A new pedagogical model: PBL-AI.

Authors

DOI: https://doi.org/10.6018/reifop.661571
Keywords: educational innovation, emerging technologies, active methodologies, digital transformation

Abstract

This article presents the results of a research study introducing a new learning model: ABP-IA.
This innovative model enhances academic performance, individualization, and personalization
of learning, as well as self-assessment, by combining project-based learning (PBL) with artificial
intelligence (AI). Through a quasi-experimental study, the results of two distinct groups were
compared: the first group implemented the ABP-IA model, while the second group followed the
traditional PBL model. The findings after implementing both models showed significant
differences in favor of the ABP-IA model, not only by slightly improving students' academic performance but also by increasing their motivation. The test results validate that the adaptive
feedback provided by AI integrated into PBL is highly beneficial for boosting students' motivation
and willingness to learn. Thus, ABP-IA emerges as a new learning model that combines the
most practical and beneficial elements of PBL with the support of AI tools, offering a more
personalized, up-to-date, and innovative learning experience.

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References

Aravantinos, S., Lavidas, K., Voulgari, I., Papadakis, S., Karalis, T., & Komis, V. (2024). Educational approaches with AΙ in primary school settings: A systematic review of the literature available in Scopus. Education Sciences, 14(7), 744. https://doi.org/10.3390/educsci14070744

Birenbaum, M. (2023). The chatbots’ challenge to education: Disruption or destruction? Education Sciences, 13(7), 711. https://doi.org/10.3390/educsci13070711

Cabero-Almenara, J., Palacios-Rodríguez, A., Loaiza-Aguirre, M. I., & Rivas-Manzano, M. d. R. d. (2024). Acceptance of educational artificial intelligence by teachers and its relationship with some variables and pedagogical beliefs. Education Sciences, 14(7), 740. https://doi.org/10.3390/educsci14070740

de Barros, V. A. M., Paiva, H. M., & Hayashi, V. T. (2023). Using PBL and agile to teach artificial intelligence to undergraduate computing students. IEEE Access, 11, 77737–77748. https://doi.org/10.1109/ACCESS.2023.3298294

Djalilova, Z. O. (2024). The pedagogical-psychological aspects of artificial intelligence technologies in integrative education. International Journal of Literature and Languages, 4(3), 13–19. https://doi.org/10.37547/ijll/Volume04Issue03-03

Elsayary, A. (2024). Integrating generative AI in active learning environments: Enhancing metacognition and technological skills. Proceedings of the 15th International Multi-Conference on Complexity, Informatics and Cybernetics (IMCIC 2024), 135–138. https://doi.org/10.54808/IMCIC2024.01.135

Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., & Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: A literature review. Education Sciences, 13(12), 1216. https://doi.org/10.3390/educsci13121216

González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021). Artificial intelligence for student assessment: A systematic review. Applied Sciences, 11(12), 5467. https://doi.org/10.3390/app11125467

Ito, T., Tanaka, M. S., Shin, M., & Miyazaki, K. (2021). The online PBL (Project-Based Learning) education system using AI (Artificial Intelligence). Proceedings of the International Conference on Engineering and Product Design Education, 9–10 September 2021, VIA University College, Herning, Denmark. https://doi.org/10.35199/epde.2021.19

Kanders, K., Stupple-Harris, L., Smith, L., & Gibson, J. L. (2024). Perspectives on the impact of generative AI on early-childhood development and education. Infant and Child Development, 33(4), e2514. https://doi.org/10.1002/icd.2514

Kolmos, A., Holgaard, J. E., & Clausen, N. R. (2021). Progression of student self-assessed learning outcomes in systemic PBL. European Journal of Engineering Education, 46(1), 67–89. https://doi.org/10.1080/03043797.2020.1789070

Kusam, V. A., Moore, L., Shrestha, S., Song, Z., Lu, J., & Zhu, Q. (2024). Generative-AI assisted feedback provisioning for project-based learning in CS courses. Proceedings of the ASEE Annual Conference & Exposition. https://doi.org/10.18260/1-2--47494

Lu, W.-Y., & Fan, S.-C. (2023). Developing a weather prediction project-based machine learning course in facilitating AI learning among high school students. Computers and Education: Artificial Intelligence, 5, 100154. https://doi.org/10.1016/j.caeai.2023.100154

Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020

Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599. https://doi.org/10.1007/s40593-016-0110-3

Salas-Pilco, S. Z., Xiao, K., & Hu, X. (2022). Artificial intelligence and learning analytics in teacher education: A systematic review. Education Sciences, 12(8), 569. https://doi.org/10.3390/educsci12080569

Sanusi, I. T., Olaleye, S. A., Agbo, F. J., & Chiu, T. K. F. (2022). The role of learners’ competencies in artificial intelligence education. Computers and Education: Artificial Intelligence, 3, 100098. https://doi.org/10.1016/j.caeai.2022.100098

Schiff, D. (2022). Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527–563. https://doi.org/10.1007/s40593-021-00270-2

Son, H., & Im, H. (2024). A study on students’ affective attitudes and learning experiences in PBL activities utilizing an AI app in general English classes. Asia-Pacific Journal of Convergent Research Interchange, 10(10), 413–422. https://doi.org/10.47116/apjcri.2024.10.31

Su, J., & Yang, W. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence, 3, 100049. https://doi.org/10.1016/j.caeai.2022.100049

Su, J., Ng, D. T. K., & Chu, S. K. W. (2023). Artificial intelligence (AI) literacy in early childhood education: The challenges and opportunities. Computers and Education: Artificial Intelligence, 4, 100124. https://doi.org/10.1016/j.caeai.2023.100124

Tan, X., Cheng, G., & Ling, M. H. (2025). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education: Artificial Intelligence, 8, 100355. https://doi.org/10.1016/j.caeai.2024.100355

Tendrita, M., & Hidayati, U. (2024). The influence of project-based learning assisted by artificial intelligence-based mind mapping on digital literacy competence of biology education students. KULIDAWA: Journal of Biology Education, 5(2), 82–89. https://doi.org/10.31332/kd.v5i2.9990

Wan, C., & Hu, Z. (2022). Research on application of artificial intelligence teaching mode based on project-based learning. International Journal of Education and Humanities, 6(1), 121–122. https://doi.org/10.54097/ijeh.v6i1.3063

Yang, W. (2022). Artificial intelligence education for young children: Why, what, and how in curriculum design and implementation. Computers and Education: Artificial Intelligence, 3, 100061. https://doi.org/10.1016/j.caeai.2022.100061

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16(39). https://doi.org/10.1186/s41239-019-0171-0

Published
02-06-2025
How to Cite
Ruiz-Palmero, J., Sánchez-Rivas, E., & Ruiz-Viruel, S. (2025). A new pedagogical model: PBL-AI. Interuniversity Electronic Journal of Teacher Formation, 28(2), 63–79. https://doi.org/10.6018/reifop.661571