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Artificial intelligence literacy in secondary education: methodological approaches and challenges

Marienko, Maiia V.; Семеріков, Сергій Олексійович; Markova, Oksana M.

URI: https://ceur-ws.org/Vol-3679/paper21.pdf
http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/10373

Date: 2024-05-06

Abstract:

Analysis of recent research and publications has shown that there is a serious problem in Ukrainian society regarding the use of artificial intelligence. The analysis of ZN.UA survey data showed that the majority of respondents do not know what artificial intelligence is and do not use it. Therefore, there are certain prejudices regarding the use of artificial intelligence in education. The concept of “artificial intelligence literacy” as a component of digital competence needs further research. Literacy in the field of artificial intelligence can be the basis for creating methods of using artificial intelligence in secondary education in Ukraine. The article presents the main components of literacy in the field of artificial intelligence. The author proposes to adapt the experience of digital story writing to the secondary education of Ukraine. At the same time, digital storytelling involves the use of artificial intelligence services as aids. It is shown that the toolkit of the European cloud of open science contains not only cloud services of open science, but also services of artificial intelligence (which are both cloud-based and based on the principles of open science). For example, the basic principles of working with the artificial intelligence service AI-GeoSpecies (included in the European cloud of open science) are considered. Within the framework of the performed research, an intermediate section of the ascertaining stage of the pedagogical experiment was conducted. It was found that teachers need further professional development measures on the topic of using artificial intelligence services. There is a need to create methods for secondary education using artificial intelligence in the educational process. The attitude of teachers towards artificial intelligence services is positive. Educators have repeatedly used artificial intelligence and know the interpretation of this term.

Description:

