PRISMA Review on the implementation of Machine Learning in education: Social challenges and opportunities in shaping the citizens of tomorrow
DOI:
https://doi.org/10.31637/epsir-2026-1620Keywords:
Artifical Intelligence, Machine Learning, Chatbot, Education, ChatGPT, Technology, Teacher training, Schoolar AIAbstract
Introduction: The boundaries between humanity and artificial intelligence are becoming blurred, posing significant challenges in the field of education. Although institutions are showing interest in incorporating technologies such as ChatGPT, debates persist about their impact on the development of critical citizens and future leaders. Methodology: This systematic review, guided by the PRISMA method, analyses studies on the use of AI tools in school contexts, combining qualitative approaches to assess their pedagogical relevance and quantitative approaches to identify publication trends. Results: While much research focuses on scientific disciplines where AI is already integrated, the findings reveal that the educational field still faces difficulties in adapting to these technologies, which could exacerbate existing inequalities. Discussion: The incorporation of AI in education requires strategies that consider not only the technological dimension, but also the social, ethical, and pedagogical factors that influence its effective implementation. Conclusions: There is a need to advance research with sociological and educational approaches that enable the design of effective policies and practices for integrating artificial intelligence into the school system, training critical, ethical and competent students in an increasingly digitalised society.
Downloads
References
Alonso-Arévalo, J. (2015). Zotero: reference managers: software for the management and maintenance of bibliographic references in research works. Salamanca: Ediciones del Universo. https://acortar.link/bBC9ZT
Bailey, D. (2019). Chatbots as conversational agents in the context of language learning. En Proceedings of the Fourth Industrial Revolution and Education (pp. 27-29). Dajeon, Korea.
Barsky, E. (2010). Mendeley. Issues in Science and Technology Librarianship, 62. https://doi.org/10.29173/istl2541 DOI: https://doi.org/10.29173/istl2541
Billingsley, B., Heyes, J. M., Lesworth, T. y Sarzi, M. (2023). Can a robot be a scientist? Developing students' epistemic insight through a lesson exploring the role of human creativity in astronomy. Phys. Educ, 58. DOI: https://doi.org/10.1088/1361-6552/ac9d19
Biurrun, A. (2023, March 31). Italy temporarily bans ChatGPT artificial intelligence. The reason.
Chang, C. Y., Hwang, G. J. y Gau, M. L. (2022). Promoting students' learning achievement and self-efficacy: A mobile chatbot approach for nursing training. British Journal of Educational Technology, 53(1), 171-188. https://doi.org/10.1111/bjet.13158 DOI: https://doi.org/10.1111/bjet.13158
Chatterjee, S. y Bhattacharjee, K. K. (2020). Adoption of artificial intelligence in higher education: a quantitative analysis using structural equation modelling. Education and Information Technologies, 25(5), 3443-3463. https://doi.org/10.1007/s10639-020-10159-7 DOI: https://doi.org/10.1007/s10639-020-10159-7
Chong, J. V. y Curtis, C. J. (2020). Perspectives on Aied Biola university perspectives on Artificial Intelligence in education: a study of public elementary school teachers. [Doctoral dissertation, BIOLA University]. https://acortar.link/lOzYad
Chung, D., Jeong, P., Kwon, D. y Han, H. (2023). Technology acceptance prediction of robo-advisors by machine learning. Intelligent Systems with Applications, 18 https://doi.org/10.1016/j.iswa.2023.200197 DOI: https://doi.org/10.1016/j.iswa.2023.200197
