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Artificial Intelligence for Personalized Learning in K-12 Education. A Scoping Review

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Higher Education Learning Methodologies and Technologies Online (HELMeTO 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2076))

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Abstract

The ongoing evolution of Artificial Intelligence technology is able to influence different fields of human experience, also including communication and professional activities. Artificial Intelligence has been playing a relevant role in education and literature has already addressed the design, impact, and challenges of such technological solutions designed for educational purposes. On the other hand, technology integration, and especially the integration of solutions related to Artificial Intelligence, has started to exert a crucial function in enabling and enhancing Personalized Learning experience. In this regard, the present paper reports the results of a scoping review conducted with the aim of describing the empirical research evaluating the impact of Artificial Intelligence tools and systems as integrated in Personalized Learning approaches designed for K-12 education. The results shows that personalized solutions supported by Artificial Intelligence technology mainly consisted in Intelligent Tutoring Systems designed for online learning platforms and addressed STEM (especially Mathematics and Physics topics) and language learning. Overall, all the studies selected for the purposes of the current reviews reported a positive impact of the Artificial Intelligence-based personalized systems on students’ learning outcomes.

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References

  1. Mc Carthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence. AI Mag. 27(4), 12–14 (1995)

    Google Scholar 

  2. Xia, Q., Chiu, T.K., Zhou, X., Chai, C.S., Cheng, M.: Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Comp. Edu. Artif. Intell. 4, 100118 (2023)

    Google Scholar 

  3. Zhang, K., Aslan, A.B.: AI technologies for education: recent research & future directions. Comp. Edu. Artif. Intell. 2, 100025 (2021)

    Google Scholar 

  4. Chen, L., Chen, P., Lin, Z.: Artificial intelligence in education: a review. IEEE Access 8, 75264–75278 (2020)

    Article  Google Scholar 

  5. Chen, X., Zou, D., Xie, H., Cheng, G., Liu, C.: Two decades of artificial intelligence in education: contributors, collaborations, research topics, challenges, and future directions. Educ. Technol. Soc. 25(1), 28–47 (2022)

    Google Scholar 

  6. Shemshack, A., Spector, J.M.: A systematic literature review of personalized learning terms. Smart Learning Environments 7(1), 33 (2020)

    Google Scholar 

  7. Walkington, C., Bernacki, M.L.: Appraising research on personalized learning: definitions, theoretical alignment, advancements, and future directions. J. Res. Technol. Educ. 52(3), 235–252 (2020)

    Article  Google Scholar 

  8. Bernacki, M.L., Greene, M.J., Lobczowski, N.G.: A Systematic review of research on personalized learning: personalized by whom, to what, how, and for what purpose(s)? Educ. Psychol. Rev. 33(4), 1675–1715 (2021)

    Article  Google Scholar 

  9. Zhang, L., Basham, J.D., Yang, S.: Understanding the implementation of personalized learning: A research synthesis. Educ. Res. Rev. 31, 100339 (2020)

    Article  Google Scholar 

  10. Xie, H., Chu, H.C., Hwang, G.J., Wang, C.C.: Trends and development in technology-enhanced adaptive/personalized learning: A systematic review of journal publications from 2007 to 2017. Comput. Educ. 140, 103599 (2019)

    Article  Google Scholar 

  11. Maghsudi, S., Lan, A., Xu, J., van der Schaar, M.: Personalized education in the artificial intelligence Era: what to expect next. IEEE Signal Processing Magazine 38(3), 37–50 (2021). https://doi.org/10.1109/MSP.2021.3055032

  12. Bhutoria, A.: Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Comp. Edu. Artif. Intell. 3, 100068 (2022)

    Google Scholar 

  13. Hashim, S., Omar, M., Ab Jalil, H., Sharef, N.: Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review. Int. J. Acad. Res. Progres. Edu. Develop. 11, 884–903 (2022)

    Google Scholar 

  14. Shemshack, A., Kinshuk, Spector, J.M.: A comprehensive analysis of personalized learning components. J. Comp. Edu. 8(4), 485–503 (2021)

    Google Scholar 

  15. Zheng, L., Long, M., Zhong, L., Gyasi, J.F.: The effectiveness of technology-facilitated personalized learning on learning achievements and learning perceptions: a meta-analysis. Educ. Inf. Technol. 27(8), 11807–11830 (2022)

    Article  Google Scholar 

  16. Major, L., Francis, G.A., Tsapali, M.: The effectiveness of technology-supported personalised learning in low-and middle-income countries: A meta-analysis. Br. J. Edu. Technol. 52(5), 1935–1964 (2021)

    Article  Google Scholar 

  17. Zotero software, retrieved from www.zotero.org

  18. Chine, D.R., et al.: Educational Equity Through Combined Human-AI Personalization: A Propensity Matching Evaluation. In: Rodrigo, M.M., Matsuda, N., Cristea, V., Dimitrova, V.A. (eds.) Artificial Intelligence in Education. Lecture Notes in Computer Science, pp. 366–377. Springer International Publishing, Cham (2022)

