Flipping it online: re-imagining teaching searching for knowledge syntheses
Bibliographic record
Abstract
Introduction: This program description outlines our approach to re-developing our three-part series for graduate students on comprehensive searching for knowledge syntheses from in-person to online delivery using a flipped classroom model. The re-development coincided with our library's response to COVID-19. Description: This series followed a flipped classroom model where participants completed asynchronous modules built on Articulate Rise 360 before attending a synchronous session. Each week of content covered unique learning objectives. Pre- and post-class self-assessments were used to examine students' understanding of the materials. Outcomes: 152 unique participants registered for the series across two offerings in summer 2020. We observed high engagement with pre-work modules and active participation during synchronous sessions. Discussion: We found the flipped classroom approach to work well for our users in an online environment. Moving forward, we intend to continue with our re-developed online workshop series with minor modifications, in addition to in-person instruction.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.037 | 0.010 |
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".