Computational Philosophy as a Catalyst for Educational Innovation: A systematic review for Active Learning, Sustainability, and AI Integration

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Publiée : Ιουλ 1, 2025
DOI : https://doi.org/10.12681/keimena-paideias.40464
ELEFTHERIOS METAXOUDIS
Δημοκρίτειο Πανεπιστήμιο Θράκης
https://orcid.org/0000-0002-4716-8965
Résumé

In an era of rapid technological advancements and interdisciplinary demands, Computational Philosophy offers a transformative approach to reimagining education. This study explores its integration into pedagogy, emphasizing its potential to enhance active methodologies, promote sustainability education, and incorporate artificial intelligence (AI) tools. By leveraging computational reasoning, logic programming, and AI-driven applications, educators can foster critical thinking, collaborative problem-solving, and ethical awareness. Practical applications include simulations of ethical dilemmas, AI-powered text analysis, and computational models for resource management and environmental decision-making. Computational Philosophy bridges philosophy, computer science, and sustainability, expanding pedagogical foundations and promoting collaboration across disciplines. This study reflects on its theoretical and practical contributions, addressing societal and environmental challenges to prepare learners for an interconnected world. It highlights the importance of integrating Computational Philosophy into educational innovation, equipping students with the skills to navigate ethical and technological complexities.

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Biographie de l'auteur
ELEFTHERIOS METAXOUDIS, Δημοκρίτειο Πανεπιστήμιο Θράκης

