The Impact of Professional Development on K–12 Teacher Awareness, Use, and Perceptions of OER
Bibliographic record
Abstract
This paper reports the findings from cycles three and four in a longitudinal design-based research (DBR) study with K–12 teachers to evaluate their gains in awareness, use, and perceptions about open educational resources (OER) in general and after engaging with the Pathways Project (PP), a repository of 900 world language activities. Two groups of teachers participated in distributed learning with different engagement levels to apply the 5Rs of OER (i.e., retain, reuse, revise, remix, and redistribute), specifically using OER from the PP. The Pathways subscribers (n = 23) attended webinars and received monthly newsletters throughout the project period. A smaller group, referred to as the Pathways training cohort (n = 16), participated in a four-month cohort including a synchronous workshop, monthly synchronous meetings, and asynchronous tasks. The study was conducted in the Mountain West region of the United States, where access to quality teaching materials varies across rural and urban districts, and professional development (PD) opportunities are lacking. The findings revealed that the training cohort self-reported statistically significant increases in awareness of all 5Rs, and increased frequency of revising and remixing OER; their belief in the effectiveness of OER for learning also increased. Conversely, while the subscribers group did show some gains in awareness, use, and perceived value of OER, none of these were statistically significant. These findings suggested that K–12 teachers valued OER but require strategic, long-term PD to achieve gains in awareness, use, and perceived value of OER. This study responded to the challenge of sustaining open pedagogy, particularly for an under-studied K–12 population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".