Conference Session

Research Methods I: Developing Research Tools and Methods

Collection

2016 ASEE Annual Conference & Exposition

Authors

Freddy Solis, Purdue University, West Lafayette; Alexandra Coso Strong, Franklin W. Olin College of Engineering; Robin Adams, Purdue University, West Lafayette; Jennifer A. Turns, University of Washington; David P. Crismond, City College of New York

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Educational Research and Methods

interested in all aspects of engineering education, including how to support engineering students in reflecting on experience, how to help engineering educators make effective teach- ing decisions, and the application of ideas from complexity science to the challenges of engineering education.Dr. David P. Crismond, City College of New York David P. Crismond is an Associate Professor in the School of Education at City College, City University of New York, 138th St. & Convent Ave. NAC 6/207b, New York, NY 10031; dcrismond@ccny.cuny.edu. His research interests relate to engineering design cognition and instruction, and helping teachers build their own design pedagogical content knowledge, create their own video-based

Conference Session

Faculty Development I: Attitudes Towards Teaching

Collection

2016 ASEE Annual Conference & Exposition

Authors

Kristen Bethke Wendell, Tufts University; Jessica E. S. Swenson, Tufts Center for Engineering Education and Outreach; Tejaswini S. Dalvi, University of Massachusetts, Boston

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science teaching methods course and volunteered for a follow-up engineeringprofessional development institute, which was the context for this study. Data sources includedvideos of the teachers solving design problems, teachers’ written and oral reflections onengineering teaching experiences, and researcher field notes from the after-school week. Wegenerated thick descriptions of the cases of Ana and Ben and used these to develop conjecturesabout their engineering epistemologies. Following microethnographic methodology andstrategies from discourse analysis, we re-examined transcripts and other data artifacts forconfirming and disconfirming evidence of these conjectures.We found that Ana and Ben framed engineering learning as building knowledge

Conference Session

Student Success III: Affect and Attitudes

Collection

2016 ASEE Annual Conference & Exposition

Authors

Paul M. Yanik, Western Carolina University; Yanjun Yan, Western Carolina University; Sudhir Kaul, Western Carolina University; Chip W. Ferguson, Western Carolina University

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response to self-reported vulnerabilities and concerns of engineeringstudents. This paper presents data from practical efforts to identify and mitigate anxiety amongengineering students. A group of twenty-seven engineering and engineering technology studentswho were part of a scholarship program was asked to submit journal entries in which theyreflected on their fears and anxieties related to their participation in their degree program.Prominent themes which emerged from student reflection included time management and itseffects on academics and social activities, the likelihood of degree completion and success inengineering-specific coursework (e.g. senior capstone projects), and aspects of life followinggraduation such as handling accumulated

Conference Session

Student Success I: Interventions and Programs

Collection

2016 ASEE Annual Conference & Exposition

Authors

Joanna Perry Weaver, University of Louisville; Marci S. Decaro, University of Louisville; Jeffrey Lloyd Hieb, University of Louisville; Patricia A. Ralston, University of Louisville

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encouraging collaboration andreducing competition may increase achievement. Cooperative learning is one such instructionalstrategy that has been shown to improve affective outcomes, such as self-efficacy in students.12Cooperative Learning Group learning can take a variety of forms, and many of the terms to describe these formsare used interchangeably (e.g., cooperative, collaborative and problem-based learning13). Thesegroup learning varieties have been found to increase student motivation and achievement, butdiffer in terms of level of task structure, the assignment of roles to group members, use of sharedmaterials, involvement of instructors, and built-in reflection on the process. One particular grouplearning structure used in the current

Conference Session

Research Methods II: Meeting the Challenges of Engineering Education Research

Collection

2016 ASEE Annual Conference & Exposition

Authors

Brent K. Jesiek, Purdue University, West Lafayette; Natascha Trellinger Buswell, Purdue University, West Lafayette; Andrea Mazzurco, Purdue University, West Lafayette

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interviewed twice to capture new experiences and changes in perspectivesafter switching job roles, or after graduating and starting their first full-time positions. Anothergroup of subjects is being asked to respond to a series of guided reflection prompts during theirinternship or co-op rotations, culminating with an exit interview. This work goes beyondinvestigating how early career engineers grapple with technical problems to more broadly studythe nature of their encounters with boundary spanning situations and challenges, in part viewedthrough the boundary spanning typology and themes identified during the first project phase.This paper offers additional details about the development and evolution of our ethnographicinterviewing protocol, as well

