Does OER Research-Based Learning Improve Performance: A Case Study from Students Enrolled in a Community College at City University of New York (CUNY)
Bibliographic record
Abstract
This study investigates the effectiveness of Open Education Resources (OER) and research-based learning. A quantitative analysis was conducted on students enrolled in Macroeconomic courses at a City University of New York (CUNY) community college in Spring 2018 and Spring 2019. Prior studies have shown the positive effects of conducting research in natural sciences. Yet, there is a lot to be inquired about regarding the impact of research-based learning on social sciences and the use of OER materials as a cheaper and more equitable alternative to commercial textbooks. Additionally, this study evaluates the academic effectiveness of research-based learning through assessment scores through a new indicator, the growth mindset profile. Findings should be used to assess critically research-based learning applications incorporated with OER materials and open pedagogy, as well as to consider the duration, wide application throughout the program rather than isolated courses, and design of course assignments and research projects to engage students actively and effectively.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".