MODELO DE ROTAÇÃO DE ESTAÇÕES DE APRENDIZAGEM EM BANDA NO ENSINO SUPERIOR
ALCANÇAR UM EQUILÍBRIO ENTRE O ENSINO EM LINHA E PRESENCIAL
DOI:
https://doi.org/10.18316/rcd.v16i41.11434Palavras-chave:
aprendizagem mista, modelo rotativo, universidades, Ucrânia, digitalizaçãoResumo
O objetivo do artigo é testar empiricamente a eficácia do modelo de ensino com estações rotativas num formato misto com base num inquérito realizado entre professores de instituições de ensino superior na Ucrânia. O estudo utiliza uma abordagem de metodologia mista para recolher dados qualitativos e quantitativos de 65 professores durante o primeiro semestre do ano letivo de 2023-2024. Os principais instrumentos são questionários e entrevistas a professores que utilizaram o Modelo de Rotação de Estações. As respostas foram processadas utilizando estatísticas descritivas e análise comparativa para identificar quaisquer diferenças significativas nos resultados. Os resultados sublinham a necessidade de uma seleção cuidadosa de uma plataforma para o ensino à distância e a aquisição de competências na criação de recursos electrónicos. Os resultados do estudo fornecem recomendações práticas para a implementação do modelo no contexto do ensino superior ucraniano. Isto é importante para as instituições de ensino superior ucranianas que procuram métodos óptimos de aprendizagem mista. Os resultados do estudo sublinham a atitude positiva dos professores em relação ao modelo proposto, que promove a individualização da aprendizagem e o desenvolvimento de competências digitais. No entanto, a implementação requer tempo adicional e competências digitais avançadas dos professores. A pontuação média da eficácia do modelo (aproximadamente 4,046) e a distribuição percentual nas pontuações 4 (47,69%) e 5 (30,77%) indicam um elevado nível de aceitação desta abordagem pelos professores modernos. As recomendações baseiam-se na experiência individual dos professores, indicando a variabilidade na escolha do melhor meio de comunicação com os alunos. O estudo contribui para a compreensão da eficácia do modelo de ensino misto e ajudará a otimizar a sua aplicação mais ampla.
Referências
Barber, S. (2022). Blended synchronous learning case study. Pacific Journal of Technology Enhanced Learning, 4(1), 1–8. https://doi.org/10.24135/pjtel.v4i1.153
Biliuk, O., Stepanenko, O., & Kyrychenko, V. (2023). Modern tools for distance education: Information and analytical prospectus. Futurity Education, 3(2), 233–247. https://doi.org/10.57125/FED.2023.06.25.15
Bieliaieva, N., Holiiad, I., Dynko, V., & Mogilat, A. (2023). Developing and implementing a distance learning model for training specialists of the future. Futurity Education, 3(2), 182–198. https://doi.org/10.57125/FED.2023.06.25.12
Bushman, I. (2022). Education in the 21st century: Philosophical foundations and principles. Futurity Philosophy, 1(2), 4–15, 2022. https://doi.org/10.57125/FP.2022.06.30.01
But, V., & Panchenko, G. (2016). Implementation modern forms of lifelong learning in Ukraine. Continuing Professional Education: Theory and Practice, (3–4), 122–126. https://doi.org/10.28925/1609-8595.2016(3-4)122126
Dobrovolska, N., Moroz, L., Shpak, M., Tsekhmister, Y., & Vovchenko, O. A. (2021). Мotivational mechanisms of emotional intelligence development in рracticing psychologists. AD ALTA: Journal of Interdisciplinary Research, 11(21), 54–59. https://lib.iitta.gov.ua/732654/1/A_08.pdf
Dovhal, S., Tukhtarova, T., & Volokitina, N. (2021). Distance learning in Ukraine: Problems and prospects. Dnipro Academy of Continuing Education Herald. Series: Philosophy, Pedagogy, 1(1), 48–53. https://doi.org/10.54891/2786-7005-2021-1-8
Harb, G. (2019). Reshaping undergraduates research experience with station rotation learning model. International Journal of Advanced Research, 7(11), 702–710. https://doi.org/10.21474/ijar01/10061
Hordiichuk, O., Nikolenko, L., Shavel, K., Zakharina, M., & Khomyk, T. (2022). Analysis of models of inclusive education in European countries (Experience for Ukraine). Revista Eduweb, 16(4), 32–41. https://doi.org/10.46502/issn.1856-7576/2022.16.04.3
Järvis, M., Tambovceva, T., & Virovere, A. (2021). Scientific innovations and advanced technologies in higher education. Futurity Education, 1(1), 13–23. https://doi.org/10.57125/FED.2022.10.11.2
Kolbina, T., & Oleksenko, O. (2020). Implementation of distance learning in Ukraine. Educational Challenges, 25(1), 46–54. https://doi.org/10.34142/2709-7986.2020.25.1.04
Kulichenko, A., Shramko, R., Rakhno, M., & Polyezhayev, Y. (2022). Resistencia educativa bidimensional en el establecimiento educativo terciario moderno de Ucrania. Apuntes Universitarios, 13(1), 474–493. https://doi.org/10.17162/au.v13i1.1351
Krymets, L. (2022). Philosophical and educational traditions of the future. Futurity Philosophy, 1(1), 4–18. https://doi.org/10.57125/FP.2022.03.30.01
Larsari, V. N., Dhuli, R., & Chenari, H. (2023). Station rotation model of blended learning as generative technology in education: An evidence-based research. In S. Motahhir & B. Bossoufi (Eds.), Digital technologies and applications. ICDTA 2023. Lecture notes in networks and systems (Vol. 668, pp 441–450). Springer. https://doi.org/10.1007/978-3-031-29857-8_45
