Conference Session

DEED Technical Session 2: Postcard Session

Collection

2022 ASEE Annual Conference & Exposition

Authors

Davor Copic, United States Coast Guard Academy; Nathan Barnes, United States Coast Guard Academy; Joshua Pennington, United States Coast Guard Academy; Alexandria Bass; Joseph Camean, United States Coast Guard Academy; Richard Freeman, United States Coast Guard Academy

means andstandard deviations (SD). These summary results are shown Table 4. The difference in both designand feature novelty between CB levels is compared using the Student’s t-Test, and, in all cases, foundnot to be statistically significant at an alpha value of 0.1. This is suggestive of design novelty notplaying a role in the performance of the boats, at least as measured by CB level. The reason for this isnot clear, but it may reflect the limitation of CB as a performance metric. Table 4. Novelty mean and SD per boat feature grouped by performance. Block Hull shape Bow shape Stern shape Structure Design novelty coefficient Mean

Conference Session

Biomedical Engineering Division: Integrating Design Across the BioE/BME Curriculum

Collection

2022 ASEE Annual Conference & Exposition

Authors

Mostafa Elsaadany, University of Arkansas; Mary Jia, University of Arkansas; Jordan Crosby, University of Arkansas; Raj Rao, University of Arkansas

relationto CAD-related software and simulations were heavily biased toward no experience (Figure 4),which confirms that students are not likely to have used SolidWorks in their undergraduatecareer prior to this Sophomore class. Notably, the students in this study were not included in thecohort that was provided a SolidWorks module in the intro course for biomedical engineeringand has yet to take the Senior Design course that typically requires SolidWorks for prototyping.Therefore, their curriculum up to this point has included zero basic SolidWorks training and thedistribution of students with training in 3D design reflects this.For questions gauging likeliness to use SolidWorks in students’ future careers and studentinterest in SolidWorks

Conference Session

Student Division Technical 2: Instruction & Learning Delivery

Collection

2022 ASEE Annual Conference & Exposition

Authors

Ibukun Osunbunmi, Utah State University - Engineering Education; Ning Fang, Utah State University

review, identifying the scope and statingthe research questions, defining inclusion criteria, finding and cataloging sources, critiquing andappraising, and synthesizing [3]. Other authors have suggested steps that are involved inconducting a systematic review [1, 4, 5, 6].Project-based learning processes are “learning by absorption” and “learning by reflection” [7]. Ithas been suggested that there are 13 forms of project-based learning including “communitystudies, designing technological gadgets, environmental projects, expeditionary projects, fieldstudy, foxfire approach, micro-society studies, museum approach, problem-based approach,project approach in early childhood education, senior project approach, service learning, andwork-based learning

Conference Session

Statics Fanatics 2

Collection

2022 ASEE Annual Conference & Exposition

Authors

Sridhar Condoor, Saint Louis University; Sanjay Jayaram, Saint Louis University; Jalil Kianfar, Saint Louis University

addressingthe lowest common denominator students and not challenging advanced students, designproblems provide differential learning opportunities that empower weak and advanced studentsin stretching their thinking abilities. Research questions help students explore the areas of theirinterest and learn state-of-the-art technology while reflecting on their findings. Table 3. Example of design projects and research experiences Sample Design Project Asymmetric Equilibrium - Design an aesthetic, efficient and economical Design structure with the problems inspiration from the concepts of equilibrium, center of gravity

Conference Session

Student Division Technical 3: Mixed - Research, Engineering Design, Design Thinking, and Curriculum Design

Collection

2022 ASEE Annual Conference & Exposition

Authors

Julia Brisbane, Virginia Polytechnic Institute and State University; Jeremi London, Virginia Polytechnic Institute and State University; Kingsley Reeves, University of South Florida

the aim todetermine the extent to which tolerance for ambiguity can be influenced by introducing thedesign process in an introductory probability and statistics course to help deal with uncertainty.AcknowledgementsThis work is supported by the U.S. National Science Foundation award #2106242. Any opinions,findings, and conclusions or recommendations expressed in this material are those of the authorsand do not necessarily reflect the views of the National Science Foundation.References[1] “Grand Challenges - 14 Grand Challenges for Engineering.” http://www.engineeringchallenges.org/challenges.aspx (accessed Jan. 31, 2022).[2] C. J. Atman, O. Eris, J. McDonnell, M. E. Cardella, and J. L. Borgford-Parnell, “Engineering Design Education

