Internet usage among undergraduate nursing students: A case study of a selected university in South Africa
Bibliographic record
Abstract
Background: Globally, the internet is becoming an increasingly indispensable tool in academic institutions and the workplace. Nursing students are required to use the computer and the internet to search for information and to use various software, for which computer and internet literacy are essential. Despite becoming an important tool for teaching and learning, literature reflects an under-utilization of the internet in academic and non-academic settings for a number of reasons. This article explores the general internet usage of undergraduate nursing students at a selected university in South Africa.Methods: A quantitative, non-experimental, exploratory descriptive design was used, with 115 undergraduate nursing students participating in the study. Data was collected using a questionnaire survey after obtaining ethical clearance from the university’s ethics committee and were analysed descriptively.Results: The findings revealed that the internet was used for various purposes including; academic (96.5%); communication (82.6%), pleasure (71.3%), and work-related activity (53.9%). Facebook (77.4%) was the most commonly used social network. Constraints encountered in using Barriers to the use of the internet include restriction of access to certain sites (62.6%), very slow internet connection (55.7%), little training on how to use internet facilities (38.3%), and a limited number of computers (37.4%).Conclusions: Contrary to other studies, this study shows that students do use the internet for a number of reasons, and recommend structured support on how to use if for academic purposes.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".