Innovation in Digital Language Teaching: Emerging Lessons from Two Interpretative Studies in Portugal
Bibliographic record
Abstract
This study explores how digital innovation is conceptualized and enacted in foreign language teaching, by drawing on two interpretative studies carried out in Portugal before and during the COVID-19 pandemic. The first examined 265 English teachers’ reported practices with technologies, while the second explored 127 language teachers’ experience during emergency remote teaching. A comparative interpretative synthesis was used to examine thematic patterns regarding pedagogical purposes, teaching strategies, and challenges. Findings are interpreted through professional development frameworks, such as TPACK, and critical perspectives on pedagogical integration of technologies. Results reveal that, despite increased technology use, traditional teaching practices largely prevailed. Innovation emerged mostly in teachers’ strategic intention rather than in structural transformation. The study highlights that technology alone does not drive pedagogical change, and that only well-substantiated pedagogical integration may lead to meaningful innovation. Implications for teacher education are discussed, particularly the need to align digital competence with pedagogical purpose.
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How this classification was reachedexpand
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".