A pilot investigation comparing instructional packages for MTS training: "Manual alone" vs. "manual-plus-computer-aided personalized system of instruction."
Bibliographic record
Abstract
Matching-to-sample (MTS) training consists of presenting a stimulus as a sample followed by stimuli called comparisons from which a subject makes a choice. This study presents results of a pilot investigation comparing two packages for teach- ing university students to conduct MTS training. Two groups - control and experimental - with 2 participants in each group were used. Accuracy in conducting MTS training was assessed during baseline and post-training. During training the control group received a manual, and the experimental group received both the manual and computer-aided personalized system of instruction or CAPSI. Baseline and post-training combined scores for control and experimental groups were 72.5% and 100%, and 72.7% and 95%, respectively. Results showed that the manual and the manual-plus-CAPSI packages produced similar effects in delivering knowledge in MTS training. We suggest that future studies using a larger sample size are neces- sary. In addition, we suggest that it is necessary to test new versions of the manual and the interaction of CAPSI with other components, such as demonstration videos.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".