In Discover education
A synthesized investigation, employing graphical and analytical approach, has been conducted to examine inadequacy of electronic education and limitations posed by transformative mode of learning from students' perspective. Moreover, the breadth of subject understanding through digital mode and students' preference for physical or electronic mode of learning in the future were examined. A descriptive analysis was executed through R programming for the obtained numeric-characteristic statistics. For computational analysis of the data to determine proportion of deteriorating virtual-assessment performance attributed to conditioned subject-command, a machine learning approach of interaction-regression is adopted. It is implied through the obtained results that a majority of students felt discontented at not being able to achieve optimized learning outcomes post-virtual-attendance of study programs. It is also concluded that blended influence of online learning and partial subject-command resulted in insufficient assessment performance. Additionally, the current study highlights the importance of need-based adaptations to facilitate automated mode of learning and virtual platforms' uniform access to students.
Shahid Nazish
2022
Data visualization, Digital mode of education, Insufficient subject understanding, Interaction-Regression, Machine learning, Uniform access to digital coaching platforms
