A methodological framework for investigating TPACK integration in educational activities using ICT by prospective early childhood teachers
Bibliographic record
Abstract
This paper proposes a methodological framework for the study of how the Technological Pedagogical Content Knowledge (TPACK) model is integrated into educational activity design and implementation. The proposed framework was elaborated and applied in the context of a course in which student teachers from an early childhood education undergraduate program integrate TPACK into activity design and implementation using information and communications technologies (ICT). The specific methodological framework was designed to take into account the building blocks of TPACK for each part of the course (teaching, designing, and implementing) and to investigate and recombine these using appropriate methods and tools, such as thematic analysis for qualitative data processing and multidimensional data analysis. Findings show that after applying our initial methodological framework, several elements, for example the particular features and specificities of each subject matter in preschool education, needed to be revisited.
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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 | 0.115 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 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".