The Adventure of Artificial Intelligence Technology in Education: Comprehensive Scientific Mapping Analysis

Year 2023, Volume: 10 Issue: 4, 144 - 165, 01.07.2023

Adem Karaca , Bahadır Kılcan

https://doi.org/10.17275/per.23.64.10.4

Cited By: 3

Abstract

It is known that recent studies on artificial intelligence technologies have been handled by different branches of science. One of the mentioned branches of science is education. The rapid increase in the production of artificial intelligence studies in the field of education in recent years attracts the attention of researchers. In this context, the purpose of the present study was to analyze the bibliometric aspects of journal publications on artificial intelligence technology in educational research. The R-Studio tool was used to examine the data set, which was collected from the Web of Science database. The only index fields allowed for articles are SSCI, SCI-Expanded, and ESCI. According to the results of the study, the journal articles on artificial intelligence technologies have appeared to have significantly increased in recent years. The United States, China, and Spain are the most prolific nations in this regard. Despite being among the ten most productive nations, Türkiye and Russia are among those that do not collaborate internationally. It has been found that journal articles on artificial intelligence give a lot of attention to subjects like dropout, chatbot, language learning, student involvement and performance, e-learning, and collaborative learning. We hope that this research will give academics who desire to study artificial intelligence technologies a general overview.

