Stories from Students in Their First Semester of Distance Learning
Bibliographic record
Abstract
Online and distance learning is becoming increasingly common. Some would say it has quickly become the preferred or 'new normal' mode of study throughout the world. However, surprisingly little is known about what actually happens to first year distance students once they have enrolled in tertiary institutions; what motivates them and how they actually experience the transition to formal study by distance. This gap in the literature presents a challenge for distance education providers who worldwide are coming under increasing scrutiny in light of poor retention, progression and completion rates. Against this backdrop, the purpose of the current study was to gather insights and seek a deeper understanding from first-time distance learners about the nature of their experiences. The study was framed around Design-based Research involving a mixed method approach over three phases. This paper focuses on the third phase, which was the major component of the study. The lived experiences of 20 first-time distance learners were gathered, in their own words, using weekly video diaries for data collection. Over 22 hours of video data was transcribed and thematically analysed, from which five themes have been reported. The discussion reflects on the ways that video diaries have provided a unique insight around the complexities of distance learning — as distinct from campus-based learning. The paper concludes that the new digital learning environment made possible by the Internet offers a number of exciting possibilities for distance learners; however, more needs to be done by institutions to change the ‘lone wolf’ preconception of distance education and to avoid the ‘goulash approach’ to supporting distance learners. The lives of first-time distance learners are not black and white; they are complex shades of grey and this needs to be taken in to account when designing appropriate learning experiences and supports to ensure student success.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".