The spread of COVID-19 presents an opportunity for many educational institutions to implement distance learning and ensure the provision of educational resources and services, secure income and revenues, and contribute to the control and prevention of the coronavirus. This study was conducted to investigate the impact of demographic characteristics on academic performance. Students’ grades and grade point averages (GPA) were collected from the Admission and Registration Unit, Al Ain University in Al Ain, United Arab Emirates. The data were used to measure academic performance in face-to-face (F2F) learning and distance learning (DL) implemented by the university to prevent the spread of COVID-19. Statistical analysis including the Mann-Whitney test, Spearman’s rho test, and a regression test were used to answer research questions and verify hypotheses. Students demonstrated better academic performance in DL than F2F learning. It was found that the number of weak students in F2F learning dropped sharply by more than 11% in DL. Demographic characteristics demonstrated a significant impact on students’ academic performance and predicted at least 7.4% variation in F2F learning and DL. Findings of the study support the model developed by Tinto (1975) which proposed the impact of student’s attributes, experiences, and family backgrounds on academic performance. The findings suggest non-DL institutions should continue offering DL side-by-side with F2F learning programs.

This study examined the similarities and differences in the processes and facilities for distance education at National Open University of Nigeria (NOUN), a single-mode distance learning institution, and Obafemi Awolowo University (OAU), Ile-Ife, a dual-mode distance learning institution. The study adopted a case study research design, with a population of administrators/facilitators and distance learning students at both NOUN and OAU. The sample for the study consisted of 38 key informants (30 administrators/facilitators and 8 students) selected using a purposive sampling technique. All the administrators/facilitators responded to a key informant questionnaire; 8 of the administrators/facilitators and all 8 students were also interviewed. The 16 interviewees were selected based on gender, institution, educational role, and mode of distance learning. The collected data were analysed using tabular juxtaposition and phenomenological analysis techniques. Results showed that similarities in the operational structures at NOUN and OAU included the use of blended learning approaches. Differences in operations included compulsory tutorial attendance at OAU and the deployment of part-time and quasi part-time facilitators at NOUN and OAU, respectively. The study recommended an increase in the use of information and communications technology (ICT).

This paper explores learners’ awareness of and satisfaction with the e-services that an open university provides its learners through its Website. The paper further highlights the influence of age, gender, and education levels on learners’ awareness and satisfaction levels. A case-study approach was adopted and an online survey was used to collect data from learners in various programs of study at Uttarakhand Open University, India. The questionnaire measured the awareness levels of learners regarding 15 frequently used e-services and their satisfaction levels with the 12 most frequently used e-services that the university offers. Results show that gender, age, and education level have a significant influence on the awareness and satisfaction level of the participants. When maturity level and education level of the participants increased, they are more aware of the e-services provided by the University. In some cases, up to 58% of users were unaware of the university’s e-services, and a large number of respondents were either dissatisfied with or undecided regarding the university’s e-services. Results indicate that infrastructure is required for learners’ optimal use of information and communication technology and the e-services that the university offers, including the provision of Internet connectivity at all of the university’s learning support centers.

Computer programming MOOCs attract people who have different motivations. Previous studies have hypothesized that the motivation declared before starting the course can be an important predictor of distinctive dropout rates. The aim of this study was to outline the main motivation clusters of participants in a computer programming MOOC, and to compare how these clusters differed in terms of intention to complete and actual completion rate. The sample consisted of 1,181 respondents to the pre-course questionnaire in the Introduction to Programming MOOC. A validated motivation scale, based on expectancy-value theory and k-means cluster analysis, was used to form the groups. The four identified clusters were named as Opportunity motivated (27.7%), Over-motivated (28.6%), Success motivated (19.6%) and Interest motivated (24.0%). Comparison tests and chi-square test were used to describe the differences among the clusters. There were statistically significant differences among clusters in self-evaluated probability of completion. Also, significant differences emerged among three clusters in terms of percentages of respondents who completed the MOOC. Interestingly, the completion rate was the lowest in the Over-motivated cluster. A statistically significant higher ratio of completers to non-completers was found in the Opportunity motivated, Success motivated, and Interest motivated clusters. Our findings can be useful for MOOC instructors, as a better vision of participants’ motivational profiles at the beginning of the MOOC might help to inform the MOOC design to better support different needs, potentially resulting in lower dropout rates.

With rising societal interest in the subject areas of science, technology, engineering, art and mathematics (STEAM), a micro:bit robotics course with an online group study (OGS) system was designed to foster student learning anytime and anywhere. OGS enables the development of a learning environment that combines real-world and digital-world resources, and can enhance the effectiveness of learning among students from a remote area. In this pre- and post-test experiment design, we studied 22 (8 males and 14 females) 5th grade students from a remote area of Taiwan. A t test performed before and after the robotics course showed a positive increase in students’ proportional reasoning, probabilistic reasoning, and ability to analyze a problem. Results also revealed a gender difference in the association between students’ logical reasoning and problem-solving ability.

Post-Pandemic Future: Implications for Privacy The time has come for privacy to expand beyond compliance to include determinations about what should be protected and consideration of ethical implications, balancing institutional priorities with the rights of individuals. The intersection of issues including COVID-19, student success, and the emergence of the chief privacy officer (CPO) role highlights […]

The study examines the effectiveness of adaptive learning technology as a supplemental component in online precalculus courses using data from vendor software and a public university system in the southeastern United States. Outcomes examined include final exam score and course completion with a passing grade. The results highlight that not all students utilize the technology […]

This article presents a work-based learning and research approach to professional postgraduate education specifically in the case of Higher Degree by Research (HDR) programs. It highlights a prototype of the Cohort-based Advisory Team (CAT) model as a useful strategy. The authors propose that a design thinking approach that empathises with the student experience as the […]

The University of Southern Queensland’s online study environment continues to grow with over 16,000 students studying online. Pre-Covid-19, online enrolments typically represent around 67% of all students studying at USQ. This article usefully analyses quantitative data in order to evaluate the effectiveness of the pilot of an online peer-assisted learning program for first-year Law students. […]