Factors affecting student drop out from the university introductory physics course, including the anomaly of the Ontario double cohort
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 course drop-out rate is the fraction of students per year who drop a course after starting it. This statistic is important both as a measure of the difficulty or relevance of the course compared to others at a university, and as one indication of the success of measures taken to improve teaching. The drop-out rate of students from the first-year university physics course at Trent University increased from about 8% in the 1980s to over 20% in 1999, primarily under the same instructor, with the exception of the Ontario “double-cohort” years 2003–2004 and 2004–2005 when it plummeted to about 9% before rebounding in 2005–2006. A similar decrease in this rate for the double-cohort years has been observed at Brock University and the University of Guelph, and so was probably widespread. It is speculated that the main cause of the decrease for these two years was an improved work ethic of the double-cohort students. Possible causes of the steady increase in the drop-out rate from the 1980s to the present are discussed including high-school courses taken; gender balance; and grade inflation. The last of these combined with a dramatic increase in the percentage of high-school students continuing their education, appears to have resulted in weaker and less motivated students being admitted to university. Results are also given of a survey of recent first-year Trent University physics students for possible reasons for dropping out of the course: students who have not taken the final-year high-school physics course, do not live in residence, or do not work together on their assignments are much more likely to drop the course. PACS No.: 01.40.gb
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 | 0.000 |
| 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