Abstract
BACKGROUND AND AIM:Given the absence of a scale specially designed to measure willingness to mobile learning (m-learning) in medical sciences students, the present study was conducted to design and evaluate the psychometric properties of “willingness to m-learning” scale for medical sciences students.METHODOLOGY:The study was carried out as a mixed-method study in two phases at Saveh University of Medical Sciences in 2019. Phase one was a qualitative study to elaborate on the students' perception of m-learning. Then, the statements were extracted, and statement pool was completed through reviewing the text. In the second phase, the psychometric properties including face, content, and construct validities (using explorative factor analysis), internal consistency (Cronbach's alpha), and test–retest reliability (intercluster correlation test) were measured. A total of 482 students who were selected randomly participated in the second phase. Data analysis was done with MAXQDA software (VERBI Software 2019, Berlin, Germany) for qualitative data and SPSS 19 software (SPSS Inc., Chicago, IL, USA) for quantitative data.RESULTS:Based on qualitative content analysis and literature review, 92 statements were extracted. After checking face and content validity, 55 statements remained in the study. Construct validity of the questionnaire based on explorative factor analysis removed 10 more statements and the remaining 45 statements were categorized into nine factors, namely technophilia, perceived attraction, perceived ease, perceived conflict, self-management, attitude, behavioral intention to use, educational use, and efficacy of m-learning. Reliability of the scale was obtained as 0.95 based on Cronbach's alpha and stability was checked using test–retest method (intercluster correlation coefficient; r = 0.92).CONCLUSION:Willingness to m-learning scale had an acceptable reliability and validity in medical sciences students. Therefore, it can be used for medical sciences students for improve learning and education.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have