Factors Affecting Students' Digital Distraction In E-Learning In The Covid Pandemic 19

Abstract
At the end of 2019, with the emergence of a new type of coronavirus called Covid 19, the world underwent extensive and profound changes in various areas of human life. One of the aspects that has been strongly affected by this phenomenon is the field of education and learning; with the spread of the Covid Pandemic, followed by the abolition of traditional and face-to-face education, e-learning became one of the most important methods of education in the world. The learning of this method was such that for the first time in the history of the world, almost all teachers and educators taught virtually, and all learners also taught virtually. Meanwhile, the beginning and continuation of e-learning due to the conflict of countries with this sudden and widespread phenomenon that involved all sectors of a country from industry to education faced many challenges. Lack of necessary infrastructure, economic, cultural, technical problems, etc. are among them. In the field of education and in particular, one of the challenges of e-learning is the student not being seen while teaching in the virtual classroom and the lack of two-way interactions between teacher and student and, consequently, their distraction. This phenomenon is called digital distraction. E-learning has given rise to digital distraction as a pervasive phenomenon as learning environments evolve. The implementation of all traditional classrooms virtually, which has naturally been accompanied by a reduction in the supervision of professors and teachers, has exacerbated this problem. Unintentional use of electronic devices can be a source of digital distraction. On the other hand, studies have shown that people who use electronic devices and are not satisfied with their education are more likely to have multifunctional and divided attention in the classroom. This group of learners is more distracted. Sometimes digital distraction leads to personal injury; the entire above can be mentioned in the discussion of personal injuries. But sometimes this phenomenon damages the learning of other students. For example, open and closed laptops, doing extracurricular activities, changing background photos, etc. are some of the things that distract other students more and this is done by subconsciously changing their attention to electronic devices and damaging their learning. Therefore, electronic devices such as laptops, etc. cause disorders in students 'senses and are considered a factor in reducing their accuracy, and as a result, reduce their comprehension and, consequently, their learning rate, and significantly affect students' academic performance. . In fact, it can be added that students use laptops and mobile phones to check emails, browse and browse social networks, update personal pages, read news, watch movies, shop online, and play games while teaching professors. It has a negative effect on students' learning, and impairs their understanding of the curriculum and their classroom performance in general. Therefore, identifying students' digital distractions and the factors affecting it is important. The aim of this study was to design and validate tools for measuring the factors affecting students' digital distraction in e-learning. The main research method of the combined research was a sequential exploratory design of the tool development model; the focus of this article is on the report of the quantitative research section. These types of projects start with qualitative data with the aim of recognizing the phenomenon and then continue with the implementation of the secondary or quantitative stage. In other words, the purpose of this type of design is that the results of the first (qualitative) method cause the formation and clarification of the second (quantitative) method. Because no tools or measurements were available in this type of design, the variables were also unknown and there was no guiding framework or theory; therefore, first the researcher used a qualitative format to process the data collection. At this stage, after compiling the interview questions, a semi-structured interview was conducted with 30 students of Birjand Faculty of Educational Sciences and Psychology, and after theoretical saturation of the data, qualitative data were analyzed. Then, in the quantitative part, using the extracted categories, the items of the digital distraction questionnaire of the students in the electronic classroom were compiled. After making the questionnaire, the online questionnaire link was provided to the students. In the quantitative part, the research method was descriptive correlation and applied. 160 students of the Faculty of Educational Sciences and Psychology of Birjand University were selected by convenience sampling method and sampling was continued until the sample adequacy was estimated by KMO test. The data collection method was a researcher-made digital distraction questionnaire with 46 items. To measure psychometric properties, validity methods (face, content and structure) and reliability (Cronbach's alpha coefficient) were used. In order to assess the face and content validity, this questionnaire was thoroughly and critically reviewed by several faculty members of the Faculty of Educational Sciences and Psychology of Birjand University. After final approval, it was implemented and finally shared to collect data. Exploratory factor analysis with varimax rotation was used to assess the validity of the structure. The results of exploratory factor analysis led to the identification of seven components for the digital distraction variable of students in e-learning during the Quaid pandemic, which explained 62% of the structural variance of "digital distraction". 1) digital distraction; 2) Lesson and teacher; 3) Attitudes towards e-learning in the Quaid days; 4) teaching method; 5) Common distractions; 6) distraction management techniques; 7) interactive teaching; Factors were identified. The reliability of the instrument was 88% using the Cronbach's alpha coefficient for the whole instrument and between 0.69 and 0.81 for its subscales. The results of calculating the correlation coefficients between the subscales of the questionnaire and the total score showed a coefficient between 0.27 up 0.73. All subscales except "Attitude to e-learning" have a positive and high correlation with the overall score of the scale. According to the research results, the present scale can be used to assess the factors affecting students' digital distraction in e-learning. This tool can help researchers in planning and conducting various researches on Iranian university students and has a desirable capability in Iranian culture. Therefore, researchers are expected to conduct new research on the role of social networks in the digital distraction of students at other universities and higher education institutions.