Navigating Distance and Traditional Higher Education: Online faculty experiences
Bibliographic record
Abstract
The academic culture of higher educational institutions is characterized by specific pedagogical philosophies, assumptions about rewards and incentives, and values about how teaching is delivered. In many academic settings, however, the field of distance education has been viewed as holding marginal status. Consequently, the goal of this qualitative study was to explore faculty members’ experiences in a distance education, online university while simultaneously navigating within a traditional environment of higher education. A total of 28 faculty members participated in a threaded, asynchronous discussion board that resembled a focus group. Participants discussed perceptions about online teaching, working in an institution without a traditional tenure system, and the role of research in distance education. Findings indicated that online teaching is still regarded as less credible; however, participants also noted how this perception is gradually changing. Several benchmarks of legitimacy were identified for online universities to adopt in order to be viewed as credible. The issue of tenure still remains highly debated, although some faculty felt that tenure will be less crucial in the future. Finally, recommendations regarding attitudinal shifts within academic circles are described with particular attention to professional practice, program development, and policy decision-making in academia. Key words: distance education, online education, online faculty experiences, academia, tenure
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".