Keywords

Artifical Intelligence, Machine Learning, Map Analysis, R-Studio

References

• Afrianto, (2018). Being a professional teacher in the era of industrial revolution 4.0: opportunities, challenges and strategies for innovative classroom practices, English Language Teaching and Research, 2(1), 1-13.
• Akcan, C., Doğan, M. & Ablak, S. (2023). Bibliometric analysis of studies on 21st century skills in education. Gazi University Journal of Gazi Educational Faculty, 43(1), 331-362.
• Alam, A. (2021). Should robots replace teachers? Mobilisation of AI and learning analytics in education, 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3), Mumbai, India, pp. 1-12, doi: 10.1109/ICAC353642.2021.9697300.
• Aldosari, S. A. M. (2020). The future of higher education in the light of artificial intelligence transformations, International Journal of Higher Education, 9(3), 145-151.
• 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
• Arslan, K. (2020). Artificial intelligence and applications in education. The Western Anatolia Journal of Educational Sciences, 11(1), 71-88.
• Asakura, K., Occhiuto, K., Todd, S., Leithead, C., & Clapperton, R. (2020). A call to action on artificial intelligence and social work education: Lessons learned from a simulation project using natural language processing. Journal of Teaching in Social Work, 40(5), 501-518.
• Bañeres, D., Rodríguez-González, M. E., Guerrero-Roldán, A., & Cortadas, P. (2023). An early warning system to identify and intervene online dropout learners. International Journal of Educational Technology in Higher Education, 20(1), 1-25. https://doi.org/10.1186/s41239-022-00371-5
• Basnet, R. B., Johnson, C. H., & Doleck, T. (2022). Dropout prediction in moocs using deep learning and machine learning. Education and Information Technologies, 27(8), 11499-11513. https://doi.org/10.1007/s10639-022-11068-7
• Becker, B. A. (2017). Artificial intelligence in education: What is it, where is it now, where is it going. Ireland’s Yearbook of Education 2017-2018, 42-46. https://www.brettbecker.com/wp-content/uploads/2019/04/Becker-AI-in-Education-with-cover-sheet.pdf
• Bhutoria, (2022). Personalized education and artificial intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model, Computers and Education: Artificial Intelligence, 3, https://doi.org/10.1016/j.caeai.2022.100068
• Bozdoğan, K. & Sönmez, Ö. F. (2023). Bibliometric analysis of educational research articles published in the field of history education based on the web of science database. Cumhuriyet International Journal of Education, 12(1), 16-28. https://doi.org/10.30703/cije.1104813
• Burgard, W. (2022). Artificial intelligence key technologies and opportunities, S. Voeneky, P. Kellmeyer, O. Mueller and W. Burgard (Eds.) in The Cambridge Handbook of Responsible Artificial Intelligence interdisciplinary perspectives, Cambridge University Press.
• Burgsteiner, H., Kandlhofer, M., & Steinbauer, G. (2016). IRobot: Teaching the basics of artificial ıntelligence in high schools. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.9864
• Cao, X., Li, Z., & Zhang, R. (2021). Analysis on academic benchmark design and teaching method improvement under artificial intelligence robot technology. International Journal of Emerging Technologies in Learning, 15(5). https://doi.org/10.3991/ijet.v16i05.20295
• Cantú-Ortiz, F.J., Galeano Sánchez, N., Garrido, L., Terashima-Marin, H., Brena, R. F. (2020). An artificial intelligence educational strategy for the digital transformation. International Journal on Interactive Design and Manufacturing (IJIDeM) ,14, 1195–1209. https://doi.org/10.1007/s12008-020-00702-8
• Chai, C. S., Lin, P.-Y., Jong, M. S.-Y., Dai, Y., Chiu, T. K. F., & Qin, J. (2021). Perceptions of and behavioral intentions towards learning artificial intelligence in primary school students. Educational Technology & Society, 24(3), 89–101. https://www.jstor.org/stable/27032858
• Chen, X., Xie, H., Zou, D., & Hwang, G. (2020). Application and theory gaps during the rise of artificial intelligence in education. Comput. Educ. Artif. Intell., 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
• Chiu, T. K. F., Meng, H., Chai, C. S., King, I., Wong, S. & Yam, Y. (2022). Creation and evaluation of a pretertiary artificial intelligence (AI) curriculum," IEEE Transactions on Education, 65(1), pp. 30-39, doi: 10.1109/TE.2021.3085878.
• Chiu, T.K.F. (2021). A holistic approach to the design of artificial intelligence (AI) education for K-12 schools. TechTrends 65, 796–807 https://doi.org/10.1007/s11528-021-00637-1
• Chu, S., Hwang, G., & Tu, Y. (2022). Artificial intelligence-based robots in education: A systematic review of selected SSCI publications. Computers & Education: Artificial Intelligence, 3, 100091. https://doi.org/10.1016/j.caeai.2022.100091
