عنوان مقاله [English]
We are witnessing an increase in technology use which has turned out to be a major element to improve students' teaching and learning processes in today’s educational system. One impact of this change has been various positive educational technology outcomes for learners. Also, using educational technology and innovation is considered as one of the essential components of developing creativity and innovation in students. Over time, much attention has been paid to what teachers need to know in order to effectively use technology in the classroom, and in addition, the competencies needed to nurture creative students. Since creativity and technology are vital for the success of educational organizations, especially universities, extensive studies have made efforts in order to determine the relationship between these two areas. These studies examine the way in which various emerging technologies offer many specific benefits to educational organizations. However, there seem to be three outstanding benefits in the realm of creativity and innovation, which is a product of the technological world: an improved ability to the connection and empowerment of the learners, an improved ability to organize the knowledge base of educational centers, and an improved ability of the organization to go beyond borders. The aim of this study was to investigate the relationship between using educational technology and creativity and innovation of the University of Kurdistan’s educational sciences students. Regarding methodology, the current study was applied in terms of purpose and also it is a descriptive survey research in terms of method. In this research, documentary method was utilized i.e. using books, articles, English and Farsi theses, and a field questionnaire to collect the required data. The questionnaire has been prepared and arranged in three parts; The first part includes 4 demographic questions (gender, age, marital status and education). Of the 43 questions in the main body of the standard questionnaire, 30 questions were on the dimensions of technology, 8 questions measured creativity, and finally 5 questions investigated innovation concept in the students. All the analyses, descriptive and inferential statistics were performed via the SPSS26 and Smart PLS3 packages. By using Smart PLS3 software, reliability, validity, divergence and convergence were measured. The participants were students of educational sciences in the University of Kurdistan, including both undergraduate and postgraduate students. In order to determine the sample size, Cochran’s formula was used and 235 participants were selected by simple random sampling. In order to examine the educational technology variable, four components including "Educational objectives, educational conditions, educational resources and educational efficiency" were used on 5 levels of the Likert scale (1 = "very little" to 5 = "very much"). Also, the variable of innovation and creativity (combined creativity and advanced creativity) was validated and measured at 5 levels of the Likert spectrum (1 = "completely disagree" to 5 = "completely agree"). As for the mean and standard deviation of variables of creativity and innovation obtained, the most creativity variable related to "summary" variables with a mean of 3.84 and a standard deviation of 1.08, and the variable of "internal affairs development" with a mean of 3.81 and a standard deviation of 1.12. The lowest variable of creativity according to students related to the variable "lack of proper planning" with a mean of 2.49 and a standard deviation of 1.13. A Pearson correlation analysis was conducted in order to assess the relationship between research variables. The results showed that there was a positive and significant relationship between educational goals and educational resources (p<0.01, r=0.73). Also, there was a positive and significant relationship between educational resources and educational conditions (p<0.01, r=69). Further, the Pearson moment correlation for other research variables showed a positive and significant relationship at p<0.01 level. Regarding structural equation model fit, the value of T statistic calculated for all components and sub-components was higher than 1.96. Thus, the significance of questions and relationships between variables can be confirmed at the 95% confidence level. The second criterion regarding structural equation model fit was R2 coefficients, which represent the percentage of variance explained by the independent variable of a dependent variable. As for R2 values, the data obtained was 0.688 for educational dimensions, and 0.818 for educational conditions. The acquired data for the other dimensions were higher than 0.67 which indicated a strong fit of the structural model of the research. The third criterion in structural equation model fit was the Q2 criterion, which showed the predictive power of the model. The Q2 value for educational technology dimensions and also creativity and innovation was higher than 0.15. which represented a moderate to high structural model fit. Therefore, it can be concluded that due to the predictive value of “learning performance”, which was 0.395, higher than 0.35, this dimension had the strongest predictive value compared to other research dimensions. Finally, after examining and confirming the conceptual model of the research, and analyzing data by using PLS, and also results obtained from the connection between variables, path coefficients, T-statistics, significance level, mean, and rank in relation to the research questions, with the path coefficient of 0.911, the obtained T= 66.708 was confirmed. Thus, it revealed that there was a positive relationship between educational resources and creativity and innovation of the students. The same positive result was obtained for the relationship between educational conditions and creativity and innovation with a path coefficient of 0.904 and T=80.625. Regarding the third question, the relationship between educational efficiency and creativity and innovation of the students was also positive. Further, the obtained data for the fourth question, path coefficient of 0.898 and T= 70/334 revealed a significant and positive relationship between educational aims and creativity and innovation of the students. In conclusion, based on the findings, it was showed that the educational technology variable was able to explain 57% of the changes in creativity and innovation. Among the dimensions of educational technology, the effect observed from the highest to the lowest, related to educational conditions, educational resources, educational goals, and educational efficiency. As final remarks, it was suggested that education policymakers integrate more technology into course contents, hold educational technology workshops in order to develop creativity and innovation in students, and provide sufficient educational infrastructure to incorporate modern technologies into classrooms.