The Effect of the B-STAD Learning Model on Problem-Solving Ability Reviewed from Self-Regulation Among Elementary School Teacher Education Students
DOI:
https://doi.org/10.47453/edubase.v6i1.3266Keywords:
B-STAD, Problem Solving, Self-Regulation, Elementary School Teacher EducatioAbstract
Objective: This study aimed to examine the effectiveness of the B-STAD learning model in enhancing problem-solving ability and to analyze the interaction between learning models and students’ self-regulation. Methods : The study employed a quantitative method with a quasi-experimental design involving 186 Elementary School Teacher Education students who enrolled in 2022. The researchers used problem-solving ability tests and self-regulation questionnaires as instruments, both tested for validity and reliability. The analysis results revealed a significant difference between the group using the B-STAD model and the control group. The average problem-solving ability score for the B-STAD group reached 78.5, while the control group averaged only 65.3. A two-way ANOVA test produced a p-value of < 0.05, indicating that the B-STAD model significantly improved problem-solving ability. Furthermore, the analysis showed that students’ self-regulation had a correlation coefficient of 0.65 with problem-solving ability, demonstrating a strong positive relationship. Results: The findings conclude that implementing the B-STAD model significantly enhances the problem-solving ability of Elementary School Teacher Education students, with an average increase of 13.2 points compared to traditional learning methods. Conclusion: This study recommends that educators consistently apply the B-STAD model in the learning process while also focusing on developing students’ self-regulation. Therefore, this research provides valuable insights into the effectiveness of innovative learning models for improving educational outcomes.
Downloads
References
Altynbassov, B., Bayanbayeva, A., Tolegen, M., & Zhamankarin, M. (2024). A comprehensive bibliometric analysis of trends in higher education leadership in the Global South, 2013-2023: Contemporary perspectives and developments. International Journal of Educational Research, 127. https://doi.org/10.1016/j.ijer.2024.102421
Cahyani, H., & Setyawati, R. W. (2016). Pentingnya Peningkatan Kemampuan Pemecahan Masalah Melalui PBL untuk Mempersiapkan Generasi Unggul Menghadapi MEA. PRISMA, Prosiding Seminar Nasional Matematika.
Fraenkel, J. R., & Wallen, Norman. E. (2009). How to Design and Evaluate Research in Education (7th ed.). The McGraw-Hill Companies.
Edward, G., Carmines, & Zeller, R. A. (2011). Reliability and Validity Assessment . SAGE Publications, Inc. https://doi.org/https://doi.org/10.4135/9781412985642
Graham, C. R. (2006). Blended learning systems: Definition, current trends, and future directions. In Handbook of blended learning: Global perspectives, local designs.
Halder, S., & Saha, S. (2023). Models of Teaching. In The Routledge Handbook of Education Technology. https://doi.org/10.4324/9781003293545-12
Herman. (2021). Kepemimpinan Pendidikan Transformasional di Era Revolusi Industri 4.0. Jurnal Dedikasi Pendidikan, 5(2).
Husna, A. N., Hidayati, F. N. R., & Ariati, J. (2014). REGULASI DIRI MAHASISWA BERPRESTASI. Jurnal Psikologi Undip. https://doi.org/10.14710/jpu.13.1.50-63
Indarta, Y., Jalinus, N., Abdullah, R., & Samala, A. D. (2021). 21st Century Skills : TVET dan Tantangan Abad 21. EDUKATIF : JURNAL ILMU PENDIDIKAN, 3(6). https://doi.org/10.31004/edukatif.v3i6.1458
Jaramillo, A., Salinas-Cerda, J. P., & Fuentes, P. (2022). Self-Regulated Learning and Academic Performance in Chilean University Students in Virtual Mode During the Pandemic: Effect of the 4Planning App. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.890395
Junaštíková, J. (2024). Self-regulation of learning in the context of modern technology: a review of empirical studies. In Interactive Technology and Smart Education (Vol. 21, Issue 2). https://doi.org/10.1108/ITSE-02-2023-0030
Kim, Y. eun, Zepeda, C. D., & Butler, A. C. (2023). An Interdisciplinary Review of Self-Regulation of Learning: Bridging Cognitive and Educational Psychology Perspectives. In Educational Psychology Review (Vol. 35, Issue 3). https://doi.org/10.1007/s10648-023-09800-x
L. Lohr, S. (2019). Sampling: Design and Analysis (2nd Edition). Chapman and Hall/CRC.
Loh, R. C. Y., & Ang, C. S. (2020). Unravelling Cooperative Learning in Higher Education: A Review of Research. Research in Social Sciences and Technology.
Md. Mehadi Rahman. (2019). 21st Century Skill “Problem Solving”: Defining the Concept. Asian Journal of Interdisciplinary Research, 2(1).
Prensky, M. (2001). Digital Natives, Digital Immigrants Part 1. On the Horizon, 9(5). https://doi.org/10.1108/10748120110424816
Sari, D. N. (2015). Pengaruh Pembelajaran Kooperatif STAD dipadu dengan Blended Learning terhadap HasilBelajar Kognitif Materi NMR Mahasiswa Jurusan Kimia Universitas Negeri Malang. Universitas Negeri Malang.
Timotheou, S., Miliou, O., Dimitriadis, Y., Sobrino, S. V., Giannoutsou, N., Cachia, R., Monés, A. M., & Ioannou, A. (2023). Impacts of digital technologies on education and factors influencing schools’ digital capacity and transformation: A literature review. Education and Information Technologies, 28(6). https://doi.org/10.1007/s10639-022-11431-8
Urbina, S., Villatoro, S., & Salinas, J. (2021). Self-regulated learning and technology-enhanced learning environments in higher education: A scoping review. In Sustainability (Switzerland) (Vol. 13, Issue 13). https://doi.org/10.3390/su13137281
Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In Handbook of Self-Regulation.
Additional Files
Published
Issue
Section
License
Copyright (c) 2025 Authors

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.



