High‐impact practices in cancer education and research: Undergraduate students' perceptions of skills and career development
Bibliographic record
Abstract
High-impact practices (HIPs) are educational practices that foster student success. HIPs have not been widely used in cancer education and research despite the need for students to develop key transferable skills and cultivate social responsibility. Our study addresses this need by implementing four community-based learning HIPs within the context of cancer education and research. Each HIP was classified as having low, moderate, or high alignment with the traits of effective HIPs. Undergraduate science students participated in one to four HIPs as a Feedback Participant, General Volunteer, Student Leader, or Cancer Undergraduate Research and Education (CURES) Class Student. We then studied the effect of these HIPs on students' development of knowledge and skills; career interest and preparedness; and social responsibility. Results from self-reported questionnaires showed that HIPs increased students' cancer knowledge and developed their transferable and technical skills. Many students reported that these HIPs strongly impacted their career preparedness; positively influenced their interest in pursuing careers in health or biomedical sciences; and encouraged them to participate in community service activities. Thus, these findings provide new insights into the perceived benefits of HIPs in cancer education and research by undergraduate students.
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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 | 0.000 | 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".