabled routing protocols for UAV networks: Trends, challenges, and future outlook. Ad Hoc Networks DOI link |
27 | Reviews AI applications in liver transplantation for donor-recipient matching, survival prediction, and post-transplant management while acknowledging limitations like data imbalance and privacy. | Dragan Gašević, George Siemens, Shazia Sadiq (2023). Empowering learners for the age of artificial intelligence. Computers and Education Artificial Intelligence DOI link |
28 | Comprehensive review of AI methods optimizing renewable energy systems covering forecasting, monitoring, control, grid integration, and future trends like explainable AI and reinforcement learning. | Ali Darvishi, Hassan Khosravi, Shazia Sadiq, Dragan Gašević, George Siemens (2023). Impact of AI assistance on student agency. Computers & Education DOI link |
29 | Reviews how ML/DL tools and big data have rationalized drug discovery, detailing DL tools for target ID, structure prediction, de novo design, ADMET, and clinical trial assistance with challenges and prospects. | Shimaa A. Abdel Hakeem, Hanan Hussein, HyungWon Kim (2022). Security Requirements and Challenges of 6G Technologies and Applications. Sensors DOI link |
30 | Case study of ChatGPT-3.5 in an engineering course shows potential benefits for student learning and assessment preparation but emphasizes need for training on effective interaction and integrity considerations. | Hao Ding, Jiamin Wu, Wuyuan Zhao, JP Matinlinna, Michael F. Burrow, James Kit Hon Tsoi (2023). Artificial intelligence in dentistry—A review. Frontiers in Dental Medicine DOI link |
31 | Review outlines AI's transformative effects on personalized learning, teaching methods, assessment, and administration while noting challenges like privacy, bias, and teacher training needs. | Muh. Putra Pratama, Rigel Sampelolo, Hans Lura (2023). REVOLUTIONIZING EDUCATION: HARNESSING THE POWER OF ARTIFICIAL INTELLIGENCE FOR PERSONALIZED LEARNING. KLASIKAL JOURNAL OF EDUCATION LANGUAGE TEACHING AND SCIENCE DOI link |
32 | Survey and empirical comparison of CNN-based intrusion detection systems organizes approaches, datasets, architectures, and metrics, noting comparability issues and presenting experimental comparisons on standard datasets. | Michael B. Wallace, Prateek Sharma, Pradeep Bhandari, James E. East, Giulio Antonelli, Roberto Lorenzetti, M Vieth, Ilaria Speranza, Marco Spadaccini, Madhav Desai, Frank Lukens, Genci Babameto, Daisy Batista, Davinder Singh, William C. Palmer, Francisco C. Ramirez, Rebecca Palmer, Tisha Lunsford, Kevin Ruff, Elizabeth Bird-Liebermann, Victor Ciofoaia, Sophie Arndtz, David J. Cangemi, Kirsty Puddick, Gregory A. Derfus, Amitpal S. Johal, Mohammed Barawi, L. Longo, Luigi Moro, Alessandro Repici, Cesare Hassan (2022). Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia. Gastroenterology DOI link |
33 | Presents Industry 4.0 pillar technologies (including AI, IoT, robotics, AR/VR, blockchain) and foundation technologies, proposing a model factory integrating these for modern manufacturing. | Mamatha Bhat, Madhumitha Rabindranath, Beatriz Sordi Chara, Douglas A. Simonetto (2023). Artificial intelligence, machine learning, and deep learning in liver transplantation. Journal of Hepatology DOI link |
34 | Reviews federated learning for medical applications, highlighting privacy-preserving distributed model training, statistical/device/security challenges, and promise for generalizable diagnostic tools. | Kingsley Ukoba, Kehinde O. Olatunji, Eyitayo Adeoye, Tien‐Chien Jen, Daniel M. Madyira (2024). Optimizing renewable energy systems through artificial intelligence: Review and future prospects. Energy & Environment DOI link |
35 | Discusses AI/ML integration for future IoT and 6G-enabled networks to improve energy efficiency, security, and services across smart domains and identifies open research challenges. | Sagorika Nag, Anurag T. K. Baidya, Abhimanyu Mandal, Alen T. Mathew, Bhanuranjan Das, Bharti Devi, Rajnish Kumar (2022). Deep learning tools for advancing drug discovery and development. 3 Biotech DOI link |
36 | Analyzes doctoral students' interaction patterns with GAI writing assistants, finding iterative, interactive collaboration yields better writing performance than linear, supplementary use. | Thanh Trung Pham, Thanh Nguyen, Son Tung Ha, Ngoc Thanh Nguyen Ngoc (2023). Digital transformation in engineering education: Exploring the potential of AI-assisted learning. Australasian Journal of Educational Technology DOI link |
