Assessment of Online Teaching Using Statistical and Unsupervised Learning Methods

The objective of the present study is to assess different aspects of online teaching from faculties’ perspective. We investigate the level of the difficulties faced by faculty members in handling Moodle, the satisfaction level of online teaching, and online evaluation, and the role of previous awareness/training programs in facing difficulties handling Moodle. Finally, we find the grey areas in online teaching. We collected data from 104 faculty members of Graphic Era Hill University (GEHU) for the present study. Analysis of variance approach and t-test are used for different purposes. K-Means Clustering method is used for analyzing the role of training programs in facing difficulties in handling Moodle. We found that different aspects of Moodle handling were considered equally difficult; satisfaction level in content delivery only is considered high. Satisfaction levels in two components of evaluation, multiple choice questions (MCQ) and descriptive questions (DQ) were neither considered the same nor high; however, satisfaction in MCQ is considered a little more than in DQ. Through clustering patterns, we found a significant effect of previous awareness/training in facing difficulty in handling Moodle. These findings may be useful for making strategies for online teaching in the future.