    Chapter  Google Scholar 

  19. Cui, W., Xue, Z., Thai, K.P.: Performance comparison of an AI-based adaptive learning system in China. In: 2018 Chinese Automation Congress (CAC), pp. 3170–3175. IEEE (2018)

    Google Scholar 

  20. Pardamean, B., Suparyanto, T., Cenggoro, T.W., Sudigyo, D., Anugrahana, A.: AI-based learning style prediction in online learning for primary education. IEEE Access 10, 35725–35735 (2022)

    Article  Google Scholar 

  21. Rzepka, N., Simbeck, K., Müller, H.G., Pinkwart, N.: Go with the flow: personalized task sequencing improves online language learning. In: Wang, N., Rebolledo-Mendez, G., Matsuda, N., Santos, O.C., Dimitrova, V. (eds.) Artificial Intelligence in Education, Lecture Notes in Computer Science, pp. 90–101. Springer Nature, Cham, Switzerland (2023)

    Google Scholar 

  22. Alharbi, K., Alrajhi, L., Cristea, A.I., Bittencourt, I.I., Isotani, S., James, A.: Data-driven analysis of engagement in gamified learning environments: a methodology for real-time measurement of MOOCs. In: Kumar, V., Troussas, C. (eds.) In Intelligent Tutoring Systems. Lecture Notes in Computer Science, pp. 142–151. Springer International Publishing, Cham (2020)

    Google Scholar 

  23. Ingkavara, T., Panjaburee, P., Srisawasdi, N., Sajjapanroj, S.: The use of a personalized learning approach to implementing self-regulated online learning. Comp. Edu. Artif. Intell. 3, 100086 (2022)

    Google Scholar 

  24. Wongwatkit, C., Panjaburee, P.: A duplex adaptation mechanism in the personalized learning environment. J. Comp. Edu. (2023)

    Google Scholar 

  25. Ma, L., Li, J.: Influence of educational informatization based on machine learning on teaching mode. Int. Trans. Electr. Ener. Sys. e6180113 (2022)

    Google Scholar 

  26. Vainas, O., et al.: Staying in the zone: sequencing content in classrooms based on the zone of proximal development. In: Proceedings of the 12th International Conference on Educational Data Mining EDM, pp. 659–669 (2019)

    Google Scholar 

  27. Gentile, M., Città, G., Perna, S., Allegra, M.: Do we still need teachers? Navigating the paradigm shift of the teacher’s role in the AI era. Frontiers in Education 8 (2023)

    Google Scholar 

  28. Pitrella, V., Gentile, M., Città, G., Re, A., Tosto, C., Perna, S.: La percezione dell’utilizzo dell’intelligenza artificiale nello svolgimento dei compiti a casa in un campione di insegnanti italiani. Annali online della Didattica e della Formazione Docente 15(26), 300–318 (2023)

    Google Scholar 

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Authors and Affiliations

  1. Institute for Educational Technology, National Research Council, via Ugo La Malfa 153, 90146, Palermo, Italy

    Vanessa Pitrella, Salvatore Perna, Mario Allegra, Manuel Gentile, Simona Ottaviano, Anna Re, Crispino Tosto & Giuseppe Città

  2. Dipartimento Chirurgico, Medico, Odontoiatrico e di Scienze Morfologiche con Interesse Trapiantologico, Oncologico e di Medicina Rigenerativa, Università di Modena e Reggio Emilia, via del Pozzo 71, 41124, Modena, Italy

    Vanessa Pitrella

Authors
  1. Vanessa Pitrella
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  2. Salvatore Perna
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  3. Mario Allegra
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  4. Manuel Gentile
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  5. Simona Ottaviano
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  6. Anna Re
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  7. Crispino Tosto
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  8. Giuseppe Città
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Corresponding author

Correspondence to Vanessa Pitrella .

Editor information

Editors and Affiliations

  1. University of Bari, Bari, Italy

    Gabriella Casalino

  2. Pegaso University, Naples, Italy

    Raffaele Di Fuccio

  3. National Research Council of Italy, Institute for Educational Technology, Palermo, Italy

    Giovanni Fulantelli

  4. eCampus University, Novedrate, Como, Italy

    Paolo Raviolo

  5. Alma Mater Studiorum University of Bologna, Bologna, Italy

    Pier Cesare Rivoltella

  6. National Research Council of Italy, Institute for Educational Technology, Palermo, Palermo, Italy

    Davide Taibi

  7. University of Foggia, Foggia, Italy

    Giusi Antonia Toto

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Pitrella, V. et al. (2024). Artificial Intelligence for Personalized Learning in K-12 Education. A Scoping Review. In: Casalino, G., et al. Higher Education Learning Methodologies and Technologies Online. HELMeTO 2023. Communications in Computer and Information Science, vol 2076. Springer, Cham. https://doi.org/10.1007/978-3-031-67351-1_25

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  • DOI: https://doi.org/10.1007/978-3-031-67351-1_25

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