37 | Thematic analysis shows Fintech, including blockchain and AI, transforms banking with opportunities for efficiency and risks like job loss and security concerns, requiring regulation and collaboration. | Oseremi Onesi-Ozigagun, Yinka James Ololade, Nsisong Louis Eyo-Udo, Damilola Oluwaseun Ogundipe (2024). REVOLUTIONIZING EDUCATION THROUGH AI: A COMPREHENSIVE REVIEW OF ENHANCING LEARNING EXPERIENCES. International Journal of Applied Research in Social Sciences DOI link |
38 | Proposes seven pedagogical roles for LLMs (tutor, coach, mentor, teammate, tool, simulator, student) and recommends strategies to maintain human oversight, critical assessment, and mitigate AI risks in classrooms. | Leila Mohammadpour, Teck Chaw Ling, Chee Sun Liew, Alihossein Aryanfar (2022). A Survey of CNN-Based Network Intrusion Detection. Applied Sciences DOI link |
39 | Phenomenographic study identifies six teacher conceptions for teaching AI in K-12, from surface to deep (technology bridging to intellectual development), and suggests learning paths for teacher preparation. | Georgios Tsaramirsis, Antreas Kantaros, Izzat Al‐Darraji, Dimitrios Piromalis, Charalampos Apostolopoulos, Athanasia Pavlopoulou, Muath Alrammal, Zamhar Ismail, Seyed M. Buhari, Miloš Stojmenović, Hatem Tamimi, Princy Randhawa, Akshet Patel, Fazal Qudus Khan (2022). A Modern Approach towards an Industry 4.0 Model: From Driving Technologies to Management. Journal of Sensors DOI link |
40 | Reviews 6G visions, enabling technologies (including AI/ML, THz, IRS), services like XR and holograms, and contrasts 5G/6G while outlining future research directions. | Ashish Rauniyar, Desta Haileselassie Hagos, Debesh Jha, Jan Erik Håkegård, Ulaş Bağcı, Danda B. Rawat, Vladimir Vlassov (2023). Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions. IEEE Internet of Things Journal DOI link |
41 | Bibliometric review of 711 studies maps AI and BDA bibliometrics across disciplines, highlighting growth areas and key subject clusters and informing future research in five major domains. | Neil J. Rowan (2022). The role of digital technologies in supporting and improving fishery and aquaculture across the supply chain – Quo Vadis?. Aquaculture and Fisheries DOI link |
42 | Small survey in Albania shows no difference in critical thinking with AI exposure but finds reliance on AI negatively correlates with problem-solving skills while improving perceived academic efficiency. | M. Rezwanul Mahmood, M. A. Matin, Panagiotis Sarigiannidis, Sotirios K. Goudos (2022). A Comprehensive Review on Artificial Intelligence/Machine Learning Algorithms for Empowering the Future IoT Toward 6G Era. IEEE Access DOI link |
43 | Describes development and validation of an AI-enabled English language learning (AIELL) system for authentic mobile learning, confirming usability and identifying design improvements. | Andy Nguyen, Yvonne Hong, Belle Dang, Xiaoshan Huang (2024). Human-AI collaboration patterns in AI-assisted academic writing. Studies in Higher Education DOI link |
44 | Reviews ChatGPT applications for Industry 4.0, arguing it can enhance process optimization, human-machine interfaces, and automation across manufacturing through NLP and virtual assistants. | Parminder Varma, Shivinder Nijjer, Kiran Sood, Simon Grima, Ramona Rupeika-Apoga (2022). Thematic Analysis of Financial Technology (Fintech) Influence on the Banking Industry. Risks DOI link |
45 | Comparative study shows a generative AI chatbot (SRLbot) outperforms rule-based chatbots in enhancing secondary students’ science knowledge, engagement, motivation, and self-regulated learning habits. | Ethan Mollick, Lilach Mollick (2023). Assigning AI: Seven Approaches for Students, with Prompts. SSRN Electronic Journal DOI link |
46 | Theoretical and literature review shows AI systems can improve entrepreneurial decision-making and proposes frameworks for AI-enhanced policymaking considering contextual moderating factors. | King Woon Yau, Ching Sing Chai, Thomas K. F. Chiu, Helen Meng, Irwin King, Yeung Yam (2022). A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools. Education and Information Technologies DOI link |
