Faculty Survey on OER: Perceptions, Behaviors, and Implications for Library Practice
Bibliographic record
Abstract
INTRODUCTION The Mary Couts Burnett Library at Texas Christian University (TCU) seeks to learn more about university faculty members’ perceptions and behaviors related to open educational resources (OER), and to identify one or more initiatives to increase adoption of OER at the university. METHODS The researchers sent a survey to all university faculty using Qualtrics™, and 104 persons responded. The survey used a combination of multiple-choice and free-text questions, and covered OER adoption and creation by faculty members, their perceptions of OER, and recommendations related to possible initiatives to increase OER interest. RESULTS Among respondents, almost half used OER either currently or in the past, while a fifth created their own OER. When comparing OER to traditional textbooks in terms of being scholarly, the majority indicated that OER and traditional textbooks were about the same level, but a quarter of faculty indicated that traditional textbooks were more scholarly. When asked about initiatives the library could pursue to increase faculty OER creation, the leading responses included financial support of faculty using OER, along with training opportunities. DISCUSSION The researchers were pleased to see that many faculty have used OER either currently or in the past, and that many had positive views surrounding OER. The researchers now have data that support the establishment of OER initiatives. CONCLUSION The survey informs the TCU Library and academic libraries in general. Two initiatives that libraries should consider are establishing an OER training program for faculty and developing a grant program to support faculty members who are adopting or creating OER. Libraries should collaborate with other units on campus such as the center for teaching excellence or the faculty senate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.014 |
| 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; both teacher heads agree on what is shown here.
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".