Real, virtual, or simulated: Approaches to emergency remote learning in engineering

Author(s):  
Karel Kruger ◽  
Karin Wolff ◽  
Kieran Cairncross
Keyword(s):  
2020 ◽  
Author(s):  
Laura Leticia Salazar Preciado ◽  
Sally Haack ◽  
Luis Renee González Lucano ◽  
Ricardo Javier Díaz Domínguez ◽  
Inbal Mazar

BACKGROUND COVID-19 represents a major global health crisis and has resulted in drastic changes to daily life. While even prior to the start of the pandemic college students had a high prevalence of mental health conditions, this group is even more at risk during the pandemic. OBJECTIVE To investigate the emotional impact of quarantine and transition to remote learning on health science students from two countries, regarding anxiety prevalence, mental wellbeing and coping behaviors during the first month of the COVID-19 outbreak. METHODS A total of 28 students from Tecnologico de Monterrey (TEC) in Guadalajara, Mexico and 19 students from Drake University (Drake) in Iowa, United States participated in the study. All students were studying health sciences, including degree programs such as medicine, pharmacy, and nutrition and wellness. This longitudinal study assessed students’ immediate psychological response during the COVID-19 pandemic by using an anonymous online questionnaire administered in April and again in May 2020. The survey was created to assess anxiety levels, coping mechanisms, and changes in daily habits. Demographics such as gender, age, non-academic working, living arrangements, household size, and number of roommates/co-habitants were also collected. RESULTS The April survey sample included 47 students and the May survey sample included 41 students. At least 50% of respondents were females, 20 to 21 years of age. The April survey results showed that more TEC students rated their food intake as higher than before the pandemic when compared to Drake students (p=0.032). Alcohol consumption reportedly stayed the same for Drake students and was lower for TEC students (p=0.004). The May survey results showed a statistically significant difference only for the alcohol consumption (p<0.001). Sleep time between April and May in TEC students showed a significant statistical difference, with students reporting less sleep time in May (p=0.016). The analysis for the level of anxiety according to the Beck Anxiety Inventory showed no statistically significant differences, neither when comparing between intra (TEC p=0.189 and Drake p=0.879) and inter group survey times (TEC vs Drake in April p=0.919 and TEC vs Drake in May p=0.305). The most common physical symptoms reported by students during both study periods were: feeling hot, nervous, fear of losing control, inability to relax, and fear of the worst happening. CONCLUSIONS There is growing concern surrounding the mental health status and needs of health science students during the pandemic. It is important to monitor changes in students’ mental health in response to the pandemic and to create interventions that target students appropriately.


2021 ◽  
Vol 7 ◽  
pp. 237802312098820
Author(s):  
Thurston Domina ◽  
Linda Renzulli ◽  
Brittany Murray ◽  
Alma Nidia Garza ◽  
Lysandra Perez

Using data from a spring 2020 survey of nearly 10,000 parents of elementary school parents in one large southeastern public school district, the authors investigate predictors of elementary school student engagement during the initial period of pandemic remote learning. The authors hypothesize that household material and technological resources, school programming and instructional strategies, and family social capital contribute to student engagement in remote learning. The analyses indicate that even after controlling for rich measures of family socioeconomic resources, students with access to high-speed Internet and Internet-enabled devices have higher levels of engagement. Exposure to more diverse socioemotional and academic learning opportunities further predicts higher levels of engagement. In addition, students whose families remained socially connected to other students’ families were more likely to engage online.


Author(s):  
Liz O. Boltz ◽  
Aman Yadav ◽  
Brittany Dillman ◽  
Candace Robertson
Keyword(s):  
K 12 ◽  

Author(s):  
Monira I. Aldhahi ◽  
Abdulfattah S. Alqahtani ◽  
Baian A. Baattaiah ◽  
Huda I. Al-Mohammed

AbstractThe overarching objective of this study was to assess learning satisfaction among students and to determine whether online-learning self-efficacy was associated with online learning satisfaction during the emergency transition to remote learning. This cross-sectional study involved a survey distributed to 22 Saudi Arabian universities. The survey used in this study consisted of an online learning self-efficacy (OLSE) questionnaire and an electronic learning (e-learning) satisfaction questionnaire. A total of 1,226 respondents voluntarily participated in and completed the survey. Students in medical fields made up 289 (23.6%). A Kruskal–Wallis H test and a chi-square test were used to compare the student’s satisfaction based on the educational variables. Spearman’s correlation and multiple linear regression analyses were performed to assess the association between self-efficacy and satisfaction. The findings revealed degrees of satisfaction ranging between high satisfaction and dissatisfaction. The majority of students (51%) expressed high satisfaction, and 599 students (49%) reported experiencing a low level of satisfaction with e-learning. A comparison of groups with low and high satisfaction scores revealed a significant difference in the OLSE. High satisfaction was positively correlated with the OLSE domains: time management, technology, and learning. The OLSE regression analysis model significantly predicted satisfaction. It showed that the model, corrected for education level and grade point average of the students, significantly predicted e-learning satisfaction (F = 8.04, R2 = 0.59, p = .004). The study concluded that students’ satisfaction with the e-learning experience is influenced by e-learning self-efficacy. The study’s findings lead to the practical implications and identify the need to improve the remote learning, time management and technology self-efficacy to enhance students’ satisfaction.


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