Smartphone Use among Undergraduate STEM Students during COVID-19: An Opportunity for Higher Education?

The association between smartphone use and sleep quality, psychological distress, and loneliness among health care students and workers in Saudi Arabia

BACKGROUND

The use of smartphones among the general public and health care practitioners, in particular, is ubiquitous. The aim of this study was to investigate the relationship between smartphone addiction and sleep quality, psychological distress, and loneliness among health care students and workers in Saudi Arabia.

METHODS

This cross-sectional study used an online questionnaire to collect data on smartphone addiction, sleep quality, psychological distress, and loneliness as well as demographic information.

RESULTS

A total of 773 health care students and workers participated in the study, with an average age of 25.95 ± 8.35, and 59.6% female participants. The study found a positive significant association between smartphone addiction and psychological distress (F(1,771) = 140.8, P < 0.001) and emotional loneliness (F(1,771) = 26.70, P < 0.001). Additionally, a significant negative association between smartphone addiction and sleep quality was found (F(1,771) = 4.208, P = 0.041). However, there was no significant relationship between smartphone addiction and social loneliness (F (1,771) = 0.544, P < 0.461).

CONCLUSION

These findings suggest that smartphone addiction has a negative impact on psychological distress, sleep quality, and emotional loneliness among health care students and workers. It is important to promote strategies to reduce smartphone dependency in order to avoid the harmful consequences of smartphone addiction.

Factors affecting young customers' smartphone purchase intention during Covid-19 pandemic

Purchase intention has become a critical issue to the marketers of smartphones as the market has become very competitive, volatile, uncertain and dynamic during Covid-19 than ever before. For sustaining in the competitive market, every marketer is trying to upgrade its product appearance, product quality, service quality, attractive features, and latest version of software as a whole. This study has investigated the effects of product features, brand image, product price, and social influences on young customers' purchase intention of smartphone during this Covid-19 pandemic time. Survey was conducted using structured questionnaire by collecting data from 305 respondents by using convenience sampling technique. Statistical Package for the Social Sciences (SPSS) integrated with AMOS was employed for data analysis. Cronbach's alpha, composite reliability and average variance extracted (AVE) were used to test the reliability and validity of the collected data while hypotheses were tested by using Structural equation modeling (SEM). The findings of the study shows that, there is a significant effect of product features, brand image, and product price on purchase intention of a smartphone but social influences has no significant impact on young customers' purchase intention. The study results will help the smartphone marketers to redesign their pandemic and post pandemic segmenting, targeting, differentiation and positioning strategies. Practical and managerial implications along with the future research directions have been discussed at the end of this paper also.

Smartphone Usage and Studying: Investigating Relationships between Type of Use and Self-Regulatory Skills

The purpose of this study is to investigate the relationships between self-regulated learning skills and smartphone usage in relation to studying. It is unclear whether poor learning habits related to smartphone usage are unique traits or a reflection of existing self-regulated learning skills. The self-regulatory skills (a) regulation, (b) knowledge, and (c) management of cognition were measured and compared to the smartphone practices (a) multitasking, (b) avoiding distractions, and (c) mindful use. First-year undergraduates (n = 227) completed an online survey of self-regulatory skills and common phone practices. The results support the predictions that self-regulatory skills are negatively correlated with multitasking while studying and are positively correlated with distraction avoidance and mindful use of the phone. The management of cognition factor, which includes effort, time, and planning, was strongly correlated with multitasking (r = −0.20) and avoiding distractions (r = 0.45). Regulation of cognition was strongly correlated with mindful use (r = 0.33). These results support the need to consider the relationship between self-regulation and smartphone use as it relates to learning.

Lockdown Fatigue and University Students: Exploring the Factors That Play Significant Roles in the Level of Lockdown Fatigue Among University Students in the Era of COVID-19

Background

Due to the COVID-19 global pandemic, the educational sector has undergone a series of changes which have affected both learners and students alike. As a result, the distortion of the students’ daily routine, isolation, social distancing and potential exposure to the COVID-19 virus changed almost all of the aspects of student life which has led to exhaustion of students, with both psychological and emotional challenges. Therefore, the main aim of this study is to determine the factors that have a significant impact on the level of lockdown fatigue among university students in the era of COVID-19.

Methods

A cross sectional was undertaken for this study. A questionnaire was designed and then shared electronically with the respondents of this study. The respondents were 819 students from tertiary institutions in Iraq. Some of the scales used in ranking the responses of the participants are the Lockdown Fatigue scale, Brief Resilience Scale and Coping Behaviours questionnaire. Data analysis was.

Results

Overall, the students had a high level of fatigue due to lockdown-measurement. Emptiness was one of the dominant feelings experienced by the students, along with concern for the safety and well-being of their own families. There was general agreement that students take a long time to return to normal routines after stressful events. The students also indicated that they cope with the lockdown through a variety of activities, ranging from making jokes about the situation to putting their faith in a higher power. Male student were less likely to suffer from lockdown-fatigue, however, studying in public university, being from urban areas, and studying in science field are the most significant factors that increase the level of lockdown. However, lower levels of lockdown fatigue were linked to significantly higher levels of personal resilience and coping abilities.

Conclusion

High level of lockdown fatigue among students is noticed, and several factors have been identified. Therefore, it is helpful for students to consistently work on reinforcing positive habits which would help them to build resilience when they are subjected to stressful conditions and scenarios.

Smartphones and Learning: An Extension of M-Learning or a Distinct Area of Inquiry

The smartphone has become an integral part of the education landscape. While there has been significant smartphone research in education under the guise of m-learning, the unique role of the device suggests that m-learning may not be an appropriate characterization. The purpose of this paper is to review the use of m-learning as a primary descriptor for smartphone- and learning-related research. In support of this goal, the paper reviews the definitions associated with m-learning, smartphones, and related technologies from the perspective of educational research. In addition, a review of author keywords of research on smartphones in education is used to provide context to the classification of the research. Finally, three theoretically guided smartphone programs are presented as evidence of the unique nature of smartphone and learning research. This review concludes with recommendations for the characterization of future research.

Smartphone Handwritten Circuits Solver Using Augmented Reality and Capsule Deep Networks for Engineering Education

Resolving circuit diagrams is a regular part of learning for school and university students from engineering backgrounds. Simulating circuits is usually done manually by creating circuit diagrams on circuit tools, which is a time-consuming and tedious process. We propose an innovative method of simulating circuits from hand-drawn diagrams using smartphones through an image recognition system. This method allows students to use their smartphones to capture images instead of creating circuit diagrams before simulation. Our contribution lies in building a circuit recognition system using a deep learning capsule networks algorithm. The developed system receives an image captured by a smartphone that undergoes preprocessing, region proposal, classification, and node detection to get a Netlist and exports it to a circuit simulator program for simulation. We aim to improve engineering education using smartphones by (1) achieving higher accuracy using less training data with capsule networks and (2) developing a comprehensive system that captures hand-drawn circuit diagrams and produces circuit simulation results. We use 400 samples per class and report an accuracy of 96% for stratified 5-fold cross-validation. Through testing, we identify the optimum distance for taking circuit images to be 10 to 20 cm. Our proposed model can identify components of different scales and rotations.