PurposeThis study investigated how behavioral and emotional forms of engagement are associated with faculty support and student-faculty interactions among engineering students.Design/methodology/approachQuantitative research methods were used to analyze survey data from 781 undergraduates in seven large undergraduate engineering courses. Linear hierarchical regression models were used to evaluate the relationships between demographics (gender, race/ethnicity, family education, US status and transfer status) and student engagement and between faculty behaviors and engagement.FindingsFaculty support was consistently, significantly and positively linked to all forms of student engagement, while student-faculty interactions were significantly and positively linked to effort and positive emotional engagement and negatively linked to attention and (an absence of) negative emotional engagement. Gender, race/ethnicity, international student status and transfer status significantly predicted at least one form of engagement.Research limitations/implicationsAlthough this was a single institution study and cross-sectional, the findings suggest that faculty support and student-faculty interactions, while important for engagement, have different effects on different types of students. Faculty and teacher professional development efforts should raise awareness of these differences in order to enhance diversity and inclusion in engineering courses and curricula at all levels.Originality/valueThe analysis of behavioral and emotional forms of engagement represents more of a motivational lens on engagement in contrast to the traditional focus on time-on-task or time spent in fruitful educational practices, as is the norm with much of the engagement literature in higher education.

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Hierarchical linear regression models using cross-sectional survey data from over 750 students at a single large public institution were used to assess relationships between TA support, TA-student interactions, and three forms of student behavioral engagement. <br>

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Do students explicitly value the self-efficacy of their teaching assistants? If so, how does the self-efficacy of their TAs affect how students engage in their courses? This study explores these two questions in a variety of TA-intensive undergraduate engineering courses through qualitative analysis of semi-structured interviews conducted with 30 students from those courses.Student interviews were first coded to identify references to how important a TA's self-efficacy was to students in their choices to engage and participate in the learning experience. Almost 50% of students interviewed explicitly spoke to how important it was for TAs to be confident in their teaching. Students' use of the terms confidence, confident, or self-confident were interpreted to mean self-efficacy given the task-oriented context in which these terms were used.A second coding pass with the interview data looked at the implications and potential benefits of building teacher self-efficacy among TAs to better serve student learning and engagement. Teachers with high teacher self-efficacy are known to exhibit certain behaviors more often or more effectively than those teachers with lower self-efficacy. Previous research studies have identified these behaviors, allowing the second phase of this study to use these behaviors as a basis for further deductive coding of student interview data. The second phase of this study evaluated the impact and importance of these self-efficacious behaviors as discussed by students in our interview pool. Of those behaviors that result from high teacher efficacy, many students look for indications that the TA puts effort into teaching, teaches with clarity and organization, will support students through difficulty, and demonstrates enthusiasm. Although mentioned by fewer students, other valued teacher efficacy behaviors that emerge from this study include refraining from criticizing student mistakes or knowledge gaps, preparing adequately for class, being willing to experiment instructionally, facilitating small-group work, and being fair. These results reinforce existing research by confirming that content knowledge is only part of what students seek in good teachers, and also provides insight into which behavioral benefits of high teacher efficacy are most salient to undergraduate students in engineering.

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This IUSE-funded study investigated differences in behavioral and emotional engagement that emerge across family income, gender, and race in engineering classrooms. Engagement levels and engagement patterns were measured across seven sophomore-and junior-level engineering courses at a large public university. Differences in engagement were evaluated quantitatively between the two numerical majority races in this study (Asian, white), between genders, between international and domestic students, and across three levels of family income. Sample sizes for other racial groups (black, Pacific Islander, Native American, Hispanic, and Other) were too small to support analyses by family income and were not included in this study. Initial analyses of variance (ANOVA) revealed significant differences in at least one form of engagement between Asian and white students, between men and women, between domestic and international students, and across family income levels. As a result, all four demographic variables (race, gender, country of origin, family income) were retained in a subsequent linear regression to understand potential interactions among these demographic variables. Since these models were weak, the analysis then looked at engagement patterns rather than engagement levels. In this next phase of analysis, scores for the five engagement variables were classified using a non-parametric k-means clustering approach. The data optimally separated into two main categories: less engaged students (Cluster 1) and more engaged students (Cluster 2). Among domestic students, 100% of low income Asian women and 82% of low income Asian men (82%) fell into the more engaged cluster, while high-income Asian women (83%) fell into the less engaged cluster. Among international students (who were entirely Asian in this sample), low income Asian men and high income Asian women were among those who had the highest percentage of lesser engaged students (40% of each group, respectively) while middle income Asian men and middle income Asian women had the highest percentage of more engaged students (approximately 80% of each). Overall, the k-means clustering approach provided greater insight into the data than traditional statistical analysis techniques. Differences and trends among all four demographic variables (gender, family income, race, country of origin) emerged, showing that students from some demographic groups seem more susceptible to remaining less engaged in courses than other groups.

This research paper explores the beliefs that students hold around major social issues including social justice, global disparities, and the role of technology in alleviating injustice. In a survey completed by almost 400 students from four different areas of study at a major public university, scores from three subscales of social responsibility beliefs show that education and environmental studies majors express stronger beliefs about global disparities than engineering students. Significant differences among environmental, education, business, and engineering majors also emerged regarding beliefs about the potential for technology to support solutions to major social issues. In contrast, no significant difference among engineering, education, environmental studies, and business majors emerged in terms of beliefs about social justice. Depending on the model, sustainability either embodies social responsibility within global environmental limits or overlaps social responsibility with economic and environmental concerns about providing the next generation with opportunities comparable to the present generation. Regardless of which model is accepted, sustainable development includes critical issues of social responsibility, but can also be presented in the context of specific challenges (e.g. resource scarcity, sustainable energy). These allow us to study how social responsibility extends from beliefs and knowledge to responsibility for supporting sustainable development. To this end, three additional scales oriented around the specific issues of sustainability and sustainable development are also addressed in this study to examine the interrelationships among beliefs, knowledge, and responsibility. A hierarchical linear regression model was constructed to study these interrelationships using student major, four belief subscales, and one knowledge subscale as independent variables, and responsibility for sustainable development as a dependent variable. Results showed that beliefs about social justice and sustainability as well as knowledge about sustainability significantly predicted responsibility for sustainability. However, beliefs about global disparities and the role of technology did not predict this outcome. No interactions between student major and beliefs or knowledge were found, thereby suggesting that these relationships among beliefs, knowledge, and responsibility remain true across area of study. In conjunction with existing studies, these results support the public perception that engineers are less concerned with social issues, but also promote the idea that education targeted toward developing beliefs and improving knowledge can potentially impact the level of responsibility for social issues adopted by students in school and subsequently in their chosen professions.