Enhancing Learning Through Productive Classrooms: A Case Study At Jining Normal University

Main Article Content

Yang Mingxia
Zainudin Mohd Isa

Abstract

This study examines the effectiveness of implementing productive classroom strategies to improve learning outcomes among undergraduate students at Jining Normal University in China. The research seeks to accomplish three primary goals: firstly, to evaluate the effect of effective classroom practices on student engagement and participation; secondly, to assess the impact of these strategies on academic performance and knowledge retention; and thirdly, to investigate student perceptions and satisfaction regarding the implementation of productive classroom techniques. The study employs a quantitative analysis methodology, encompassing 130 participants from diverse academic fields within the university. The data collection instruments comprise a meticulously designed, structured questionnaire consisting of 30 items. These items are specifically aimed at assessing the experiences and perceptions of students regarding effective classroom methodologies. The questionnaire covers elements such as active learning methodologies, cooperative exercises, teacher-student engagement, and classroom ambiance. The effectiveness of productive classroom practices in enhancing learning outcomes is determined by analysing participants' responses using statistical methods. The study's findings are anticipated to offer valuable insights into the effects of effective classroom strategies on student engagement, academic achievement, and overall learning experiences in a higher education setting in China. Furthermore, the research seeks to enhance the current body of knowledge on pedagogical strategies that facilitate active learning and student-centred education. The study's practical implications involve advising educators and institutions to incorporate effective classroom techniques into their teaching methods. This is done to create a dynamic and supportive learning environment that meets the diverse needs of students in modern educational settings.

Article Details

How to Cite
Yang Mingxia, & Zainudin Mohd Isa. (2024). Enhancing Learning Through Productive Classrooms: A Case Study At Jining Normal University. Journal for ReAttach Therapy and Developmental Diversities, 7(1), 82–88. https://doi.org/10.53555/jrtdd.v7i1.2463
Section
Articles
Author Biographies

Yang Mingxia

CITY University, Malaysia. Jining Normal University, China.

Zainudin Mohd Isa

CITY University, Malaysia.

References

Børte, K., Nesje, K., & Lillejord, S. (2023). Barriers to student active learning in higher education. Teaching in Higher Education, 28(3), 597-615.

Sauer, A., Gramacy, R. B., & Higdon, D. (2023). Active learning for deep Gaussian process surrogates. Technometrics, 65(1), 4-18.

Gao, W., & Wang, C. (2023). Active learning-based sampling for high-dimensional nonlinear partial differential equations. Journal of Computational Physics, 475, 111848.

Zhu, R., Peng, W., Wang, D., & Huang, C. G. (2023). Bayesian transfer learning with active querying for intelligent cross-machine fault prognosis under limited data. Mechanical Systems and Signal Processing, 183, 109628.

Wong, Z. Y., Liem, G. A. D., Chan, M., & Datu, J. A. D. (2023). Student engagement and its association with academic achievement and subjective well-being: A systematic review and meta-analysis. Journal of Educational Psychology.

Kassab, S. E., Taylor, D., & Hamdy, H. (2023). Student engagement in health professions education: AMEE Guide No. 152. Medical Teacher, 45(9), 949-965.

Yang, D., Wang, H., Metwally, A. H. S., & Huang, R. (2023). Student engagement during emergency remote teaching: A scoping review. Smart Learning Environments, 10(1), 1-17.

McCormick, A. C., Moore, J. V., & Kuh, G. D. (2023). Working during college: Its relationship to student engagement and education outcomes. In Understanding the working college student (pp. 179-212). Routledge.

Peramunugamage, A., Ratnayake, U. W., & Karunanayaka, S. P. (2023). Systematic review on mobile collaborative learning for engineering education. Journal of Computers in Education, 10(1), 83-106.

Zabolotna, K., Malmberg, J., & Järvenoja, H. (2023). Examining the interplay of knowledge construction and group-level regulation in a computer-supported collaborative learning physics task. Computers in Human Behavior, 138, 107494.

Lipponen, L. (2023, January). Exploring foundations for computer-supported collaborative learning. In Computer support for collaborative learning (pp. 72-81). Routledge.

Qureshi, M. A., Khaskheli, A., Qureshi, J. A., Raza, S. A., & Yousufi, S. Q. (2023). Factors affecting students’ learning performance through collaborative learning and engagement. Interactive Learning Environments, 31(4), 2371-2391.

Rashid, M. H., & Sipahi, E. (2021). The importance of quantitative research in language testing and assessment: in the context of social works. Linguistics and Culture Review, 5 (S1), 317-330.

Rashid, M. H., Shamem, A. S. M., & Hui, W. (2022). The position of culture in English language teaching. Linguistics and Culture Review, 6(S2), 43-51.

Rashid, M. H., Lan, Y., & Hui, W. (2022). The perspectives of English teachers toward writing education, as well as the obstacles they encounter. International Journal of Applied Linguistics and English Literature, 11(1), 54-58.

Rashid, M. H., Rai, R. P. M., & Hui, W. (2023). Interventions for Impulsive Personality Disorder: Evaluating Effectiveness and Treatment Approaches. Journal for ReAttach Therapy and Developmental Diversities, 6(10s), 1719-1725.

Woods, P. J., & Copur-Gencturk, Y. (2024). Examining the role of student-centred versus teacher-cantered pedagogical approaches to self-directed learning through teaching. Teaching and Teacher Education, 138, 104415.

Mena-Guacas, A. F., Rodríguez, J. A. U., Trujillo, D. M. S., Gómez-Galán, J., & López-Meneses, E. (2023). Collaborative learning and skill development for educational growth of artificial intelligence: A systematic review. Contemporary Educational Technology, 15(3), ep428.

Nieminen, J. H., Bearman, M., & Ajjawi, R. (2023). Designing the digital in authentic assessment: is it fit for purpose? Assessment & Evaluation in Higher Education, 48(4), 529-543.

Wilson, M. L. (2023). The impact of technology integration courses on preservice teacher attitudes and beliefs: A meta-analysis of teacher education research from 2007–2017. Journal of research on Technology in Education, 55(2), 252-280.

Chang, H., Ding, Q., Zhao, W., Hou, N., & Liu, W. (2023). The digital economy, industrial structure upgrading, and carbon emission intensity——empirical evidence from China's provinces. Energy Strategy Reviews, 50, 101218.

Fischer, H. E., Boone, W. J., & Neumann, K. (2023). Quantitative research designs and approaches. In Handbook of research on science education (pp. 28-59). Routledge.

Khoa, B. T., Hung, B. P., & Hejsalem-Brahmi, M. (2023). Qualitative research in social sciences: data collection, data analysis and report writing. International Journal of Public Sector Performance Management, 12(1-2), 187-209.

Verd, J. M. (2023). Using a hybrid data collection tool: Analysis of youth labour market trajectories integrating quantitative, qualitative and social network data. International Journal of Social Welfare, 32(1), 9-19.

Guzik, P., & Więckowska, B. (2023). Data distribution analysis–a preliminary approach to quantitative data in biomedical research. Journal of Medical Science, 92(2), e869-e869.