Аңдатпа
Smart learning technologies employed in education encompass a range of tools and platforms that facilitate learning and instructional activities. Here are several significant smart learning technologies: e-learning platforms, smart learning content tools, video conferencing environments, virtual and augmented reality, game-based learning, smart learning assessment tools, and mobile applications. Determining the attitudes of prospective teachers toward smart learning technologies is an important research need. The purpose of this research was to evaluate teacher candidates' attitudes toward the use of smart learning technologies. In this study, the relational screening model, which is among the quantitative research methods, was used to examine teachers' smart learning competence levels and their relationships with various variables. The sample of the research consisted of 688 university students studying at various education faculties in universities in Kazakhstan. Research data were collected using the attitude scale for smart learning technologies in education developed by the researchers. Research data were calculated using the SPSS 20.0 statistical package program. Parametric tests were applied to the data set. The data set underwent tests such as the weighted mean, standard deviation, independent variables t-test, and ANOVA. We discussed the attitudes of university students participating in the research towards smart learning technologies in education based on the gender variable. The findings showed that there was no significant difference between the attitudes of male and female university students toward smart learning technologies in education. The attitudes of university students participating in the research towards smart learning technologies in education were discussed according to the variable of the class they were studying in. As a result of the findings, no significant difference was found between the attitudes of first-year, second-year, and third-year university students towards smart learning technologies in education.