Cruz-Jesus, F., Castelli, M., Oliveira, T., Mendes, R., Nunes, C., Sa-Velho, M. y Rosa-Louro, A. (2020). Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country. Heliyon, 6(6), 2405-8440. https://doi.org/10.1016/j.heliyon.2020.e04081 DOI: https://doi.org/10.1016/j.heliyon.2020.e04081
Cuatrecasas-Monforte, C. (2022). Artificial Intelligence in the Spanish criminal investigation process: possible benefits and potential risks. [Doctoral Thesis, Universitat Ramon Llull]. http://hdl.handle.net/10803/675100
Druzhinina, O. V., Karpacheva, I. A., Masina, O. N. y Petrov, A. A. (2021). Development of an Integrated Complex of Knowledge Base and Tools of Expert Systems for Assessing Knowledge of Students in Mathematics within the Framework of a Hybrid Intelligent Learning Environment. International Journal of Education and Information Technologies, 15, 122-129. https://doi.org/10.46300/9109.2021.15.12 DOI: https://doi.org/10.46300/9109.2021.15.12
Garcia-Corretjer, M. A. (2022). On the Relationship between People, Objects, & Interactive Technologies: Transforming Digital & Physical experiences through the process of Realizing Empathy. [Doctoral dissertation, Universitat Ramon Llull]. http://hdl.handle.net/10803/675718
Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A. y Chartash, D. (2023). How does ChatGPT perform on the United States medical licensing examination? the implications of large language models for medical education and knowledge assessment. JMIR Medical Education, 9. https://doi.org/10.2196/45312 DOI: https://doi.org/10.2196/45312
Grunhut, J., Marques, O. y Wyatt, A. T. M. (2022). Needs, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum. JMIR Medical Education, 8(2). https://doi.org/10.2196/35587 DOI: https://doi.org/10.2196/35587
Harati H, Sujo-Montes L, Tu C-H, Armfield SJW, Yen C-J (2021). Assessment and Learning in Knowledge Spaces (ALEKS) Adaptive System Impact on Students' Perception and Self-Regulated Learning Skills. Education Sciences, 11(10), 603. https://doi.org/10.3390/educsci11100603 DOI: https://doi.org/10.3390/educsci11100603
Hoosain, M. S., Paul, B. S. y Ramakrishna, S. (2020). The impact of 4ir digital technologies and circular thinking on the united nations sustainable development goals. Sustainability (Switzerland), 12(23), 1-16. https://doi.org/10.3390/su122310143 DOI: https://doi.org/10.3390/su122310143
How, M. L. y Hung, W. L. D. (2019). Educing AI-thinking in science, technology, engineering, arts, and mathematics (STEAM) education. Education Sciences, 9(3). https://doi.org/10.3390/educsci9030184 DOI: https://doi.org/10.3390/educsci9030184
Hutton, B., Catala-Lopez, F. y Moher, D. (2016). The PRISMA statement extension for systematic reviews incorporating network meta-analysis: PRISMA-NMA. Med Clin (Barc), 147(6), 262-266. DOI: https://doi.org/10.1016/j.medcle.2016.10.003
Jara, I. y Ochoa, J. M. (2020). Uses and effects of artificial intelligence in education. Inter-American Development Bank. http://dx.doi.org/10.18235/0002380 DOI: https://doi.org/10.18235/0002380
Jeong, G. H. (2020). Artificial intelligence, machine learning, and deep learning in women's health nursing. Korean Journal of Women Health Nursing, 26(1), 5–9. https://doi.org/10.4069/kjwhn.2020.03.11 DOI: https://doi.org/10.4069/kjwhn.2020.03.11
Jokhan, A., Chand, A. A., Singh, V. y Mamun, K. A. (2022). Increased Digital Resource Consumption in Higher Educational Institutions and the Artificial Intelligence Role in Informing Decisions Related to Student Performance. Sustainability (Switzerland), 14(4). https://doi.org/10.3390/su14042377 DOI: https://doi.org/10.3390/su14042377
