Technological Ignatian Pedagogical Content Knowledge of Language Teachers: An Enhanced Framework for Ignatian Schools
Bibliographic record
Abstract
The study explores how the Technological Content Knowledge (TCK) framework can align with the Ignatian Pedagogical Paradigm (IPP) in Ignatian schools. Using a researcher-made interview guide and the TIPACK (Technological, Ignatian Pedagogical, and Content Knowledge) survey instrument, data were collected from 15 Senior High School (SHS) language teachers and six focus group participants. Results revealed that teachers excel in 21st-century higher-order thinking skills and TIPACK but face challenges in integrating IPP, requiring mentorship and training on technology use. Recommendations include addressing these challenges, enhancing TIPACK competencies, integrating IPP in online education standards, and conducting further studies on the enhanced TIPACK framework in other Jesuit SHSs. These findings aim to advance effective pedagogy, addressing the technological and pedagogical needs of SHS teachers within an Ignatian context.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".