More Like this

1. Innovation Self-Efficacy: A Very Brief Measure for Engineering Students.

   Schar, M.; Gilmartin, S.; Harris, A.; Rieken, B.; Sheppard, S. (January 2017, Proceedings for the American Society for Engineering Education Annual Conference, June 25-28. Columbus, OH.)

   When survey time is limited, education researchers may be faced with the choice of using an extremely brief measure of innovativeness or using no measure at all. To meet the need for a very brief measure, a 5-item innovation self-efficacy (ISE.5) scale was developed using the 19- item Dyer et al. Innovative Behavior Scale (IBS) as a starting point, adapted for undergraduate engineering students, and then condensed using confirmatory factor analysis. The ISE.5 measures innovation self-efficacy as a unitary construct drawn from Dyer et al.’s five innovative behavior components (Questioning, Observing, Experimenting, Networking Ideas and Associational Thinking) and has good internal and external validity as well as good test-retest reliability. The ISE.5 (as a measure of innovation self-efficacy) is shown to be an important mediator between innovation interests and a desire to pursue innovative work as a career postgraduation. This mediator relationship is consistent among important sub-populations of engineering students such as females, underrepresented minorities and first generation college students. While not a substitute for a full multi-factor innovation assessment tool, the ISE.5 can serve as an important indicator of innovation self-efficacy among an undergraduate engineering student population. 

   more » « less
2. A Measure of Affect toward Key Elements of Engineering Professional Practice.

   Patrick, A D; Choe, N H; Martins, L L; Borrego, M J; Kendall, M R; Seepersad, C C (June 2017, ASEE annual conference & exposition proceedings)

   Identity, or how people choose to define themselves, is emerging as an attractive explanation for who persists in engineering. Many studies of engineering identity build off of prior work in math and science identity, emphasizing the academic aspects of engineering. However, affect towards professional practice is also central to engineering identity development. This paper describes the methods used to create a new survey measure of individuals’ affect toward elements of engineering practice. We followed the item generation, refinement, and instrument validation steps required for psychometric validation of a new survey measure. We generated items deductively using the literature on engineering professional skills and practice and inductively based on interviews with practicing engineers, engineering graduate students, and engineering undergraduate students. We blended the inductively and deductively derived item lists to create a list of initial items for the measure. We circulated this list of items to a set of engineering and professional identity experts to establish face validity and made modifications based on their feedback. The final list included 34 items. These 34 items were administered in a questionnaire survey in the fall of 2016 to 1465 engineering undergraduates in three majors at two institutions. We conducted an exploratory factor analysis (EFA) and established internal consistency using Cronbach’s alpha on a subset of the analytical sample data (n=384). The resulting factors fit our a priori assumption of the factors theorized to characterize affect towards engineering professional practice. Using the remaining data (n=904), we conducted a confirmatory factor analysis on the reduced set of items resulting from EFA. The results indicate an emergent factor structure for affect towards elements of engineering practice. 

   more » « less
3. Exploring the Relationship Between Students’ Engineering Identity and Leadership Self-Efficacy

   Schell, William J.; Hughes, Bryce E.; Tallman, Brett; Annand, Emma; Beigel, Romy; Kwapisz, Monika B. (June 2019, American Society for Engineering Education)

   In order to lead the social process required to solve society’s grandest challenges and ensure that the capabilities of an expanded engineering workforce are successfully harnessed, new engineers must be more than just technical experts, they must also be technical leaders. Thankfully, greater numbers of engineering educators are recognizing this need and are consequently establishing engineering leadership certificates, minors, and even full degree programs through centers at universities throughout the country. However, for these programs to reach their full potential, engineering educators must be successful in integrating leadership into the very identity of engineers. This study seeks to better understand the relationship between engineering identity and leadership, so tools can be developed that enable engineering educators to more effectively integrate leadership into an engineering identity. This paper explores this relationship using a national sample of 918 engineering students who participated in the 2013 College Senior Survey (CSS). The CSS is administered by the Higher Education Research Institute (HERI) at UCLA to college students at the end of their fourth year of college; data from the CSS are then matched to students’ prior responses on the 2009 Freshman Survey (TFS), which was administered when they first started college, to create a longitudinal sample. Using a leadership construct developed by HERI as the outcome variable, this work utilizes Hierarchical Linear Modelling (HLM) to examine the impact of engineering identity and a host of other factors shown to be important in college student development on leadership. HLM is especially appropriate since individual student cases are grouped by schools, and predictor variables include both student-level and institution-level variables. The leadership construct, referred to as leadership self-efficacy in this work, includes self-rated growth in leadership ability, self-rating of leadership ability relative to one’s peers, participation in a leadership role and/or leadership training, and perceived effectiveness leading an organization. The primary independent variable of interest was a factor measuring engineering identity comprised of items available on both the TFS and CSS instruments. Including this measure of engineering identity from two different time periods in the model provides the relationship between engineering identity in the fourth year and leadership self-efficacy, controlling for engineering identity in the first year as a pretest. Statistically significant results were found across each of the areas tested, including the fourth-year engineering identity factor as well as several collegiate experiences, pre-college experiences, major, and institutional variables. Taken together, these results present a nuanced picture of what matters to predicting leadership outcomes for undergraduate engineering students. For example, while engineering identity is a significant positive predictor of the leadership construct, computer engineers score lower than mechanical engineers on leadership, while interacting with faculty appears to enhance leadership self-efficacy. 

