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1. First-year engineering students’ identification of models in engineering

   Shah, Nishith ; Thaker, Pujan ; Rodgers, Kelsey J. ; Verleger, Matthew A. ( April 2020 , Discovery Day presented by The Office of Undergraduate Research at Embry-Riddle Aeronautical University)

   Background To succeed in engineering careers, students must be able to create and apply models to certain problems. The different types of models include physical, mathematical, computational, graphical, and financial, which are used both in academics, research, and industry. However, many students struggle to define, create, and apply relevant models in their engineering courses. Purpose (Research Questions) The research questions investigated in this study are: (1) What types of models do engineering students identify before and after completing a first-year engineering course? (2) How do students’ responses compare across different courses (a graphical communications course - EGR 120 and a programming course - EGR 115), and sections? Design/Methods The data used for this study were collected in two introductory first-year engineering courses offered during Fall 2019, EGR 115 and EGR 120. Students’ responses to a survey about modeling were qualitatively analyzed. The survey was given at the beginning and the end of the courses. The data analyzed consisted of 560 pre and post surveys for EGR 115 and 384 pre and post surveys for EGR 120. Results Once the analysis is complete, we are hoping to find that the students can better define and apply models in their engineering coursesmore »after they have completed the EGR 115 and/or EGR 120 courses.« less
2. Effects of High Impact Educational Practices on engineering and computer science student participation, persistence, and success at land grant universities: YEAR 2.

   Asghar, M. ( August 2022 , 2022 ASEE Annual Conference & Exposition)

   Effects of High Impact Educational Practices on Engineering and Computer Science Student Participation, Persistence, and Success at Land Grant Universities: Award# RIEF-1927218 – Year 2 Abstract Funded by the National Science Foundation (NSF), this project aims to investigate and identify associations (if any) that exist between student participation in High Impact Educational Practices (HIP) and their educational outcomes in undergraduate engineering and computer science (E/CS) programs. To understand the effects of HIP participation among E/CS students from groups historically underrepresented and underserved in E/CS, this study takes place within the rural, public university context at two western land grant institutions (one of which is an Hispanic-serving institution). Conceptualizing diversity broadly, this study considers gender, race and ethnicity, and first-generation, transfer, and nontraditional student status to be facets of identity that contribute to the diversity of academic programs and the technical workforce. This sequential, explanatory, mixed-methods study is guided by the following research questions: 1. To what extent do E/CS students participate in HIP? 2. What relationships (if any) exist between E/CS student participation in HIP and their educational outcomes (i.e., persistence in major, academic performance, and graduation)? 3. How do contextual factors (e.g., institutional, programmatic, personal, social, financial, etc.) affectmore »E/CS student awareness of, interest in, and participation in HIP? During Project Year 1, a survey driven quantitative study was conducted. A survey informed by results of the National Survey of Student Engagement (NSSE) from each institution was developed and deployed. Survey respondents (N = 531) were students enrolled in undergraduate E/CS programs at either institution. Frequency distribution analyses were conducted to assess the respondents’ level of participation in extracurricular HIPs (i.e., global learning and study aboard, internships, learning communities, service and community-based learning, and undergraduate research) that have been shown in the literature to positively impact undergraduate student success. Further statistical analysis was conducted to understand the effects of HIP participation, coursework enjoyability, and confidence at completing a degree on the academic success of underrepresented and nontraditional E/CS students. Exploratory factor analysis was used to derive an "academic success" variable from five items that sought to measure how students persevere to attain academic goals. Results showed that a linear relationship in the target population exists and that the resultant multiple regression model is a good fit for the data. During the Project Year 2, survey results were used to develop focus group interview protocols and guide the purposive selection of focus group participants. Focus group interviews were conducted with a total of 27 undergraduates (12 males, 15 females, 16 engineering students, 11 computer science students) across both institutions via video conferencing (i.e., ZOOM) during the spring and fall 2021 semesters. Currently, verified focus group transcripts are being systematically analyzed and coded by a team of four trained coders to identify themes and answer the research questions. This paper will provide an overview of the preliminary themes so far identified. Future project activities during Project Year 3 will focus on refining themes identified during the focus group transcript analysis. Survey and focus group data will then be combined to develop deeper understandings of why and how E/CS students participate in the HIP at their university, taking into account the institutional and programmatic contexts at each institution. Ultimately, the project will develop and disseminate recommendations for improving diverse E/CS student awareness of, interest in, and participation in HIP, at similar land grant institutions nationally.« less
3. Types of Models Identified by First-Year Engineering Students

   Rodgers, K ; Thompson, A ; Verleger, M ; Marbouti, F ; Shah, N ; Thaker, P ( July 2021 , 2021 ASEE Annual Conference)

