Design and Validation of the College Readiness Test (CRT) for Filipino K to 12 Graduates
Bibliographic record
Abstract
Designing and validating a college readiness test addresses the absence of standardized Philippine-based College Readiness Test (CRT) congruent with the College Readiness Standards (CRS) set by the Philippine Commission on Higher Education (CHED). It also resolves the varied and arbitrary indices used by Higher Education Institutions (HEIs) to measure the preparedness of K to 12 Filipino graduates to enter college. In this regard, this study establishes the validity and reliability of the CRT to measure the combination of knowledge, skills, and reflective thinking necessary for the K to 12 graduates to be admitted and to succeed without remediation in the General Education courses in HEIs. Using multi-stage sampling in a select province of the Philippines and with due consideration of the district, type of school, and academic tracks offered in senior high school, the study has generated that the 200-item CRT has desirable difficulty index (65.64), reasonably good discrimination index (0.22), and large functioning distractors (68.91% distractor efficiency). Notably, there is a significant positive relationship between discrimination and difficulty indices as well as the distractor efficiency and difficulty index of the CRT items. Also, the CRT is reliable as it possesses inter-item consistency (r=0.796). Thus, it is a valid and reliable instrument to measure the college readiness of Filipino K to 12 graduates with its features of being contextualized, gender-fair, and criterion-referenced.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".