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PurposeSupporting community college transfer students represents a critical strategy for broadening participation in STEM. In addition to being a racially diverse group, students who pursue STEM degrees by way of community college report frequent interests in graduate study and academic careers. Thus, supporting and expanding transfer students’ PhD interests can help to diversify the STEM professoriate. This study aims to identify the experiences that predict PhD interests among students who transferred into the computer science major from a community college. Design/methodology/approachRelying on longitudinal survey data from over 150 community college transfer students throughout their first year at their receiving four-year university, we used regression analysis to identify the post-transfer college experiences that predict early interest in PhDs. FindingsWe found that receiving information about PhDs from a professor strongly predicted PhD interest among transfer students. Relationships with other variables indicate that the provision of information about graduate school was more likely to occur for students who participated in undergraduate research experiences than for those participating in internships. Descriptive data document inequities in who has access to these types of experiences. Originality/valueThis paper provides new insight into how STEM departments can develop targeted efforts to ensure that information about PhD training is equitably available to all transfer students. Working to ensure that faculty equitably communicate with students about PhD opportunities may go a long way in countering potential deterrents among transfer students who may be interested in such pathways.
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Publishing Ecological Data in a Repository: An Easy Workflow for Everyone
Abstract For many ecologists, publishing data in a data repository is a new, unfamiliar task. To reduce the learning curve, the Environmental Data Initiative has developed user‐friendly software to make capturing and submitting data and metadata a simple process. In this article, we introduce ezEML and discuss use cases for researchers who publish data infrequently or information managers who regularly update multiple datasets.
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- Award ID(s):
- 1931174
- PAR ID:
- 10475949
- Publisher / Repository:
- Wiley Periodicals LLC
- Date Published:
- Journal Name:
- The Bulletin of the Ecological Society of America
- Volume:
- 103
- Issue:
- 4
- ISSN:
- 0012-9623
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/bes2.2018
