The Challenges Distance Education Students Experience during Their Education Degree Program in the Faculty of Education at the University of Namibia
Bibliographic record
Abstract
The main purpose of this study was to identify the challenges distance education students experience during their education degree studies. The specific objectives studied included the following: to investigate the technical and technology limitations, limited interactivity between lecturers and students and among distance education students, and lack of support from administrative staff. The research design employed in this study was the survey research design. The distance education students were asked to complete an online survey to determine their experiences doing their studies on a distance mode. The target population for this study included all distance education students (1675) who are enrolled at the Centre for Open, Distance and eLearning (CODEL) at the University of Namibia in 2020. The questionnaire instrument was administered via google form, 354 responses were received in spreadsheet formats, and chats generated from the responses, the Statistical Package of the Social Sciences (SPSS) file, the descriptive and reliability statistics for all the variables. Based on the findings of this study, this study concludes that the University of Namibia needs to improve slow internet speeds, limited internet access, lecturer student interaction, collaboration between distance education students, lack of computers, among others. Some of the recommendations made by this study include: increased funding in ICT infrastructure for distance education students, better training for lecturers on how to deliver pedagogy and the CODeL administrative staff to better support distance education students.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".