Conference Session

Software Engineering Division Technical Session 1

Collection

2022 ASEE Annual Conference & Exposition

Authors

Margaret Ellis; Ryan Gniadek, Virginia Polytechnic Institute and State University; Godmar Back, Virginia Polytechnic Institute and State University; Kirk Cameron, Virginia Polytechnic Institute and State University

container,” GitLab. [Online]. Available:https://docs.gitlab.com/runner/install/docker.html. [Accessed: 2021].AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant Nos. CNS1565314 and CNS 1939076. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.

Conference Session

Entrepreneurship & Engineering Innovation Division Technical Session 5

Collection

2022 ASEE Annual Conference & Exposition

Authors

Lauri Olivier, Villanova University; Megan Kempf; Rick Stumpf, Villanova University

Entrepreneurship Summer Institute at Villanova UniversityAbstract. We recently developed a multilayered mentor model for our popular EngineeringEntrepreneurship Summer Institute at Villanova University. Our multilayered mentor modellayers the experience, social capital and empathy associated with peer mentoring together withthe transfer of knowledge, skills, and ability associated with traditional mentors. Peer mentors,selected from recent graduates of our Engineering Entrepreneurship Summer Institute, werepaired with successful entrepreneurs to guide student venture teams. The multilayered mentormodel, developed to reflect current best mentor practices, included mentor matching, goalsetting, coaching and guidance. Our exit survey

Conference Session

Student Division Technical 4: Student Experience & Competencies

Collection

2022 ASEE Annual Conference & Exposition

Authors

Hamidreza Taimoory, Virginia Polytechnic Institute and State University; David Knight, Virginia Polytechnic Institute and State University; Walter Lee, Virginia Polytechnic Institute and State University

and donot necessarily reflect the views of the National Science Foundation.Reference[1] W. C. Lee and H. M. Matusovich, “A Model of Co-Curricular Support for Undergraduate Engineering Students,” J. Eng. Educ., vol. 105, no. 3, pp. 406–430, Jul. 2016, doi: 10.1002/jee.20123.[2] M. K. Brown, C. Hershock, C. J. Finelli, and C. O’Neal, “Teaching for retention in science, engineering, and math disciplines: A guide for faculty,” Occas. Pap., vol. 25, pp. 1–12, 2009.[3] R. M. Felder, G. N. Felder, and E. J. Dietz, “A Longitudinal Study of Engineering Student Performance and Retention. V. Comparisons with Traditionally-Taught Students,” J. Eng. Educ., vol. 87, no. 4, pp. 469–480, Oct. 1998, doi: 10.1002/j.2168

Conference Session

PCEE Technical Session 5: STEM Teacher Instructional Moves

Collection

2022 ASEE Annual Conference & Exposition

Authors

Shaffiq Welji, University of Georgia; James Drimalla, University of Georgia; Aida Alibek, University of Georgia; AnnaMarie Conner; Lorraine Franco; Jenna Menke, University of Georgia; Tim Foutz, University of Georgia; Barbara Crawford

analytics to understand the learning pathways of novice programmers,” Journal of the Learning Sciences vol. 22, no. 4, 2013. [Online]. Available: https://doi.org/10.1080/10508406.2013.836655. (Accessed Feb. 12, 2022).[17] Ozobot. “OzoBlockly.” Ozobot.com. https://ozobot.com/create/ozoblockly. (Accessed Feb. 12, 2022).AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant #1741910. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.

