zivar sbaghinejad

Critical thinking is used to improving individual skills to determine the value and advantages of a phenomenon, factor or, information.

The current descriptive research was conducted using a cross-sectional survey method. The research population included 260 graduate students of Ahvaz Jundishapur University of Medical Sciences who randomly participated in the research. Exploratory factor analysis, confirmatory factor analysis, difficulty factor, and discrimination factor were used to standardize the test.

The findings of the exploratory factor analysis led to the identification of a model with 28 items and four factors "evaluation", "analysis", "deduction" and "interpretation". This model with an internal similarity of 0.832 can explain more than 41% of the changes in critical thinking. The correlation between all identified factors was positive and significant. The findings of confirmatory factor analysis showed CFI=0.861, GFI=0.838 and, RMSEA=0.049 and indicate the confirmation. Findings of difficulty and discrimination indices showed that more than half of the test questions are difficult and have a weak ability to distinguish between strong and weak students. Also, 4 questions had a discrimination index of zero or negative.

California Critical Thinking Test Form B is norm and valid for Iranian students. However, due to the high difficulty of more than half of the questions and their weak ability to distinguish weak and strong students, it needs to be modified for use in Iranian students.

E-learning plays a crucial role in teaching and learning communities to be noticed to study, and achieving this ideal requires investigating acceptance of e-learning.  hence this study investigated E-learning acceptance among postgraduate students studing in Ahvaz Jundishapur University of Medical Sciences based on Davis Technology Acceptance Model. This descriptive-correlational study that was conducted by survey method. 330 postgraduate students were selected through stratified random sampling method to participate in the study. Data were collected using questionnaire through self-report; and then data were analyzed using both descriptive statistics and inferential statistics through SPSS software. Accordingly, the outcomes revealed adequate validity and reliability for the application of Technology Acceptance Model among participants. Perceived ease of use, usefulness about E-learning, students’ attitudes toward E-learning, and the intention to use E-learning were the factors that affect E-learning’s acceptance and actual positively use. Considering the fact that attitudes toward E-learning had more predictive power than other variables of technology acceptance model, emphasis on students’ favorable attitudes toward E-learning can be effective in accelerating its acceptance and leadsto improve students' learning outcomes.