47 | Literature review argues generative AI can personalize instruction, create interactive content, and adaptive assessments, but ethical concerns (privacy, bias) require collaboration for responsible integration. | Saddam Alraih, Ibraheem Shayea, Mehran Behjati, Rosdiadee Nordin, Nor Fadzilah Abdullah, Asma Abu-Samah, Dalia Nandi (2022). Revolution or Evolution? Technical Requirements and Considerations towards 6G Mobile Communications. Sensors DOI link |
48 | Reviews adoption and future directions of AI-ML platforms in pathology and medicine, highlighting impacts on diagnostics, workflows, research, ML operations, multimodal AI, and educational virtualization. | P. V. Thayyib, Rajesh Mamilla, M.Y. Khan, Humaira Fatima, Mohammed Asim, Imran Anwar, M. K. Shamsudheen, Mohd. Asif Khan (2023). State-of-the-Art of Artificial Intelligence and Big Data Analytics Reviews in Five Different Domains: A Bibliometric Summary. Sustainability DOI link |
49 | Qualitative study finds AI models act as mentors that reduce math anxiety and boost confidence by offering step-by-step personalized support, suggesting opportunities for AI-assisted psychological interventions. | Xi-Hui Jia, Jui-Che Tu (2024). Towards a New Conceptual Model of AI-Enhanced Learning for College Students: The Roles of Artificial Intelligence Capabilities, General Self-Efficacy, Learning Motivation, and Critical Thinking Awareness. Systems DOI link |
50 | Experiment shows social network–based interaction enhances effectiveness of AI speaking apps for English practice among Chinese university students, improving attitudes and speaking skills. | Eriona Çela, Mathias Fonkam, Rajasekhara Mouly Potluri (2024). Risks of AI-Assisted Learning on Student Critical Thinking. International Journal of Risk and Contingency Management DOI link |
51 | Designs and tests Learning Design Patterns to foster human-AI co-learning in a human-robot rescue task, finding improved human understanding of the robot partner but no impact on collaboration fluency or team performance. | Fenglin Jia, Daner Sun, Qing Ma, Chee‐Kit Looi (2022). Developing an AI-Based Learning System for L2 Learners’ Authentic and Ubiquitous Learning in English Language. Sustainability DOI link |
52 | Case study in Central Java shows AI tools aid academic writing planning and drafting but have limitations for Indonesian text editing; recommends feature improvements and AI literacy training. | Mohd Javaid, Abid Haleem, Ravi Pratap Singh (2023). A study on ChatGPT for Industry 4.0: Background, potentials, challenges, and eventualities. Journal of Economy and Technology DOI link |
53 | Systematic review identifies forms and drivers of academic dishonesty in online assessments and finds both technological (AI, proctoring, analytics) and pedagogical solutions can mitigate cheating and improve trustworthiness. | Davy Tsz Kit Ng, Chee Wei Tan, Jac Ka Lok Leung (2024). Empowering student self‐regulated learning and science education through <scp>ChatGPT</scp>: A pioneering pilot study. British Journal of Educational Technology DOI link |
54 | Systematic review maps AI/ML/DL applications in nutrition, covering personalized nutrition, dietary assessment, food recognition, predictive disease modeling, and highlights challenges and future directions. | Cowan Ho, Zitong Zhao, Xiu Fen Chen, Jan Sauer, Sahil Ajit Saraf, Rajasa Jialdasani, Kaveh Taghipour, Aneesh Sathe, Li-Yan Khor, Kiat‐Hon Lim, Wei Qiang Leow (2022). A promising deep learning-assistive algorithm for histopathological screening of colorectal cancer. Scientific Reports DOI link |
55 | Reviews biodiesel, nanofluids, and AI/ML integration for improving internal combustion engine performance, discussing environmental benefits, optimization, and future research perspectives. | Navaneetha Krishnan Rajagopal, Naila Iqbal Qureshi, S. Durga, Edwin Ramírez-Asís, Rosario Huerta-Soto, Shashi Kant Gupta, Sukheja Deepak (2022). Future of Business Culture: An Artificial Intelligence‐Driven Digital Framework for Organization Decision‐Making Process. Complexity DOI link |
56 | Provides a practical guide for medical educators on reading, conducting, and evaluating AI research in medical education, defining terminology and matching problems/data suited for AI. | Kadaruddin Kadaruddin (2023). Empowering Education through Generative AI: Innovative Instructional Strategies for Tomorrow's Learners. International Journal of Business Law and Education DOI link |
