Integrating AI Technology to Optimize Learning for SD Muhammadiyah Kebumen
DOI:
https://doi.org/10.61667/g0x3ak63Keywords:
Artificial intelligence, Education, Integrating TechnologyAbstract
Artificial intelligence has the potential to revolutionize education by enhancing teaching and learning experiences. By integrating AI technology, SD Muhammadiyah Kebumen can optimize its teaching methods and improve the overall learning outcomes for students. However, successfully integrating AI technology into education requires addressing specific challenges and considerations. These challenges include the profit-oriented nature of current AI applications in education, the lack of pedagogical knowledge among AI developers, and the need for teachers' input and collaboration in the development process. This paper explores the potential of integrating AI technology to optimize SD Muhammadiyah Kebumen's learning. The method of this research is a mix of methods, combining both quantitative and qualitative approaches. The quantitative approach will involve analyzing data on the current teaching methods and learning outcomes of SD Muhammadiyah Kebumen. The qualitative approach will include conducting interviews and surveys to gather insights and perceptions from teachers regarding the use and effectiveness of AI technology in their classrooms. The results show that integrating AI technology in teaching can improve the quality and effectiveness of instruction, enhance student engagement and personalized learning experiences, and provide teachers with valuable insights and data to inform their teaching practices. The score is approximately 3.78, suggesting a somewhat positive attitude towards AI among the respondents. Current use of technological tools: This category scored the highest, with a mean score of around 4.12, indicating that the current use of technological tools is favorable among the participants. Perceived benefits of AI integration include improved student outcomes, increased efficiency in teaching, personalized learning experiences, enhanced engagement, and access to valuable data for informed decision-making. The study found that integrating AI technology in teaching can potentially optimize learning for SD Muhammadiyah Kebumen
References
Al Braiki, B., Harous, S., Zaki, N., & Alnajjar, F. (2020). Artificial intelligence in education and assessment methods. Bulletin of Electrical Engineering and Informatics, 9(5), 1998–2007. https://doi.org/10.11591/eei.v9i5.1984
Antwi, W. K., Akudjedu, T. N., & Botwe, B. O. (2021). Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers' perspectives. Insights into Imaging, 12(1). https://doi.org/10.1186/s13244-021-01028-z
Banerjee, M., Chiew, D., Patel, K. T., Johns, I., Chappell, D., Linton, N., Cole, G. D., Francis, D. P., Szram, J., Ross, J., & Zaman, S. (2021). The impact of artificial intelligence on clinical education: perceptions of postgraduate trainee doctors in London (UK) and recommendations for trainers. BMC Medical Education, 21(1), 1–10. https://doi.org/10.1186/s12909-021-02870-x
Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial intelligence and reflections from educational landscape: A review of AI studies in half a century. Sustainability (Switzerland), 13(2), 1–16. https://doi.org/10.3390/su13020800
Çalışkan, S. A., Demir, K., & Karaca, O. (2022). Artificial intelligence in medical education curriculum: An e-Delphi study for competencies. PLoS ONE, 17(July 7), 1–11. https://doi.org/10.1371/journal.pone.0271872
Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8
Chen, J., Li, R., Gan, M., Fu, Z., & Yuan, F. (2020). Public Acceptance of Driverless Buses in China: An Empirical Analysis Based on an Extended UTAUT Model. Discrete Dynamics in Nature and Society, 2020. https://doi.org/10.1155/2020/4318182
Chiu, T. K. F., & Chai, C. S. (2020). Sustainable curriculum planning for artificial intelligence education: A self-determination theory perspective. Sustainability (Switzerland), 12(14). https://doi.org/10.3390/su12145568
Coghlan, S., Miller, T., & Paterson, J. (2021). Good Proctor or "Big Brother"? Ethics of Online Exam Supervision Technologies. Philosophy and Technology, 34(4), 1581–1606. https://doi.org/10.1007/s13347-021-00476-1
Cooper, G. (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. Journal of Science Education and Technology, 32(3), 444–452. https://doi.org/10.1007/s10956-023-10039-y
Cox, A. M. (2021). Exploring the impact of Artificial Intelligence and robots on higher education through literature-based design fictions. International Journal of Educational Technology in Higher Education, 18(1). https://doi.org/10.1186/s41239-020-00237-8
Cukurova, M., Luckin, R., & Kent, C. (2020). Impact of an Artificial Intelligence Research Frame on the Perceived Credibility of Educational Research Evidence. In International Journal of Artificial Intelligence in Education (Vol. 30, Issue 2). International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-019-00188-w
Dignum, V. (2021). The role and challenges of education for responsible ai. London Review of Education, 19(1), 1–11. https://doi.org/10.14324/LRE.19.1.01
Garg, S., & Sharma, S. (2020). Impact of artificial intelligence in special need education to promote inclusive pedagogy. International Journal of Information and Education Technology, 10(7), 523–527. https://doi.org/10.18178/ijiet.2020.10.7.1418
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1
Huang, L. S., Su, J. Y., & Pao, T. L. (2019). A context aware Smart classroom architecture for smart campuses. Applied Sciences (Switzerland), 9(9). https://doi.org/10.3390/app9091837
Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education. In Education and Information Technologies (Vol. 27, Issue 5). Springer US. https://doi.org/10.1007/s10639-021-10831-6
Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M. D., Păun, D., & Mihoreanu, L. (2021). Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability (Switzerland), 13(18), 1–16. https://doi.org/10.3390/su131810424
Lee, H. S., & Lee, J. (2021). Applying artificial intelligence in physical education and future perspectives. Sustainability (Switzerland), 13(1), 1–16. https://doi.org/10.3390/su13010351
Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., & Daradoumis, A. (2022). Educational AI Chatbots for Content and Language Integrated Learning. Applied Sciences (Switzerland), 12(7). https://doi.org/10.3390/app12073239
Nadarzynski, T., Miles, O., Cowie, A., & Ridge, D. (2019). Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. Digital Health, 5, 1–12. https://doi.org/10.1177/2055207619871808
Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers' AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023-10203-6
Ouyang, F., Wu, M., Zheng, L., Zhang, L., & Jiao, P. (2023). Integration of artificial intelligence performance prediction and learning analytics to improve student learning in online engineering course. International Journal of Educational Technology in Higher Education, 20(1), 1–23. https://doi.org/10.1186/s41239-022-00372-4
Porayska-Pomsta, K. (2016). AI as a Methodology for Supporting Educational Praxis and Teacher Metacognition. International Journal of Artificial Intelligence in Education, 26(2), 679–700. https://doi.org/10.1007/s40593-016-0101-4
Schiff, D. (2021). Out of the laboratory and into the classroom: the future of artificial intelligence in education. AI and Society, 36(1), 331–348. https://doi.org/10.1007/s00146-020-01033-8
Sit, C., Srinivasan, R., Amlani, A., Muthuswamy, K., Azam, A., Monzon, L., & Poon, D. S. (2020). Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey. Insights into Imaging, 11(1), 7–12. https://doi.org/10.1186/s13244-019-0830-7
Yau, K. W., Chai, C. S., Chiu, T. K. F., Meng, H., King, I., & Yam, Y. (2023). A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools. Education and Information Technologies, 28(1), 1041–1064. https://doi.org/10.1007/s10639-022-11161-x
Zhang, H., Lee, I., Ali, S., DiPaola, D., Cheng, Y., & Breazeal, C. (2023). Integrating Ethics and Career Futures with Technical Learning to Promote AI Literacy for Middle School Students: An Exploratory Study. International Journal of Artificial Intelligence in Education, 33(2), 290–324. https://doi.org/10.1007/s40593-022-00293-3
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