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| Поле DC | Значення | Мова |
|---|---|---|
| dc.contributor.author | Fadieieva, Liliia | - |
| dc.contributor.author | Семеріков, Сергій Олексійович | - |
| dc.contributor.author | Фадєєва, Лілія Олександрівна | - |
| dc.date.accessioned | 2024-12-03T11:30:51Z | - |
| dc.date.available | 2024-12-03T11:30:51Z | - |
| dc.date.issued | 2024-10-08 | - |
| dc.identifier.citation | Fadieieva L. Exploring the Interplay of Moodle Tools and Student Learning Outcomes: A Composite-Based Structural Equation Modelling Approach / Liliia Fadieieva, Serhiy Semerikov // Information Technology for Education, Science, and Technics : Proceedings of ITEST 2024, Volume 2 / editors : Emil Faure, Yurii Tryus, Tero Vartiainen, Olena Danchenko, Maksym Bondarenko, Constantine Bazilo, Grygoriy Zaspa // Lecture Notes on Data Engineering and Communications Technologies. – Cham : Springer, 2024. – Vol. 222. – P. 418–435. – DOI : https://doi.org/10.1007/978-3-031-71804-5_28 | uk |
| dc.identifier.isbn | 978-3-031-71803-8 | - |
| dc.identifier.isbn | 978-3-031-71804-5 | - |
| dc.identifier.uri | https://link.springer.com/chapter/10.1007/978-3-031-71804-5_28 | - |
| dc.identifier.uri | https://doi.org/10.1007/978-3-031-71804-5_28 | - |
| dc.identifier.uri | http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/10946 | - |
| dc.description | Philosophy (2006). https://tinyurl.com/yck8br28. Accessed 12 May 2024 Regulation on using the distance learning technologies in the educational activity of the Kryvyi Rih State Pedagogical University (2021). https://tinyurl.com/2p8yc7jr. Accessed 12 May 2024 Regulation on the system of assessment of the students’ learning outcomes in the Kryvyi Rih State Pedagogical University (2022). https://tinyurl.com/db9at3ru. Accessed 12 May 2024 Abuzinadah, N., et al.: Role of convolutional features and machine learning for predicting student academic performance from MOODLE data. PLOS ONE 18, 1–22 (2023). https://doi.org/10.1371/journal.pone.0293061 Cohen, J.: Statistical Power Analysis for the Behavioral Sciences, 2 edn. Routledge, New York (1988). https://doi.org/10.4324/9780203771587 Fadieieva, L., Semerikov, S.: ADANCO output on dataset from https://zenodo.org/doi/10.5281/zenodo.10938018 (2024). https://ssemerikov.github.io/Fadieieva/. 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Accessed 12 May 2024 Henseler, J.: Composite-Based Structural Equation Modeling: Analyzing Latent and Emergent Variables. Methodology in the Social Sciences. The Guilford Press, New York (2021) Google Scholar Iyer, S.S., Gernal, L., Subramanian, R., Mehrotra, A.: Impact of digital disruption influencing business continuity in UAE higher education. Educ. Technol. Q. 2023(1), 18–57 (2023). https://doi.org/10.55056/etq.29 Jordan, C.: Comparison of International Baccalaureate (IB) chemistry students’ preferred vs actual experience with a constructivist style of learning in a Moodle e-learning environment. Int. J. Lesson Learning Stud. 2(2), 155–167 (2013). https://doi.org/10.1108/20468251311323397 Article Google Scholar Kaensar, C., Wongnin, W.: Analysis and prediction of student performance based on Moodle log data using machine learning techniques. Int. J. Emerg. Technol. 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Accessed 12 May 2024 Vlasenko, K.V., Chumak, O.O., Lovianova, I.V., Achkan, V.V., Sitak, I.V.: Personal e-Learning Environment of the Maths teacher’ online course as a means of improving ICT competency of a Mathematics teacher. J. Phys. Conf. Ser. 2288(1), 012038 (2022). https://doi.org/10.1088/1742-6596/2288/1/012038 Article Google Scholar Vlasenko, K.V., Volkov, S.V., Lovianova, I.V., Sitak, I.V., Chumak, O.O., Bohdanova, N.H.: Exploring usability principles for educational online courses: a case study on an open platform for online education. Educ. Technol. Q. 2023(2), 173–187 (2023). https://doi.org/10.55056/etq.602 | uk |
| dc.description.abstract | This study is dedicated to researching the interconnectedness of Moodle resources and activities and their influence on student learning outcomes. We developed a conceptual model using a quantitative structural equation modelling approach based on the social constructionist pedagogy underlying Moodle’s development and the university’s regulations regarding Moodle’s course structure and assessment. The model is comprised of five elements: Information, Resources, Activities, Communication, and Assessment. The modelling results revealed a strong positive relationship between the Activities construct (interactive learning activities) and the Communication construct, suggesting that increased utilisation of interactive activities within Moodle courses is associated with higher levels of communication and engagement. Additionally, a moderate positive relationship was observed between the Resources and Activities construct, indicating that the availability and variety of resources within a Moodle course are linked to the inclusion of diverse learning activities. Furthermore, a moderate positive relationship was found between the Information construct (course description, syllabus, introduction) and the Assessment construct (student grades), implying that well-designed and informative course materials are associated with better student performance on assessments. Notably, the study did not find evidence of a significant direct relationship between Communication or Activities and the Assessment construct, suggesting that their impact on assessment performance is more complex and influenced by other factors. The research highlights that the mere use of Moodle tools does not guarantee the implementation of adaptive learning for students of pedagogical universities. To truly leverage the potential of adaptive learning, instructors and course designers must employ a deliberate and strategic approach, integrating appropriate pedagogical strategies and using Moodle’s adaptive capabilities in alignment with specific learning objectives and student needs. | uk |
| dc.language.iso | en | uk |
| dc.publisher | Springer, Cham | uk |
| dc.subject | Moodle | uk |
| dc.subject | structural equation modelling | uk |
| dc.subject | adaptive learning | uk |
| dc.subject | pedagogical universities | uk |
| dc.subject | student learning outcomes | uk |
| dc.subject | Moodle tools interconnectedness | uk |
| dc.title | Exploring the Interplay of Moodle Tools and Student Learning Outcomes: A Composite-Based Structural Equation Modelling Approach | uk |
| dc.type | Book chapter | uk |
| Розташовується у зібраннях: | Кафедра інформатики та прикладної математики | |
Файли цього матеріалу:
| Файл | Опис | Розмір | Формат | |
|---|---|---|---|---|
| ITEST_2024_vol_2-429-446_Fadieieva_Semerikov.pdf | 485.27 kB | Adobe PDF | Переглянути/Відкрити |
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