Bibliographic record
Abstract
This qualitative multi-method study investigated faculty member perspectives on e-learning policy, and its influence on their use of e-learning. The research was conducted at one medium sized comprehensive university in Ontario, Canada. Data were collected from interviews with 12 full-time faculty members, eight of whom had taught at least one online undergraduate university course. Data were also collected from institutional and government documents. Respondents noted e-learning increased flexibility and/or convenience with respect to both their engagement with students, and student engagement with course material. E-learning was identified positively for its ability to save time by some respondents, and negatively as being time intensive by others. Increased student and government demand for on-line courses, as well as the opportunity to use technology for instructional purposes, increased respondents’ use of e-learning. Additionally, the university’s pedagogical centre, which provided direct support to respondents, was considered key in supporting their transition to e-learning. Respondents were generally unable to identify specific university policy related to e-learning, and some noted the lack of specific policy had hampered e-learning course development in their departments. The documents reviewed tended to view e-learning in favourable terms, highlighting it as a response to changing political, economic, and societal conditions, and promoting it for its ability to reduce costs to the university, increase student enrolment, and provide more equitable access to university programs, particularly for under-represented groups such as new Canadians, Indigenous peoples, and first-generations students. Whereas government documents tended to focus on mandates (e.g. the intent to change the university system based on each university’s strengths), institutional documents focused on teaching, learning, and e-learning, both in response to government mandates, and in alignment with the University’s strategic direction. Collectively, the documents shared the respondents’ perceptions regarding flexibility, time, and demand. However, while government documents focused on issues of cost, changing conditions, enrolment and equitable access, institutional documents explained e-learning, the differences with face-to-face teaching and learning, and how best to integrate e-learning into practice.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".