Impacts of interdisciplinary project-based learning on high school students' future-readiness: a mixed methods study
Bibliographic record
Abstract
Project-based learning (PBL) is an emerging pedagogy which shows promise in improving student outcomes but has not been widely studied. An explanatory sequential mixed methods study was conducted in rural Manitoba which examined participant-reported future readiness across several purposes of education to better understand reported differences in future readiness between an education based on traditional pedagogy and one based on PBL. The participants’ current life situation was considered as a moderating variable to determine if it impacted what facets of each pedagogy participants believed was most helpful. Participants from the group which received primarily traditional pedagogy were first surveyed in January of the year after they graduated, and then select participants of this group were interviewed roughly four months later. A year later a group of students who received primarily PBL went through the same process of surveys and interviews. 18 participants were surveyed from each group, and from those who were surveyed 8 were interviewed from each group. Survey results indicated that students who attended university or were taking a gap year had nearly identical future readiness scores, while students going to college or directly into the workforce with no further plans for education saw an increase in future readiness from the PBL pedagogy. The interviews indicated that while gap-year and university attending students shared concerns about readiness for high stakes testing, the collaborative and more independent nature of PBL was found to increase future readiness across all groups.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".