Researcher‐Supported Professional Learning and Development for Instructors in Adult L2 Programs: Factors Leading to Ongoing Communities of Practice
Bibliographic record
Abstract
Abstract We describe a longitudinal (5‐year) researcher‐supported initiative designed to strengthen the research–practice link (RPL) and serve as an effective form of situated professional learning and development (PLD) in adult second language programs. We facilitated the formation of and supported 9 professional reading groups of 6–12 instructors (N= 76). The groups met monthly to discuss peer‐reviewed journal articles to address shared PLD needs. Using retrodictive qualitative modeling, we traced the underlying factors in our RPL initiative that contributed to the rise of ongoing autonomous communities of practice in which instructors continued to engage in monthly cycles of implementing and adapting research knowledge and co‐constructed knowledge and practices gleaned from their reading and group discussions of peer‐reviewed articles. Data included participants’ responses to questionnaires, audio recordings of focus group interviews and reading group discussions, and researchers’ field notes. The results indicated that different types of communities of practice emerged over time through complex dynamic interactions between multiple factors in the RPL initiative (e.g., researchers, practitioners, and institutional and environmental forces). We discuss how researchers can strengthen the RPL by fostering the development of communities of practice that combine both research and practical knowledge to improve and create new educational practices.
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 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 | 0.055 | 0.113 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".