Journals / Kuram ve Uygulamada Eğitim Bilimleri / 2015 / Cilt: 15 - Sayı: 3

Structural Equation Modeling Towards Online Learning Readiness, Academic Motivations, and Perceived Learning

Pages
759–770
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It was determined as a result of the model obtained from the research that academic motivation is effective in increasing perceived learning in online learning, and increasing readiness is an effective way to increase academic motivation

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The relationship between online learning readiness, academic motivations, and perceived learning was investigated via structural equation modeling in the research.
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Key Findings & Data:The population of the research consisted of 750 students who studied using the online learning programs of Sakarya University. 420 of the students who volunteered for the research and filled the scales via the convenience sampling method constituted the research sample.
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Conclusion & Impact:It was determined as a result of the model obtained from the research that academic motivation is effective in increasing perceived learning in online learning, and increasing readiness is an effective way to increase academic motivation
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The relationship between online learning readiness, academic motivations, and perceived learning was investigated via structural equation modeling in the research. The population of the research consisted of 750 students who studied using the online learning programs of Sakarya University. 420 of the students who volunteered for the research and filled the scales via the convenience sampling method constituted the research sample. The correlational research model was used in the research. The scales of online learning readiness, academic motivation, and perceived learning were applied to the participants. The relationship among the variables of the research and the research hypotheses for the model were tested via structural equation modeling. It was revealed as a result of the research that the online-learning readiness levels of students predicted their academic motivations directly and their perceived learning indirectly. It was also found that student academic motivations predicted their perceived learning directly. The proposed model was verified in accordance with the data obtained from the research. It was determined as a result of the model obtained from the research that academic motivation is effective in increasing perceived learning in online learning, and increasing readiness is an effective way to increase academic motivation

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Cite This Article

HORZUM, M. B., KAYMAK, Z. D., GÜNGÖREN, Ö. C. (2015). Structural Equation Modeling Towards Online Learning Readiness, Academic Motivations, and Perceived Learning. Kuram ve Uygulamada Eğitim Bilimleri, Cilt: 15 - Sayı: 3, 759–770. https://ajindex.com/articles/346072

References (4)

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