This paper reports on a study conducted by college students at a private university in Saudi Arabia. The research examines the online learning experiences of their peers during the first wave of the coronavirus covid-19 pandemic. Many assumptions exist about online learning and its impact in higher education, but these are mainly based on the views of instructors and leaders of institutions. Hitherto, the perspectives of those meant to be beneficiaries of digital technologies have been given little consideration even though students use cyberspace for academic work and beyond. To address this silence, a group of student-researchers conducted a case study to examine students' views of cyberlearning. The research used a qualitative analysis approach to address the following questions: (1) What were the cyberlearning experiences of students at our university during the first two semesters of lockdown? (2) What are students' understandings of cyberlearning? (3) What are their aspirations for cyberlearning? Data were collected through an online survey administered to the entire student body at the university. Responses were received from 3574 students. The data were analysed using thematic analysis. The research participants perceive cyberlearning to be the same as online learning and see it as a viable educational option. They reported that the dominant mode of instruction in online classrooms is instructors delivering information. Respondents also highlighted the need for improved online teaching pedagogies and curbing academic dishonesty in online classrooms. Students' aspirations for cyberlearning were clearly articulated. Respondents suggested that increasing online learning opportunities would have a positive impact on their academic progress. Through this research students demonstrate a sense of agency and provide opportunities for equity strategies at their university. The results show that serious attempts should be made to include cyberlearning as part of everyday educational activity in an attempt to increase student engagement.
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http://dx.doi.org/10.1007/s10639-022-11564-w | DOI Listing |
JMIR Public Health Surveill
January 2025
School of Arts and Media, Wuhan College, Wuhan, China.
Background: The global aging population and rapid development of digital technology have made health management among older adults an urgent public health issue. The complexity of online health information often leads to psychological challenges, such as cyberchondria, exacerbating health information avoidance behaviors. These behaviors hinder effective health management; yet, little research examines their mechanisms or intervention strategies.
View Article and Find Full Text PDFJ Strength Cond Res
February 2025
Sports Medicine and Movement Laboratory, School of Kinesiology, Auburn University, Auburn Alabama.
Bordelon, NM, Agee, TW, Wasserberger, KW, Downs-Talmage, JL, Everhart, KM, and Oliver, GD. Field-testing measures related to youth baseball hitting performance. J Strength Cond Res 39(2): 210-216, 2025-The purpose of the study was to determine the relationship between field tests and youth hitting performance (batted-ball velocity).
View Article and Find Full Text PDFActa Bioeng Biomech
June 2024
3Med Coach, Non-public Continuing Education Institution, Kraków, Poland.
: The aim of this work was to assess the effect of a conservative therapeutic intervention on the changes in the foot load distribution in people with femoroacetabular impingement (FAI) syndrome practising long-distance running. : The study involved 44 men, aged 30 to 50 years, practising long-distance running. Two rounds of tests were conducted in the Laboratory of Biokinetics of the AWF in Kraków.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Statistics, University of Oxford, St Giles', Oxford, OX1 3LB, United Kingdom.
Motivation: Machine learning-based scoring functions (MLBSFs) have been found to exhibit inconsistent performance on different benchmarks and be prone to learning dataset bias. For the field to develop MLBSFs that learn a generalisable understanding of physics, a more rigorous understanding of how they perform is required.
Results: In this work, we compared the performance of a diverse set of popular MLBSFs (RFScore, SIGN, OnionNet-2, Pafnucy, and PointVS) to our proposed baseline models that can only learn dataset biases on a range of benchmarks.
PLoS One
January 2025
SSL Lab, Dept. of CSE, Islamic University of Technology, Dhaka, Bangladesh.
Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation. However, categorizing raw recipes found online into appropriate food genres can be challenging due to a lack of adequate labeled data. In this study, we present a dataset named the "Assorted, Archetypal, and Annotated Two Million Extended (3A2M+) Cooking Recipe Dataset" that contains two million culinary recipes labeled in respective categories with extended named entities extracted from recipe descriptions.
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