Prediction of Physics Lesson Learning Level by Students’ Characteristics and Teaching-Learning Process

Zeynep Şen Akçay, Nuray Senemoğlu
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Abstract


The aim of this study is to determine the predictive strength of the students’ characteristics and their teaching-learning process on the physics course learning level.  The variables were also examined according to the academic achievement levels. The study is a descriptive study in survey model. Purposive sampling method was used in the formation of the study group, and 621 ninth grade students were selected for the study group. Cognitive Entry Behaviors (CEB) test, Academic Self-Concept (ASC) scale, Perception of Teaching Service Adequacy (PTSA) scale, Time Allotted to Learning (TAL) form and Learning Level (LL) test were used to collect the data. One-way variance, simple linear regression, and stepwise regression technique were used in the data analysis.  The results of the study showed that the predictive strength of the variables examined about the student and the teaching-learning process was significant. The variability in the learning level is 59.9% in CEB, 18.1% in ASC, and 17.1% in PTSA.  The relationship between the individual time allocated to learning and the learning level is negative, and has the power to explain the variability in learning level by 2.9%.  All variables have the power to explain the variability in learning level by 62.7% together. One of the most important results of this study is that the magnitude of the predictive power of cognitive entry behaviors on the learning level has been revealed. It is thought that the results of the study will contribute to the literature aimed at increasing the learning level of the physics course.

Keywords


Physics lesson, Cognitive entry behaviors, Academic self-concept, Predictive strength

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References


Sen Akcay, Z. & Senemoglu, N. (2021). Prediction of physics lesson learning level by students’ characteristics and teaching-learning process. International Journal of Education in Mathematics, Science, and Technology (IJEMST), 9(4), 625-654. https://doi.org/10.46328/ijemst.1754




DOI: https://doi.org/10.46328/ijemst.1754

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