Kadhim, M. K. y Hassan, A. K. (2020). Towards Intelligent E-Learning Systems: A Hybrid Model for Predicatingthe Learning Continuity in Iraqi Higher Education. Webology, 17(2), 172-188. https://doi.org/10.14704/WEB/V17I2/WEB17023 DOI: https://doi.org/10.14704/WEB/V17I2/WEB17023
Kanglang, L. (2021). Artificial Intelligence (AI) and Translation Teaching: A Critical Perspective on the Transformation of Education. International Journal of Educational Sciences, 33(1-3). https://doi.org/10.31901/24566322.2021/33.1-3.1159 DOI: https://doi.org/10.31901/24566322.2021/33.1-3.1159
Khan, I., Ahmad, A. R., Jabeur, N. y Mahdi, M. N. (2021). An artificial intelligence approach to monitor student performance and devise preventive measures. Smart Learning Environments, 8(1). https://doi.org/10.1186/s40561-021-00161-y DOI: https://doi.org/10.1186/s40561-021-00161-y
Kubsch, M., Czinczel, B., Lossjew, J., Wyrwich, T., Bednorz, D., Bernholt, S., Fiedler, D., Strauß, S., Cress, U., Drachsler, H., Neumann, K. y Rummel, N. (2022). Toward learning progression analytics — Developing learning environments for the automated analysis of learning using evidence centered design. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.981910 DOI: https://doi.org/10.3389/feduc.2022.981910
Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M. D., Păun, D. y Mihoreanu, L. (2021). Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability (Switzerland), 13(18). https://doi.org/10.3390/su131810424 DOI: https://doi.org/10.3390/su131810424
Lampos, V., Mintz, J. y Qu, X. (2021). An artificial intelligence approach for selecting effective teacher communication strategies in autism education. NPJ Science of Learning, 6(1). https://doi.org/10.1038/s41539-021-00102-x DOI: https://doi.org/10.1038/s41539-021-00102-x
Lee, D. y Yeo, S. (2022). Developing an AI-based chatbot for practicing responsive teaching in mathematics. Computers and Education, 191. https://doi.org/10.1016/j.compedu.2022.104646 DOI: https://doi.org/10.1016/j.compedu.2022.104646
Li, L. (2022). The Impact of Artificial Intelligence Painting on Contemporary Art From Disco Diffusion's Painting Creation Experiment. Proceedings - 2022 International Conference on Frontiers of Artificial Intelligence and Machine Learning, FAIML 2022, 52-56. https://doi.org/10.1109/FAIML57028.2022.00020 DOI: https://doi.org/10.1109/FAIML57028.2022.00020
Li, J., Wang, X., Ahmad, S., Huang, X. y Khan, Y. A. (2023). Optimization of investment strategies through machine learning, Heliyon, 9(5), 2405-8440. https://doi.org/10.1016/j.heliyon.2023.e16155 DOI: https://doi.org/10.1016/j.heliyon.2023.e16155
Luckin, R. y Cukurova, M. (2019). Designing educational technologies in the age of AI: A learning sciences-driven approach. British Journal of Educational Technology, 50(6),
2824-2838. https://doi.org/10.1111/bjet.12861 DOI: https://doi.org/10.1111/bjet.12861
Marques, L. S., Gresse von Wangenheim, C. y Hauck, J. C. R. (2020). Teaching machine learning in school: A systematic mapping of the state of the art. Informatics in Education, 19(2), 283-321. https://doi.org/10.15388/INFEDU.2020.14 DOI: https://doi.org/10.15388/infedu.2020.14
Mengmeng, Z., Xiantong, Y. y Xinghua, W. (2019). Construction of STEAM Curriculum Model and Case Design in Kindergarten. American Journal of Educational Research, 7(7),
485-490. https://doi.org/10.12691/education-7-7-8 DOI: https://doi.org/10.12691/education-7-7-8
Muniasamy, A. y Alasiry, A. (2020). Deep learning: The impact on future eLearning. International Journal of Emerging Technologies in Learning, 15(1), 188-199. https://doi.org/10.3991/IJET.V15I01.11435 DOI: https://doi.org/10.3991/ijet.v15i01.11435
Murphy-Kelly, S. (2023, March 29). Elon Musk and other tech leaders call for pause in 'out of control' AI race. CNN Business.
