Integrating Technology and Access to Digital Literacy in Secondary Education in British Columbia
Bibliographic record
Abstract
This action research study was conducted in British Columbia and employed an embedded mixed-methods case study design. It used the technological pedagogical content knowledge framework as an analytical lens for exploring how teacher preparation and school information technology (IT) infrastructure mediate the use of technology in secondary science classrooms. The four study participants were purposely selected from within the science department at the researcher’s school and included the researcher herself. All participants were grade 10 science teachers who taught the course at least once in the two years before the study. Data collection commenced with the review of the grade 10 science curriculum, followed by an online teacher questionnaire and semi-structured interviews. The data was triangulated to enhance trustworthiness, and the transcripts of the teacher interviews and the study manuscript were member-checked. The study findings suggest that teachers’ self-perceived low levels of technological knowledge, lack of technological training, and inadequate school IT infrastructure inhibit teachers’ and students’ engagement with technology. The study revealed relevant and context-specific insights that, in addition to addressing the initial hypothesis, can propel changes in how the school and the district mediate teachers’ and students’ use of technology across the district’s classrooms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.012 | 0.004 |
| Open science | 0.001 | 0.001 |
| 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".