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S-STEM scholarships are provided to academically talented low-income engineering students with the intent of increasing retention as well as successful transfer and subsequent graduation rates for a bachelor's degree in an Engineering or Computer Science (ECS) field. Since the spring of 2020, 71 unique students have been awarded scholarships. At this time, there are 22 active scholars, 34 have already successfully transferred to complete their ECS degree and a quarter of those scholars have since graduated. Beyond the financial support, NSF S-STEM programs center on providing academic, social and professional development. In addition, the research component of this program at a midwestern HSI community college is exploring the following questions: Do students recognize themselves as engineers prior to transfer? Do students feel a sense of belonging in their Engineering and Computer Science programs? Does being an NSF S-STEM Scholar impact either of these outcomes? The importance of developing a strong engineering identity as an indicator of persistence to degree completion has been the focus of considerable research over the last fifteen years. However, there is limited understanding of how community college experiences influence engineering identity development. Since the spring of 2020, students have been completing surveys during the first six weeks of the fall semester and during the last four weeks of the spring semester. Engineering identity was explored with questions centered on interest, recognition and competence as well as self-efficacy in skills such as tinkering, design and experimentation. Sense of belonging indicators were examined in terms of inclusion, sense of belonging to the community and sense of belonging to their major. This paper will provide quantitative analysis of the data examining outcomes based on demographics including ethnicity, gender, scholar status and length of time in the program.
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Enhancing Sense of Belonging among Engineering and Artificial Intelligence Students: First Insights from the NSF S-STEM Grant in Community College
Introduction: Chandler-Gilbert Community College (CGCC) in Arizona offers two-year degrees for diverse engineering disciplines and Artificial Intelligence and Machine Learning (AIM) studies. After their Associate’s degree, students transfer to Universities to complete their bachelor’s degree. Since the Fall of 2023, CGCC has nurtured students through the NSF S-STEM Grant initiative called Scholarships, Mentoring, and Professional Support to Improve Engineering & Artificial Intelligence Student Success at Community Colleges. This grant, also known as Reaching Engineering and Artificial Intelligence Career Heights (REACH), empowers students with scholarships, personalized mentoring, and industry-oriented activities. This study delves into the sense of belonging and academic integration of REACH recipients and their peers. Methodology: A survey was administered to students across six courses: engineering (3), AIM, chemistry, and physics. The courses were chosen because one REACH student was attending the same course, with the same instructor. The survey, adapted from Gurganus et al., was comprised of demographic data and 20 questions categorized into Sciences Identity, Expectations and Goals, Academic Integration, Sense of Belonging to the program, and Sense of Belonging to the campus. Unpaired t-tests were utilized to compare the responses of 5 REACH students with 58 of their peers, with significance set at p≤0.05. Results: Sixty-three students agreed and filled out the study, comprising 5 REACH students and 58 peers. Students are enrolled in AAS, Engineering Technology (1 REACH, 1 peers), AAS, Emphasis in Artificial Intelligence (2 REACH, 3 peers), AAS, Emphasis in Engineering (2 REACH, 30 peers), and 24 were not registered in one of those degrees. Twenty females, 41 males, and one binary student in their first to sixth semester at CGCC filled out the survey. Among those total students, 7 identified as Asian, 2 as black or African American, 11 as Hispanic or Latino, 39 as White, and 4 as Other. In the category of Sciences Identity, REACH students demonstrated a significantly stronger sense of belonging compared to their peers. Specifically, REACH recipients scored higher on three questions: "I have a strong sense of belonging to the community of engineering or AI" (REACH 4.40 vs Peers 3.47, p=0.017), "I feel like I belong in the field of engineering or AI" (REACH 4.60 vs Peers 3.71, p=0.032), and "The daily work of an engineer or AI scientist is appealing to me" (REACH 5.00 vs Peers 3.98, p=0.011). Furthermore, REACH students reported a significantly stronger sense of belonging to Chandler-Gilbert Community College compared to their peers (REACH 4.60 vs Peers 3.78, p=0.046). However, concerning academic integration, REACH students identified areas that require attention. Notably, they provided a lower score for the question "Understand what your professors expect of you academically" (REACH 1.20 vs Peers 2.00, p=0.025). REACH recipients also scored lower for: “Develop effective study skills”, “Adjust to the academic demands of college”, and “Manage your time effectively”. Academic Integration is the only category where REACH students scored less than their peers. Conclusion: The REACH initiative at CGCC has notably enhanced the sense of belonging and connection to the college among engineering and AIM students. While REACH students showed superior community affiliation, they identified areas for academic integration enhancement. A tailored workshop focusing on study skills and time management is planned for Spring 2024 to address these concerns. As the program expands in 2024, involving six more students, continued assessment and support mechanisms will foster a more inclusive and integrated academic environment. Acknowledgment: The authors would like to express their sincere thanks and gratitude to the National Science Foundation (NSF) for the Scholarship in Science, Technology, Engineering, and Mathematics (S-STEM) award No. 2220959.
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- Award ID(s):
- 2220959
- PAR ID:
- 10561475
- Publisher / Repository:
- 2024 ASEE Annual Conference & Exposition
- Date Published:
- Subject(s) / Keyword(s):
- NSF Grantees Poster Session S-STEM Community College Engineering Artificial Intelligence Machine learning
- Format(s):
- Medium: X
- Location:
- https://peer.asee.org/46837
- Sponsoring Org:
- National Science Foundation
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