Generic Skills, Academic Achievement, and Means of Improving the Former
Bibliographic record
Abstract
In Canada, in general – and in the Province of Ontario in particular – academics, employers, and government agencies are concerned with the low generic skill levels of university students and graduates. The assumption is that such deficiencies detract from academic and job success. Despite this concern, in Canada, research has not focused on potential links between objectively measured generic skills and grades recorded in administrative records. In view of this lacuna, the current research has two objectives. First, to assess the net effect of objectively measured generic skills on academic achievement as recorded in administrative records. Second, to determine the efficacy of an online course dedicated to the development of generic skills. Overall, I found that generic skills were better predictors of students’ achievement than high school grades used in admission processes; the relationship between high school grades and generic skill levels was weak; students’ generic skill levels did not improve over time; and an online course devoted to increasing students’ generic skills was effective in boosting skills to an acceptable level. Accordingly, if they are concerned with academic achievement, universities in Ontario and in other jurisdictions in which students are admitted to university primarily based on their secondary school grades might make the development of generic skills a priority; however, unless such skills are demanded across the curriculum, they will atrophy.
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.
How this classification was reachedexpand
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 | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".