Investigating a blended learning context that incorporates two-stage quizzes and peer formative feedback in STEM education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Researchers have expressed concern about the state of STEM education. To improve this situation, new pedagogies, such as blended learning, have been proposed and tested. The last decade has seen an increase in the use of blended learning to support learning; however, the effect of blended learning on learning remains unclear and often mixed. The two studies in this paper draw on data from pre-university science students in the following courses: (1) Electricity and Magnetism (E&M) and (2) Waves, Optics & Modern Physics (Waves). In study 1, the treatment group (blended learning coupled with two-stage quizzes & peer formative feedback) performed significantly higher than the control group (lecture format with online homework & instant feedback) in the standardized final exam. In contrast, in study 2, there was a non-significant main effect of groups, indicating that the treatment group (blended learning with online homework & instant feedback) and the control group (lecture format with online homework & instant feedback) performed similarly in the standardized final exam. The finding of study 1 suggests that the effect of an instructional pedagogical framework embedded in a blended learning context improves performance in STEM education. Whereas the finding of study 2 suggests that a blended learning context without incorporating any instructional framework or support for cognition other than the lecture is comparable to a traditional face-to-face course.
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.
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it