57 | Comprehensive review of AI/ML/DL in clinical virology highlights improved diagnostics, sequencing, drug discovery, and outbreak prediction, while addressing data security, bias, and ethical challenges. | Matthew G. Hanna, Liron Pantanowitz, Rajesh Dash, James H. Harrison, Mustafa Deebajah, Joshua Pantanowitz, Hooman H. Rashidi (2025). Future of Artificial Intelligence (AI) - Machine Learning (ML) Trends in Pathology and Medicine. Modern Pathology DOI link |
58 | Contextual review outlines AI/ML roles and 39 emerging technologies for precision crop protection in Ag5.0, detailing taxonomies, case studies, and future perception-based decision systems. | Hermie V. Inoferio, Marcelino Espartero, Masnona Asiri, Michelle Damin, Jason V. Chavez (2024). Coping with math anxiety and lack of confidence through AI-assisted Learning. Environment and Social Psychology DOI link |
59 | Systematic mapping of K-12 emerging technology education (AI, ML, IoT, AR, VR) identifies fragmented research and calls for inter-/transdisciplinary agendas centered on human-centered HCI approaches. | Bin Zou, Xin Guan, Yinghua Shao, Peng Chen (2023). Supporting Speaking Practice by Social Network-Based Interaction in Artificial Intelligence (AI)-Assisted Language Learning. Sustainability DOI link |
60 | Defines Sustainability 4.0 as applying AI, IoT, MV, AM, and other technologies for resource-efficient, inclusive manufacturing and outlines technologies and applications to achieve sustainable production. | Tjeerd Schoonderwoerd, Emma M. van Zoelen, Karel Van den Bosch, Mark A. Neerincx (2022). Design patterns for human-AI co-learning: A wizard-of-Oz evaluation in an urban-search-and-rescue task. International Journal of Human-Computer Studies DOI link |
61 | Systematic review of AI-based crop disease detection highlights vision-centered approaches, dataset limitations, model trends (transfer learning, attention CNNs), and need for lightweight robust models for field use. | 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 |
62 | Survey of Canadian medical students finds strong belief that AI will affect medicine and should be taught, but formal AI education is largely absent from curricula. | Ence Surahman, Tzu‐Hua Wang (2022). Academic dishonesty and trustworthy assessment in online learning: A systematic literature review. Journal of Computer Assisted Learning DOI link |
63 | Quasi-experimental study shows AI-assisted digital art training (outline recognition, color matching, AR) can improve imagination and painting performance in elementary students. | Tagne Poupi Theodore Armand, Kintoh Allen Nfor, Jung-In Kim, Hee‐Cheol Kim (2024). Applications of Artificial Intelligence, Machine Learning, and Deep Learning in Nutrition: A Systematic Review. Nutrients DOI link |
64 | Demonstrates using LIME to explain AI/ML employee turnover predictions, proposing a transparent framework to increase interpretability and trust for HR decision-makers. | Manzoore Elahi M. Soudagar, Sagar Shelare, Deepali Marghade, Pramod Belkhode, Mohammad Nur‐E‐Alam, Tiong Sieh Kiong, S. Ramesh, Armin Rajabi, Harish Venu, T. M. Yunus Khan, M.A. Mujtaba, Kiran Shahapurkar, M.A. Kalam, I.M. Rizwanul Fattah (2024). Optimizing IC engine efficiency: A comprehensive review on biodiesel, nanofluid, and the role of artificial intelligence and machine learning. Energy Conversion and Management DOI link |
65 | Examines AI-driven learning analytics in STEM education, highlighting curriculum paradigms, benefits, obstacles, ethical concerns, and the need for responsible data-driven practices. | Martin G. Tolsgaard, Martin Pusic, Stefanie S. Sebok‐Syer, Brian C. Gin, Morten Bo Søndergaard Svendsen, Mark D. Syer, Ryan Brydges, Monica M. Cuddy, Christy Boscardin (2023). The fundamentals of Artificial Intelligence in medical education research: AMEE Guide No. 156. Medical Teacher DOI link |
66 | Comparative review of vision-based human activity recognition surveys deep learning (CNN/RNN) methods, datasets, taxonomies, and future challenges for HAR applications. | Abhishek Padhi, Ashwini Agarwal, Shailendra K. Saxena, C.D.S. Katoch (2023). Transforming clinical virology with AI, machine learning and deep learning: a comprehensive review and outlook. VirusDisease DOI link |