Conference Session

Mechanical Engineering: Thermodynamics

Collection

2022 ASEE Annual Conference & Exposition

Authors

Emmanuel Glakpe, Howard University

wellfor future classes leading to the award of a degree. Different course instructors have differentstyles of teaching and are reflected on what students learn and understand after taking aparticular course. It is up to the individual instructor to determine who passed and who failed acourse based on some general guidelines provided in the course outline. A few of the publishedliterature [4-12] have extensively documented the difficulty students face in thermodynamicsclasses. One would assume that as the science of energy, and since energy is used in everydayactivities, students of thermodynamics would embrace the subject matter and do well in a classon the subject matter. Among the recommendations [10] for improving the situation are the useof

Conference Session

NEE Technical Session - Innovative Teaching Strategies II

Collection

2022 ASEE Annual Conference & Exposition

Authors

Ariful Bhuiyan; Jana Willis; Roberto Dugnani; Felipe Trujillo-Wheeler, University of Houston - Clear Lake

Kaczala, , Eccles, 2005). Stage 1 associates the codes discovered in stage 0with the four subjective task value (STV) categories outlined by Eccles: (a) accomplishment, (b)intrinsic, (c) utility, and (d) relative cost. The definition of Attainment is how an individual'sview of a task reflects their sense of self. Intrinsic value, also known as interest value, is theenjoyment individuals have while performing a task. Utility value is described as a student'sview of the future involvement of a particular task, and relative cost is the cost associated withengaging in a particular task, as measured by time, effort, or psychological aspects. Table 1: Coding scheme at stage-0 TotalCategory Code

Conference Session

Aerospace Division Technical Session: New and Innovative Technologies in Aerospace

Collection

2022 ASEE Annual Conference & Exposition

Authors

Sanjay Jayaram, Saint Louis University; Hunter Pritzlaff, Saint Louis University; Andrew Stack, Saint Louis University

. Inaddition, due to the nature of rocket combustion, sampling rates must be upwards of 1000 Hznear the combustion chamber to reduce the effects of aliasing (2). For measuring the pressures on the combustion chamber as well as the tanks, straingauges were examined as a possible choice. Strain gauges provide an effective way to measurepressure using hoop stress (3). It should be noted that this measurement is a derivedmeasurement, however the benefits of a strain gauge’s non-intrusiveness far make up for anydownsides at this stage of development at RPL.Data Acquisition System Design Goals The main goal of the DAQ is to be quickly set up and applied to many different prototypedesigns. The selection of sensors reflects this as the only

Conference Session

Engineering Design Graphics Division Technical Session 3

Collection

2022 ASEE Annual Conference & Exposition

Authors

Sheryl Sorby, University of Cincinnati; Savannah Stark, University of Cincinnati; Christina Carnahan, University of Cincinnati

curriculum includes 10 modules including the following topics: 1) surfacesand solids of revolution; 2) combining solid objects; 3) isometric drawings and coded plans; 4)orthographic drawings; 5) orthographic projections of inclined and curved surfaces; 6) flatpatterns; 7) rotation of objects about a single axis; 8) rotation of objects about two or more axes;9) object reflections and symmetry; and 10) cutting planes and cross sections. Longitudinalstudies have shown the efficacy of the curriculum [10], [11], [12]. While the National Science Board’s Vision 2030 suggests that increasing “STEM skills andopportunities for all Americans” [16] is essential for addressing the labor gap for technicalworkers in STEM fields, one group noticeably missing

Conference Session

NSF Grantees Poster Session

Collection

2022 ASEE Annual Conference & Exposition

Authors

Todd Freeborn, The University of Alabama

gateway course and reportedstudents’ experience. Students who have completed the prep course have a lower DFW rate(5.6%) in the gateway course compared to recent rates of all students in the gateway course(34.1%) and report high levels of satisfaction (4.8 out of 5) with the course and experience.AcknowledgementsThis material is based upon work supported by the National Science Foundation, specifically theS-STEM program of the Division of Undergraduate Education (DUE), under Grant No. 1642508.Any opinions, findings, conclusions, or recommendations expressed in this material are those ofthe author(s) and do not necessarily reflect the views of the National Science Foundation.References[1] T.J. Freeborn, S. Burkett, D. McCallum, E. Steele, S

Conference Session

NSF Grantees Poster Session

Collection

2022 ASEE Annual Conference & Exposition

Authors

Kimberly Cook-Chennault, Rutgers, The State University of New Jersey; Ahmad Farooq, Rutgers, The State University of New Jersey

previous internship experience) indicated that an engineer could engagein different aspects of the design and/or production process, so not physically taking measurementsdid not mean that one was not engaging in aspects of engineering. Therefore, participating in thelab did in fact affirm his engineering identity. Another man student affirmed this believe thoughhe had no previous internship experience prior to participating in this lab.5.2.7 Did any of aspects of the lab relate to your prior internship/work experiences? Only one of the three students who participated in the interviews indicated that he hadinternship experience. He did not think that the majority of the labs in school reflected anythingthat he had experienced while working