   more » « less
4. Prediction of Engineering Identity in Engineering Graduate Students

   https://doi.org/10.1109/TE.2019.2901777  

   Choe, Nathan Hyungsok; Borrego, Maura (March 2019, IEEE Transactions on Education)

   Contribution: This study shows that identification with engineering for engineering graduate students is positively and significantly predicted by engineering interest, competence, recognition, and interpersonal skills competence. Background: Prior studies of engineering identity on undergraduates identified several factors (e.g., engineering interest, engineering recognition) as positive predictors of identification of engineering. Engineering competence, achieved by participating in design projects, is a crucial part of students’ efforts to become more innovative engineers. Identity theory is used to understand undergraduates’ persistence in engineering, as students with stronger engineering identification are more likely to persist. More work is needed focusing on graduate students. Research Questions: Do engineering identity measurement frameworks studied for undergraduate students also apply to graduate students? Do they correlate with intention to complete the degree? What predicts the engineering identity of engineering Master's and doctoral students? Methodology: Interviews informed development and adaptation of a multi-scale survey instrument. Factor analyses identified four factors that relate to graduate engineering identity: engineering interest, engineering recognition, engineering competence, and interpersonal skills competence. Three sequential multiple linear regression models were used to predict engineering graduate students’ engineering identity. Findings: The final regression model, which includes student characteristics and the four factors resulting from Confirmatory Factor Analysis, predicts 60% of the variance in engineering identity—substantially more than similar undergraduate engineering identity models. All four factors were significant and positive predictors of graduate students’ engineering identity. The engineering recognition factor in particular needed adaptation to emphasize peers and faculty members over family, although family remained important. 

   more » « less
5. Work in Progress: Understanding Student Perceptions of Stress as part of Engineering Culture

   Cross, Kelly J.; Jensen, Karin J. (January 2018, American Society of Engineering Education Conference Proceedings)

   High levels of stress and anxiety are common amongst college students, particularly engineering students. Students report lack of sleep, grades, competition, change in lifestyle, and other significant stressors throughout their undergraduate education (1, 2). Stress and anxiety have been shown to negatively impact student experience (3-6), academic performance (6-8), and retention (9). Previous studies have focused on identifying factors that cause individual students stress while completing undergraduate engineering degree programs (1). However, it not well-understood how a culture of stress is perceived and is propagated in engineering programs or how this culture impacts student levels of identification with engineering. Further, the impact of student stress has not been directly considered in engineering regarding recruitment, retention, and success. Therefore, our guiding research question is: Does the engineering culture create stress for students that hinder their engineering identity development? To answer our research question, we designed a sequential mixed methods study with equal priority of quantitative survey data and qualitative individual interviews. Our study participants are undergraduate engineering students across all levels and majors at a large, public university. Our sample goal is 2000 engineering student respondents. We combined three published surveys to build our quantitative data collection instrument, including the Depression Anxiety Stress Scales (DASS), Identification with engineering subscale, and Engineering Department Inclusion Level subscale. The objective of the quantitative instrument is to illuminate individual perceptions of the existence of an engineering stress culture (ESC) and create an efficient tool to measure the impact ESC on engineering identity development. Specifically, we seek to understand the relationships among the following constructs; 1) identification with engineering, 2) stress and anxiety, and 3) feelings of inclusion within their department. The focus of this paper presents the results of the pilot of the proposed instrument with 20 participants and a detailed data collection and analysis process. In an effort to validate our instrument, we conducted a pilot study to refine our data collection process and the results will guide the data collection for the larger study. In addition to identifying relationships among construct, the survey data will be further analyzed to specify which demographics are mediating or moderating factors of these relationships. For example, does a student’s 1st generation status influence their perception of stress or engineering identity development? Our analysis may identify discipline-specific stressors and characterize culture components that promote student anxiety and stress. Our objective is to validate our survey instrument and use it to inform the protocol for the follow-up interviews to gain a deeper understanding of the responses to the survey instrument. Understanding what students view as stressful and how students identify stress as an element of program culture will support the development of interventions to mitigate student stress. References 1. Schneider L (2007) Perceived stress among engineering students. A Paper Presented at St. Lawrence Section Conference. Toronto, Canada. Retrieved from: www. asee. morrisville. edu. 2. Ross SE, Niebling BC, & Heckert TM (1999) Sources of stress among college students. Social psychology 61(5):841-846. 3. Goldman CS & Wong EH (1997) Stress and the college student. Education 117(4):604-611. 4. Hudd SS, et al. (2000) Stress at college: Effects on health habits, health status and self-esteem. College Student Journal 34(2):217-228. 5. Macgeorge EL, Samter W, & Gillihan SJ (2005) Academic Stress, Supportive Communication, and Health A version of this paper was presented at the 2005 International Communication Association convention in New York City. Communication Education 54(4):365-372. 6. Burt KB & Paysnick AA (2014) Identity, stress, and behavioral and emotional problems in undergraduates: Evidence for interaction effects. Journal of college student development 55(4):368-384. 7. Felsten G & Wilcox K (1992) Influences of stress and situation-specific mastery beliefs and satisfaction with social support on well-being and academic performance. Psychological Reports 70(1):291-303. 8. Pritchard ME & Wilson GS (2003) Using emotional and social factors to predict student success. Journal of college student development 44(1):18-28. 9. Zhang Z & RiCharde RS (1998) Prediction and Analysis of Freshman Retention. AIR 1998 Annual Forum Paper. 

   more » « less