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Artificial Intelligence for a Sustainable Future in the 21st Century: Impacts and Reflections on Education Cover

Artificial Intelligence for a Sustainable Future in the 21st Century: Impacts and Reflections on Education

By: Gökçe Ok,  Deniz Kaya and  Tamer Kutluca  
Open Access
|Apr 2025

References

  1. Alamäki, A., Nyberg, C., Kimberley, A., & Salonen, A. O. (2024) Artificial intelligence literacy in sustainable development: A learning experiment in higher education. Frontiers Education, 9(1), 1-10. https://doi.org/10.3389/feduc.2024.1343406
  2. Alamäki, A., Mäki, M., & Kauttonen, J. (2023). How students’ information sensitivity, privacy trade-offs and stages of customer journey affect consent to utilize personal data. Interdisciplinary Journal of Information, Knowledge, and Management, 18, 127-174. https://doi.org/10.28945/5098
  3. Algureìn, B. (2021). How to bring about change-A literature review about education and learning activities for sustainable development. Discourse and Communication for Sustainable Education, 12(1), 5-21. https://doi.org/10.2478/dcse-2021-0002
  4. Al-Sharafi, M. A., Al-Emran, M., Iranmanesh, M., Al-Qaysi, N., Iahad, N. A., & Arpaci, I. (2023). Understanding the impact of knowledge management factors on the sustainable use of AI-based chatbots for educational purposes using a hybrid SEM-ANN approach. Interactive Learning Environments, 31(10), 7491-7510. https://doi.org/10.1080/10494820.2022.2075014
  5. Al-Zahrani, A. M. (2024). Unveiling the shadows: Beyond the hype of AI in education. Heliyon, 10(9), 1-15. https://doi.org/10.1016/j.heliyon.2024.e30696
  6. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
  7. Arksey, H., & O’Malley, L. (2005). Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology: Theory & Practice, 8(1), 19–32. https://doi.org/10.1080/-1364557032000119616
  8. Bağış, M. (2021). Main analysis techniques used in bibliometric research. In Öztürk, O., & Gürler, G. (Eds.) Bibliometric analysis as a literature review tool (pp. 97-123). Nobel Academic.
  9. Birkle, C., Pendlebury, D. A., Schnell, J., & Adams, J. (2020). Web of Science as a data source for research on scientific and scholarly activity. Quantitative Science Studies, 1(1), 363–376. https://doi.org/10.11-62/qss_a_00018
  10. Cevikbas, M., Kaiser, G., & Schukajlow, S. (2024). Trends in mathematics education and insights from a meta-review and bibliometric analysis of review studies. ZDM Mathematics Education 56(2), 165–188. https://doi.org/10.1007/s11858-024-01587-7
  11. Cevikbas, M., Kaiser, G., & Schukajlow, S. (2022). A systematic literature review of the current discussion on mathematical modelling competencies: State-of-the-art developments in conceptualizing, measuring, and fostering. Educational Studies in Mathematics, 109(2), 205–236. https://doi.org/10.1007/s10649-021-10104-6
  12. Chen, H. E., Sun, D., Hsu, T. C., Yang, Y., & Sun, J. (2023). Visualising trends in computational thinking research from 2012 to 2021: A bibliometric analysis. Thinking Skills and Creativity, 47(7), 1-18. https://doi.org/10.1016/j.tsc.2022.101224
  13. Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1(3), 1-20. https://doi.org/10.1016/j.caeai.2020.100002
  14. Chen, X., Yu, G., Cheng, G., & Hao, T. (2019). Research topics, author profiles, and collaboration networks in the top-ranked journal on educational technology over the past 40 years: A bibliometric analysis. Journal of Computers in Education, 6(4), 563-585. https://doi.org/10.1007/s40692-019-00149-1
  15. Chiu, T. K., & Chai, C. S. (2020). Sustainable curriculum planning for artificial intelligence education: A self-determination theory perspective. Sustainability, 12(14), 1-18. https://doi.org/10.3390/su1214-5568
  16. Cobo, M., Lopez-Herrera, A., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field. Journal of Informetrics, 5(1), 146-166. https://doi.org/10.1016/j.joi.2010.10.002
  17. Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches (3rd Ed.), Sage.
  18. Dağhan, G., & Akkoyunlu, B. (2015). General trends of the studies about the sustainability of the technology usage in education: a thematic content analysis study. Education and Science, 40(178), 225-253. http://dx.doi.org/10.15390/EB.2015.4175
  19. Dhiman, R., Miteff, S., Wang, Y., Ma, S. C., Amirikas, R., & Fabian, B. (2024). Artificial intelligence and sustainability-A review. Analytics, 3(1), 140-164. https://doi.org/10.3390/analytics3010008
  20. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133(5), 285-296. https://doi.org/10.1016/-j.jbusres.2021.04.070
  21. Findlay, K., & van Rensburg, O. (2018). Using interaction networks to map communities on Twitter. International Journal of Market Research, 60(2), 169-189. https://doi.org/10.1177/147078531-7753025
