Investigation of the Relationships between E-Learning Styles, Educational Technology Self-Efficacy Perceptions and Problem-Solving Skills of Pre-Service Elementary Mathematics Teachers'

This study aims to determine the relationship between pre-service elementary mathematics teachers' e-learning styles, educational technology self-efficacy perceptions, and problem-solving skills. The sample of the study, in which the relational screening model was used, consists of 150 pre-service teachers studying in a state university's elementary mathematics teaching department. Of the participants, 68% (n=102) were female and 32% (n=48) were male. Data collection tools, e-learning styles, education technology self-efficacy, and measurement tools consisting of non-routine problems were used to determine problem-solving skills and an information form. Pearson product-moment correlation technique and multiple linear regression analysis were used to analyze the data set. According to the study's findings, significant relationships were determined between the sub-dimensions of e-learning styles, education technology self-efficacy, and problem-solving skills. Predictive variables consisting of sub-dimensions of e-learning styles and education technology self-efficacy explained 36% of the variance of the problem-solving skill. At the same time, audio-visual learning, verbal learning, active learning, logical learning, modeling digital-age work and learning, designing and developing digital-age learning experiences and assessments, and engaging in professional growth and leadership variables were effective in problem-solving. Finally, according to the findings, some suggestions are presented.

This study aims to determine the relationship between pre-service elementary mathematics teachers' e-learning styles, educational technology self-efficacy perceptions, and problem-solving skills. The sample of the study, in which the relational screening model was used, consists of 150 pre-service teachers studying in a state university's elementary mathematics teaching department. Of the participants, 68% (n=102) were female and 32% (n=48) were male. Data collection tools, e-learning styles, education technology self-efficacy, and measurement tools consisting of non-routine problems were used to determine problem-solving skills and an information form. Pearson product-moment correlation technique and multiple linear regression analysis were used to analyze the data set. According to the study's findings, significant relationships were determined between the sub-dimensions of e-learning styles, education technology self-efficacy, and problem-solving skills. Predictive variables consisting of sub-dimensions of e-learning styles and education technology self-efficacy explained 36% of the variance of the problem-solving skill. At the same time, audio-visual learning, verbal learning, active learning, logical learning, modeling digital-age work and learning, designing and developing digital-age learning experiences and assessments, and engaging in professional growth and leadership variables were effective in problem-solving. Finally, according to the findings, some suggestions are presented.