Conference Session

PCEE Technical Session 8: Engineering Design in Elementary School

Collection

2022 ASEE Annual Conference & Exposition

Authors

Ron Skinner, University of California, Santa Barbara; Danielle Harlow

grades[4], [10], [11].One study of teacher reflections on student response to design failure found that upperelementary students engaged in engineering design did not always experience design failure andthose who did, responded to design failure in a wide range of ways including denial that failurehad occurred by ignoring proper testing procedures [4].In addition to testing procedures that were ignored or test results that were not easilyinterpretable, this lack of design failure might also be explained by design challenges that weretoo easy and thus actually did not result in design failure [10], [12]. Through interviewsconducted with kindergarteners after they engaged in engineering design, Lottero-Perdue andTomayko [13] concluded that

Conference Session

Computing & Information Technology Division Technical Session 4

Collection

2022 ASEE Annual Conference & Exposition

Authors

Kylan Stewart; Bruce Debruhl; Zoe Wood

responding that they ‘strongly disagree’ or ‘disagree’ that their resume isimpressive. This measure of competence more closely matches the data reflected in (Q3) aboutstudent sense of their computer science identity. We did not find any statistically significant dif-ferences between white and BIPOC students or men and women in 2019 or 2020. 1 (Strongly Disagree) 2 3 4 5 (Strongly Agree) 100 n = 35 n = 33 80 n = 30 n = 27 60% n = 39 n = 22 40

Conference Session

ERM: Instruction and Engagement

Collection

2022 ASEE Annual Conference & Exposition

Authors

Rachel Sangree, The Johns Hopkins University

– 2018, but“chunked” into two to three - 20-minute lectures that were easier for students to digest.To ensure that students watched and retained some of the information from the video lectures,they were required to submit short electronic journal entries through the Learning ManagementSystem (LMS) before each class. This form of reflection is called “write to learn” and can helpstudents improve their ability to retrieve information, make connections between new and oldmaterial, and explain concepts in their own words. [14] These journal entries were used toassign the “preparation grade” (see Table 1), and the questions asked by students in their journalentries formed the basis of a short (10 – 15 minute) review of the lecture material at

Conference Session

ERM: Systematic Reviews!

Collection

2022 ASEE Annual Conference & Exposition

Authors

Ethan Geheb, University of Maine; Asli Sezen-Barrie, University of Maine; Karissa Tilbury

Engineering,” Journal of Engineering Education, vol. 105, no. 2, pp. 278–311, Apr. 2016.[28] A. Antink-Meyer and D. Z. Meyer, “Science teachers’ misconceptions in science and engineering distinctions: Reflections on modern research examples,” J. Sci. Teacher Educ., vol. 27, no. 6, pp. 625–647, 2016.[29] M. Koch, P. Lundh, and C. J. Harris, “Investigating STEM Support and Persistence Among Urban Teenage African American and Latina Girls Across Settings,” Urban Education, vol. 54, no. 2, pp. 243–273, Feb. 2019.[30] R. L. Carr and J. Strobel, “Engineering in the K-12 STEM Standards of the 50 U.S. States: An Analysis of Presence and Extent,” Journal of Engineering Education, vol. 101, no. 3, pp. 539–564, 2012.[31] M. Borrego

Conference Session

ERM: Exploring Educational Technology in Engineering

Collection

2022 ASEE Annual Conference & Exposition

Authors

Danielle Dickson; Rafal Jonczyk; Elif Gunay; Janet Van Hell, Pennsylvania State University; Zahed Siddique, University of Oklahoma

associations to determine whether an answer ismore or less distant in semantic space from the prompt word, with more distanced responsewords receiving higher creativity scores. The highest performing model combines output frommultiple semantic models of English word associations. However, the utility of SemDis has notbeen systematically tested on AUT outcomes produced across linguistically diverse students andsecond language learners.This is relevant for two main reasons. First, the models underlying the automated rating systemassume a uniformity of language exposure and ability that might not be reflected in morelinguistically diverse populations. Depending on language experience, some multilinguals mayhave smaller, and less accessible vocabularies

