The relationship between gender and student engagement in college. Paper presented at the Annual Conference of the Association for the Study of Highe r Education
Bibliographic record
Abstract
This paper examines the engagement patterns of male and female undergraduates in different types of baccalaureate-granting institutions. Descriptive statistics and hierarchical linear modeling show that on balance, undergraduate women participate more frequently than their male counterparts in educationally purposeful activities. Male first-year and senior students devote less time and effort to academic challenge tasks, such as working hard to meet expectations and spending time studying; senior males also participated less often in active and collaborative learning activities. Institutional type is unrelated to gender differences in engagement. The results point to areas where institutions could focus efforts to enhance the quality of the undergraduate experience for all students. 2 The Relationship between Gender and Student Engagement in College For more than a quarter century, undergraduate women have outnumbered their male counterparts at U.S. colleges and universities (U.S. Department of Education, 2001; Peter & Horn, 2005). Although the number of bachelor’s degrees awarded to men has increased during this period (King, 2006), undergraduate enrollment at most baccalaureate-granting institutions is
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".