COVID-19 Pandemic Impact on E-Learning Adoption and Its Utilization at Higher Education: A Comparative Analysis of Institutions and Students' Perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
COVID-19 has forced Somali universities to implement e-learning systems to ensure education continuity. This study identifies the components that drive the effectiveness of e-learning platforms within Somali private universities by utilizing insights from student feedback. To accomplish this, the study employed the renowned DeLone and McLean's Information Systems Success (D&M IS) model, serving as a framework for evaluating and validating the factors pertaining to the e-learning platform's success. A questionnaire has been employed with the aim of gathering data from students to satisfy the research's objectives. In this study, 867 respondents were collected and analyzed using a structural equation model (SEM). Additionally, the results showed that Service Quality (SRQ), System Use (SU), System Quality (SQ), and User Satisfaction (US) significantly influenced Net Benefit (NB) of the e-learning platforms. However, there was no correlation between Information Quality (IQ) and User Satisfaction (US). This study provides useful insight to guide policy decisions and support e-learning. However, the study is limited since it is narrowly focused on Somalia, which limits its generalizability to other developing countries.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it