• Clyde, J., Hopkins, H., Wilkinson, G. (2012). Beyond the “historical” simulation: Using theories of history to inform scholarly game design. Loading… The Journal of the Canadian Game Studies Association, 6(9), 3-16.
• Cope, B., Kalantzis, M. & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies, Educational Philosophy and Theory, 53(12), 1229-1245, DOI: 10.1080/00131857.2020.1728732
• Çetin, M. & Aktaş, A. (2021). Artificial intelligence and future scenarios in education. OPUS International Journal of Society Researches, Educational Sciences Special Issue, 4225-4268 DOI: 10.26466/opus.911444
• Domínguez, A. C., Saenz-De-Navarrete, J., De-Marcos, L., Fernandez-Sanz, L., Pagés, C., & Martinez-Herraiz, J. (2013). Gamifying learning experiences: Practical implications and outcomes. Computers & Education, 63, 380–392. https://doi.org/10.1016/j.compedu.2012.12.020
• Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of big data—evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021
• Dyatkin, B. (2022). Private and public efforts infuse artificial intelligence into materials research. MRS Bulletin, 524-528.
• Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact?. Scientometrics, 105, 1809-1831. https://doi.org/10.1007/s11192-015-1645-z
• Fahimirad, M. & Kotamjani, S. S. (2018). A review on application of artificial intelligence in teaching and learning in educational contexts, International Journal of Learning and Development, 8(4), 106-118. https://doi.org/10.5296/ijld.v8i4.14057
• Fitria, T. N. (2021). Artificial intelligence (AI) in education: Using AI tools for teaching and learning process. Prosiding Seminar Nasional & Call for Paper STIE AAS, 4(1), 134–147. Retrieved from https://prosiding.stie-aas.ac.id/index.php/prosenas/article/view/106
• Francesc, P., Miguel, S., Axel, R., & Paula, V., (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. UNESCO Working Papers on Education Policy. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000366994
• Garfield, E. (1990). Keywords Plus: ISI’s breakthrough retrieval method. Part 1. Expanding your searching power on current contents on diskette. Current Comments, 1(32), 5-9.
• Gamage, S. H. P. W., Ayres, J. R., & Behrend, M. (2022). A systematic review on trends in using Moodle for teaching and learning. International Journal of STEM Education, 9(1). https://doi.org/10.1186/s40594-021-00323-x
• Golonka, E. M., Bowles, A. R., Frank, V. M., Richardson, D. L., & Freynik, S. (2014). Technologies for foreign language learning: A review of technology types and their effectiveness. Computer Assisted Language Learning, 27(1), 70–105. https://doi.org/10.1080/09588221.2012.700315
• Guerrero-Bote, V.P., & Moya-Anegón, F. (2012). A further step forward in measuring journals’ scientific prestige: The SJR2 indicator. Journal of Informetrics, 6(4), 674-688. https://doi.org/10.1016/j.joi.2012.07.001
• Hinojo-Lucena, F.J., Aznar-Díaz, I., Cáceres-Reche, M.P., & Romero-Rodríguez, J.M. (2019). Artificial intelligence in higher education: A bibliometric study on its impact in the scientific literature. Education Sciences, 9(1), 51. https://doi.org/10.3390/educsci9010051
• Holmes, W., Bialik, M. & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston, MA: Center for Curriculum Redesign. https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf
• Holmes, W., Persson, J., Chounta, I. A., Wasson, B., & Dimitrova, V. (2022) Artificial intelligence and education a critical view through the lens of human rights, democracy and the rule of law. The Council of Europe: Strasbourg, France.
• Huang, S. (2021). Design and development of educational robot teaching resources using artificial intelligence technology. International Journal of Emerging Technologies in Learning, 15(5). https://doi.org/10.3991/ijet.v16i05.20311
• Huawei Technologies Co., Ltd. (2021). “A General Introduction to Artificial Intelligence.” Artificial Intelligence Technology, Springer. https://link.springer.com/book/10.1007/978-981-19-2879-6
• Hwang, G., & Chang, C. (2021). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 1–14. https://doi.org/10.1080/10494820.2021.1952615
• Hwang, G., Tu, Y., & Tang, K. (2022). AI in online-learning research: Visualizing and interpreting the journal publications from 1997 to 2019. The International Review of Research in Open and Distributed Learning, 23(1), 104–130. https://doi.org/10.19173/irrodl.v23i1.6319
• Hwang, G., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of artificial intelligence in education. Computers & Education: Artificial Intelligence, 1, [100001]. https://doi.org/10.1016/j.caeai.2020.100001
• İşler, B. & Kılıç, M. (2021). The use and development of artificial intelligence in education. e-Journal of New Media, 5(1), 1-11.
