Leveraging Innovation and Optimizing Nurturing in STEM (NSF S-STEM #2130022, known locally as LION STEM Scholars) is a program developed to serve low-income undergraduate Engineering students at Penn State Berks, a regional campus of the Pennsylvania State University. As part of the program, scholars participate in a four-year comprehensive multi- tiered mentoring program and cohort experience. The LION STEM curricular program includes Engineering Ahead (a 4-week summer residential math-intensive bridge program prior to entering college), a first semester First-Year Seminar, and a second semester STEM-Persistence Seminar. Co-curricular activities focus on professional communication skills, financial literacy, career readiness, undergraduate research, and community engagement. The program seeks to accomplish four goals: (1) adapt, implement, and analyze evidence-based curricular and co- curricular activities to support, retain, and graduate a diverse set of the project's engineering scholars, (2) implement, test, and study through research and project evaluation strategies for systematically supporting student academic and career pathways in STEM, including development of STEM identity, (3) contribute to the knowledge base through investigation of the project's four-year multi-modal program so that other colleges may successfully implement similar programs, and (4) disseminate outcomes and findings related to the supports and interventions that promote student success to other institutions working to support low-income STEM students. The purpose of this paper is to analyze data from a repeated-measures design to provide a holistic narrative about the effects that the academic and support activities offered to LION STEM Scholars have on the development of their future-engineer role identity throughout their first year as an undergraduate engineering student. This paper presents data collected from semi- structured (Smith & Osborn, 2007) audio-recorded interviews from the first cohort of LION STEM Scholars (n=7) at three different time points (pre-summer bridge, post-summer bridge, end of first semester) as well as data collected from a written survey at the end of scholars’ second semester.
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Digital imaging and vision analysis in science project improves the self-efficacy and skill of undergraduate students in computational work
In many areas of science, the ability to use computers to process, analyze, and visualize large data sets has become essential. The mismatch between the ability to generate large data sets and the computing skill to analyze them is arguably the most striking within the life sciences. The Digital Image and Vision Applications in Science (DIVAS) project describes a scaffolded series of interventions implemented over the span of a year to build the coding and computing skill of undergraduate students majoring primarily in the natural sciences. The program is designed as a community of practice, providing support within a network of learners. The program focus, images as data, provides a compelling ‘hook’ for participating scholars. Scholars begin the program with a one-credit spring semester seminar where they are exposed to image analysis. The program continues in the summer with a one-week, intensive Python and image processing workshop. From there, scholars tackle image analysis problems using a pair programming approach and can finish the summer with independent research. Finally, scholars participate in a follow-up seminar the subsequent spring and help onramp the next cohort of incoming scholars. We observed promising growth in participant self-efficacy in computing that was maintained throughout the project as well as significant growth in key computational skills. DIVAS program funding was able to support seventeen DIVAS over three years, with 76% of DIVAS scholars identifying as women and 14% of scholars identifying as members of an underrepresented minority group. Most scholars (82%) entered the program as first year students, with 94% of DIVAS scholars retained for the duration of the program and 100% of scholars remaining a STEM major one year after completing the program. The outcomes of the DIVAS project support the efficacy of building computational skill through repeated exposure of scholars to relevant applications over an extended period within a community of practice.
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- Award ID(s):
- 1557417
- PAR ID:
- 10338811
- Editor(s):
- Hacisalihoglu, Gokhan
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 16
- Issue:
- 5
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0241946
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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