Conference Session

NSF Grantees Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Kent J. Crippen, University of Florida; Lorelie Imperial, University of Florida; Corey Payne, University of Florida; Chang-Yu Wu, University of Florida; Maria Korolev, University of Florida; Philip J. Brucat, University of Florida

Tagged Topics

NSF Grantees Poster Session

opportunity for students to practice doing science and form links betweenmacroscopic phenomena and molecular-level interpretations. Moreover, laboratory activities canmotivate students to learn more about chemical concepts [4]. For engineering majors, situatingthese activities in authentic practice strengthens the connection between the domain knowledgeof chemistry and its application in everyday work. Such activities target student retention byfocusing their work on authentic collaboration and learning chemistry in context, whichleverages student interest in order to build personal identity with being an engineer as well as thenecessary self-efficacy for persisting with challenging coursework [5]-[6].In this paper, we present results from usability

Conference Session

Engineering Career Attitudes

Collection

2018 ASEE Annual Conference & Exposition

Authors

Sarah A. Roller, University of Alabama, Huntsville; Sandra A. Lampley, University of Alabama, Huntsville; Monica Letrece Dillihunt, University of Alabama, Huntsville; Michael P.J. Benfield, University of Alabama, Huntsville; Matthew William Turner, University of Alabama, Huntsville

Tagged Divisions

Pre-College Engineering Education

actions, or efforts to implement one’s goals such asseeking additional training (Lent, 2013). For example, after gaining entry into medical school, astudent may have difficulty completing the required coursework. He may also conclude that thework conditions and rewards available as a medical doctor suit him less well than he initiallyanticipated. These learning experiences may incite the student to revise his self-efficacy beliefsand outcome expectations, leading to a shift in interest and goals (selection of a new career path).Other instruments based on SCCTWhile there are instruments that measure student outcomes (content knowledge, reasoning skills,psychosocial attributes) after participating in various disciplines of STEM fields (Minner

Conference Session

Engineering Physics and Physics Division Technical Session 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Genaro Zavala, Tecnologico de Monterrey, Monterrey, Mexico and Universidad Andres Bello, Santiago, Chile; Angeles Dominguez, Tecnologico de Monterrey, Monterrey, Mexico, and Universidad Andres Bello, Santiago, Chile

Tagged Topics

Diversity

Tagged Divisions

Engineering Physics and Physics

whoparticipated in a STEM competition. The review of the information gathered with these studentsis particularly critical in our main project since these students have a strong orientation towardSTEM. Students had a choice to participate in up to two subjects out of five available: physics,mathematics, biology, chemistry and computer science. We administered a science andtechnology questionnaire and 657 students out of 721 who participated in the competitionresponded. The survey included 13 questions in a Likert scale regarding self-efficacy andperception of the importance of the subjects presented. In the first section of the questionnaire,students responded to queries that assess physics, biology, chemistry, mathematics and computerscience self

Conference Session

Women in Engineering Division Technical Session 2

Collection

2018 ASEE Annual Conference & Exposition

Authors

Madison E. Andrews, University of Texas, Austin

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

include 1 mixed-method, 6 qualitative and 6quantitative studies. The sample sizes ranged from 4 to 15,771. All the sources included werepeer-reviewed and framed as research studies, rather than as practitioner papers. Additionally,the quality of each of these studies was systematically assessed. The full texts of the 13remaining qualifying studies were then examined and coded to reveal themes within the existingbody of knowledge.DiscussionAlthough the total number of publications examined was quite small, clear trends existed in thedata collected. The majority of articles measured students’ confidence or some form of self-efficacy in the classroom or the workplace. The quantitative studies measured a variety ofoutcomes, but almost never found

Conference Session

Connecting BME education to the "real world"

Collection

2018 ASEE Annual Conference & Exposition

Authors

Julia N. Savoy, University of Wisconsin-Madison; Mia K. Markey, The University of Texas at Austin; Henry Grady Rylander III P.E., The University of Texas at Austin

Tagged Divisions

Biomedical Engineering

were built on those used in previous studies of predoctoral student careerdevelopment, including the formation of self-efficacy beliefs [48] - [50]. We asked trainees howthey selected externship sites, what kind of projects they completed, the goals they identified,and whether those goals were achieved. We asked how participating in the externship influencedtheir self-efficacy beliefs, career interests, and goals. We finally asked about the extent to whichtrainees received feedback, and how the results of the externship were woven into futureprofessional development or research after returning to their home institution.Survey measures were developed from career development literature focusing on clinicalresearchers, predoctoral students, and

Conference Session

NSF Grantees Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Rachel Vitali, University of Michigan; Noel C. Perkins, University of Michigan; Cynthia J. Finelli, University of Michigan

Tagged Topics

NSF Grantees Poster Session

understanding of engineering dynamics with a collection of 29 questions focused on 14important and/or commonly misunderstood concepts. The results of this survey will evaluatehypothesis (1) that this intervention will increase student conceptual understanding of dynamics.The modified LAESE consists of 45 items designed to measure four subfactors: 1) engineeringself-efficacy, 2) course-specific self-efficacy, 3) intention to persist in the field, and 4) feelingsof inclusion. These items use a Likert-type scale, thus the values were normalized by themaximum value of the question’s scale, and the subfactor scores are computed as the arithmeticmean of the associated normalized item scores. This survey’s results will inform hypotheses (2)-(4) that this