• Kannan, J. & Munday, P. (2018). New trends in second language learning and teaching through the lens of ICT, networked learning, and artificial intelligence. Círculo de Lingüística Aplicada a la Comunicación, 76, 13-30 http://dx.doi.org/10.5209/CLAC.62495
• Kasepalu, R., Prieto, L. P., Ley, T., & Chejara, P. (2022). Teacher artificial intelligence-supported pedagogical actions in collaborative learning coregulation: A wizard-of-oz study. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.736194
• Khemani, D. (2013). A first course in artificial intelligence, India: McGraw Hill Education.
• Kim, H., Yang, H., Shin, D., & Lee, J. H. (2022). Design principles and architecture of a second language learning chatbot. Language Learning & Technology, 26(1), 1-18.
• Kloft, M., Stiehler, F., Zheng, Z., & Pinkwart, N. (2014, October). Predicting MOOC dropout over weeks using machine learning methods. In Proceedings of the EMNLP 2014 workshop on analysis of large-scale social interaction in MOOCs (pp. 60-65).
• Lameras, P. & Arnab, S. (2022). Power to the teachers: an exploratory review on artificial intelligence in education. Information, 13(1):14. https://doi.org/10.3390/info13010014
• Lasso-Rodríguez, G., & Gil-Herrera, R. (2019). Robotic process automation applied to education: a new kind of robot teacher? ICERI Proceedings. https://doi.org/10.21125/iceri.2019.0669
• Lykourentzou, I., Giannoukos, I., Nikolopoulos, V., Mpardis, G., & Loumos, V. (2009). Dropout prediction in e-learning courses through the combination of machine learning techniques. Computers & Education, 53(3), 950–965. https://doi.org/10.1016/j.compedu.2009.05.010
• Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60.
• Malik, R., Shrama, A., Trivedi, S., & Mishra, R. (2021). Adoption of chatbots for learning among university students: role of perceived convenience and enhanced performance. International Journal of Emerging Technologies in Learning (iJET), 16(18), 200-212. https://doi.org/10.3991/ijet.v16i18.24315
• Martin F., & Kumar, S. (2018). “Frameworks for Assessing and Evaluating e-Learning Courses and Programs.” In Leading and Managing e-learning Educational Communications and Technology: Issues and Innovations, edited by A. Piña, V. Lowell, and B. Harris, 271-80. Cham: Springer. https://doi.org/10.1007/978-3-319-61780-0_19.
• McBurney, M. K., & Novak, P. L. (2002, September). What is bibliometrics and why should you care? In Proceedings. IEEE international professional communication conference (pp. 108-114). IEEE.
• McKnight, L. (2021). Electric sheep? Humans, robots, artificial intelligence, and the future of writing. Changing English, 28(4), 442-455.
• Melo, E., Silva, I., Costa, D. P., De Assis Viegas, C. A., & Barros, T. H. B. (2022). On the use of eXplainable artificial intelligence to evaluate school dropout. Education Sciences, 12(12), 845. https://doi.org/10.3390/educsci12120845
• Moore, J. L., Dickson-Deane, C., & Galyen, K. (2011). E-Learning, online learning, and distance learning environments: Are they the same? Internet and Higher Education, 14(2), 129–135. https://doi.org/10.1016/j.iheduc.2010.10.001
• Morgenstern, D. M. (1992). Shifting paradigms, shifting sands: Interactive multimedia for language learning. Simulation & Gaming, 23(1), 82-87.
• Müller, A. M., Goh, C. E., Lim, L., & Gao, X. (2021). COVID-19 Emergency eLearning and beyond: Experiences and perspectives of university educators. Education Sciences, 11(1), 19. https://doi.org/10.3390/educsci11010019
• Norouzi, N., Chaturvedi, S., & Rutledge, M. (2020, April). Lessons learned from teaching machine learning and natural language processing to high school students. In Proceedings of the AAAI conference on artificial intelligence (Vol. 34, No. 09, pp. 13397-13403).
• Oke, A., and Fernandes F.A.P. (2020). Innovations in teaching and learning: Exploring the perceptions of the education sector on the 4th industrial revolution (4IR). Journal of Open Innovation: Technology, Market, and Complexity, 6(2):31. https://doi.org/10.3390/joitmc6020031
• Onan, A. (2020). Mining opinions from instructor evaluation reviews: A deep learning approach. Computer Applications in Engineering Education, 28(1), 117–138. https://doi.org/10.1002/cae.22179
• Palaz, T. (2022). Science mapping research on social studies education: A bibliometric analysis of international publications. International Online Journal of Education and Teaching, 9(1), 46-68.
• Pokrivčáková, S. (2019). Preparing teachers for the application of AI-powered technologies in foreign language education. Journal of Language and Cultural Education, 7(3), 135–153. https://doi.org/10.2478/jolace-2019-0025
• Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education, Research and Practice in Technology Enhanced Learning, 12(22), 1-13. DOI 10.1186/s41039-017-0062-8