Conference Session

Faculty Development II: Building Community Among STEM Educators

Collection

2016 ASEE Annual Conference & Exposition

Authors

Cheryl Allendoerfer, University of Washington; Ken Yasuhara, University of Washington, Center for Engineering Learning & Teaching; Jennifer A. Turns, University of Washington; Cynthia J. Atman, University of Washington

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Paper ID #16372Making an Impact on Engineering Education Communities: Learning fromthe Past and Looking ForwardDr. Cheryl Allendoerfer, University of Washington Dr. Allendoerfer is a Research Scientist in the College of Engineering at the University of Washington.Dr. Ken Yasuhara, University of Washington, Center for Engineering Learning & Teaching Ken Yasuhara is a research scientist at the Center for Engineering Learning & Teaching (CELT), a campus lead for the Consortium to Promote Reflection in Engineering Education (CPREE), and an instructional consultant in the Office for the Advancement of Engineering Teaching

Conference Session

Engineering Cultures and Identity

Collection

2016 ASEE Annual Conference & Exposition

Authors

Dina Verdin, Purdue University, West Lafayette ; Allison Godwin, Purdue University, West Lafayette; Brenda Capobianco, Purdue University, West Lafayette

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ASEE Diversity Committee, Diversity

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science teachers’ integration of the engineering design process to improve science learning. c American Society for Engineering Education, 2016 Systematic Review of the Funds of Knowledge Framework in STEM EducationIntroductionFor over two decades, there have been significant and consistent calls to increase the quantity anddiversity of engineering graduates to not only support the workforce demand but also to improveengineering solutions to better reflect the demographics of the U.S. population.1–4 However, thecall to increase the diversity of engineering often has been centered on simply increasing thepercentages of underrepresented groups in engineering. Once these

Conference Session

Research Methods I: Developing Research Tools and Methods

Collection

2016 ASEE Annual Conference & Exposition

Authors

Rosa Cabedo, Universidad Politecnica de Madrid; Tovar Caro Edmundo, Universidad Politecnica de Madrid; Manuel Castro, Universidad Nacional de Educacion a Distancia

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Michael Moore32.MaterialsThe interface used is RStudio Version 0.99.491 licenced under the terms of version 3 of theGNU Affero General Public License. Furthermore, R 3.2.3 GUI 1.66 Mavericks build (7060),part of the Free Software Foundation’s GNU Project, is the selected environment forperforming this study.Data cleaningThe dataset for this study was a reflection of real-world data, so in order to a successful KDD,it was needed an arduous effort in the data cleaning process. Data cleaning seeks an unifiedlogical view of databases with issues such as encouraging a single naming convention orprovision of strategies for data handling such as outliers or missing data30. This stage includedto deal with extrem outliers and in order to reduce their

Conference Session

Research Methods II: Meeting the Challenges of Engineering Education Research

Collection

2016 ASEE Annual Conference & Exposition

Authors

Todd Fernandez, Purdue University, West Lafayette; Allison Godwin, Purdue University, West Lafayette; Jacqueline Doyle, Florida International University; Dina Verdin, Purdue University, West Lafayette; Hank Boone, University of Nevada - Reno; Adam Kirn, University of Nevada - Reno; Lisa Benson, Clemson University; Geoff Potvin, Florida International University

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more diverse in acceptedcategories or more accepting of complex identities that may not fit a single category7(p8). Thesechanges reflect shifting social norms, and appropriate assumptions about the individuals beingasked demographic questions7,8. For example, the first US census, conducted in 1790, countedboth (Whitea) males and (White) females, which was a novel approach at the time. However, ittook 180 years, until 1970, for the census to differentiate people of Hispanic or Latino originfrom those who identified as White, a change introduced to help measure anti-discriminationcompliance9. Beyond simply including new categories or dimensions of demographics, smallchanges in how questions are asked such as a shift from “select one” a response

Conference Session

Works in Progress: Facilitating Student Success and Inclusion

Collection

2016 ASEE Annual Conference & Exposition

Authors

Julie P. Martin, Clemson University; Samuel S. Newton, Clemson University

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currently included in the CCW framework, such as spiritual capital. Thus,we believe that our work has the potential to extend these frameworks.AcknowledgementsThis material is based upon work supported by the National Science Foundation (NSF), undergrant number 1463808. Any opinions, findings, and conclusions or recommendations expressedin these findings are those of the authors and do not necessarily reflect the views of the NSF.References1. Frehill LM. The Gendered Construction of the Engineering Profession in the United States, 1893-1920. Men Masc. 2004;6(4):383-403. doi:10.1177/1097184X03260963.2. Pawley AL. What counts as “engineering”: Towards a redefinition. In: Pawley AL, Riley DM, eds. Engineering and Social Justice: In

