Open Educational Resources and Student Course Outcomes: A Multilevel Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p class="3">Salt Lake Community College (SLCC) is Utah’s largest open enrollment college, and as an institution, is concerned about the expense associated with attaining a degree. All students face challenges in paying for their education, but SLCC students tend to have fewer resources to dedicate to school than students at other institutions in the state. While faculty and administrators have little control over the rising cost of tuition, they are able to offer students open educational resources (OER) to cut down on textbook costs. Salt Lake Community College’s OER initiative was implemented in Summer 2014, and has since expanded to include 125 sections in Spring 2016. We examine OER’s impact on three measures of student success: course grade, likelihood of passing, and likelihood of withdrawing. We use a multilevel modeling (MLM) approach in order to control for student, instructor, and course effects, and found no difference between courses using OER and traditional textbooks for continuing students. For new students, there is evidence that OER increases average grade. However, student-level differences such as demographic background and educational experience have a far greater impact on course grade and likelihood of passing or withdrawing than an instructor’s use of an OER text. Future research should focus on longer-term impacts of OER on retention, completion, and transfer.</p>
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.
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 | 0.007 | 0.003 |
| 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 | 0.001 |
| Open science | 0.006 | 0.006 |
| 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 it