The COVID-19 pandemic and the enforced restrictions have harshly affected educational sectors in 161 countries around the world. With more than 1.6 billion students away from normal school life, the crisis threatens the teaching and learning processes and the students’ emotional health. Herein, we present the result of a careful assessment of the feelings of over 13,000 students at high school, undergraduate, and postgraduate levels across 36 campuses over 8 subsequent weeks from the onset of the COVID-19 pandemic. The results indicate a general low energy level and dominance of negative feelings among the students regardless of their academic levels. We have recorded 5 responses (being
anxious
,
stressed
,
overwhelmed
,
tired
, and
depressed
) as the most frequently reported feelings in the time of lockdown. Overall, 14% of those who have reported to suffer from these feelings have also identified a need for professional help in managing their feelings throughout the quarantine period. The current study also presents several strategies to combat the undesirable consequences of COVID-19 pandemic.
Today, modern educational models are concerned with the development of the teacher-student experience and the potential opportunities it presents. User-centric analyses are useful both in terms of the socio-technical perspective on data usage within the educational domain and the positive impact that data-driven methods have. Moreover, the use of information and communication technologies (ICT) in education and process innovation has emerged due to the strategic perspectives and the process monitoring that have shown to be missing within the traditional education curricula. This study shows that there is an unprecedented increase in the amount of text-based data in different activities within the educational processes, which can be leveraged to provide useful strategic intelligence and improvement insights. Educators can apply the resultant methods and technologies, process innovations, and contextual-based information for ample support and monitoring of the teaching-learning processes and decision making. To this effect, this paper proposes an Educational Process and Data Mining (EPDM) model that leverages the perspectives or opinions of the students to provide useful information that can be used to enhance the end-to-end processes within the educational domain. Theoretically, this study applies the model to determine how the students evaluate their teachers by considering the gender of the teachers. We analyzed the underlying patterns and determined the emotional valence of the students based on their comments in the Students Evaluation of Teaching (SET). Thus, this work implements the proposed EPDM model using SET comments captured in a setting of higher education.
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