The Reciprocal Nature of Pedagogical and Technical Knowledge and Skill Development between Experts and Novices
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
This paper outlines the findings of a study focused on the impact an expert teacher’s pedagogical and technical knowledge and skill may have on the pedagogical and technical development of pre-service technology education teachers. Specifically, this inquiry falls within the context of traditional wooden boat building in Newfoundland and Labrador, Canada. Understanding the relationship between an expert’s knowledge and skill, and the development of a novice’s knowledge and skill is vitally important for institutions charged with graduating technology education teachers. Exploring the impact of pre-service teachers’ pedagogical and technical development was considered in relation to an expert teacher’s pedagogical content knowledge, and the nuance between declarative and procedural knowledge within technological activity. Data were collected from semi-structured interviews, workshop session observations, and researcher/participant journal entries. The sample was purposeful as the participants were recruited from boat building workshops between 2017 and 2019 and the 2017-2018 technology education diploma program cohort from Memorial University. Thematic analysis was used to identify major themes within the data. A descriptive visual framework based on the data analysis was constructed to highlight the complexities of teaching and learning within the multifaceted setting of a technical activity. An analysis of the data indicates that fostering and maintaining reciprocal interpersonal relationships between experts, novices, and peers are critical for the development of pre-service teacher technical and pedagogical knowledge and skill
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.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it