Conference Session

Student Success II: Self-Regulatory, Metacognitive, and Professional Skills

Collection

2016 ASEE Annual Conference & Exposition

Authors

Sergio Celis, Universidad de Chile; Camila Aguirre, Universidad de Chile

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instructor was strict with punctuality and had control over class participation. On theother hand, he made students participate and asked questions that made students think andengage. Often our interviewees compared their positive experience in their second semesterwith negative ones in the first semester. They criticized the distant and blackboard-focusedinstructors they had in their first semester. Student also pointed out that they did not believeinstructors took into account the fact that there were some important differences regardingthe academic preparation among first year students.Self-awareness and Self-efficacy When students reflected on their moments of crisis and how they overcame it, all ofthem suggested that their failures were

Conference Session

Works in Progress: Innovation Through Propagation

Collection

2016 ASEE Annual Conference & Exposition

Authors

Susan M. Lord, University of San Diego; Denise Rutledge Simmons P.E., Virginia Tech; Larry J. Shuman, University of Pittsburgh

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betterunderstanding of racism in the same way sociologists do, for example. However, by not namingracism, we allow racism to persist.Data Driven ResearchData driven research is crucial to elucidate many pathway impediments in engineering, informthe community and move toward strategies for improvement. It is important that this researchtakes multiple forms: large quantitative studies, small qualitative investigations and personalself-reflections. We need to expand the categories of data we collect, where possible, includinggeneration in college status, veteran status, disability, LGBTQA (lesbian, gay, bi-sexual,transgender, queer or questioning, and ally or asexual). We also need to collect demographicvariables aligned with our current understanding of

Conference Session

Works in Progress: Assessment and Research Tools

Collection

2016 ASEE Annual Conference & Exposition

Authors

Tamara Ball, University of California - Santa Cruz; Linnea Kristina Beckett, University of California - Santa Cruz; Michael S. Isaacson, University of California - Santa Cruz

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California, Santa Cruz. Beckett’s continuing dissertation research examines a community-university collaboration situated in a low-income, predominantly Latino community, that created and used digital stories as artifacts and learning tools to engage members of the community (parents, teachers, district officials, union leaders, students, non-profit service providers, etc.) in reflection and dialogue around the economic, social, and cultural barriers that constituents face when advocating for student academic achievement, and to identify the strengths and solidarities that can be created to change the school system to better serve the student body (Beckett, Glass, & Moreno, 2012). Beckett has presented her research at

Conference Session

Engineering Cultures and Identity

Collection

2016 ASEE Annual Conference & Exposition

Authors

Stephen Secules, University of Maryland, College Park; Andrew Elby, University of Maryland, College Park; Ayush Gupta, University of Maryland, College Park

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pseudonyms), was much slower than the class norm (e.g., in labprogramming assignments), and two students appeared to particularly excel. By the end of terminterviews, the professor and other students could pick out who in particular was struggling andslow, as could Isaac himself, who reflected “I just don’t think I have the brain for programming.”This happened, in spite of the fact that programming in the professional world is rarely a timedactivity with “winners” easily noticed, and in spite of the fact that the students with whom hecompared himself arguably did not belong in an introductory programming class. Specifically,two out of the five students arrived through non-traditional pathways (a second bachelor’sdegree, a community college transfer

Conference Session

Mentoring, Advising, and Facilitating Learning

Collection

2016 ASEE Annual Conference & Exposition

Authors

Kevin O'Connor, University of Colorado, Boulder; Frederick A. Peck, University of Montana; Julie Cafarella, University of Colorado, Boulder; Jacob (Jenna) McWilliams, University of Colorado, Boulder

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QuestionsFollowing from this perspective, we aim to address the following questions: • How do representations of students by instructors function during a meeting in which instructors are working to determine grades for the course? More specifically: o How do the instructors position themselves and one another? o How do the instructors position students within categories that have consequences for success and lack of success? o How do these positionings reflect an instantiate particular ideologies and sets of values regarding calculus and its role in engineering?4. Research Context, Data, and MethodsOur research focuses on a the Access Program, a diversity-promoting program in

Conference Session

Works in Progress: Learning and Engagement

Collection

2016 ASEE Annual Conference & Exposition

Authors

Vimal Kumar Viswanathan, Tuskegee University; John T. Solomon, Tuskegee University

