Bibliographic record
Abstract
This multiple case study investigates how a cohort of thirty-eight elementary teacher candidates (TC) and a volunteer subgroup of eight teacher candidate researchers (TCR) were prepared to use ICT in their teacher education program (TEP). The authors expected social and cultural relationships would contribute to the formation of these beginning teacher’s pedagogical perspectives and practices in relation to ICT. The study examined both TC and TCR uses of ICT from multiple perspectives: as students in the TEP; as teachers in their practicum classrooms; and as research participants. The researchers collected data on how their TEP, and ICT ecologies of learning (ICT-EL) experiences, influenced the formation of TC and TCR ICT perspectives regarding curriculum knowledge (ICT literacies) and pedagogy (ICT practices). This chapter describes the role institutional isomorphism and knowledge and curriculum fragmentation appear to play in the formation of oppositional, or resistant, ICT perspectives. It argues for active socially engaged learning (ASEL), efficacious learning, and critical inquiry as emergent systems that are in a continuous state of formation and change within these institutional contexts.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".