Blended Learning for Professional Development: An Evaluation of A Program for Middle School Mathematics and Science Teachers
Bibliographic record
Abstract
Background Improving the subject matter knowledge and pedagogical skills of teachers of mathematics and science is a key priority for many jurisdictions. Blended learning is a promising, yet so far seldom used model for supporting teacher professional development. This model combines the advantages of traditional face-to-face interaction with the flexibility of online learning. Purpose In this study, we examine two one-year professional development programs for middle-school mathematics and science/technology teachers that employed blended learning. The goal of our research was to understand how the program affected teacher attitudes toward and pedagogical practices in these subjects and on student perceptions and learning of the subjects. Participants Participants in the study were 68 mathematics and 65 science/technology teachers in grades 6, 7, and 8 in several school districts in a large urban center, along with their students: 477 students from the mathematics teachers’ classes and 551 from the science/technology teachers’ classes. Program The blended learning program, known as the Teacher eLearning Project (TeL), began at the start of the school year with a module that consisted of a daylong face-to-face session followed by an eight-week online session. The first year of TeL focused on the mathematics teachers who had a total of three modules to complete; in the second year, science/technology teachers had two modules. Research design We used Guskey's (2000) five-level evaluation framework to assess the impact of the programs on teachers’ attitudes and knowledge, institutional support for the programs, changes in classroom practices, and student perceptions and learning of the subjects. Data were obtained using a pre-post design that included surveys, classroom observations, and key informant interviews. Findings Overall our results indicate that the program appeared to influence positively teacher attitudes and content knowledge in certain curricular areas and motivated many to transform their classroom practice to varying degrees. Despite this, student responses were mixed: students viewed mathematics less favorably by the end of the program, but became more positively inclined towards science/technology. Conclusions The blended learning model shows potential for teacher professional development, although further research preferably through controlled studies is needed. Aspects that need to be examined further include the nature of the online tasks given to teachers, the role of the online facilitators, the impact on student achievement, and the implications of providing teachers with less release time than was available in this study.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".