Nicoletti, M. C. y Oliveira, O. L. (2020). A Machine Learning-Based Computational System Proposal Aiming at Higher Education Dropout Prediction. Higher Education Studies, 10(4), 12. https://doi.org/10.5539/hes.v10n4p12 DOI: https://doi.org/10.5539/hes.v10n4p12
Nuankaew, P. (2022). Self-Regulated Learning Model in Educational Data Mining. International Journal of Emerging Technologies in Learning, 17(17), 4-27. https://doi.org/10.3991/ijet.v17i17.23623 DOI: https://doi.org/10.3991/ijet.v17i17.23623
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P. y Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. International Journal of Surgery, 88, 105906. https://www.bmj.com/content/372/bmj.n71 DOI: https://doi.org/10.31222/osf.io/v7gm2
Page, M. J. y Moher, D. (2017). Evaluations of the uptake and impact of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement and extensions: a scoping review. Systematic reviews, 6(1), 1-14.
https://doi.org/10.1186/s13643-017-0663-8 DOI: https://doi.org/10.1186/s13643-017-0663-8
Page, M. J., Moher, D. y McKenzie, J. E. (2022). Introduction to PRISMA 2020 and implications for research synthesis methodologists. In Research Synthesis Methods, 13(2), 156-163. https://doi.org/10.1002/jrsm.1535 DOI: https://doi.org/10.1002/jrsm.1535
Palasundram, K., Sharef, N. M., Nasharuddin, N. A., Kasmiran, K. A. y Azman, A. (2019). Sequence to sequence model performance for education chatbot. International Journal of Emerging Technologies in Learning, 14(24), 56-68. https://doi.org/10.3991/ijet.v14i24.12187 DOI: https://doi.org/10.3991/ijet.v14i24.12187
Peramunugamage, A., Ratnayake, U. W. y Karunanayaka, S. P. (2022). Systematic review on mobile collaborative learning for engineering education. Journal of Computers in Education. https://doi.org/10.1007/s40692-022-00223-1 DOI: https://doi.org/10.1007/s40692-022-00223-1
Pikhart, M. y Klímová, B. (2020). Elearning 4.0 as a sustainability strategy for generation z language learners: Applied linguistics of second language acquisition in younger adults. Societies, 10(2). https://doi.org/10.3390/soc10020038 DOI: https://doi.org/10.3390/soc10020038
Prendes-Espinosa, M. P. y Cerdán-Cartagena, F. (2021). Advanced technologies to face the challenge of educational innovation. ITEN-Revista Iberoamericana de Educacion a Distancia, 24(1), 35-53. https://doi.org/10.5944/ried.24.1.28415 DOI: https://doi.org/10.5944/ried.24.1.28415
Pu, S., Ahmad, N. A., Khambari, M. N. M. y Yap, N. K. (2021). Identification and analysis of core topics in educational artificial intelligence research: A bibliometric analysis. Cypriot Journal of Educational Sciences, 16(3), 995-1009. https://doi.org/10.18844/CJES.V16I3.5782 DOI: https://doi.org/10.18844/cjes.v16i3.5782
Rodríguez-García, J. D., Moreno-León, J., Román-González, M. y Robles, G. (2020). LearningML: A tool to foster computational thinking skills through practical artificial intelligence projects. Journal of Distance Education, 20(63). https://doi.org/10.6018/RED.410121 DOI: https://doi.org/10.6018/red.410121
Ruiperez-Valiente, J. A., Munoz-Merino, P. J., Alexandron, G. y Pritchard, D. E. (2019). Using Machine Learning to Detect “Multiple-Account” Cheating and Analyze the Influence of Student and Problem Features. IEEE Transactions on Learning Technologies, 12(1),
112-122. https://doi.org/10.1109/TLT.2017.2784420 DOI: https://doi.org/10.1109/TLT.2017.2784420
Salas-Rueda, R. A. y Salas-Rueda, R. D. (2020). Impact of the web application for the educational process on the compound interest considering data science. Turkish Online Journal of Distance Education-TOJDE. DOI: https://doi.org/10.17718/tojde.762030