Conference Session

ERM: Student Professional Development: Professional Skills and Moving Beyond the Classroom

Collection

2022 ASEE Annual Conference & Exposition

Authors

Beata Johnson, Purdue University at West Lafayette (COE); Joyce Main, Purdue University at West Lafayette (COE)

also help inform university programming and advising tosupport students in these choices. In future research, we plan to explore further the interactions ofstudent participation in multiple extra-/co-curricular activities and how this participationinfluences students individually.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grants1842166 and 1505006. Any opinions, findings, conclusions, or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation. We thank Tram Dang, Athena Lin, Jocelyn Nardo, Christina Pantoja, Li Tan, andCasey Wright for their helpful feedback throughout the analysis and writing

Conference Session

Graduate Studies Division Technical Session 2

Collection

2022 ASEE Annual Conference & Exposition

Authors

Jutshi Agarwal, University of Cincinnati; Samieh Askarian, University of Cincinnati; Gregory Bucks, University of Cincinnati; Teri Murphy, University of Cincinnati

Feedback from other participants, peers, self -reflection Instructor level feedback Feedback of TAs from instructor of record, mentoring faculty Program level feedback Broader than individual feedback, such as standardized tests, department level review Unclear/Need more information Response open to multiple interpretations and leading to ambiguous coding Don’t know Respondent not sure what evidence should be needed for TPD evaluation No responseFindings Table 2 shows the distribution of responses across the codes for each of the questionsasked in the survey with some example responses. It must be pointed out that several responsesmentioned

Conference Session

Computers in Education 4 - Online and Distributed Learning I

Collection

2022 ASEE Annual Conference & Exposition

Authors

Mariana Silva, University of Illinois at Urbana - Champaign; Geoffrey Herman, University of Illinois at Urbana - Champaign; Yucheng Jiang; Seth Poulsen, University of Illinois at Urbana - Champaign; Matthew West, University of Illinois at Urbana - Champaign; Yueqi Jiang, University of Illinois at Urbana - Champaign

team roles can lead students to default intodomineering team leaders or passive free-loaders [25]. Evidence-based practices such as pairprogramming [12], role scripting [26, 27] and Process Oriented Guided Inquiry Learning(POGIL) [9, 13] have shown that providing students with structured roles can help themparticipate more equally during collaborative learning. Structured roles are designed to createpositive interdependence between the roles.In our classes, we based our structured roles on POGIL roles. The “recorder” writes the team’sanswers to problems, the “manager” is responsible for keeping the team on task, and the“reflector” is responsible for guiding the team in reflection activities on their learning process.POGIL has primarily been

Conference Session

Civil Engineering Division - Changing How We Teach: Flipping, Project-Based Learning, and More!

Collection

2022 ASEE Annual Conference & Exposition

Authors

Monique Head, University of Delaware; Christos Aloupis, University of Delaware; James Hanson, Rose-Hulman Institute of Technology; Allen Jayne, University of Delaware

both the virtual and in-personlearning environment.BackgroundThe abrupt interruption of human interaction, caused by COVID-19 pandemic, forced manyeducational institutions, globally, to seek alternatives to the conventional face-to-face instruction[1-4]. With the first pandemic wave hitting during the spring semester of 2020, universities in anattempt to deescalate the transmission of the virus pivoted to deliver instruction online in themiddle of the semester. With summer break intervening, the education community regrouped andhad some time to reflect on delivering high quality instruction online and how to improveexisting pedagogies when teaching in the virtual environment [5, 6], in order to get ready andpivot given the uncertainties of the

Conference Session

CPDD Technical Session 1 - Design of Professional Development Curricula

Collection

2022 ASEE Annual Conference & Exposition

Authors

Navid Yaghoubisharif, Oregon State University; Shane Brown, Oregon State University; Amy Brooks, Oregon State University

course content and future lesson plans. Implementation of interactivefeedback can be beneficial for instructors. He often asks students to provide feedback by self-reflecting on their learning instead of simply recalling facts learned in lectures. He mentioned thelimitation of getting feedback in some online classes resulted in less effective activities duringthe course. "But I think that the in-person, it's much easier because you get that feedbackfrom the students, right? You can see people's faces." In this situation, he used daily quizzesas a tool to gather additional feedback. This helped him for future activity design andimplementation. According to the instructor, after implementing feedback in the quizzes, they"realized that the students

