The challenges and benefits to teachers' practices in constructivist learning : environments supported by technology
Bibliographic record
Abstract
This research is intended for educational policy makers. This is an exploratory study that investigates Quebec's classrooms as a new educational reform is implemented. There are two relevant pieces of legislation in the reform that elicited this study. First, teachers are required to adopt constructivist teaching practices; second, teachers must use ICT in classrooms. The questions being addressed are: (1) What are the current challenges and benefits impacting teachers with the integration of computers in the classroom environment? (2) What do classroom practices look like given (a) in the context of Quebec's constructivist-learning environment and (b) the possibility of ICT support. Case studies with teachers from elementary and high schools show changes in teacher and student role; however, lack of guidelines hinder constructivist teaching practices. Five predominant challenges were identified: lack of personal development, lack of time, technical support, accessibility, and classroom management. The study also identifies five elements as benefits: sharing of information; communication; editing; monitoring; web access.
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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 | 0.031 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.024 |
| Scholarly communication | 0.023 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".