Conference Session

Electrical and Computer Division Technical Session 7

Collection

2018 ASEE Annual Conference & Exposition

Authors

Joshua Alexéi García Sheridan, Virginia Tech; Richard M. Goff, Virginia Tech; Seungmo Kim, Georgia Southern University; Vuk Marojevic, Virginia Tech; Carl B. Dietrich, Virginia Tech

Tagged Divisions

Electrical and Computer

– Positive social functioning, good behavior related to feelings for the activity E_NSF Engagement – Negative social functioning, bad behavior related to feelings for the activity E_IL Engagement – Involvement in learning, the apprehension a student takes in an activity E_D Engagement – Disposition, particular actions performed by student that indicates their engagement in the activity SE Self-efficacy, the belief of the student that they can succeed in a particular taskMost measures were composed of 2-4 questions that were weighted equally into an average.“Self-efficacy (SE)” was composed of 4 questions

Conference Session

Women in Engineering Division Technical Session 5

Collection

2018 ASEE Annual Conference & Exposition

Authors

Kristin E. Sherwood, Stony Brook University; Angela M Kelly, Stony Brook University; Monica Bugallo, Stony Brook University

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

TransitionAbstractPeer mentoring has been shown to be an effective means of improving the retention of women inengineering, but few studies have explored the impact of participation on the development of theleadership abilities of undergraduate women. Transitioning to a leadership mentality as a peermentor has the potential to foster self-efficacy in science, technology, engineering, andmathematics (STEM) and socially stable academic relationships that may be replicated in post-graduate study and/or the workplace. This one-year study explored the experiences of junior andsenior female students in STEM majors (N=11) serving as mentors to first-year students in theWomen in Science and Engineering Honors Program (WISE) at Stony Brook University, a largeresearch

Conference Session

Women in Engineering Division Technical Session 2

Collection

2018 ASEE Annual Conference & Exposition

Authors

Malle R Schilling, University of Dayton; Margaret Pinnell, University of Dayton

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

,engineering, and math (STEM) a function of objectively measured math competencies. Second,students are more likely to select math and science courses when they are confident in theirability to do well in these courses. In other words, students with greater self-efficacy in scienceand math are more likely to choose these courses. Third, the value a student places on particularschool subjects are important for their career trajectory. Finally, the perception of strong socialsupport for achievement is vital when a student is considering a career choice, which isparticularly true for females [7].Through the use of implicit and self-report measure, it was found that elementary school femalessupported the stereotype that math is for males, demonstrating

Conference Session

NSF Grantees Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Muhammad Dawood, New Mexico State University; Karen Trujillo, New Mexico State University; Patti Wojahn, New Mexico State University; Melissa J. Guynn, New Mexico State University; Luis Manuel Rangel Jr.; S. M. Yahea Mahbub, New Mexico State University

Tagged Topics

NSF Grantees Poster Session

spanning 6 decades from engineering programs, Geisingeret al. [8] identified five factors that contribute to poor retention rates in engineering nationwide.These factors include classroom and academic climate; grades and conceptual understanding;self-efficacy and self-confidence; interest and career goals; and race and gender. Of primaryconcern are both discipline-specific skills and knowledge (e.g., mathematics), as well as moregeneral, non-discipline-specific self-efficacy and metacognitive knowledge and skills.Metacognition, often defined as “thinking about thinking,” is primarily about knowing,understanding, monitoring, and controlling one’s cognitive processes, leading to altered andideally more productive behaviors [9] – [13]. The study of

Conference Session

Women in Engineering Division Technical Session 5

Collection

2018 ASEE Annual Conference & Exposition

Authors

Jennifer A Gatz, Stony Brook University ; Angela M Kelly, Stony Brook University; Monica Bugallo, Stony Brook University

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

be measured in terms of gradeperformance and intellectual development during the college years [22]. While ability has beenpositively associated with college persistence, commitment to the goal of completion is the mostinfluential factor in determining persistence [22]. A feeling of success and congruence in theacademic environment may lead to increased motivation to study, which may lead to betterperformance, increased academic self-efficacy, and institutional commitment [23]. Learningcommunities are a way to combine academic and social aspects of an institution to help increaseacademic performance and retention, particularly in the transition from high school to college[24]. Learning communities that include mentoring encourage personal

Conference Session

Robotics

Collection

2018 ASEE Annual Conference & Exposition

Authors

Abhidipta Mallik, New York University; S.M. Mizanoor Rahman, New York University; Sheila Borges Rajguru, New York University; Vikram Kapila, New York University