Sharma, K., Papamitsiou, Z. y Giannakos, M. (2019). Building pipelines for educational data using AI and multimodal analytics: A “grey-box” approach. British Journal of Educational Technology, 50(6), 3004-3031. https://doi.org/10.1111/bjet.12854 DOI: https://doi.org/10.1111/bjet.12854
Soysal, D., Bani-Yaghoub, M. y Riggers-Piehl, T. A. (2022). A Machine Learning Approach to Evaluate Variables of Math Anxiety in STEM Students. Pedagogical Research, 7(2), em0125. https://doi.org/10.29333/pr/11978 DOI: https://doi.org/10.29333/pr/11978
Stadelmann, T., Keuzenkamp, J., Grabner, H. y Würsch, C. (2021). The ai-atlas: Didactics for teaching ai and machine learning on-site, online, and hybrid. Education Sciences, 11(7). https://doi.org/10.3390/educsci11070318 DOI: https://doi.org/10.3390/educsci11070318
Stokel-Walker, C. (2022). AI bot ChatGPT writes smart essays — should academics worry? Nature. https://doi.org/10.1038/d41586-022-04397-7 DOI: https://doi.org/10.1038/d41586-022-04397-7
Su, J., Zhong, Y. y Ng, D. T. K. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence, 3, 100065. https://doi.org/10.1016/j.caeai.2022.100065 DOI: https://doi.org/10.1016/j.caeai.2022.100065
Talan, T. (2021). Artificial Intelligence in Education: A Bibliometric Study. International Journal of Research in Education and Science, 822-837. https://doi.org/10.46328/ijres.2409 DOI: https://doi.org/10.46328/ijres.2409
Thompson, A., Gallacher, A. y Howarth, M. (2018). Stimulating task interest: human partners or chatbots? In Future-proof CALL: language learning as exploration and encounters. EUROCALL 302–306. https://doi.org/10.14705/rpnet.2018.26.854 DOI: https://doi.org/10.14705/rpnet.2018.26.854
Urrútia, G. y Bonfill, X. (2010). PRISMA declaration: A proposal to improve the publication of systematic reviews and meta-analyses. Clinical Medicine, 135(11), 507-511. https://doi.org/10.1016/j.medcli.2010.01.015 DOI: https://doi.org/10.1016/j.medcli.2010.01.015
Vázquez-Cano, E., Mengual-Andrés, S. y López-Meneses, E. (2021). Chatbot to improve learning punctuation in Spanish and to enhance open and flexible learning environments. International Journal of Educational Technology in Higher Education, 18(1). https://doi.org/10.1186/s41239-021-00269-8 DOI: https://doi.org/10.1186/s41239-021-00269-8
Vijayakumar, R., Bhuvaneshwari, B., Adith, S. y Deepika, M. (2019). AI Based Student Bot for Academic Information System using Machine Learning. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 590-596. https://doi.org/10.32628/cseit1952171 DOI: https://doi.org/10.32628/CSEIT1952171
Vir-Singh, S. y Kant-Hiran, K. (2022). The Impact of AI on Teaching and Learning in Higher Education Technology. Journal of Higher Education Theory and Practice, 22(13). DOI: https://doi.org/10.33423/jhetp.v22i13.5514
Winkler, R. y Söllner, M. (2018): Unleashing the Potential of Chatbots in Education: A State-of-the-Art Analysis. Academy of Management Annual Meeting (AOM). https://www.alexandria.unisg.ch/publications/254848 DOI: https://doi.org/10.5465/AMBPP.2018.15903abstract
Zammit, M., Voulgari, I., Liapis, A. y Yannakakis, G. N. (2022). Learn to Machine Learn via Games in the Classroom. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.913530 DOI: https://doi.org/10.3389/feduc.2022.913530
Zawacki-Richter, O., Marín, V. I., Bond, M. y Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? In International Journal of Educational Technology in Higher Education, 16(1). https://doi.org/10.1186/s41239-019-0171-0 DOI: https://doi.org/10.1186/s41239-019-0171-0
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Manuel Reina-Parrado, Pedro Román-Graván, Carlos Hervás-Gómez
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Non Commercial, No Derivatives Attribution 4.0. International (CC BY-NC-ND 4.0.), that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