• Rapanyane, M. B. & Sethole, F. R. (2020) The rise of artificial intelligence and robots in the 4th Industrial Revolution: implications for future South African job creation, Contemporary Social Science, 15:4, 489-501, DOI: 10.1080/21582041.2020.1806346
• Roll, I. & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. Int J Artif Intell Educ 26, 582–599. https://doi.org/10.1007/s40593-016-0110-3
• Rosé, C. P., Wang, Y., Cui, Y., Arguello, J., Stegmann, K., Weinberger, A., & Fischer, F. (2008). Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning. International Journal of Computer-supported Collaborative Learning, 3(3), 237–271. https://doi.org/10.1007/s11412-007-9034-0
• Russell, S. J. & Norvig, P (2010). Artificial Intelligence: A Modern Approach, 3rd ed. Pearson Education, Upper Saddle River, New Jersey.
• Sandu, N., & Gide, E. (2019, September). Adoption of AI-Chatbots to enhance student learning experience in higher education in India. In 2019 18th International Conference on Information Technology Based Higher Education and Training (ITHET) (pp. 1-5). IEEE.
• Sanusi, I. T., Oyelere, S. S., Vartiainen, H., Suhonen, J., & Tukiainen, M. (2022). A systematic review of teaching and learning machine learning in K-12 education. Education and Information Technologies. https://doi.org/10.1007/s10639-022-11416-7
• Schulze, M. (2008). AI in CALL-artificially inflated or almost imminent? Calico Journal, 25(3), 510-527.
• Shaikh, A.A., Kumar, A., Jani, K., Mitra, S., García-Tadeo, D.A. & Devarajan, A. (2022). The role of machine learning and artificial intelligence for making a digital classroom and its sustainable impact on education during COVID-19. Mater. Today Proc. 56, 3211–3215.
• Shukla, S. S. & Jaiswal, V. (2013). Applicability of artificial intelligence in different fields of life, International Journal of Scientific Engineering and Research (IJSER), (1)1,28-35.
• Sökmen, Y., & Nalçacı, A. (2020). A bibliometric analysis of the articles about values education. International Journal of Curriculum and Instruction, 12(2), 720-735.
• Tamayo, P. R. V., Herrero, A. M., Martín, J., Navarro, C., & Tránchez, J. M. (2020). Design of a chatbot as a distance learning assistant. Open Praxis, 12(1), 145. https://doi.org/10.5944/openpraxis.12.1.1063
• Tripathi, M., Kumar, S., Sonker, S. K., & Babbar, P. (2018). Occurrence of author keywords and keywords plus in social sciences and humanities research: A preliminary study. Journal of Scientometrics and Information Management, 12(2), 215-232. doi:10.1080/09737766.2018.1436951
• Van Den Berghe, R., Verhagen, J., Oudgenoeg-Paz, O., Van Der Ven, S. H., & Leseman, P. P. (2019). Social robots for language learning: A Review. Review of Educational Research, 89(2), 259–295. https://doi.org/10.3102/0034654318821286
• Viktorivna, K. S., Oleksandrovych, V. A., Oleksandrivna, K. L., & Oleksandrivna, K. L. (2022). Artificial intelligence in language learning: What are we afraid of. Arab World English Journal, 8, 262–273. https://doi.org/10.24093/awej/call8.18
• Wang, J., & Zhan, Q. (2021). Visualization analysis of artificial intelligence technology in higher education based on SSCI and SCI Journals from 2009 to 2019. International Journal of Emerging Technologies in Learning (IJET), 16(08), 20. https://doi.org/10.3991/ijet.v16i08.18447
• Wu, L., Chen, Y., Shen, K., Guo, X., Gao, H., Li, S., & Long, B. (2023). Graph neural networks for natural language processing: A survey. Foundations and Trends® in Machine Learning, 16(2), 119-328.
• Xing, W., & Du, D. (2019). Dropout prediction in MOOCs: Using deep learning for personalized intervention. Journal of Educational Computing Research, 57(3), 547–570. https://doi.org/10.1177/0735633118757015
• Xing, W., Tang, H., & Pei, B. (2019). Beyond positive and negative emotions: Looking into the role of achievement emotions in discussion forums of MOOCs. Internet and Higher Education, 43, 100690. https://doi.org/10.1016/j.iheduc.2019.100690
• Yang, C., Huan, S., & Yang, Y. (2020). A Practical teaching mode for colleges supported by artificial intelligence. International Journal of Emerging Technologies in Learning (İJET), 15(17), pp. 195–206. https://doi.org/10.3991/ijet.v15i17.16737
• Zhan, Z., Tong, Y., Lan, X., & Zhong, B. (2022a). A systematic literature review of game-based learning in artificial intelligence education. Interactive Learning Environments, 1–22. https://doi.org/10.1080/10494820.2022.2115077
• Zhan, Z., He, G., Li, T., Zhang, H., & Xiang, S. (2022b). Effect of groups size on students’ learning achievement, motivation, cognitive load, collaborative problem‐solving quality, and in‐class interaction in an introductory AI course. Journal of Computer Assisted Learning, 38(6), 1807–1818. https://doi.org/10.1111/jcal.12722