A methodological framework for investigating TPACK integration in educational activities using ICT by prospective early childhood teachers
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 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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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.002 | 0.001 |
| 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