Organizational Complexities of Experiential Education: Institutionalization and Logic Work in Higher Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Universities continue to experience pressure to prepare work-ready graduates. In Ontario, this has recently taken the form of new provincial funding metrics which include experiential education. This places more formal pressure on all provincial universities to foster experiential education. Purpose: This study focuses on the organizational dynamics within a selected university as it developed an Experiential Education Certificate (EEC). Methodology/Approach: Using a qualitative approach, this case study relies on multiple methods. Content analysis was used to analyze textual data that framed the EEC. Semi-structured interviews ( n = 12) with institutional actors were used to analyze how experiential education is framed administratively and practiced at the technical level of the university. Findings/Conclusions: Although the EEC reflected a management logic, it was not fully aligned with the academic logic of ground-level technical actors (e.g., professors). Institutionalizing experiential education has implications for multiple logics at play within universities and thus requires more “logic work” of those working within. Implications: This exploratory study lays the groundwork for further theorizing experiential education from an organizational perspective, namely, studying experiential education across disciplines, theorizing at the field level, and including administrators.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it