A CASE STUDY ON BLENDED LEARNING IN ENGINEERING 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
This paper explores a case study of implementing blended learning in a third-year engineering course. In “Mechanical and Thermal Energy Conversion Processes”, blended learning was implemented by flipping the classroom (i.e. reversing the roles of lectures and homework) for selected units of the course. While flipping an entire course can be a significant undertaking, it can be much easier to take a blended approach and only flip lectures on selected topics. Many studies on flipped classroom learning have focused on the production of online lectures and active learning methods; often these case studies have overlooked the mechanisms to bring homework into the classroom. In this case study, homework was adapted into a variety of in-class activities, composed of hands-on learning, problem solving, and classroom discussions. In addition, a variety of classroom space types were used to conduct these activities. In this paper, the successes, challenges, and lessons learned for each type of activity and classroom space are discussed. Strategies for student engagement and acceptance of blended learning are also discussed.
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 | 0.003 | 0.014 |
| 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 | 0.000 |
| 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