DATA ANALYTICS IN EDUCATION: FACTORS AFFECTING THE UTILIZATION OF DATA ANALYTICS FOR EDUCATION IN QATAR

Abstract

Data analytics in education is an emerging concept in the field of information technology. The purpose of this study is to examine the factors that affect professors' and lecturers' intention to use data analytics in the context of making evaluation decisions related to students. The study is based on a modified version of the unified theory of acceptance and use of technology (UTAUT2). Price value, habit, and experience have been replaced by privacy, management support, and trust. The reason for this modification is that the new variables have shown a significant correlation with the intention in the education domain. In contrast, the removed variables harm the measurement of intention in the learning field. Many previous studies on the adoption of technology have demonstrated positive results using UTAUT2. Several studies have been modified to suit the domain. The research question is what are the factors that influence professors' and lecturers' intentions to use data analytics in evaluating students? Eight hypotheses were developed based on the model variables. An online survey was used as the research instrument to collect the data. The targeted respondent was professors and lecturer in higher education institutions in Qatar. The total number of valid responses that were collected was 158. Results indicate that performance expectations are the most influential factor affecting the intention to use data analytics by higher education educators in Qatar, followed by management support and trust. However, effort expectancy, social influence, facilitating conditions, hedonic motivation, and privacy were not significant. In the equation generated from the three significant variables, the R square is 0.664, The F value is 101.44, and the residual has a degree of freedom of 153. The P value is less than 0.001. By emphasizing the use of data analytics for student evaluation, the research contributed significantly to the knowledge and literature in Qatar. Universities should ensure the right tools are used in conjunction with the right data, as well as the integrity and availability of the data. University management should help professors, lecturers, instructors, and teaching assistants understand the factors necessary for the successful implementation of data analytics applications.