Conference Session

WIED: Support for All in the WIED Community

Collection

2022 ASEE Annual Conference & Exposition

Authors

Nivia Diaz, Universidad Andres Bello; Angeles Dominguez, Tecnologico de Monterrey, Mexico; Universidad Andres Bello, Chile.

study is qualitative inductive, with an initial field immersion, data collection throughsemi-structured interviews, and interpretation of the content. The scope of the research isdescriptive [19]. The research design is non-experimental and cross-sectional, locating andcategorizing the data to provide the vision of the mining community in Chile. The sample selectionwas non-probabilistic.The study made a reflective, in-depth analysis with a complete description of the situation. Theparticipation requirement was to be a mining or supply company manager, a member of miningleadership associations, managers of universities, managers of mining research institutes, orprofessionals with experience working in companies and the university in teaching

Conference Session

Computers in Education 3 - Modulus I

Collection

2022 ASEE Annual Conference & Exposition

Authors

Andrew Deorio, University of Michigan; Christina Keefer, University of Michigan

use theresults of this study to validate our data. This paper then looks beyond the queueing tool toanalyze how automated feedback mechanisms affect wait times.4 MethodsIn this section, we describe data collection from peer teaching office hours queues, the context ofthe computer science curriculum, the different types of automated feedback mechanisms, and ourstatistical methods.The raw office hours queue data contains 195251 records, and after cleaning and filtering, thereare 105941 records reflecting 17 unique courses: 2 100-level, 4 200-level, 2 300-level, and 9400-level. The records occur between September 2016 and December 2019, before theCOVID-19 pandemic began.4.1 Data CollectionOur data set was collected from two web-based

Conference Session

Statics Fanatics 1

Collection

2022 ASEE Annual Conference & Exposition

Authors

Yemisi Oyewola, Utah State University; Brian Cowburn, Rochester Institute of Technology (COE); Ryan Barlow, zyBooks, A Wiley Brand; Wade Goodridge, Utah State University; Kurt Becker, Utah State University - Engineering Education

asked in a semi-structured interview. The questions will providea deeper understanding of quantitative results when students are able to contextualize theiranswers to the previous survey. One set of questions will attempt to answer, “What are thereasons provided by students, with regards to a change in self-efficacy, reflective of theimplementation of environmental and biological engineering problems in a statics course?”.Another set of questions will attempt to answer, “How does the composition of study groupswithin Statics impact self-efficacy of students engaged in solving homework problems?”.Also, more data would be collected in future semesters to reach a conclusion about the impact ofthese problems solely on biological and environmental

Conference Session

Environmental Engineering Division Technical Session 3

Collection

2022 ASEE Annual Conference & Exposition

Authors

Andrew Pfluger, United States Military Academy; Michael Butkus, United States Military Academy; Benjamin Michael Wallen P.E., United States Military Academy

least one-half of the selected embedded indicator assignments. For example, keyword “A” is “public health”, which was addressed in 8 embedded indicator assignments (2 timesin Course #1, 3 times in Course #2, and 3 times in Course #2). As we had selected 16 totalembedded indicator assignments across the three courses for SO 2, we were able to achieve the50% goal (i.e., 8 embedded indicator assignments address key word “A” of the 16 totalassignments, or 50%). Similarly, we were able to exceed the 50% goal for key words “B”through “H” (ranging from 9 / 16 (56%) to 13 / 16 (81%)).However, after reflection and in the vein of continuous improvement, we determined that ourinitial assessment approach captured in Table 3 failed to reach the level of

Conference Session

ECE Division Technical Session 2: Long-Term Institutional Outcome Evaluations and Capstone Innovations

Collection

2022 ASEE Annual Conference & Exposition

Authors

Alexander Mackay, University of Toronto; Hamid Timorabadi, University of Toronto