Teacher learning, informal and formal: results of a Canadian Teachers' Federation survey
Bibliographic record
Abstract
As part of a larger national study examining informal learning practices across the general population, a representative random sample of elementary and secondary school teachers across English Canada were sent English language questionnaire forms in October of 1998, inquiring into their practices and opinions concerning their own on-going learning. Respondents (N=753) were asked to comment on any informal learning they may have done in the past year in their workplaces, their homes and their communities. They were also asked to report on any formal learning activities in which they participated in, including courses, workshops or conferences. Most questions replicated closely those asked in the 1998 national telephone survey (N=1562) of Canadian adults' learning practices (see Livingstone 1999). Over 85% of all teachers indicated that they had engaged in formal courses and workshops in the previous year, as compared to 49% of the entire Canadian labour force, and 67% of those in the labour force with university level education. Similarities and differences among teachers' responses were examined, based on gender, age, region, elementary/secondary school placement, urban/rural residence, position in the system. Teachers reported spending an average of over eight hours per week engaged in their own formal learning activity (including course time, reading and preparing assignments). In addition to this formal learning, teachers reported that they also spent an average of 4 hours per week in informal learning related to their jobs and an average of 10 hours per week devoted to informal learning activities generally (related to their employment, housework, community volunteer work and other general interests.) Again, there were variations among teachers as well as within the general labour force. As one example, 89% of teachers, as compared to only 61% of the overall labour force and 77% of employed professionals had engaged in informal learning of computers in the previous year (Authors' abstract).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".