Artificial Intelligence Supporting Education: A Systematic Mapping of Digital Platforms and Unplugged Learning Activities
Resumo
Artificial Intelligence (AI) has been incorporated into education through adaptive systems, conversational agents, and data-driven environments. In parallel, unplugged approaches have emerged in technologically limited contexts. This work presents a systematic mapping of 151 primary studies on AI-supported education. Results indicate predominance of machine learning systems and conversational agents, especially in higher education. Although less frequent, unplugged approaches enable accessibility in low-resource contexts and conceptual understanding through low-cost practices. Findings suggest an imbalance between technological expansion and pedagogical diversification in AI-supported education, highlighting the need for inclusive models.
Palavras-chave:
Artificial Intelligence in Education, Unplugged Activities, Digital Platforms
Referências
ACM (2026). Digital library. Avaliable at [link]. Accessed on 03/15/2026.
Akhmetshin, E., Barmuta, K., Vasilev, V., Okagbue, H., and Ijezie, O. (2020). Principal directions of digital transformation of higher education system in sustainable education. In E3S Web of Conferences, volume 208, page 09042. EDP Sciences.
Chen, P., Yang, D., Metwally, A. H. S., Lavonen, J., and Wang, X. (2023). Fostering computational thinking through unplugged activities: A systematic literature review and meta-analysis. International Journal of STEM Education, 10(47).
Connelly, L., Bilstrup, K.-E. K., and Petersen, M. G. (2025). Beyond llms as black boxes: Activities and an educational tool supporting unplugged and digital ai learning activities for k-12 classrooms. In Adjunct Proceedings of the Sixth Decennial Aarhus Conference: Computing X Crisis (AAR Adjunct 2025), pages 1–4. ACM.
Dai, Y. (2024). Integrating unplugged and plugged activities for holistic ai education: An embodied constructionist pedagogical approach. Education and Information Technologies, 30:6741–6764.
Dieste, O., Grimán, A., and Juristo, N. (2009). Developing search strategies for detecting relevant experiments. Empirical Software Engineering., 14(5):513–539.
Efremova, N. (2023). Gamification resources in the system of specialist training for the agricultural complex. In E3S Web of Conferences, volume 431, page 01052. EDP Sciences.
Elsevier (2026). Scopus. Avaliable at [link]. Accessed on 03/15/2026.
Hmoud, M., Daher, W., and Ayyoub, A. (2025). The impact of ai, xr, and combined ai-xr on student satisfaction: A moderated mediation analysis of engagement and learner characteristics. IEEE Access, 13:140614–140626.
Huang, W. and Looi, C.-K. (2021). A critical review of literature on "unplugged" pedagogies in k-12 computer science and computational thinking education. Computer Science Education, 31(1):83–111.
IEEE (2026). Xplore digital library. Avaliable at [link]. Accessed on 03/15/2026.
Ifenthaler, D., Majumdar, R., Gorissen, P., Judge, M., Mishra, S., Raffaghelli, J., and Shimada, A. (2024). Artificial intelligence in education: Implications for policymakers, researchers, and practitioners. Technology, Knowledge and Learning, 29:1693–1710.
Kitchenham, B. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical report, Keele University and Durham University Joint Report.
Kitchenham, B., Sjøberg, D. I. K., Brereton, O. P., Budgen, D., Dybå, T., Höst, M., Pfahl, D., and Runeson, P. (2010). Can we evaluate the quality of software engineering experiments? In 4th International Symposium on Empirical Software Engineering and Measurement (ESEM 2010), pages 1–8, Bolzano, Italy. ACM.
Moroianu, A. et al. (2023). Artificial intelligence in education: A systematic review. In Proceedings of the International Conference on e-Learning.
Munir, H., Moayyed, M., and Petersen, K. (2014). Considering rigor and relevance when evaluating test driven development: a systematic review. Information and Software Technology, 56(4):375–394.
Namli, N. A. and Aybek, B. (2022). An investigation of the effect of block-based programming and unplugged coding activities on fifth graders' computational thinking skills, self-efficacy and academic performance. Contemporary Educational Technology, 14(1):ep341.
Oproiu, G. C. (2015). A study about using e-learning platform (moodle) in university teaching process. Procedia - Social and Behavioral Sciences, 180:426–432.
Petersen, K., Vakkalanka, S., and Kuzniarz, L. (2015). Guidelines for conducting systematic mapping studies in software engineering. Information and Software Technology, 64:1–18.
Singhal, V. (2022). Precoding skills: Teaching computational thinking to preschoolers in singapore using unplugged activities. In CTE-STEM 2022 International Teacher Forum.
Smirnov, E., Dvoryatkina, S., and Shcherbatykh, S. (2021). Technology of development of a hybrid intelligent system of teaching mathematics. In European Proceedings of Social and Behavioural Sciences (EpSBS), Education in a Changing World: Global Challenges and National Priorities (EdCW 2020). European Publisher.
Song, Y., Tian, X., Regatti, N., Katuka, G. A., Boyer, K. E., and Israel, M. (2024). Artificial intelligence unplugged: Designing unplugged activities for a conversational ai summer camp. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education. ACM.
Threekunprapam, A. and Yasri, P. (2020). Patterns of computational thinking development while solving unplugged coding activities coupled with the 3s approach for self-directed learning. European Journal of Educational Research, 9(3):1025–1045.
Triantafyllou, S. A., Sapounidis, T., and Oikonomou, A. (2024). Trying to develop and assess computational thinking in computer science unplugged activities with gamification. In 2024 32nd National Conference with International Participation (TELECOM), pages 1–4.
Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th international conference on evaluation and assessment in software engineering, pages 1–10.
Wohlin, C., Runeson, P., Host, M., Ohlsson, M. C., Regnell, B. j., and Wessln, A. (2012). Experimentation in software engineering. Springer Publishing Company, Incorporated.
Akhmetshin, E., Barmuta, K., Vasilev, V., Okagbue, H., and Ijezie, O. (2020). Principal directions of digital transformation of higher education system in sustainable education. In E3S Web of Conferences, volume 208, page 09042. EDP Sciences.
Chen, P., Yang, D., Metwally, A. H. S., Lavonen, J., and Wang, X. (2023). Fostering computational thinking through unplugged activities: A systematic literature review and meta-analysis. International Journal of STEM Education, 10(47).
Connelly, L., Bilstrup, K.-E. K., and Petersen, M. G. (2025). Beyond llms as black boxes: Activities and an educational tool supporting unplugged and digital ai learning activities for k-12 classrooms. In Adjunct Proceedings of the Sixth Decennial Aarhus Conference: Computing X Crisis (AAR Adjunct 2025), pages 1–4. ACM.
Dai, Y. (2024). Integrating unplugged and plugged activities for holistic ai education: An embodied constructionist pedagogical approach. Education and Information Technologies, 30:6741–6764.
Dieste, O., Grimán, A., and Juristo, N. (2009). Developing search strategies for detecting relevant experiments. Empirical Software Engineering., 14(5):513–539.
Efremova, N. (2023). Gamification resources in the system of specialist training for the agricultural complex. In E3S Web of Conferences, volume 431, page 01052. EDP Sciences.
Elsevier (2026). Scopus. Avaliable at [link]. Accessed on 03/15/2026.
Hmoud, M., Daher, W., and Ayyoub, A. (2025). The impact of ai, xr, and combined ai-xr on student satisfaction: A moderated mediation analysis of engagement and learner characteristics. IEEE Access, 13:140614–140626.
Huang, W. and Looi, C.-K. (2021). A critical review of literature on "unplugged" pedagogies in k-12 computer science and computational thinking education. Computer Science Education, 31(1):83–111.
IEEE (2026). Xplore digital library. Avaliable at [link]. Accessed on 03/15/2026.
Ifenthaler, D., Majumdar, R., Gorissen, P., Judge, M., Mishra, S., Raffaghelli, J., and Shimada, A. (2024). Artificial intelligence in education: Implications for policymakers, researchers, and practitioners. Technology, Knowledge and Learning, 29:1693–1710.
Kitchenham, B. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical report, Keele University and Durham University Joint Report.
Kitchenham, B., Sjøberg, D. I. K., Brereton, O. P., Budgen, D., Dybå, T., Höst, M., Pfahl, D., and Runeson, P. (2010). Can we evaluate the quality of software engineering experiments? In 4th International Symposium on Empirical Software Engineering and Measurement (ESEM 2010), pages 1–8, Bolzano, Italy. ACM.
Moroianu, A. et al. (2023). Artificial intelligence in education: A systematic review. In Proceedings of the International Conference on e-Learning.
Munir, H., Moayyed, M., and Petersen, K. (2014). Considering rigor and relevance when evaluating test driven development: a systematic review. Information and Software Technology, 56(4):375–394.
Namli, N. A. and Aybek, B. (2022). An investigation of the effect of block-based programming and unplugged coding activities on fifth graders' computational thinking skills, self-efficacy and academic performance. Contemporary Educational Technology, 14(1):ep341.
Oproiu, G. C. (2015). A study about using e-learning platform (moodle) in university teaching process. Procedia - Social and Behavioral Sciences, 180:426–432.
Petersen, K., Vakkalanka, S., and Kuzniarz, L. (2015). Guidelines for conducting systematic mapping studies in software engineering. Information and Software Technology, 64:1–18.
Singhal, V. (2022). Precoding skills: Teaching computational thinking to preschoolers in singapore using unplugged activities. In CTE-STEM 2022 International Teacher Forum.
Smirnov, E., Dvoryatkina, S., and Shcherbatykh, S. (2021). Technology of development of a hybrid intelligent system of teaching mathematics. In European Proceedings of Social and Behavioural Sciences (EpSBS), Education in a Changing World: Global Challenges and National Priorities (EdCW 2020). European Publisher.
Song, Y., Tian, X., Regatti, N., Katuka, G. A., Boyer, K. E., and Israel, M. (2024). Artificial intelligence unplugged: Designing unplugged activities for a conversational ai summer camp. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education. ACM.
Threekunprapam, A. and Yasri, P. (2020). Patterns of computational thinking development while solving unplugged coding activities coupled with the 3s approach for self-directed learning. European Journal of Educational Research, 9(3):1025–1045.
Triantafyllou, S. A., Sapounidis, T., and Oikonomou, A. (2024). Trying to develop and assess computational thinking in computer science unplugged activities with gamification. In 2024 32nd National Conference with International Participation (TELECOM), pages 1–4.
Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th international conference on evaluation and assessment in software engineering, pages 1–10.
Wohlin, C., Runeson, P., Host, M., Ohlsson, M. C., Regnell, B. j., and Wessln, A. (2012). Experimentation in software engineering. Springer Publishing Company, Incorporated.
Publicado
05/10/2026
Como Citar
CAIXETA, Lucas et al.
Artificial Intelligence Supporting Education: A Systematic Mapping of Digital Platforms and Unplugged Learning Activities. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 37. , 2026, Goiânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 1190-1203.
DOI: https://doi.org/10.5753/sbie.2026.27657.
