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The Attitudes of K–12 Schools’ Teachers in Serbia towards the Potential of Artificial Intelligence

Author

Listed:
  • Valentin Kuleto

    (LINK Group Belgrade, Information Technology School ITS-Belgrade, Faculty of Contemporary Arts Belgrade, University Business Academy in Novi Sad, 11000 Belgrade, Serbia)

  • Milena P. Ilić

    (LINK Group Belgrade, Information Technology School ITS-Belgrade, Faculty of Contemporary Arts Belgrade, University Business Academy in Novi Sad, 11000 Belgrade, Serbia)

  • Rocsana Bucea-Manea-Țoniş

    (Doctoral School, National University of Physical Education and Sport, 060057 Bucharest, Romania)

  • David-Florin Ciocodeică

    (Marketing Department, The Bucharest University of Economic Studies, 010404 Bucharest, Romania)

  • Horia Mihălcescu

    (Marketing Department, The Bucharest University of Economic Studies, 010404 Bucharest, Romania)

  • Veronica Mindrescu

    (Faculty of Physical Education and Mountain Sports, Transylvania University Brasov, 010374 Brasov, Romania)

Abstract

Similar to so many other aspects of modern life, education is gradually being automated by technological means. The software, apps, systems, platforms, and digital devices that permeate modern education are inextricably linked to these automated processes. One of the primary goals of automation has always been to improve quality and efficiency by reducing the number of human repetitive tasks based on machine learning (ML) algorithms and applications that facilitate the automation of decision-making of artificial intelligence (AI). Thus, computers and robots are predictable and do exactly what they are programmed to do. It is impossible for a computer’s memory or processing power to become “tired” because machines never rest, and now some activities can be automated, thanks to advances in artificial intelligence. Schools nowadays have software that analyses data and makes decisions based on the data rather than relying solely on human analysts regarding repetitive administrative tasks. The exploratory research within the K–12 group of teachers from LINK Educational Alliance from Serbia was performed on 109 persons to identify the genuine knowledge about AI and the potential for automatisation of work processes. Based on the teachers’ opinions regarding opportunities brought about by AI in K–12 schools, we analysed their implications in implementing AI in the educational process in K–12 education.

Suggested Citation

  • Valentin Kuleto & Milena P. Ilić & Rocsana Bucea-Manea-Țoniş & David-Florin Ciocodeică & Horia Mihălcescu & Veronica Mindrescu, 2022. "The Attitudes of K–12 Schools’ Teachers in Serbia towards the Potential of Artificial Intelligence," Sustainability, MDPI, vol. 14(14), pages 1-12, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8636-:d:862844
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    References listed on IDEAS

    as
    1. Valentin Kuleto & Milena Ilić & Mihail Dumangiu & Marko Ranković & Oliva M. D. Martins & Dan Păun & Larisa Mihoreanu, 2021. "Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions," Sustainability, MDPI, vol. 13(18), pages 1-16, September.
    2. Sebastian Ion Ceptureanu & Eduard Gabriel Ceptureanu & Doina Popescu & Olguta Anca Orzan, 2020. "Eco-innovation Capability and Sustainability Driven Innovation Practices in Romanian SMEs," Sustainability, MDPI, vol. 12(17), pages 1-18, August.
    3. Marko Sarstedt & Christian M. Ringle & Joseph F. Hair, 2022. "Partial Least Squares Structural Equation Modeling," Springer Books, in: Christian Homburg & Martin Klarmann & Arnd Vomberg (ed.), Handbook of Market Research, pages 587-632, Springer.
    4. Albérico Travassos Rosário & Joana Carmo Dias, 2022. "Sustainability and the Digital Transition: A Literature Review," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
    5. Ninni Singh & Vinit Kumar Gunjan & Amit Kumar Mishra & Ram Krishn Mishra & Nishad Nawaz, 2022. "SeisTutor: A Custom-Tailored Intelligent Tutoring System and Sustainable Education," Sustainability, MDPI, vol. 14(7), pages 1-24, March.
    6. Marko Sarstedt & Jun-Hwa Cheah, 2019. "Partial least squares structural equation modeling using SmartPLS: a software review," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 196-202, September.
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    Cited by:

    1. Sebastian Fitzek, 2024. "Ethical challenges and transformative potential: examining the impact of artificial intelligence on patient care, data security, and the healthcare workforce in Romania," Journal of Community Positive Practices, Catalactica NGO, issue 1, pages 59-86.

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