WHAT RESEARCH AND EVALUATION METHODS HAVE BEEN USED TO STUDY COGNITIVE AND NON-COGNITIVE FACTORS IN STUDENT TRANSITION BETWEEN HIGH SCHOOL AND FIRST YEAR POST-SECONDARY EDUCATION?
Bibliographic record
Abstract
Students undergoing post-secondary transition are impacted by cognitive and non-cognitive factors. This paper will review available literature on the factors, which affect students during the post-secondary transition and perform a comparative analysis to compare and summarize what research and evaluation methods are used in these studies. The research methodologies described in each study are scrutinized, and details in the methodology used are tabulated and compared. Non-cognitive studies generally prefer medium-sized (N=100 to 500) samples, assessed with numerically-scored pre-established questionnaires, whereas cognitive studies do not show a specific sample size or assessment preferences. However, cognitive studies are shown to employ a wide range of data analysis techniques, whereas non-cognitive studies heavily prefer statistical analysis only. A proposed framework is extracted to describe the preferred research methodologies for investigations into cognitive and non-cognitive factors.
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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 | 0.202 | 0.319 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.018 | 0.021 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".