Factors propelling mathematics learning: insights from a quantitative empirical study

Yuliya Popova, M. Abdualiyeva, Yerlan Torebek, Pulat Saidakhmetov
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Abstract

Mathematics learning (ML) is a fundamental aspect of education that lays the groundwork for various academic disciplines and practical applications. Understanding the factors that propel ML is crucial for optimizing educational outcomes. This quantitative empirical study investigates the impact of logical reasoning (LR), critical thinking (CT), information technology (IT), and distance learning (DL) on ML. The study employs structural equation modeling (SEM) using SmartPLS 4 for data analysis and hypothesis testing. The findings reveal that LR, CT, IT, and DL positively influence ML. The results highlight the importance of fostering LR, CT, and the integration of IT in mathematics education. This study contributes to the existing body of knowledge by providing insights into the factors that promote effective ML. These findings have implications for educators, policymakers, and curriculum developers, aiding in the design of instructional strategies and the integration of technology to enhance ML outcomes.
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推动数学学习的因素:一项定量实证研究的启示
数学学习(ML)是教育的一个基本方面,它为各种学科和实际应用奠定了基础。了解推动数学学习的因素对于优化教育成果至关重要。本定量实证研究探讨了逻辑推理(LR)、批判性思维(CT)、信息技术(IT)和远程学习(DL)对数学学习的影响。研究采用 SmartPLS 4 的结构方程模型(SEM)进行数据分析和假设检验。研究结果表明,LR、CT、IT 和 DL 对 ML 有积极影响。结果凸显了在数学教育中促进 LR、CT 和信息技术整合的重要性。本研究对促进有效数学学习的因素进行了深入分析,为现有知识体系做出了贡献。这些研究结果对教育工作者、政策制定者和课程开发者具有启示意义,有助于设计教学策略和整合技术以提高数学学习成果。
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