Training Pre-Service Teachers in Career Education: Developing Foundational Perceptions, Knowledge and Skills
Bibliographic record
Abstract
Students in the K-12 educational system benefit from access to high quality career support (Campbell & Ungar, 2008). However, students report that they are not able to access effective career services (Campbell & Ungar, 2008). Either this support is unavailable or if it is available it is ineffective (Domene, Shapka, & Keating, 2006; Osborn & Baggerly, 2004). This article describes a pilot project offered by the Faculty of Education at the University of Lethbridge that seeks to address these issues. Through this pilot project pre-service teachers receive training in career education and learn to infuse career support in regular curriculum. This article examines the findings of a research project that investigated whether this pilot project effectively prepares pre-service teachers to integrate career education into regular curriculum. The findings suggest that this pilot project helped preservice teachers acquire the perspectives and skills required to effectively support students in their career explorations and planning.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".