Retaining students in computer science majors has been a persistent topic among computer science educators for almost two decades. Researchers have examined the relationship between belonging and engagement, self-efficacy, retention and persistence. Our quantitative research suggests that a student's sense of belonging is related to a student's perception of his ability, possibly more so than to actual performance. Our qualitative analysis further suggests that feelings of belonging can influence students' attitudes toward the mutability of ability, based on conversation and support from their academic and nonacademic communities. Supporting a student's sense of belonging both to the discipline and their supportive communities can improve the academic resilience of computer science students, thus improving retention.

Belonging is an important factor in STEM education and is a basic human need which is dependent on social relationships for fulfillment. In this work, researchers at five institutions continued a multi-year study of belonging among engineering and science students. For this study, belonging is separated into four separate constructs: belonging to class, belonging to major, belonging to the university as an institution, and belonging to the university as a community. The focus of this work is on self-reported belonging for STEM undergraduates by classification (year in school), and the following hypothesis was tested: belonging will increase monotonically with student classification. From spring 2010 through spring 2011, a combined total of more than 900 students completed surveys at a large Research institution located in the Northwest, a Historically Black College/University (HBCU) in the Southeast, a women's college in the Northeast, a small private faith-based institution in the Northwest, and a large teaching institution in the Midwest. The four types of belonging, or scales, were included in the survey assessing individual characteristics and academic experiences. Belonging scores across all institutions ranged from 14.08 to 18.12 out of 20.00 for four item scales and 9.49 to 12.68 out of 15.00 for the three item scale (belonging to the university as a community). The results of the analysis indicate that, although statistically significant differences in belonging were observed based on student classification at individual institutions, the differences did not support a monotonic increase by classification hypothesized at all schools for all types of belonging. The authors attempt to explain these observations based on cohort effects, institutional contexts and other factors.

Prof. Melani Plett is a Professor in Electrical Engineering at Seattle Pacific University. She has over seventeen years of experience in teaching a variety of engineering undergraduate students (freshman through senior) and has participated in several engineering education research projects, with a focus how faculty can best facilitate student learning. Sometimes, Faculty Matter: The Contribution of Faculty Support to Future Engagement AbstractIn this study, we examine the contribution of student-faculty interactions to the future engagement of students in their academic endeavors. These relationships were evaluated in a one-year longitudinal study of STEM (including engineering and computer science) students at five different institutions. These five institutions include three types of Carnegie 2010 classifications (Bac-Diverse, Master's L, and RU-VH), four geographical locations including the northwest, northeast, midwest, and southeast, and both public and private institutions with total undergraduate enrollments varying from 1,900 to 29,000 students. Both behavioral (effort, participation) and emotional (positive, negative) aspects of engagement are studied. Results show that significant relationships emerged for three of the five schools between faculty support and engagement. Formal faculty support (that provided in the context of a particular course) predicted effort (a form of behavioral engagement) at the HBCU in this study and also positive emotional engagement for both the HBCU and Teaching institution. Informal faculty support (that provided outside the context of a particular course) predicted participation (another form of behavioral engagement) and positive emotional engagement at the Research institution in the study. These results suggest that institutional culture influences how what faculty do predicts future engagement outcomes for students. At the Research institution, it appears that what happens between faculty and students outside of class influences students while at smaller or teaching-oriented institutions, what faculty do inside a class matters more. These results can provide important insight to faculty as to how to guide their interactions with students at different institutions to make the most difference in students' academic lives.

Denise Wilson is a professor of electrical engineering at the University of Washington, Seattle. Her research interests in engineering education focus on the role of self-efficacy, belonging, and other noncognitive aspects of the student experience on engagement, success, and persistence and on effective methods for teaching global issues such as those pertaining to sustainability. Dr. Melani Plett, Seattle Pacific UniversityProf. Melani Plett is a Professor in Electrical Engineering at Seattle Pacific University. She has over seventeen years of experience in teaching a variety of engineering undergraduate students (freshman through senior) and has participated in several engineering education research projects, with a focus how faculty can best facilitate student learning. AbstractIn the context of Tinto's Model of Institutional Departure, faculty support is critical to academic integration, which in turn is an essential element of persistence in college. Thus, understanding students' perceptions of faculty support in varied settings can provide insight into student satisfaction, performance, and persistence in engineering programs. In this study, focus groups were conducted with 175 students from five different institutions and a variety of engineering and computer science majors. The institutions in this study included a small women's college, a historically black university, a small private university, a medium size teaching university, and a large public research university. Focus group transcripts were coded and analyzed qualitatively.Findings from this analysis show that in some settings, despite a perceived lack of formal, inclass faculty support, students are still able to find faculty support outside the classroom, while in other settings this informal support is also perceived as lacking. In general, smaller environments with smaller student-to-faculty ratios appear to support stronger perceptions of support, although through different pathways. A small class size does not guarantee that students will perceive greater faculty support in that class. Large class sizes are not automatically detrimental for students, but they can be if students in those classes feel a lack of faculty support or availability both in and out of the classroom. With regard to institution type, the notion that undergraduates perceive lower levels of faculty support at research institutions holds true. This study has not verified whether the level of faculty support is actually less at research institutions, but only that students' self-reported perceptions of that support were lower at the research-focused institution when compared to teaching-focused institutions in this study. Regardless, given the importance of faculty support in persistence and other academic outcomes, this study suggests that greater attention to the ways in which faculty support students may be in order, particularly at research institutions and other large educational settings.

She is currently an associate professor in the Electrical Engineering Department at Seattle Pacific University. Her research interests include engineering education, engineering identity and workplace persistence, and non-stationary signal processing/detection theory.