Innovative Use of Media to Increase Student Engagement for a Large Second-year Core Course: “Engineering Economics”
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
Abstract – As most practitioners are aware, student engagement in large first- or second-year engineering classes is difficult. In a traditional lecture-style presentation instructors are given the challenging task of explaining difficult technical material to several hundred students in such a way that they are not distracted by their friends, cellphones, or the lecture hall atmosphere. In the literature, various solutions to student engagement are suggested: flipped classrooms, design projects, brainstorming sessions, paraphrasing exercises, and selfrating exercises [1]. The author attempted to implement various of these interventions with little anecdotal success. However, a modification of the “think-pairshare” idea as described by Karl Smith, from a subjective point of view, seemed to capture the class more than the default lecture/powerpoint method. Enumeration of student comments about the intervention and a comparison of means from student self reports of “stimulation of learning” suggests that the intervention was successful. Future work is planned to further refine the lectures in terms of student engagement in the lecture theatre and the tutorial classroom.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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