Knowledge and Usage of Flipped Classroom Instructional Strategy: The Views of Ghanaian Teachers
Bibliographic record
Abstract
This study was designed to examine Ghanaian teachers’ knowledge and usage of the flipped classroom instructional strategy. A survey of 109 teachers who pursued a master’s degree in education during the 2018/2019 academic year was used for the study. The instrument used for collecting data was a structured questionnaire. The result of the study was analysed using descriptive statistics (frequency, percentages) and inferential statistics (T-test). The results established that majority of the teachers acknowledged the importance of student-centred instructional strategy like the flipped classroom approach, however, majority of these teachers were of the view that they have not experienced or been introduced to this instructional strategy. It was, therefore, not surprising that most of the teachers attested to the fact that they are not using the flipped classroom instructional strategy. The results from the study also revealed that there was no significant difference between school type (public and private) and teachers’ knowledge and usage of the flipped classroom instructional strategy. The results from the study attest to the fact that the flipped classroom instructional strategy has not been conceptualised into the Ghanaian classroom. The researchers, therefore, recommend that there is the need for professional development training for teachers on the use of the flipped classroom instructional strategy and sensitisation workshop for students on the use of the flipped classroom instructional strategy and its relevance.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".