Professional Learning Using a Blended-Learning Approach with Elementary Teachers Who Teach Science: An Exploration of Processes and Outcomes
Bibliographic record
Abstract
A priority for science education is to enhance pedagogical innovation in classrooms with practicing science teachers through professional development programs (PDPs). One way forward is to use a twenty-first century approach by designing a blended (i.e., online and face-to-face) program. While this approach is not new, this model has not been investigated as part of a large-scale PDP in Canada. This chapter reports on a PDP with a blended design implemented by a teaching association to support teachers’ implementation of innovative science teaching practices (e.g., inquiry, technology-enhanced teaching). The PDP had three elements: face-to-face workshops and seminars, collaboration in an online learning environment, and knowledge mobilization through sharing of developed resources. Over the PDP’s duration, 142 elementary science teachers participated. Using aggregate data from a mixed-methods approach, our evaluation research documented minor changes in elementary teachers’ views and practices with respect to the targeted innovative instructional practices. By synthesizing our findings within the current extant literature, we provide specific recommendations for future PDP designers and contribute to the research call to identify evidence-based practices from science-specific studies on blended PDPs. These recommendations include attending to technological supports, accountability considerations, and meaningful integration of online and face-to-face learning opportunities for teachers of science. Contributing to research that is designed for science teaching communities in Canada sheds light onto the nebulous area of professional learning for science teachers.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| 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".