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1. Developing an Instrument to Measure Online Engineering Undergraduate Students’ Learning Experiences and Intentions to Persist

   Lee, E. ; Brunhaver, S. ; Bekki, J. ( January 2020 , Proceedings of the American Society for Engineering Education)

   The purpose of this study is to develop an instrument to measure student perceptions about the learning experiences in their online undergraduate engineering courses. Online education continues to grow broadly in higher education, but the movement toward acceptance and comprehensive utilization of online learning has generally been slower in engineering. Recently, however, there have been indicators that this could be changing. For example, ABET has accredited online undergraduate engineering degrees at Stony Brook University and Arizona State University (ASU), and an increasing number of other undergraduate engineering programs also offer online courses. During this period of transition in engineering education, further investigation about the online modality in the context of engineering education is needed, and survey instrumentation can support such investigations. The instrument presented in this paper is grounded in a Model for Online Course-level Persistence in Engineering (MOCPE), which was developed by our research team by combining two motivational frameworks used to study student persistence: the Expectancy x Value Theory of Achievement Motivation (EVT), and the ARCS model of motivational design. The initial MOCPE instrument contained 79 items related to students’ perceptions about the characteristics of their courses (i.e., the online learning management system, instructor practices, and peer support), expectancies of course success, course task values, perceived course difficulties, and intention to persist in the course. Evidence of validity and reliability was collected using a three-step process. First, we tested face and content validity of the instrument with experts in online engineering education and online undergraduate engineering students. Next, the survey was administered to the online undergraduate engineering student population at a large, Southwestern public university, and an exploratory factor analysis (EFA) was conducted on the responses. Lastly, evidence of reliability was obtained by computing the internal consistency of each resulting scale. The final instrument has seven scales with 67 items across 10 factors. The Cronbach alpha values for these scales range from 0.85 to 0.97. The full paper will provide complete details about the development and psychometric evaluation of the instrument, including evidence of and reliability. The instrument described in this paper will ultimately be used as part of a larger, National Science Foundation-funded project investigating the factors influencing online undergraduate engineering student persistence. It is currently being used in the context of this project to conduct a longitudinal study intended to understand the relationships between the experiences of online undergraduate engineering students in their courses and their intentions to persist in the course. We anticipate that the instrument will be of interest and use to other engineering education researchers who are also interested in studying the population of online students. 

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2. Student perceptions of and learning in makerspaces embedded in their undergraduate engineering preparation programs

   Nadelson, L. S. ( April 2020 , ASEE annual conference)

   Building upon our two years of research on the use of makerspaces in undergraduate engineering programs, we engaged in a large-scale data collection from students enrolled in undergraduate engineering preparation programs with affiliated makerspaces established for a minimum of three years. Using web searches, and other sources of information (e.g. references from other researchers or faculty members), we have identified 28 institutions that met our criteria. Working with a third party, we gathered over 574 responses from undergraduate engineering students with makerspace experiences spread across the 28 institutions. To gather our data, we created and validated an online survey with a combination of quantitative and qualitative items. We constructed a survey with subscales aligned with motivation to learn, growth mindset, learning goal orientation, knowledge of engineering as a profession, and belongingness and inclusion, as associated with work within makerspaces. We found significant positive correlations among the variables, positive levels of motivation, growth mindset, knowledge of engineering as a profession, and belongingness. We found differences in levels for gender, engineering majors, and student class standing. We discuss the implications for our findings in the context of undergraduate engineering student learning in makerspaces. 

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3. Student perceptions of and learning in makerspaces embedded in their undergraduate engineering preparation programs.

   Nadelson, L. S. ; Villanueva, I. ; Bouwma-Gearhart, J. ; Soto, E. ; Lenhart, C. ; Youmans, K. ; & Choi, Y. H. ( January 2020 , Zone 1 Conference of the American Society for Engineering Education)

   Building upon our two years of research on the use of makerspaces in undergraduate engineering programs, we engaged in a large-scale data collection from students enrolled in undergraduate engineering preparation programs with affiliated makerspaces established for a minimum of three years. Using web searches, and other sources of information (e.g. references from other researchers or faculty members), we have identified 28 institutions that met our criteria. Working with a third party, we gathered over 574 responses from undergraduate engineering students with makerspace experiences spread across the 28 institutions. To gather our data, we created and validated an online survey with a combination of quantitative and qualitative items. We constructed a survey with subscales aligned with motivation to learn, growth mindset, learning goal orientation, knowledge of engineering as a profession, and belongingness and inclusion, as associated with work within makerspaces. We found significant positive correlations among the variables, positive levels of motivation, growth mindset, knowledge of engineering as a profession, and belongingness. We found differences in levels for gender, engineering majors, and student class standing. We discuss the implications for our findings in the context of undergraduate engineering student learning in makerspaces. 

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4. Learning in Academic Makerspaces: Preliminary Case Studies of How Academic Makerspaces Afford Learning for Female Students

   Tomko, Megan ; Nagel, Robert ; Alemán, Melissa ; Newstetter, Wendy ; Linsey, Julie ( July 2018 , ASEE annual conference & exposition proceedings)

   Recognizing the value of engagement in learning, recent engineering education initiatives have worked to encourage all types of students to pursue engineering while also facilitating the construction of makerspaces on university campuses. Makerspaces have the potential to engage a broader range of students by providing unique and personalized pathways into engineering. While this aims to improve the quality of an engineer’s education, the reality settles in when we begin to question whether these makerspaces are, in fact, encouraging learning in engineering for all types of students. In this work, we focus on investigating how a university makerspace affords learning for female students. We implemented an in-depth phenomenologically based interviewing approach which involved a series of three 90-minute semi-structured interviews with six highly engaged female undergraduate students involved in different makerspaces at a single university. The purpose of these interviews was to engage the students in their experiences with the makerspaces and the projects that they work on in this space, so as to inform how these spaces afford learning, specifically the impact on female student learning. All interviews were conducted by the same female graduate student. This work focuses on the second interviews of two females who had student worker roles in their respective makerspaces on campus. All of the interviews for these two females were transcribed resulting in 180 pages of single-spaced transcriptions, and the second interviews were analyzed through two phases of qualitative data analysis. Types of learning emerged in multiple forms and are presented via case studies of each female participant. For case one, these types of learning include machines learning, social learning, design learning, and self-learning. In the second case, the types of learning are tool learning, resourceful learning, space learning, and management learning. These types of learning are then further discussed according to engineering education pedagogy and implications. Makerspaces are often labeled as “open, learning environments,” and this work demonstrates how these spaces facilitate unique forms of learning that engage these women in the makerspace. 

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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. 

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