Bibliographic record
Abstract
In Canada, as in many countries, teachers are being encouraged to integrate information and communication technologies (ICT) such as the Internet into the curriculum. A study conducted in Canada in 1999-2002 examined Internet use in schools through interviews with technology leaders, through surveys of teachers and principals, and through case study investigations of three school districts, each in a different province of Canada. The case study data from the three districts was analyzed, using the NVivo software program, to address three main questions: (1) To what extent was teachers' use of the Internet consistent with “best practice,” as described by Moersch (1999)? (2) What types of support systems appeared to be essential for effective Internet use in classrooms to occur? (3) What was the role of the teacher-librarian in contributing to effective Internet use in classrooms? The study showed that teachers were integrating the Internet into their teaching, but had not yet achieved “best practice,” and that teacher-librarians were influential in supporting teachers’ progress towards “best practice” in the use of the Internet in instruction.
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 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 | 0.018 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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".