MLA Research Training Institute (RTI) 2018 and 2019: participant research confidence and program effectiveness
Bibliographic record
Abstract
Objective: The article reports on an assessment of the effectiveness of the MLA Research Training Institute (RTI) for the years 2018 and 2019. The RTI is a year-long continuing education research methods training and support program for health sciences librarians. The study focuses on assessing RTI participants' research confidence after program completion and compares these results with their perceptions of workshop/program performance and learning outcomes. In addition, the authors discuss how the findings were applied to inform and improve the program. Methods: The study used a 26-item questionnaire, RTI Research Confidence Questionnaire, to gather information on participants' self-reported research confidence before the workshop, immediately after the workshop, and one year after the workshop to determine statistically significant differences. Differences in research confidence were identified by using three nonparametric statistical tests. Additional workshop and program surveys were used to corroborate the research confidence findings. Results: Post-workshop and one-year-after-workshop research confidence ratings were significantly higher than pre-workshop levels for years 1 and 2. A comparison of median ratings between years 1 and 2 showed significant increases in research confidence for nine items in year 2. Participants' positive perceptions of workshop/program effectiveness and learning outcomes corroborated these findings. Conclusion: Overall assessment findings indicated that RTI training helped participants understand, use, and apply research skills to conduct research. Findings also revealed that participants' heightened research confidence persisted at least 12 months postintervention. The RTI Research Confidence Questionnaire proved effective for rigorously assessing and improving the RTI program. This study enhances the currently limited evidence on evidence-based approaches for assessing and improving research instruction for librarians.
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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 | 0.053 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".