67 | Historical analysis of intelligent tutoring systems shows their evolution, identity shifts, and reconception from student aids to teacher-student learning supports to enable commercialization. | Gustavo A. Mesías-Ruiz, María Pérez‐Ortiz, José Dorado, Ana Isabel de Castro, José M. Peña (2023). Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review. Frontiers in Plant Science DOI link |
68 | Reviews AI in cardiology, highlighting growing evidence of ML/DL achievements across cardiology domains and potential for AI to assume central clinical roles. | Maarten Van Mechelen, Rachel Charlotte Smith, Marie-Monique Schaper, Mariana Aki Tamashiro, Karl-Emil Kjær Bilstrup, Mille Skovhus Lunding, Marianne Graves Petersen, Ole Sejer Iversen (2022). Emerging Technologies in K–12 Education: A Future HCI Research Agenda. ACM Transactions on Computer-Human Interaction DOI link |
69 | Systematic review maps AI innovations in learning and development functions, showing AI can streamline L&D processes, assessment, and personalization while offering efficiency and scalability benefits. | Ali Darvishi, Hassan Khosravi, Shazia Sadiq, Dragan Gašević (2022). Incorporating <scp>AI</scp> and learning analytics to build trustworthy peer assessment systems. British Journal of Educational Technology DOI link |
70 | Overview of digital twin networks for 6G outlines use cases, reference architecture, data/model/interface design aspects, and a real-world Omniverse-based development example. | Mohd Javaid, Abid Haleem, Ravi Pratap Singh, Shahbaz Khan, Rajiv Suman (2022). Sustainability 4.0 and its applications in the field of manufacturing. Internet of Things and Cyber-Physical Systems DOI link |
71 | Reviews AI-assisted visual inspection techniques for cultural heritage conservation, summarizing DL-based image processing methods and case studies for damage assessment. | Wasswa Shafik, Ali Tufail, Abdallah Namoun, Liyanage C. De Silva, Rosyzie Anna Awg Haji Mohd Apong (2023). A Systematic Literature Review on Plant Disease Detection: Motivations, Classification Techniques, Datasets, Challenges, and Future Trends. IEEE Access DOI link |
72 | Mixed-methods study finds teachers generally view AI educational tools positively but face challenges in AI content knowledge, infrastructure, and potential distractions, informing PD needs. | Donghwa Lee, Hong-hyeon Kim, Seok-Hyun Sung (2022). Development research on an AI English learning support system to facilitate learner-generated-context-based learning. Educational Technology Research and Development DOI link |
73 | Hierarchical review of 6G technologies emphasizes AI/ML, terahertz, quantum communication, and reconfigurable surfaces as enablers of intelligent self-optimizing networks and highlights deployment challenges. | Aidan Pucchio, Raahulan Rathagirishnan, Natasha Caton, Peter Gariscsak, Joshua Del Papa, Jacqueline Justino Nabhen, Vicky Vo, Wonjae Lee, Fábio Ynoe de Moraes (2022). Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study. BMC Medical Education DOI link |
74 | Quasi-experiment shows ChatGPT can produce original, high-quality essays efficiently but struggles with referencing; urges rethinking assessments to focus on competence and performance. | Shih-Yeh Chen, Pei‐Hsuan Lin, Wei-Che Chien (2022). Children’s Digital Art Ability Training System Based on AI-Assisted Learning: A Case Study of Drawing Color Perception. Frontiers in Psychology DOI link |
75 | User study finds AI-enhanced learning analytics tools support career decision-making by providing information, analysis, and reflection prompts, but lack personalization and contextual depth. | Soumyadeb Chowdhury, Sian Joel-Edgar, Prasanta Kumar Dey, Sudeshna Bhattacharya, Alexander A. Kharlamov (2022). Embedding transparency in artificial intelligence machine learning models: managerial implications on predicting and explaining employee turnover. The International Journal of Human Resource Management DOI link |
76 | State-of-the-art review of AIED, EDM, and LA traces histories, methodologies, applications, and challenges, advocating interdisciplinary approaches for personalized and inclusive learning technologies. | Prasart Nuangchalerm (2023). AI-Driven Learning Analytics in STEM Education. International Journal on Research in STEM Education DOI link |
