Active Learning and Flipped Classroom, Hand in Hand Approach to Improve Students Learning in Human Anatomy and Physiology
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
Because Human Anatomy and Physiology (A&P), a gateway course for allied health majors, has high dropout rates nationally, it is challenging to find a successful pedagogical intervention. Reports on the effect of integration of flipped classrooms and whether it improves learning are contradictory for different disciplines. Thus many educators are reluctant to explore the value of flipped classrooms. Therefore, in the present study we compare incorporating flipped classroom and minimal class discussion (control group) with flipped classroom and active learning activities (experimental group) in A&P and their impacts on both students’ exam performance and their satisfaction with the course. Assessments consisted of a survey of students’ attitudes and a comparison of exam performance in experimental and control groups. Exam performance among the students in flipped-classroom and active learning activities improved significantly relative to the control group [Mean ± SD: (76.93±18.33 vs 67.8±18.81), p<0.001. Student attitude, in which students rated the efficiency of pedagogical learning on a five-point Likert scale, was positive: the majority of students strongly preferred active-learning activities that were incorporated in the flipped-classroom. Students indicated that these activities helped them learn better and to connect the materials to the goals of their future careers (73.88% and 79.77% respectively). Therefore, we conclude that flipped classroom coupled with active learning strategies can improve students’ performance and attitude in the introductory A&P course.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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