Reinforcing the Importance of Maintaining Internship Support for College Student Engagement and Anticipated Employment
Bibliographic record
Abstract
The Covid-19 pandemic has created many challenges for universities around the world, including how to keep students engaged in their professional development, despite the challenges of remote learning and virtual student services. The goal of this study was to demonstrate the continued importance of Career Professional Development Center (CPDC) support (pre-pandemic to early stages of the pandemic) for business-related internships influencing student professional development engagement (PDE) and anticipated employment upon graduation. PDE encompasses typical CPDC resources (e.g., internship search support; involvement in student professional organizations (SPOs); professional development coaching; and job search assistance). A survey, the Senior Student Satisfaction Survey (SSSS) was deployed prior to graduation to business students. Using the SSSS, two separate samples of graduating business undergraduates at a Mid-Atlantic University in the United States were surveyed, in late Spring 2019 (pre-pandemic) and late Spring 2020 (early pandemic). Pre-pandemic survey results showed that students having at least one internship experience (versus none) were more likely to: join an SPO sooner; attend more SPO meetings/semester; complete their professional development sooner; and anticipate “by graduation” full-time employment. Despite the drop in survey participation due to the pandemic onset, results consistent with this were found with the early pandemic survey. Like other academic-related and campus services in the face of the pandemic, the business school CPDC is adapting to the new remote ways of operating and successfully transitioned their delivery mode to a 100% virtual model to meet the resource challenge of supporting student PDE. It is hoped that the ideas discussed will be useful to a wider audience.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".