An investigation into the management of online teaching and learning spaces: A case study involving graduate research students
Bibliographic record
Abstract
This research evaluates the strategies implemented to support the research activities of postgraduate students pursuing online master’s programs in the University of the West Indies Open Campus, as well as the activities of their supervisors. The three main strategies employed were (1) the use of a web-based ‘teaching-learning space’ to facilitate asynchronous interaction between students and their supervisors; (2) the provision of a scheduling tool to facilitate the planning of one-on-one meetings via a synchronous web-conferencing tool; and (3) the organization of research seminars using the same web-conferencing tool. This research used Moore’s theory of transactional distance and social cognitive theoretical framework to guide the project. Moore’s model reemphasizes the need for stronger forms of communicating for online students, whereas the cognitive framework focuses on the need for social interaction among learner and teacher. Participants were graduate students (n = 34). All participants were required to complete a questionnaire online. Data were also collected from postings in discussion forums. Overall, notwithstanding limitations, the data shows there are benefits to be gained from conducting student research activities in an online environment.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".