Measuring the Impact of an Open Educational Resource and Library e-Resource Adoption Program Using the COUP Framework
Bibliographic record
Abstract
Grant programs that foster the use of open educational resources (OER) significantly reduce undergraduate student spending on textbooks per semester. The Zero-Cost Course Materials (ZCCM) grant program at the University of California, Merced (UC Merced), eliminated text costs and ensured access to course materials by replacing required commercial materials with OER and library licensed e-resources. The present study applies the COUP framework (cost, outcomes, usage, and perceptions) to evaluate the ZCCM program. The ZCCM program resulted in student cost savings and did not negatively impact student outcomes. Students in ZCCM courses demonstrated higher rates of course completion than students enrolled in previous sections. For the outcomes of final course grade, passing with a C− or better, and number of credit hours enrolled in, findings were comparable between the cohorts. Student usage and perception of course materials were gathered using a survey. Though students reported favorable views of zero-cost materials, they reported using them less frequently than commercial texts. This research contributes to a growing body of literature that confirms beneficial cost savings for students using zero-cost materials without jeopardizing students’ success.
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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.003 |
| 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".