Bibliographic record
Abstract
This paper will present the second in a series of case studies on teaching technology education within the Newfoundland and Labrador, Canada context. Specifically, this paper will discuss what is helping and hindering the teaching of technology education and skilled trades at the secondary level (grades 10-12) in relation to a previous intermediate level (grades 7-9) case study. Intermediate technology education is marginalized in relation to other areas of the general curriculum within the Canadian context. As such, this research study sought to understand if marginalization and other related themes were present at the secondary level. The Technology Education Teaching Framework (TETF) which emphasizes the role of teacher experience, professional development, and leadership was used as the primary lens of inquiry. A qualitative case study methodology framed this study. Data were collected via an online questionnaire, semi-structured interviews, and classroom observations from a purposeful typical within case sample of Canadian technology education and skilled trades teachers. Two cycle coding was used in conjunction with thematic analysis to analyze and interpret the data. Secondary technology education and skilled trades teachers share similar beliefs and pedagogical practices as their intermediate counterparts. Themes of professionalism and systemic marginalization emerged as helping and hindering teachers’ efforts. However, at this level there was an identified tension between the values associated with the technology education and skilled trades curricula. Moving forward, raising the profile of technology education is framed within the potential transferability of local strategies and solutions to other jurisdictions with similar circumstances.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.033 | 0.015 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".