A comparison of flipped learning with traditional learning (face-to-face) in large calculus courses: The effects on students’ achievement and cognitive engagement
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
This research paper investigates the effectiveness of combined flipped classroom (FC) with a plethora of <b>P</b>rep materials, small-group <b>C</b>ollaboration, student <b>P</b>resentations, <i>TopHat </i><b>C</b>lickers, and <b>E</b>ngaged labs (PCPCE) on students’ achievement and cognitive engagement from the students’ perceptions. Although FC format is not new, we use a different implementation of an FC (FC-PCPCE) in a calculus class. Educational and edutainment elements were investigated through a questionnaire that assessed learning gain, relatedness, challenges, learner-related factors, and self-reflection in terms of mathematics ability and perceived interest in the subject. We analyze both qualitative and quantitative survey responses from 354 first-year students participating in calculus classes at a large Canadian public university. We compare the perceptions of FC-PCPCE students to those of students in a traditional (i.e., non-flipped) classroom. The survey analysis shows that even with many students enjoying the implementation of FC-PCPCE format, students in the traditional classroom reported higher levels of satisfaction, interest, belonging, content recall, and experienced fewer academic challenges such as procrastination. The results of this study will aid educators in designing courses that benefit students and guide researchers who wish to pursue further studies on this topic.
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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 | 0.022 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it