In-service Training as a Factor in the Formation of the Teacher’s Individual Theory of Education
Bibliographic record
Abstract
The purpose of this paper is the investigation of the prevailing forms of in-service training, the detection of the dominant pedagogical discourse they promote as well as their contribution to the shaping of the teacher’s individual theory of education (I.T.E.). The research was conducted using semi-structured interviews with a sample of 11 teachers who work in schools in Patras and the data were analysed using B. Bernstein’s theoretical framework. The results of the research revealed that in our case, the predominant form of in-service training is the lecture, while the scientific knowledge provided refers to the content and teaching of cognitive subjects, the diagnosis and handling of learning difficulties and the acquisition of skills in the use of teaching aids. It also became clear that the I.T.E. of the teachers who participated in the research is chiefly shaped by elements of the professional biography of each teacher, in which in-service training does not seem to hold a dominant position.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".