  22. Fu, Y., Weng, Z., & Wang, J. (2024). Examining AI use in educational contexts: A scoping meta-review and bibliometric analysis. International Journal of Artificial Intelligence in Education, 1-57 (in press). https://doi.org/10.1007/s40593-024-00442-w
  23. Gašević, D., Siemens, G., & Sadiq, S. (2023). Empowering learners for the age of artificial intelligence. Computers and Education: Artificial Intelligence, 4(4), 1-4. https://doi.org/10.1016/j.caeai.2023.100-130
  24. Goralski, M. A., & Tan, T. K. (2020). Artificial intelligence and sustainable development. The International Journal of Management Education, 18(1), 1-9. https://doi.org/10.1016/j.ijme.2019.100330
  25. Hwang, G. J., Hung, P. H., Chen, N. S., & Liu, G. Z. (2014). Mindtool-assisted in-field learning (MAIL): An advanced ubiquitous learning project in Taiwan. Educational Technology and Society, 17(2), 4-16.
  26. Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability, 15(16), 1-27. https://doi.org/10.33-90/su151612451
  27. Leal Filho, W., Yang, P., Eustachio, J. H. P. P., Azul, A. M., Gellers, J. C., Gielczyk, A., Dinis, M. A. P., & Kozlova, V. (2023). Deploying digitalisation and artificial intelligence in sustainable development research. Environment, Development and Sustainability, 25(6), 4957-4988. https://doi.org/10.1007/s10668-022-02252-3
  28. Liao, H., Tang, M., Li, Z., & Lev, B. (2019). Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on essential science indicators. Omega, 88(C), 223-236. https://doi.org/10.1016/j.omega.2018.11.005
  29. Lin, C. C., Huang, A. Y. Q., & Lu, O. H. T. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: A systematic review. Smart Learning Environments, 10(41), 1-22. https://doi.org/10.1186/s40561-023-00260-y
  30. Meylani, R. (2024). Artificial intelligence in the education of teachers: a qualitative synthesis of the cutting-edge research literature. Journal of Computer and Education Research, 12(24), 600-637. https://doi.org/10.18009/jcer.1477709
  31. Mostafa, M. M. (2023). Three decades of interactive learning environments: A retrospective bibliometric network analysis. Interactive Learning Environments, 31(10), 6968-6987. https://doi.org/10.10-80/10494820.2022.2057548
  32. Nedungadi, P., Tang, K. Y., & Raman, R. (2024). The transformative power of generative artificial ıntelligence for achieving the sustainable development goal of quality education. Sustainability, 16(22), 1-27. https://doi.org/10.3390/su16229779
  33. Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53(C), 1-13. https://doi.org/10.1016/j.ijinfomgt.2020.102104
  34. Organisation for Economic Co-operation and Development (OECD) (2018). The future of education skills: Education 2030. https://www.oecd.org/en/about.html
  35. 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., Hrobjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(71), 1–9. https://doi.org/10.1136/-bmj.n71
  36. Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000366994
  37. Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach. Pearson.
  38. Saritepeci, M., & Yildiz Durak, H. (2024). Effectiveness of artificial intelligence integration in design-based learning on design thinking mindset, creative and reflective thinking skills: An experimental study. Education and Information Technologies, 29(18), 25175–25209. https://doi.org/10.1007/s10639-024-12829-2
  39. United Nations Educational, Scientific and Cultural Organization (UNESCO) (2015). Transforming our world: The 2030 agenda for sustainable development. https://www.refworld.org/legal/-resolution/unga/2015/en/111816
  40. Van Eck N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
  41. Verbeek, A., Debackere, K., Luwel, M., & Zimmermann, E. (2002). Measuring progress and evolution in science and technology-I: the multiple uses of bibliometric indicators. International Journal of Management Reviews, 4(2), 179-211. https://doi.org/10.1111/1468-2370.00083
  42. Web of Science Group (WoSG) (2025). Web of Science Core Collection. https://clarivate.com/
  43. Yeung, K. (2020). Recommendation of the council on artificial intelligence (OECD). International Legal Materials, 59(1), 27-34.
  44. Yuskovych-Zhukovska, V., Poplavska, T., Diachenko, O., Mishenina, T., Topolnyk, Y., & Gurevych, R. (2022). Application of artificial intelligence in education. Problems and opportunities for sustainable development. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 13(1), 339-356. https://doi.org/10.18662/brain/13.1Sup1/322
  45. 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(1), 1-27. https://doi.org/10.1186/s41239-019-0171-0
Language: English
Page range: 109 - 136
Published on: Apr 19, 2025
Published by: Daugavpils University
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2025 Gökçe Ok, Deniz Kaya, Tamer Kutluca, published by Daugavpils University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.