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environment19.In more recent work, these benchmarks are replaced with engagement indicators that arecategorized into four themes: academic challenge, learning with peers, experiences with facultyand campus environment48. The course material delivery framework outlined in this paper 1focuses on some of these benchmarks including higher order learning, reflective and integrativelearning and learning strategies (all under the “academic challenge” theme).There have been several research efforts over the past many years to improve engagement inengineering classrooms. These include the use of a technology-centered classroom20, formationof learning

Conference Session

Student Success I: Interventions and Programs

Collection

2016 ASEE Annual Conference & Exposition

Authors

Ben Pelleg, Drexel University; Kristin Imhoff, Drexel University ; Kevin Ayers, Drexel University; Philipp A. Boettcher

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fit within Zimmerman’s model of self-regulated learning. Students are encouragedto arrive with forethought, engage in performance, and reflect at the end of the tutoring session,time permitting. Additionally, tutors are trained on Gardner’s intelligences, learning styles, and thinkingstyles. Tutors are provided ample material and training to understand how to engage a studentbased on their demonstrated intelligences, learning styles and thinking styles. Trainingemphasizes to tutors that students receive and process information in a variety of ways. As peertutors they have the opportunity to create and increase learning opportunities for students15. Thetraining these tutors receives impacts their feedback efficacy16.III. Results and

Conference Session

Works in Progress: Learning and Engagement

Collection

2016 ASEE Annual Conference & Exposition

Authors

Catherine McGough, Clemson University; Adam Kirn, University of Nevada, Reno; Lisa Benson, Clemson University

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variability in the data14. However, this instrument did notinclude several characteristics of the FTP cone types identified in our subsequent qualitativework. The study described in this paper attempts to further refine our survey instrument bycreating items that quantitatively capture latent constructs reflected in our qualitative findings .MethodsUsing an instrument in research that does not assess what the researchers are presuming tomeasure can lead to incorrect results and wrong decisions18. In refining the MAE survey, carewas taken in the process of choosing factors, developing items, and testing for validity andreliability.Developing ItemsFactors were chosen based on the results from our previous qualitative research. Code categoriesthat were

Conference Session

Works in Progress: Learning and Engagement

Collection

2016 ASEE Annual Conference & Exposition

Authors

Alyssa Bellingham, Drexel University; John Kamal, Science Leadership Academy; Jessica S. Ward, Drexel University ; Adam K. Fontecchio, Drexel University

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mathematics (STEM) electives in high school. APh.D. student fellow from Drexel University and teacher from the Science Leadership Academy(SLA) in Philadelphia will teach robotics and engineering principles through open-endedprojects that address several of the NEA grand challenges. These projects are structured usingconstructivist pedagogy that ties into five core values: inquiry, research, collaboration,presentation, and reflection. We will introduce this study into an ethnically diverse robotics classcomprised of sophomore, junior, and senior students. The predisposition of students to studytopics relating to robotics will be assessed at the start of the study and then after each project hasbeen completed. Initially, predisposition will be

Conference Session

Works in Progress: Classroom Practice

Collection

2016 ASEE Annual Conference & Exposition

Authors

Ada Hurst, University of Waterloo; Oscar G. Nespoli, University of Waterloo

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order to optimize the classification effort while attempting toinform us of feedback activity nature and level. For example, we recognize the importance ofneed analysis and the emphasis that experts place on this stage verses novices, and so theimportant coding classifications of problem identification, representation and communication areprominent in our model. Additionally, the verification classification is available at each stage, asthis reflects best design practice. Figure 1. A generalized engineering design process model with coding classifications Initiating Planning

Conference Session

Engineering Cultures and Identity

Collection

2016 ASEE Annual Conference & Exposition

Authors

Alexis Prybutok, The University of Texas, Austin; Anita D. Patrick, University of Texas, Austin; Maura J. Borrego, University of Texas, Austin; Carolyn Conner Seepersad, University of Texas, Austin; Mary Jo Kirisits, University of Texas, Austin

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ASEE Diversity Committee, Diversity

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perceivethemselves to fit into a given group, in this case engineering,5 which in turn affects how theyprogress along the academic and career path in their field.6The engineering identity framework utilized in the study is partially based off a physics identitymodel composed of four basic factors: performance, competence, interest, and recognition.5,7Performance describes a student’s belief in their ability to perform in their classes or whenconducting engineering tasks.8 If a student performs poorly in class, they are less likely toidentify themselves as an engineer. Competence describes a student’s belief in their ability tounderstand engineering material, which is often similarly reflected in a student’s performance inclass.8 Interest describes how

Conference Session

Classroom Practice I: Active and Collaborative Learning

Collection

2016 ASEE Annual Conference & Exposition

Authors

Nancy K. Lape, Harvey Mudd College; Rachel Levy, Harvey Mudd College; Darryl H. Yong, Harvey Mudd College; Nancy Hankel, Cobblestone Applied Research & Evaluation, Inc.; Rebecca Eddy, Cobblestone Applied Research & Evaluation, Inc.