77 | Reviews specialized hardware accelerators (GPU, FPGA, ASIC, CGRA) for deep neural network training/inference, comparing power, area, throughput and future directions for DNN implementation. | Vijeta Sharma, Manjari Gupta, Anil Pandey, Deepti Mishra, Ajai Kumar (2022). A Review of Deep Learning-based Human Activity Recognition on Benchmark Video Datasets. Applied Artificial Intelligence DOI link |
78 | Extended review examines digital twin integration with IoT, AI, big data, and 5G for intelligent transportation systems, focusing on EV and autonomous vehicle challenges like battery and connectivity management. | Zhanpeng Yang, Yuanming Shi, Yong Zhou, Zixin Wang, Kai Yang (2022). Trustworthy Federated Learning via Blockchain. IEEE Internet of Things Journal DOI link |
79 | Demonstrates feasibility of AI/ML computer vision for gait pattern recognition, finding SVM and KNN outperform CNN/LSTM for classifying three gait types with high accuracy. | Shreeharsh Kelkar (2022). Between AI and Learning Science: The Evolution and Commercialization of Intelligent Tutoring Systems. IEEE Annals of the History of Computing DOI link |
80 | Proposes a typology of student-to-generative-AI relationships to better conceptualize diverse human-AI interactions in learning beyond single metaphors. | George Koulaouzidis, Tomasz Jadczyk, Dimitris K. Iakovidis, Anastasios Koulaouzidis, Marc Bisnaire, Dafni Charisopoulou (2022). Artificial Intelligence in Cardiology—A Narrative Review of Current Status. Journal of Clinical Medicine DOI link |
81 | Presents a robust statistical-feature-based random forest model for detecting DGA botnet traffic, demonstrating high accuracy and advocating blending XAI with OSINT for explainability and trust in CTI. | Parag K. Bhatt, Ashutosh Muduli (2022). Artificial intelligence in learning and development: a systematic literature review. European journal of training and development DOI link |
82 | Proposes an AI-based learning framework for higher education to adapt curricula, competencies, and industry-aligned outcomes, aiming to produce lifelong learners and close academia-industry gaps. | Xingqin Lin, Lopamudra Kundu, Chris Dick, Emeka Obiodu, Todd Mostak, Mike Flaxman (2023). 6G Digital Twin Networks: From Theory to Practice. IEEE Communications Magazine DOI link |
83 | Viewpoint discusses AI/ML impacts on accounting, outlining opportunities, challenges, and future research directions without empirical data. | Mayank Mishra, Paulo B. Lourénço (2024). Artificial intelligence-assisted visual inspection for cultural heritage: State-of-the-art review. Journal of Cultural Heritage DOI link |
84 | Argues that integrating AI, ML, Blockchain, and IoT can optimize wastewater treatment via predictive modeling, transparency, and real-time monitoring for sustainable water management. | 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 |
85 | Bibliometric analysis shows growing AI research addressing supply chain and food security disruptions, identifying key themes, leading countries, and future research directions. | Robin Chataut, Mary Nankya, Robert Akl (2024). 6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges. Sensors DOI link |
86 | Reviews biomedical device classifications and FDA regulatory pathways, highlighting the emergence of AI/ML, software as medical devices, cybersecurity risks, and the first FDA-approved AI diagnostic device. | Oluwaseun Kolade, Adebowale Owoseni, Abiodun Egbetokun (2024). Is AI changing learning and assessment as we know it? Evidence from a ChatGPT experiment and a conceptual framework. Heliyon DOI link |
Method
We queried OpenAlex for English-language journal articles matching the phrase AI in learning 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 learning” in unrelated contexts).
After filtering, the final dataset included 86 abstracts most substantively related to AI in learning. These form the basis for the key themes and relevance-ranked study summaries presented in this report.
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Text Response Hub turns free-text feedback (surveys responses, course feedback, exam answers, research abstracts, etc) into clear, actionable insights.
Metadata
Version: Text Response Hub v.2.01 • AI Engine: GPT-5-mini • Snapshot date: Oct 22, 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.