Environmental scan and evaluation of best practices for online systematic review resources
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Online training for systematic review methodology is an attractive option due to flexibility and limited availability of in-person instruction. Librarians often direct new reviewers to these online resources, so they should be knowledgeable about the variety of available resources. The objective for this project was to conduct an environmental scan of online systematic review training resources and evaluate those identified resources. METHODS: The authors systematically searched for electronic learning resources pertaining to systematic review methods. After screening for inclusion, we collected data about characteristics of training resources and assigned scores in the domains of (1) content, (2) design, (3) interactivity, and (4) usability by applying a previously published evaluation rubric for online instruction modules. We described the characteristics and scores for each training resource and compared performance across the domains. RESULTS: Twenty training resources were evaluated. Average overall score of online instructional resources was 61%. Online courses (n=7) averaged 73%, web modules (n=5) 64%, and videos (n=8) 48%. The top 5 highest scoring resources were in course or web module format, featured high interactivity, and required a longer (>5hrs) time commitment from users. CONCLUSION: This study revealed that resources include appropriate content but are less likely to adhere to principles of online training design and interactivity. Awareness of these resources will allow librarians to make informed recommendations for training based on patrons' needs. Future online systematic review training resources should use established best practices for e-learning to provide high-quality resources, regardless of format or user time commitment.
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.
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 | 0.183 | 0.286 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it