A comparison of administrator and faculty self-report and knowledge of distance education, related intellectual property laws and policy, and tenets of academic freedom
Bibliographic record
Abstract
Distance education is an emerging force in higher education that is creating new opportunities and added challenges. The purpose of this study was to identify and compare what university administrators and faculty know about issues that surround a debate about ownership of intellectual products created for distance education including technologies used in distance education and the law, university policies, and tenets of academic freedom that are supposed to stimulate intellectual creativity. An Internet-based survey was used to gather data from university faculty and administrators at four southeastern research universities in the United States. Results indicated that respondents were almost universally familiar with distance education, and that more than one-third create teaching materials expressly for use in distance education. Further, results indicated that more than two-thirds of participants were aware of university intellectual property ownership policies, but less than one-quarter reported knowing details of those policies. Although participants agreed that protections provided by U. S. Copyright Law are important, more than one-third of faculty and one-quarter of administrators admitted that their knowledge of the law was, at best, vague. Although a wide majority of respondents reported familiarity with academic freedom, when the accuracy and depth of their knowledge was examined, it seems their understanding was largely impressionistic. Although few unexpected differences were identified, administrators were shown to rely more heavily than faculty counterparts on universities to stay informed about the issues of interest in this study. Results from the study suggest that if leaders are needed to help realize the opportunities and meet the challenges created by emerging technologies and distance education, universities will need to take initiative to develop expertise among faculty and administrators.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".