Nazarenko, A. L. (2015). Blended learning vs traditional learning: What works? (A case study research). Procedia-Social and Behavioral Sciences, 200, 77–82. https://doi.org/10.1016/j.sbspro.2015.08.018
Nedermeijer, J. (2023). Case study design of the workshop ‘Redesign your course in a blended learning course’. In J. Nedermeijer (Ed.), Evidence-based blended and online learning (pp. 165–183). Brill. https://doi.org/10.1163/9789004681774_011
Nurkamto, J., Mujiyanto, J., & Yuliasri, I. (2019). The implementation of station rotation and flipped classroom models of blended learning in EFL learning. English Language Teaching, 12(12), 23–29. https://doi.org/10.5539/elt.v12n12p23
Panasenko, I. V. (2021). Distance learning in Ukraine: An analysis of threats and challenges. Business Inform, 6(521), 78–83. https://doi.org/10.32983/2222-4459-2021-6-78-83
Piamsa-nga, P., Poovarawan, Y. (2020). Design a curriculum with user-experience analysis: Case study computing science curriculum. In S. Cheung, R. Li, K. Phusavat, N. Paoprasert, & L. Kwok (Eds.), Blended learning. Education in a smart learning environment. ICBL 2020. Lecture notes in computer science, Volume 12218 (pp. 25–36). Springer. https://doi.org/10.1007/978-3-030-51968-1_3
Puspita, A., Bahri, A., & Latif, R. (2022). Bleanded learning dengan model pembelajaran maraja. Biology Teaching and Learning, 5(2), 175–188. https://doi.org/10.35580/btl.v5i2.37770
Rajab, K. D. (2018). The effectiveness and potential of e-learning in war zones: an empirical comparison of face-to-face and online education in Saudi Arabia. IEEE Access, 6, 6783–6794. https://doi.org/10.1109/access.2018.2800164
Salnyk, I., Grin, L., Yefimov, D., & Beztsinna, Z. (2023). The future of higher education: Implementation of virtual and augmented reality in the educational process. Futurity Education, 3(3), 46–61. https://doi.org/10.57125/FED.2023.09.25.03
Sherman, M., Puhovskiy, E., Kambalova, Y., & Kdyrova, I. (2022). The future of distance education in war or the education of the future (The Ukrainian case study). Futurity Education, 2(3), 14–23. https://doi.org/10.57125/FED/2022.10.11.30
Shevchenko, V., Malysh, N., & Tkachuk-Miroshnychenko, O. (2021). Distance learning in Ukraine in COVID-19 emergency. Open Learning: The Journal of Open, Distance and e-Learning, 1–16. https://doi.org/10.1080/02680513.2021.1967115
Smith, M. J. (2021). A blended learning case study. In A. G. Picciano, C. D. Dziuban, C. R. Graham, & P. D. Moskal (Eds.), Blended learning: Research perspectives, Volume 3 (pp. 178–189). New York: Routledge. https://doi.org/10.4324/9781003037736-15
Tsekhmister, Y. (2021). The problem of pedagogical innovations and trends in the development of the educational environment. Futurity Education, 1(2), 25–34. https://doi.org/10.57125/FED/2022.10.11.16
Tsekhmister, Y. V., Chalyi, A. V., & Chalyy, K. A. (2009). Teaching and learning of medical physics and biomedical engineering in Ukrainian medical universities. In Proceedings of World congress on medical physics and biomedical engineering (pp. 383—384). Berlin, Heidelberg: Springer.
Munich, Germany. Berlin, Heidelberg: Springer, 2009. P. 383—384.Tytova, N., & Mereniuk, K. (2022). Digital literacy of future teachers in the realities of large-scale military aggression (Ukrainian experience). Futurity Education, 2(3), 48–59. https://doi.org/10.57125/FED/2022.10.11.33
Truitt, A. A., & Ku, H. Y. (2018). A case study of third grade students’ perceptions of the station rotation blended learning model in the United States. Educational Media International, 55(2), 153–169. https://doi.org/10.1080/09523987.2018.1484042
Vaughan, N. D. (2021). Blended Learning and Shared Metacognition. In Blended Learning (pp. 282–299). Routledge. https://doi.org/10.4324/9781003037736-23
Voropayeva, T., Järvis, M., Boiko, S., Tolchieva, H., & Statsenko, N. (2022). European experience in implementing innovative educational technologies in the training of management specialists: Current problems and prospects for improvement. IJCSNS International Journal of Computer Science and Network Security, 22(7), 294–300. https://doi.org/10.22937/IJCSNS.2022.22.7.35
Wong, S. F., Mahmud, M. M., & Wong, S. S. (2022). Blackboard and virtual station rotation model: Effectiveness of learning calculus. In ICIEI '22: Proceedings of the 7th international conference on information and education innovations (pp. 35–40). New York: Association for Computing Machinery. https://doi.org/10.1145/3535735.3535741
Downloads
Publicado
Edição
Seção
Licença
Copyright (c) 2024 Violetta Yukhymenko, Svitlana Borysova, Olena Bazyl, Halyna Hubal, Uliana Barkar
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
Conforme recomendado pelo o Public Knowledge Project, a RCD adota para seus artigos uma licença CREATIVE COMMONS: Atribuição CC BY 4.0.
Esta licença permite que outros distribuam, remixem, adaptem e construam sobre o seu trabalho, mesmo comercialmente, desde que lhe dêem crédito pela criação original.
Esta é a licença mais adequada oferecida.
Recomendado para a máxima divulgação e uso de materiais licenciados.
