When parents become students:An examination of experiences, needs, and opportunities which contribute to student parent engagement in community college
Bibliographic record
Abstract
While college and university student profiles are changing rapidly, many of our practices and support systems are geared to traditional student profiles. This article focuses on findings from a recent study examining the experiences of student parents enrolled in community colleges, and examines the kinds of student services that help student parents remain engaged in their classes and persist to graduation. This study offers insight on transformative practices for supporting non-traditional, student parents on community college campuses. This study offers a paradigm shift for advisors, counselors and faculty at higher education institutions so that they may effectively engage and support student parents. The research includes student parents who have one or more dependent children aged 17 or younger and who are enrolled as full-time or part-time students. The study investigates some of the barriers to student parent success as well as the challenges they face. The study identifies, describes, and analyzes the support services which are being utilized by student parents, and review successful models of support in surrounding institutions. Nora’s (2006) Student Engagement Model is used as a theoretical framework for this study. The results from this study should be of interest to student affairs professionals and higher education administrators alike, as they reflect the needs and challenges of the growing student parent population and inspire those searching for ways on how to support this unique, growing community of students.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".