Metaxoudis Eleftherios, PhD

Références
Agbo, F. J., et al. (2021). Computational thinking and technology in education: A review of research and trends. Educational Technology Research and Development, 69(4), 1871–1893.
Alkhatib, M. A. (2019). A proposed framework for implementing higher-order thinking skills: Improving student outcomes through problem-solving and critical thinking. Journal of Higher Education Research & Development, 38(2), 309–325. 10.1109/ICASET.2019.8714232
Ângelo Magno de Jesus, T., & Silveira, I. F. (2019). Collaborative game-based learning frameworks: Enhancing computational thinking skills and social interaction. Journal of Educational Technology & Society, 22(4), 37–45. 10.1109/ICVRV47840.2019.00038
Asamoah, D. A., Doran, D., & Schiller, S. (2018). Interdisciplinarity in data science education: Enhancing learning experiences and outcomes. Journal of Information Systems Education, 29(1), 11–20.
Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J.-F., & Rahwan, I. (2022). Computational ethics: Building moral reasoning into AI systems. Journal of Ethics in AI Research, 5(1), 45–63.
Balladares Burgos, J., Araya-López, M., & Arrieta, J. (2016). Computational thinking as a cognitive skill for solving problems in STEM education. Journal of Educational Research and Innovation, 15(1), 34–47. 10.17163/SOPH.N21.2016.06
Burbules, N. C., Fan, G., & Repp, P. (2020). Five trends of education and technology in a sustainable future. Revista de Educación a Distancia, 20(62), 1–19.
Carr, D. (2004). Making Sense of Education: An Introduction to the Philosophy and Theory of Education and Teaching. Routledge.
Chambliss, J. J. (2009). Philosophy of Education: An Encyclopedia. Routledge.
Clemente Rodríguez-Sabiote, C., Olmedo-Moreno, E. M., & Salmerón Pérez, J. (2020). Educational innovation in the 21st century: Active methodologies and digital technologies. Procedia Computer Science, 172, 847–852. https://doi.org/10.1016/j.procs.2020.05.123
de Melo-Martín, I. (2008). Biomedical ethics and environmental health: Ethical decision-making in the face of complex dilemmas. Oxford University Press.
de Melo-Martín, I. (2009). Ethical perspectives in environmental health. Springer.
Windsor, K. (2024). Interdisciplinary collaboration across philosophy, computer science, and environmental science. Journal of Science and Technology, 29(1), 101–115.
Dorneles, A. G., Nogueira, M. A., & Ribeiro, A. A. (2012). The integration of computational and experimental activities to enhance students' understanding of electromagnetism concepts. Physics Education, 47(6), 687-692.
Easterbrook, S. (2014). Computational sustainability: Computing for a better world and a sustainable future. Springer. 10.2991/ict4s-14.2014.28
Floridi, L. (2002). What is the philosophy of information? Metaphilosophy, 33(1-2), 123-145. https://doi.org/10.1111/1467-9973.00221
Floridi, L. (2024). Ethics in the age of artificial intelligence. Oxford University Press. https://doi.org/10.1111/1467-9973.00221
Fuller, D., O’Donnell, T., & Henderson, J. (2007). Revolutionizing resource management with computational models. Journal of Environmental Science and Engineering, 3(1), 45-52.
Goetze, T. (2023). Interdisciplinary approaches to ethics in computer science education. Ethics and Information Technology, 25(2), 135–148. 10.1145/3545945.3569792
Gomes, J. (2011). Computational sustainability: A new paradigm for sustainable development. Sustainability Science, 6(2), 133-144.
Guerrero, S. M. (2005). Teacher knowledge for using technology: A new framework for understanding. Journal of Educational Computing Research, 33(3), 249–267.
Habron, G., & Dann, J. (2002). Enhancing resource management education through case studies and simulations. Natural Resources Management, 28(4), 215-223.
Iles, A., & Mulvihill, A. (2012). Green chemistry and interdisciplinary collaboration: Developing sustainable technologies. Sustainable Science Review, 10(3), 219–233.
Jonassen, D. H. (n.d.). Problem-Based Learning in higher education: Developing computational thinking and digital competences. Journal of Problem-Based Learning, 12(1), 25–39.
Laurillard, D. (2007). Building an interdisciplinary approach to innovation in teaching and learning. Technology, Pedagogy and Education, 16(3), 233–247. 10.1080/14759390701614496
Lin, C., Chen, X., & Li, Y. (2023). AI-powered approaches for sustainable education: Opportunities and challenges. Sustainability, 15(4), 1–20. https://doi.org/10.3390/su15043245
Lipman, M. (2014). Thinking in Education (2nd ed.). Cambridge University Press.
Lunn, S., Allen, J., & Bell, T. (2022). The development of computer science education as a formal discipline. ACM Transactions on Computing Education, 22(4), 1–30. 10.1145/3546581
McDermott, R., Biggers, M., & Ross, K. (2023). Reimagining computing education: Philosophical perspectives for STEM learning. Journal of Computing in Education, 10(1), 45-63.
Molina-Pérez, A., Rodríguez-Morales, J., & García-Sánchez, E. (2020). High-performance computing and mathematical models in climate change mitigation. Computational Sustainability, 10(1), 32-45. 10.3389/frobt.2020.00111
Onwueme, D. O., & Borsari, G. (2007). The sustainability asymptogram: Bridging sustainability education and community engagement. International Journal of Sustainability in Higher Education, 8(3), 359-369. 10.1108/14676370710717580
Ovesdotter Alm, C., Haider, S., & Lahti, R. (2016). Introducing computational linguistics in interdisciplinary workshops. Journal of Computing in Higher Education, 28(3), 302-321. 10.1111/lnc3.12195
Pabubung, J. (2021). Integrating AI and ethics into interdisciplinary education: A pathway for responsible development. Educational Innovations Quarterly, 8(3), 117–133.
Paulik, E. (1969). Simulation models for fisheries research and management education. Fisheries Science, 12(1), 99-104. 10.1577/1548-8659(1969)98[551:CSMFFR]2.0.CO;2
Psycharis, S., Chalatzoglidis, G., & Kalovrektis, K. (2020). Computational Pedagogy: A new dimension of STEAM education. International Journal of STEM Education, 7(1), 1-16. 10.51724/HJSTEMED.V1I1.4
Silva-Jurado, C., & Silva-Jurado, R. (2024). Personalized learning through AI: Innovations in active learning methodologies. Journal of Educational Technology Research, 12(1), 45–67.
Thagard, P. (1988). Computational philosophy of science. MIT Press.10.7551/mitpress/1968.001.0001
Vallance, M., & Towndrow, P. A. (2016). Pedagogy and the new literacies in networked learning. Educational Media International, 53(2), 80-94. 10.1080/1554480X.2016.1182437
Voskoglou, M. G., & Buckley, S. (2012). Problem-solving and computational thinking: Enhancing students' abilities through mathematical modeling. International Journal of Mathematical Education in Science and Technology, 43(6), 785–795. 10.20944/preprints202012.0672.v1
Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st-century problem-solving in K-12 classrooms. TechTrends, 60(6), 565-568. 10.1007/s11528-016-0087-7