Impact of e-Learning on students: A proposal and evaluation of enhanced e-learning model to increase the academic performance of university students

2016 ◽  
Author(s):  
L. Makkar ◽  
Abeer Alsadoon ◽  
P.W.C. Prasad ◽  
A. Elchouemi
Keyword(s):  
Academic Performance ◽  
University Students ◽  
Learning Model ◽  
E Learning

scholarly journals The Impact of Extended E-Learning on Emotional Well-Being of Students during the COVID-19 Pandemic in Saudi Arabia

Children ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Sehar-un-Nisa Hassan ◽  
Fahad D. Algahtani ◽  
Mohammad Raafat Atteya ◽  
Ali A. Almishaal ◽  
Ahmed A. Ahmed ◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Regression Analysis ◽  
Academic Performance ◽  
University Students ◽  
Emotional Health ◽  
Well Being ◽  
Female Students ◽  
Academic Calendar ◽  
E Learning ◽  
The Impact

Educational institutions in Saudi Arabia extended e-learning until the third semester of the academic calendar to prevent the spread of COVID-19 infection and to achieve 70% inoculation for the Saudi population. This study assesses the impact of extended e-learning and other associated stressors on the emotional health of university students in Saudi Arabia. An online cross-sectional survey collected data between the months of January–March 2021. The emotional signs of stress were measured by using a subset of items from the COVID-19 Adolescent Symptom and Psychological Experience Questionnaire (CASPE). Data about demographic variables, educational characteristics and academic performance were also collected. A regression analysis was performed to determine predictors of emotional health. A total of 434 university students including females (63%) and males (37%) provided responses. One-third of students (33%) indicated that the COVID-19 pandemic and its resulting changes including online distance studies greatly influenced their daily lives in a negative way. The regression analysis demonstrated that female students and students with average academic performance had increased vulnerability to experience emotional signs of stress (p < 0.05). The factors ‘Not going to university’ and ‘Not having a routine life’ were significant predictors of stress responses (p < 0.01) and (p < 0.001) respectively. E-learning during the COVID-19 pandemic made it possible for students to complete their studies as per academic calendar; simultaneously, it increased the vulnerability to experience stress, particularly for female students and students with average academic performance. These findings imply that academic advising and counseling services should be more readily available during digital studies to support at risk students.

scholarly journals Perceived stress among university students in Oman during COVID-19-induced e-learning

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
Mustafa Malik ◽  
Sarfaraz Javed
Keyword(s):  
Academic Performance ◽  
University Students ◽  
Perceived Stress ◽  
Online Courses ◽  
High Stress ◽  
Significant Negative Correlation ◽  
Health Issues ◽  
E Learning ◽  
The University ◽  
The Impact

Abstract Background Higher education institutions across the world moved to e-learning in response to the disruptions caused by the pandemic. While e-learning has an advantage for students that they can attend to their courses from anywhere at their convenience, yet the sudden disruptive shift to e-learning during the pandemic saw students facing many challenges, which had strong ability to induce mental health issues among the students. This study aimed at examining the impact of COVID-19-induced e-learning on the university students’ stress perceptions in Oman. Results A total of 966 usable responses were received. The results showed that 96.9% (moderate stress = 82.5% and high stress = 14.4%) reported having experienced stress through e-learning during COVID-19. The results further indicated that there was a significant negative correlation between perceived stress and the students’ academic performance. The family support and institutional support were observed to have a significant effect on students’ stress perception. Conclusions Students are away from the physical campuses over a year now, continuing their courses and programs online. The numerous challenges they are facing through e-learning, together with the prevailing uncertainty, have intensified stress among them. The continued stress over time will not only affect their academic performance, but their mental and physical health as well, as the stress has proven to be one of the major causes of various physical and mental disorders. While e-learning seems to emerge as a new normal, the students require proper attention, help, and support from their families and institutions. The institutions should revisit their online courses and program delivery mechanisms, methods, and practices to ensure that students are not over stressed.

Factors Influencing Academic Performance of University Students

2015 ◽  
pp. 103-115 ◽  
Author(s):  
Lucky Sibanda ◽  
Chux Gervase Iwu ◽  
Olumide Henrie Benedict
Keyword(s):  
Academic Performance ◽  
University Students ◽  
Factors Influencing

Relationship between satisfaction with learning outcomes and mental health among medical and engineering students

2020 ◽  
pp. 70-78
Author(s):  
O. Bukhanovskaya ◽  
N. Demcheva
Keyword(s):  
Mental Health ◽  
Academic Performance ◽  
Mental Disorders ◽  
University Students ◽  
Learning Outcomes ◽  
Engineering Students ◽  
Clinical Forms ◽  
Complete Survey ◽  
Medical University

Method of calculating the index of crisis of gratification has been developed on the basis of the complete survey of 995 students of medical university and 804 students of engineering university, determination of clinical and social parameters and factors related to the process of education in the specialized university. It included: a scale for the assessment of the degree of intellectual intensity, academic performance, stress situations related to the peculiarities of education. Reliable differences in values between groups of healthy students, students with preclinical and clinical forms of mental disorders are revealed as a result of calculation of the index of gratification. The authors conclude that satisfaction with the results of education has a significant impact on the mental health of university students.

scholarly journals Socio-Emotional Variables Linked to the Consumption of Drugs amongst University Students of Social Sciences: A Pilot Study

2021 ◽  
Vol 18 (9) ◽  
pp. 4502
Author(s):  
José Luis Rodríguez-Sáez ◽  
Luis J. Martín-Antón ◽  
Alfonso Salgado-Ruiz ◽  
Miguel Ángel Carbonero
Keyword(s):  
Social Support ◽  
Emotional Intelligence ◽  
Academic Performance ◽  
University Students ◽  
Regression Model ◽  
Household Survey ◽  
Predictive Variables ◽  
Cannabis Consumption ◽  
And Gender ◽  
Mood Scale

This descriptive and transversal study, carried out on an intentional sample of 211 subjects who were split in terms of their consumption of psychoactive substances over the last month and who were aged between 18 and 28 (M = 21.36, and SD = 1.90), aimed to explore the emotional intelligence, perceived socio-family support and academic performance of university students vis-à-vis their consumption of drugs and to examine the link between them. The goal was to define university student consumer profile through a regression model using the multidimensional Perceived Social Support Scale (EMAS) and the Trait Meta Mood Scale-24 (TMMS-24) as instruments, together with academic performance and gender. The results report alcohol, tobacco, and cannabis consumption rates that are above the levels indicated by the Spanish household survey on alcohol and drugs in Spain (EDADES 2019) for the 15–34-year-old age range in Castilla y León. A certain link was observed between the consumption of substances and academic performance, although no differences were seen in academic performance in terms of consumer type. There was also no clear link observed between emotional intelligence and academic performance or between social support and academic performance. The predictive contribution of the variables included in the regression model was low (9%), which would advocate completing the model with other predictive variables until more appropriate predictability conditions can be found.

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