Capstone Experience Purposes
Bibliographic record
Abstract
Capstone experiences (CEs) serve a variety of purposes in higher education as opportunities to apply academic skills, explore post-graduate life and employment, and achieve a meaningful undergraduate event. This study investigated the purposes of CEs through a content analysis of institutional course syllabi/course outlines/module outlines and catalog/calendar descriptions at five institutions of higher education: a large public research university in Canada, a large public teaching university in the United Kingdom (UK), a college of a large public research university in the United States (US), and two medium-sized private liberal arts universities in the US. Using the CE purposes found in a review of scholarly literature as a research guide, the authors analyzed 84 institutional documents. CE purposes that appeared in the sample at lower percentages when compared with published studies included oral communication, a coherent academic experience, preparation for graduate school, preparation for life after college, and civic engagement/service learning. Implications for practice include the need for instructors and administrators to consider revising CE documents to better reflect the content and goals of the courses and to address the requirements of other audiences (e.g., program reviewers, accreditation evaluators). Moreover, the results of this study may assist educators in considering reasons for omitting explicit purposes from CE documents and/or justifying the inclusion of previously omitted purposes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.007 |
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".