Faculty and Student Interaction in an Online Master’s Course: Survey and Content Analysis
Bibliographic record
Abstract
BACKGROUND: The provision of online educational courses has soared since the creation of the World Wide Web, with most universities offering some degree of distance-based programs. The social constructivist pedagogy is widely accepted as the framework to provide education, but it largely relies on the face-to-face presence of students and faculty to foster a learning environment. The concern with online courses is that this physical interaction is removed, and therefore learning may be diminished. OBJECTIVE: The Community of Inquiry (CoI) is a framework designed to support the educational experience of such courses. This study aims to examine the characteristics of the CoI across the whole of an entirely online master's course. METHODS: This research used a case study method, using a convergent parallel design to study the interactions described by the CoI model in an online master's program. The MSc program studied is a postgraduate medical degree for doctors or allied health professionals. Different data sources were used to corroborate this dataset including content analysis of both asynchronous and synchronous discussion forums. RESULTS: This study found that a CoI can be created within the different learning activities of the course. The discussion forums integral to online courses are a rich source of interaction, with the ability to promote social interaction, teaching presence, and cognitive learning. CONCLUSIONS: The results show that meaningful interaction between faculty and student can be achieved in online courses, which is important to ensure deep learning and reflection.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".