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inverted sections with those in control sections (i.e., traditional coursemodel). Treatment and control students completed the same measures (e.g., content assessmentsand student attitude surveys) and faculty members, who taught in both conditions, alsocompleted reflection papers related to their experiences. The guiding research questions for thestudy and an overview of the assessment measures are shown in Table 1 below (more details onassessment measures are included in a subsequent section of this paper). In the final year of thestudy, the researchers designed what they felt were “best practices” for the inverted model in allsections of their courses and the same outcome measures were used.Table1.EvaluationQuestionsandOutcomeMeasures

Conference Session

Classroom Practice III: Student-Centered Instruction

Collection

2016 ASEE Annual Conference & Exposition

Authors

Matthew Reyes, University of Oklahoma; Diana Bairaktarova, Virginia Tech; Anna Woodcock, California State University San Marcos

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Diversity

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Educational Research and Methods

. However, there were participants across a variety of ethnicities and from all studentclassifications, including graduate students. Other majors represented in the sample wereMechanical Engineering, Construction Science, Petroleum Engineering, and various otherEngineering programs. Data on handedness was also gathered and 12.9% (n=22) of theparticipants were left-handed which is reflective of the population as a whole. A summary of thedemographics of the participants is found in Table 3. Table 3: Demographic information Total Number of Participants: N = 170 Student Gender College Major Ethnicity

Conference Session

Works in Progress: Faculty Perspectives and Training

Collection

2016 ASEE Annual Conference & Exposition

Authors

Eugene Judson, Arizona State University; Lydia Ross, Arizona State University; James A. Middleton, Arizona State University; Stephen J. Krause, Arizona State University; Casey Jane Ankeny, Arizona State University; Ying-Chih Chen, Arizona State University; Robert J. Culbertson, Arizona State University; Keith D. Hjelmstad, Arizona State University; Yong Seok Park, Arizona State University

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to which respondents indicate their level of agreement on a Likert four-pointscale, from strongly agree to strongly disagree. Participants respond to the 26 items for each ofthe three classroom strategies (formative feedback, real-world applications, and initiatingstudent-to-student discussions), thus yielding 78 datum points.VECTERS additionally contains questions to collect demographic information about theinstructors as well as general information about the engineering course they are reflecting uponwhen responding to VECTERS. Instructor information includes information such as gender,ethnicity, and years of experience. Course information includes items to indicate the course-level(100 to 400), whether the course is required, and the

Conference Session

Classroom Practice II: Technology - and Game-Based Learning

Collection

2016 ASEE Annual Conference & Exposition

Authors

Derrick S. Harkness, Utah State University; Angela Minichiello, Utah State University; Joshua Marquit, Pennsylvania State University, Brandywine

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aremore frequently placed in the role of a passive spectator, it can often be difficult to get studentsto participate in class1-3. Despite some of its drawbacks and difficulties, discussion can also be used as a tool foractive learning when applied in an online discussion forum. During discussion, participants havethe opportunity to interact and collaborate with one another to fulfill and meet their learningneeds8. Furthermore, moving discussion to an online venue has several advantages. First,instructors and students have the convenience of being able to add to a discussionasynchronously. They have the time to reflect on discussion prompts and to formulate a well-thought out response. Second, online discussions can increase the amount of

Conference Session

Engineering Cultures and Identity

Collection

2016 ASEE Annual Conference & Exposition

Authors

Anita Patrick, University of Texas, Austin; Maura Borrego, University of Texas, Austin

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Conference Session

Research Methods I: Developing Research Tools and Methods

Collection

2016 ASEE Annual Conference & Exposition

Authors

Rachel Roberts, University of Washington School of Environmental and Forest Sciences; Denise Wilson, University of Washington

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psychographic measures developed in this study reveal nuances in student values ofsustainability and global citizenship, highlighting the importance of constant revision ofeducators’ understandings of student understanding in order to graduate informed and dedicatedstudents who will engage in, design for, and implement sustainability in their future careers.AcknowledgementsThe authors would like to gratefully acknowledge the National Science Foundation for theirsupport of this work under the TUES program (grant number DUE-1245464). Any opinions,findings, and conclusions or recommendations expressed in this material are those of the author(s)and do not necessarily reflect the views of the National Science Foundation.Bibliography 1. Beane, T.P., &