Unravelling the Rationales, Responses and Roles of practitioners when embedding Service Learning:A reflective practice workshop
Bibliographic record
Abstract
Higher education institutes (HEIs) increasingly aim to embed (community) service learning practices (Tijsma et al., 2023). However, the rationales (motivations and behaviour) behind embedding service learning can be divergent – both on the individual practitioner level and on the institutional (policy) level (Compagnucci & Spigarelli, 2020; Lounsbury & Pollack, 2001; Taylor & Kahlke, 2017).<br/><br/>In this interactive session, we take a closer look at the various rationales and make you, as a practitioner, more aware of your own rationales in relation to embedding service learning within your institutional context, by considering questions such as: What rationales drive you as a practitioner, researcher, or policy maker to embed service learning practices? And how does this (dis)align with institutional practices? What potential tensions can arise in relation to your own service learning practice? And how can you best deal with or respond to these tensions? We give meaning to this workshop based on the findings of a recently published paper (Tijsma et al., 2024). In this paper we describe different rationales, responses and roles of individual practitioners in relation to embedding service learning.
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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 | 0.003 | 0.002 |
| 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 | 0.001 |
| 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".