Success Factors in Instructional Management Using Collaborative Teaching Robots
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Abstract
The management of teaching and learning using collaborative teaching robots (Co-teaching robots) is a form of educational management in the digital age that promotes the development of essential skills in the 21st century, aligning with the changing dynamics of the current world that emphasize technology and innovation. This research aims to study the role of robots in educational management, the advantages and limitations of teaching and learning using the Co-teaching robots, and the factors influencing success in this context. The study was conducted using a mixed methods research with exploratory sequential design, starting with a qualitative research phase by selecting the 12 key informants using purposive random sampling method from among calculus, computing, science, and mathematic teachers who were later interviewed in this study. In the second phase, a quantitative study was conducted with a sample of 226 teachers in three southern border provinces, who were selected by means of simple random sampling method. The questionnaire was employed as a tool to collect the data in this phase. The descriptive statistics consist of frequency, percentage, mean, standard deviation and inferential statistics include One-Way ANOVA and Multiple Regression. The findings indicate that the Co-teaching robots play a significant role in educational management by enhancing the learning experience and serving as teaching assistants. Advantages of integrating the Co-teaching robots into education include data accuracy, unlimited data accumulation, while the limitations of teaching and learning using the Co-teaching robots include teacher attitudes, data input and accuracy. With regard to the success factors in teaching and learning with Co-teaching robots involve financial support for robotics development, the mindset of school administrators and teachers. The overall level of factors leading to success in teaching and learning using the Co-teaching robots was found to be high. This research is a guideline for organizing new and modern teaching and learning methods to enhance teachers' awareness and cultivate a positive attitude toward integrating new-age technology into teaching and learning to improve the quality of education in the digital age.
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References
Alam, A. (2021). Should robots replace teachers? Mobilisation of AI and learning analytics in education. In International Conference on Advances in Computing, Communication, and Control (ICAC3) (pp.1-12.) Mumbai, India: IEEE. https://doi.org/10.1109/ICAC353642.2021.9697300
Algerafi, M. A., Zhou, Y., Alfadda, H., & Wijaya, T. T. (2023). Understanding the factors influencing higher education students’ intention to adopt artificial intelligence-based robots. IEEE Access, 11, 99752-99764. https://doi. org/10.1109/ACCESS.2023.3314499
Belpaeme, T., Kennedy, J., Ramachandran, A., & Scassellati, B. (2018). Social robots for education: a review. Science Robotics, 3(21), 1-9. https://doi.org/10.1126/scirobotics.aat5954
Chalmers, C. (2018). Robotics and computational thinking in primary school. International Journal of Child-Computer Interaction, 17, 93-100. https://doi.org/10.1016/j.ijcci.20 18.06.005
Erol, O., Sevim-Cirak, N., & Baser Gülsoy, V. G. (2023). The effects of educational robotics activities on students' attitudes towards STEM and ICT courses. International Journal of Technology in Education, 6(2), 203-223. https://doi.org/10.46328/ijte.365
Gardenghi, C., & Gherardi, L. (2024). Teaching with the Nao Robot: Teacher-users’ attitudes. Italian Journal of Sociology of Education, 16(1), 71-86. https://doi.org/10.14658/PUPJ-IJSE-2024-1-4
Laopilai, P., & Krootjohn, S. (2020). Development of a small robot assisted language learning to promote English skills for kindergarten. Academic Journal of Management Technology, 1(1), 13-22. [In Thai]
Lookbua, C., Sriprasertpap, K., & On-ming, R. (2021). Learning model of robotics activities and problem-based learning for promoting computational thinking skill for Grade 3 elementary students at Srinakharinwirot University Prasarnmit Demonstration School. Journal of Industrial Education, 15(2), 74-88. [In Thai]
Mano, P. (2019). The impact of digital disruption to the education. Journal of Industrial Education, 18 (1), 1-16. [In Thai]
Orhani, S. (2023). Robots assist or replace teachers in the classroom. Journal of Elementary and Secondary School, 1(1), 29-41. https://doi.org/10.31098/jess.v1i1.1418.
Ouyang, F., & Xu, W. (2024). The effects of educational robotics in STEM education: A multilevel meta-analysis. International Journal of STEM Education, 11(7), 1-18. https://doi.org/10.1186/s40594-024-00469-4
Sawaddee, N., & Preechaboonyarit, S. (2022). “Who can replace a man?”: The attitudes of arts students towards the role of robots and AI in the 21st century. Journal of Arts and Thai Studies, 44 (2), 151-165. [In Thai]
The Secondary Educational Service Area Office Yala Patani Narathiwat. (2022). Personnel Directory: Three Southern Border Provinces. The Secondary Educational Service Area Office Yala Patani Narathiwat.
Thongmark, S., Neimted, W., Choosuwan, R., & Sittichai, R. (2018). Looking backwards and forwards of educational quality in three southern border provinces of Thailand. Princess of Naradhiwas University Journal of Humanities and Social Sciences, 5, 186-198. [In Thai]
Wang, H., Luo, N., Zhou, T., & Yang, S. (2024). Physical robots in education: A systematic review based on the technological pedagogical content knowledge framework. Sustainability, 16(12), 1-24. https://doi.org/10.3390/su16124987
Wisskirchen, G., Biacabe, B. T., Bormann, U., Muntz, A., Niehaus, G., Soler, G. J., & von Brauchitsch, B. (2017). Artificial Intelligence and Robotics and their Impact on the Workplace. London: IBA Global Employment Institute.
Yamane, T. (1967). Statistics: An Introductory Statistics (2nd ed.). New York: Harper & Row.
