A systematic review of research on online teaching and learning from 2009 to 2018

F Martin, T Sun, CD Westine - Computers & education, 2020 - Elsevier
Systematic reviews were conducted in the nineties and early 2000's on online learning
research. However, there is no review examining the broader aspect of research themes in …

Persistence and dropout in higher online education: Review and categorization of factors

UU Shaikh, Z Asif - Frontiers in Psychology, 2022 - frontiersin.org
Online learning is becoming more popular with the maturity of social and educational
technologies. In the COVID-19 era, it has become one of the most utilized ways to continue …

The role of demographics in online learning; A decision tree based approach

S Rizvi, B Rienties, SA Khoja - Computers & Education, 2019 - Elsevier
Research has shown online learners' performance to have a strong association with their
demographic characteristics, such as regional belonging, socio-economic standing …

On-campus students taking online courses: Factors associated with unsuccessful course completion

CA Murphy, JC Stewart - The Internet and Higher Education, 2017 - Elsevier
On-campus students are requesting online course options, and campuses are increasingly
providing online sections of core courses, with a common offering involving online science …

From emergency to sustainable online learning: Changes and disparities in undergraduate course grades and experiences in the context of COVID-19

L Alon, SY Sung, JY Cho, RF Kizilcec - Computers & Education, 2023 - Elsevier
The abrupt transition to online instruction has created an opportunity to improve models of
online instruction. We investigated changes in student grades and experiences during …

The online STEM classroom—Who succeeds? An exploration of the impact of ethnicity, gender, and non-traditional student characteristics in the community college …

C Wladis, KM Conway… - Community College …, 2015 - journals.sagepub.com
Objective: This study analyzes how ethnicity, gender, and non-traditional student
characteristics relate to differential online versus face-to-face outcomes in science …

Self-regulation in e-learning environment

D Bylieva, JC Hong, V Lobatyuk, T Nam - Education Sciences, 2021 - mdpi.com
The COVID-19 pandemic has contributed to the accelerated spread of e-learning around the
world. In e-learning, self-regulation becomes more relevant than ever. Reducing the …

Widening access to applied machine learning with tinyml

VJ Reddi, B Plancher, S Kennedy, L Moroney… - arxiv preprint arxiv …, 2021 - arxiv.org
Broadening access to both computational and educational resources is critical to diffusing
machine-learning (ML) innovation. However, today, most ML resources and experts are …

Ouroboros: early identification of at-risk students without models based on legacy data

M Hlosta, Z Zdrahal, J Zendulka - Proceedings of the seventh …, 2017 - dl.acm.org
This paper focuses on the problem of identifying students, who are at risk of failing their
course. The presented method proposes a solution in the absence of data from previous …

Understanding consumers' purchase intention towards online paid courses

Y Chen, D Ding, L Meng, X Li… - Information …, 2023 - journals.sagepub.com
With the unprecedented development of information and communication technologies,
online learning is increasingly seen as an important channel for knowledge acquisition …