Instructor immediacy strategies to facilitate group work in online graduate study
Bibliographic record
Abstract
<span>An increasing number of online graduate study programs require students to participate in collaborative work projects. And yet, educational research examining instructional strategies that facilitate learning in small groups online is limited. This article describes findings from a qualitative research project that investigated instructor immediacy at different stages of group development. The research was framed from a constructivist theoretical perspective and a descriptive research design. Participants were health care practitioners from two WebCT online graduate study programs. Data sources included four focus groups and twenty individual audio recorded transcribed interviews. The data was collected in person over a three year period, analysed for themes by two researchers, and confirmed with participants through ongoing member checking. Instructional immediacy strategies that students believed facilitated meaningful learning in small groups are presented in the three overarching stages of first, beginning/ engagement; second, middle/ encouragement; and third, ending/ closure. Findings suggested that, in the beginning/ engagement stage, learners valued knowing their instructors were available "if you need me" and that it was "safe" to contact them. In the middle/ encouragement stage, they appreciated personal help with networking and managing conflict, particularly in relation to participation and marking and they valued private feedback. And, in the ending/ closing stage, they needed opportunities to debrief and reflect.</span>
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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 | 0.013 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".