Stop, Drop, and Pivot: An Action Researcher's Lived Experience through the COVID-19 Interruption
Bibliographic record
Abstract
This article chronicles the experience of an action researcher who was conducting a study in a post-secondary setting when COVID-19 swept across the globe and interrupted the research. The researcher set out to understand the aspects that promote and increase student investment in the classroom, and what she could do to positively impact student investment. This was accomplished through a three-phase action research study that was interrupted by COVID-19. The onset of the COVID-19 pandemic necessitated a pivot in the setting of the study and the last phase of the action research plan. The purpose of this article is to focus on the researcher’s perspective as a co-participant in the study while examining the changes brought about by the pandemic, and to address the implications of the findings and directions for future research. Of the three data sources in the study, the personal reflection journal of the researcher and co-participant feature heavily in expressing the lived experience of the researcher.
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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 | 0.037 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.045 | 0.057 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.006 | 0.021 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".