Evidence-Based Pedagogy for Values Outcomes in Capstone Experiences
Bibliographic record
Abstract
Undergraduate programs that focus on disciplinary knowledge and skills can reinforce pre-existing mindsets or ideologies that can lead to insufficient questioning of certain types of information (e.g., empirical data or model results) or insufficient valuing of certain types of information (e.g., Indigenous knowledge). One way to address this challenge is to include values-based learning and assessment strategies that empower students to better understand and engage with their complex and changing worlds. General Education (GenEd) Capstone Experiences (CE) often seek to instill such values, but scholarly analysis of the pedagogies and their effectiveness is limited, as is discussion on the inclusion of similar pedagogies in discipline-focused courses. This study addresses this research disparity by using a mixed methods approach to investigate student and faculty perceptions of the values integrated by a GenEd CE program and the pedagogies used to integrate those values. Results demonstrate that the integration of reflection and discussion pedagogies has the potential to influence a variety of values-based outcomes, including thoughtfulness, openness, and responsibility. Institutional leaders and CE instructors may integrate these pedagogies into their CEs, with mindful attention to the associated values that they seek to instill.
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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 | 0.092 | 0.262 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".