   This is a Complete Research paper. Understanding models is important for engineering students, but not often taught explicitly in first-year courses. Although there are many types of models in engineering, studies have shown that engineering students most commonly identify prototyping or physical models when asked about modeling. In order to evaluate students’ understanding of different types of models used in engineering and the effectiveness of interventions designed to teach modeling, a survey was developed. This paper describes development of a framework to categorize the types of engineering models that first-year engineering students discuss based on both previous literature and students’ responses to survey questions about models. In Fall 2019, the survey was administered to first-year engineering students to investigate their awareness of types of models and understanding of how to apply different types of models in solving engineering problems. Students’ responses to three questions from the survey were analyzed in this study: 1. What is a model in science, technology, engineering, and mathematics (STEM) fields?, 2. List different types of models that you can think of., and 3. Describe each different type of model you listed. Responses were categorized by model type and the framework was updated through an iterativemore »coding process. After four rounds of analysis of 30 different students’ responses, an acceptable percentage agreement was reached between independent researchers coding the data. Resulting frequencies of the various model types identified by students are presented along with representative student responses to provide insight into students’ understanding of models in STEM. This study is part of a larger project to understand the impact of modeling interventions on students’ awareness of models and their ability to build and apply models.« less
4. Types of Models Identified by First-Year Engineering Students

   Rodgers, Kelsey J. ; Thompson, Angela ; Verleger, Matthew A. ; Marbouti, Farshid ; Shah, Nishith ; Thaker, Pujan ( July 2021 , Zone 1 Conference of the American Society for Engineering Education)

   Understanding models is important for engineering students, but not often taught explicitly in first-year courses. Although there are many types of models in engineering, studies have shown that engineering students most commonly identify prototyping or physical models when asked about modeling. In order to evaluate students’ understanding of different types of models used in engineering and the effectiveness of interventions designed to teach modeling, a survey was developed. This paper describes development of a framework to categorize the types of engineering models that first-year engineering students discuss based on both previous literature and students’ responses to survey questions about models. In Fall 2019, the survey was administered to first-year engineering students to investigate their awareness of types of models and understanding of how to apply different types of models in solving engineering problems. Students’ responses to three questions from the survey were analyzed in this study: 1. What is a model in science, technology, engineering, and mathematics (STEM) fields?, 2. List different types of models that you can think of., and 3. Describe each different type of model you listed. Responses were categorized by model type and the framework was updated through an iterative coding process. After four rounds ofmore »analysis of 30 different students’ responses, an acceptable percentage agreement was reached between independent researchers coding the data. Resulting frequencies of the various model types identified by students are presented along with representative student responses to provide insight into students’ understanding of models in STEM. This study is part of a larger project to understand the impact of modeling interventions on students’ awareness of models and their ability to build and apply models.« less
5. Instructor Use of Movable Furniture and Technology in Flexible Classroom Spaces

   Johnson, A.W. ; Swenson, J.E.S. ; Wiwel, C.R. ; Finelli, C.J. ( June 2019 , ASEE annual conference & exposition proceedings)

   Flexible classroom spaces, which have movable tables and chairs that can be easily rearranged into different layouts, make it easier for instructors to effectively implement active learning than a traditional lecture hall. Instructors can move throughout the room to interact with students during active learning, and they can rearrange the tables into small groups to facilitate conversation between students. Classroom technology, such as wall-mounted monitors and movable whiteboards, also facilitates active learning by allowing students to collaborate. In addition to enabling active learning, the flexible classroom can still be arranged in front-facing rows that support traditional lecture-based pedagogies. As a result, instructors do not have to make time- and effort-intensive changes to the way their courses are taught in order to use the flexible classroom. Instead, they can make small changes to add active learning. We are in the second year of a study of flexible classroom spaces funded by the National Science Foundation’s Division of Undergraduate Education. This project asks four research questions that investigate the relationships between the instructor, the students, and the classroom: 1) What pedagogy do instructors use in a flexible classroom space? 2) How do instructors take advantage of the instructional affordances (including the movablemore »furniture, movable whiteboards, wall-mounted whiteboards, and wall-mounted monitors) of a flexible classroom? 3) What is the impact of faculty professional development on instructors’ use of flexible classroom spaces? and 4) How does the classroom influence the ways students interpret and engage in group learning activities? In the first year of our study we have developed five research instruments to answer these questions: a three-part classroom observation protocol, an instructor interview protocol, two instructor surveys, and a student survey. We have collected data from nine courses taught in one of ten flexible classrooms at the University of Michigan during the Fall 2018 semester. Two of these courses were first-year introduction to engineering courses co-taught by two instructors, and the other seven courses were sophomore- and junior-level core technical courses taught by one instructor. Five instructors participated in a faculty learning community that met three times during the semester to discuss active learning, to learn how to make the best use of the flexible classroom affordances, and to plan activities to implement in their courses. In each course we gathered data from the perspective of the instructor (through pre- and post-semester interviews), the researcher (through observations of three class meetings with our observation protocol), and the students (through conducting a student survey at the end of the semester). This poster presents qualitative and qualitative analyses of these data to answer our research questions, along with evidence based best practices for effectively using a flexible classroom.« less