[1] N. V. Valko, T. L. Goncharenko, N. O. Kushnir, V. V. Osadchyi, Cloud technologies for basics of artificial intelligence study in school, CTE Workshop Proceedings 9 (2022) 170–183. doi:10.55056/cte.113. [2] A. V. Riabko, T. A. Vakaliuk, Physics on autopilot: exploring the use of an AI assistant for independent problem-solving practice, Educational Technology Quarterly 2024 (2024) 56–75. doi:10.55056/etq.671. [3] Y. Samaieva, The attitude of Ukrainians to artificial intelligence is surprisingly frivolous. For nothing, 2023. URL: https://zn.ua/ukr/TECHNOLOGIES/stavlennja-ukrajintsiv-do-shtuchnoho-intelektu-na-divo-lehkovazhne-darma.html. [4] K. S. Tarisayi, Strategic leadership for responsible artificial intelligence adoption in higher education, CTE Workshop Proceedings 11 (2024) 4–14. doi:10.55056/cte.616. [5] D. T. K. Ng, W. Luo, H. M. Y. Chan, S. K. W. Chu, Using digital story writing as a pedagogy to develop AI literacy among primary students, Computers and Education: Artificial Intelligence 3 (2022) 100054. doi:10.1016/j.caeai.2022.100054. [6] S. Beltozar-Clemente, F. Sierra-Liñan, J. Zapata-Paulini, M. Cabanillas-Carbonell, Augmented reality mobile application to improve the astronomy teaching-learning process, Advances in Mobile Learning Educational Research 2 (2022) 464–474. doi:10.25082/AMLER.2022.02.015. [7] E. Campos-Pajuelo, L. Vargas-Hernandez, F. Sierra-Liñan, J. Zapata-Paulini, M. Cabanillas-Carbonell, Learning the chemical elements through an augmented reality application for elementary school children, Advances in Mobile Learning Educational Research 2 (2022) 493–501. doi:10.25082/AMLER.2022.02.018. [8] G. Antoniadi, Using an augmented reality application for teaching plant parts: A case study in 1st -grade primary school students, Advances in Mobile Learning Educational Research 3 (2023) 630–637. doi:10.25082/AMLER.2023.01.012. [9] Z. H. İpek, A. İbrahim Can Gözüm, P. Stamatios, K. Michail, Educational applications of ChatGPT, an AI system: A systematic review research, Educational Process 12 (2023) 26–55. doi:10.22521/edupij.2023.123.2. [10] T. Karaköse, M. Demirkol, N. Aslan, H. Köse, R. Yirci, A Conversation with ChatGPT about the Impact of the COVID-19 Pandemic on Education: Comparative Review Based on Human-AI Collaboration, Educational Process International Journal 12 (2023) 7–25. doi:10.22521/edupij.2023.123.1. [11] S. Garg, S. Sharma, Impact of Artificial Intelligence in Special Need Education to Promote Inclusive Pedagogy, International Journal of Information and Education Technology 10 (2020) 523–527. doi:10.18178/ijiet.2020.10.7.1418. [12] J. Su, D. T. K. Ng, S. K. W. Chu, Artificial Intelligence (AI) Literacy in Early Childhood Education: The Challenges and Opportunities, Computers and Education: Artificial Intelligence 4 (2023) 100124. doi:10.1016/j.caeai.2023.100124. [13] L. O. Fadieieva, Enhancing adaptive learning with moodle’s machine learning, Educational Dimension 5 (2021) 1–7. doi:10.31812/ed.625. [14] S. O. Semerikov, T. A. Vakaliuk, I. S. Mintii, V. A. Hamaniuk, V. N. Soloviev, O. V. Bondarenko, P. P. Nechypurenko, S. V. Shokaliuk, N. V. Moiseienko, V. R. Ruban, Development of the computer vision system based on machine learning for educational purposes, Educational Dimension 5 (2021) 8–60. doi:10.31812/educdim.4717. [15] O. V. Klochko, V. M. Fedorets, V. I. Klochko, Empirical comparison of clustering and classification methods for detecting Internet addiction, CTE Workshop Proceedings 11 (2024) 273–302. URL: https://acnsci.org/journal/index.php/cte/article/view/664. doi:10.55056/cte.664. [16] M. Tedre, T. Toivonen, J. Kahila, H. Vartiainen, T. Valtonen, I. Jormanainen, A. Pears, Teaching Machine Learning in K–12 Classroom: Pedagogical and Technological Trajectories for Artificial Intelligence Education, IEEE Access 9 (2021) 110558–110572. doi:10.1109/ACCESS.2021.3097962. [17] W. Yang, Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation, Computers and Education: Artificial Intelligence 3 (2022) 100061. doi:10.1016/j.caeai.2022.100061. [18] M. Shyshkina, Y. Nosenko, Promising technologies with elements of AI for professional development of teaching, Physical and Mathematical Education 38 (2023) 66–71. doi:10.31110/2413-1571-2023-038-1-010. [19] L. Panchenko, Digital storytelling in adult education: barriers and ways to overcome them, Educational Technology Quarterly 2021 (2021) 673–688. doi:10.55056/etq.41. [20] EdTechTeacher, 8 Steps to Great Digital Storytelling, 2013. URL: https://edtechteacher.org/8-steps-to-great-digital-storytelling-from-samantha-on-edudemic/. [21] M. Marienko, M. Shyshkina, The Design and Implementation of the Cloud-Based System of Open Science for Teachers’ Training, in: M. E. Auer, W. Pachatz, T. Rüütmann (Eds.), Learning in the Age of Digital and Green Transition, Springer International Publishing, Cham, 2023, pp. 337–344. doi:10.1007/978-3-031-26876-2_31. [22] M. V. Marienko, Tools and Services of the Cloud-Based Systems of Open Science Formation in the Process of Teachers’ Training and Professional Development, in: S. Wrycza, J. Maślankowski (Eds.), Digital Transformation, Springer International Publishing, Cham, 2021, pp. 108–120. doi:10.1007/978-3-030-85893-3_8. [23] Cos4Cloud, AI-GeoSpecies, 2020. URL: https://cos4cloud-eosc.eu/services/ai-geospecies/. [24] Pl@ntNet, GeoPl@ntNet Beta version, 2024. URL: https://identify.plantnet.org/prediction.

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