WHAT SENIORS HAVE TO SAY ABOUT THEIR 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
The goal of this pre-study was to prescribe a solution to a perceived decrease in student engagement in an elective course on additive manufacturing. The objectives were to:identify in what activities the students are engaging; identify causes for lack of engagement in their studies, if any;identify possible changes to the additive manufacturing course.A mixed (quantitative and qualitative) triangulation interpretivist approach was used to address the first two objectives. Approximately half (1/2) the students stated that their studies was not their priority, two thirds (2/3) reported that they attended university primarily to earn a diploma rather than to learn and again two thirds (2/3) said that they had difficulty concentrating, signs that most students are not fully engaged in learning. The qualitative analysis provided insight and nuance to the quantitative analysis. It made it possible to identify sources for lack of engagement. Apart from the presence of electronic devices which distract attention, teaching methods, course content and evaluation modalities were often cited. Based on the findings, three changes are suggested to the course
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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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