An Examination of Student Success within Canadian Higher Education: Fifty Years of Findings and Recommendations for the Future
Bibliographic record
Abstract
This article explores the student success literature published within the Canadian Journal of Higher Education (CJHE) over the last fifty years. Sixty articles were thematically organized into seven component measures of student success to present consistent themes that have persisted within the CJHE from inception in 1971 to 2020. Analysis demonstrates that there has been a disproportionate interest in some aspects of student success such as post-college performance, while other areas such as educational attainment and student engagement have lagged considerably behind in focus. Scholars have presentedongoing concerns supported by a wide range of data regarding the underemployment of graduates from Arts and Humanities, the sparse professorial landscape and the underutilization of Canadian PhD graduates in the workforce, debate on student competence and skill measurement, and the lack of large data sets on student persistence. Results suggest that a continuous effort is required to understand and support student success in a variety of formats—both within the academy and out in the workforce. Thus, this article concludes with a discussion and recommendations for future research avenues in the field of academic success and various subfields that may be of interest to higher education scholars and those who support student success.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.024 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".