Examining an Interdisciplinary Experiential Learning Program for Doctoral Students
Bibliographic record
Abstract
Educators, researchers, and institutions have long recognized the value of experiential learning as a way of fostering students’ ongoing learning and skill development. In recent years, experiential learning has gained increased traction in higher education institutions, as there is recognized need for graduates to engage in and actively reflect on lived experiences in various disciplines. Yet, much of the research in graduate-level experiential learning focuses on discipline-specific experiential learning opportunities, often within the context of a single graduate program where students’ career outcomes and program pathways are narrowly defined. Through qualitative analysis of interview, focus group, and program data collected as part of a collaborative evaluation, we respond to a gap in existing research to examine the diverse perspectives of doctoral students engaged in an interdisciplinary experiential learning program. The study’s findings contribute to a more robust understanding of the potential for experiential learning as an interdisciplinary practice, with direct examples of how doctoral students and higher education institutions are moving this work forward in this context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".