Tagged Divisions

Pre-College Engineering Education

to their students formany years. Some individual teachers may find it challenging to engage in robotics-aided STEMeducation due to their lack of required TPACK self-efficacy (see [5,9] for details about TPACKself-efficacy). Moreover, all robotics-aided STEM lessons are not the same, i.e., their difficultylevels may vary due to variations in the required TPACK. Specifically, while some lessons maybe more complicated from the design or programming (technology) point of view, others may becomplicated from the teaching, learning, or assessment (pedagogical) point of view, and theincorporation of robots (technology) may also impact the pedagogy. Thus, it is important toconcentrate on investigating the TPACK framework for individual teacher and

Conference Session

Developing Teaching and Mentoring Skills

Collection

2018 ASEE Annual Conference & Exposition

Authors

Hyun Hannah Choi, University of Illinois, Urbana-Champaign; Yuting W. Chen, University of Illinois at Urbana-Champaign; A. Mattox Beckman Jr., University of Illinois, Urbana-Champaign; Lucas Anderson, University of Illinois at Urbana-Champaign; Blake Everett Johnson, University of Illinois, Urbana-Champaign; Matthew D. Goodman, University of Illinois, Urbana-Champaign; Chris Migotsky, University of Illinois; Nicole Johnson-Glauch

Tagged Topics

Diversity

Tagged Divisions

Graduate Studies

join our GTA training.Program EvaluationAligned with the goals of the program to improve teaching ability and based on the assumptionthat students may not see the connection between teaching and transferable professional skills,this program evaluation was designed to: 1) measure changes in students’ perceptions of theirconfidence in teaching and 2) estimate changes in students’ viewpoints toward teaching as anopportunity to enhance transferable professional skills. To these ends, we administered twosurveys before and after the course: the STEM GTA Teaching Self-Efficacy Scale 5 and a modifiedskills perception inventory. 6 This section discusses the demographics of the students whoparticipated in this evaluation and their responses to the

Conference Session

Motivation, Identity, and Belongingness

Collection

2018 ASEE Annual Conference & Exposition

Authors

Jonathan D. Stolk, Franklin W. Olin College of Engineering; Yevgeniya V. Zastavker, Franklin W. Olin College of Engineering; Michael D. Gross, Wake Forest University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

/perceived confidenceand interest/values in STEM has progressed over the past two decades, studies of students’motivational orientations (intrinsic versus extrinsic) in STEM are quite limited.Perceived confidence and self-efficacy strongly influence academic motivations [44] and serveas mediators of learning engagement and persistence [8]. As such, STEM educators areconcerned with how learners cultivate a strong sense of efficacy and expectations of success.Indeed, measurement of self-efficacy and perceived competence represents an area of notableprogress in STEM education research. Gendered patterns in learners’ perceived competence andself-efficacy within gender-role stereotyped domains such as mathematics and engineering arewidely reported [45

Conference Session

Women in Engineering Division Technical Session 4

Collection

2018 ASEE Annual Conference & Exposition

Authors

Angela M Kelly, Stony Brook University; Doreen Aveni, Stony Brook University; Monica Bugallo, Stony Brook University

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

uniqueresearch experiences must be identified for 100 students in laboratories across campus.Furthermore, the arrangement of internships depends upon strengthening and expanding thenetwork of regional industries, companies, and health services organizations. This requiresconsiderable work, however, our extensive faculty network and alumni have been supportive inproviding resources and opportunities for current WISE students.Preliminary FindingsTo measure the effectiveness of the new WISE curriculum in meeting its goals, incomingfreshmen (N = 58) were surveyed at the end of the fall semester in 2017. Baseline data werecollected to explore the following research question: How does participation in the WISEcurriculum impact students’ self-efficacy, career

Conference Session

NSF Grantees Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Amy Summerville, Miami University; Brian P. Kirkmeyer, Miami University; Jennifer Blue, Miami University

Tagged Topics

NSF Grantees Poster Session

possible foci.Next, participants’ self-efficacy was measured with 7 items (alpha = .92), each measured on a 7point scale with Likert response options “Strongly disagree”, “Disagree”; “Somewhat disagree”;“Neither agree nor disagree”; “Somewhat agree”; “Agree”; “Strongly agree”. : “I am doing wellin the course”; “I am doing poorly in the course” (reverse-scored); “I feel like I can successfullycomplete the course with a C or higher”; “I’m not sure that I can pass the course”(reverse-scored); “I’m thinking of dropping the course” (reverse-scored); “It is possible for me tosucceed in this course”; “I’m confident that I can get the grade I want in this course”.Participants were asked to indicate how much they agreed with each statement as they

Conference Session

Career Decisions and Faculty Development

Collection

2018 ASEE Annual Conference & Exposition

Authors

Trevion S. Henderson, University of Michigan; Katie A. Shoemaker, University of Michigan; Lisa R. Lattuca, University of Michigan

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

social pressure tosucceed in engineering. Students were asked to respond on a 5-point Likert scale (1=StronglyDisagree and 5=to Strongly Agree)to the survey item that read, “I would be embarrassed if Ifound out that my work in my science or engineering major was inferior to that of my peers.”Finally, since Ajzen argued that perceived behavioral control is highly compatible withBandura’s concept of perceived self-efficacy, we measured perceived behavioral control using asubscale of our engineering self-efficacy measure. Items in the subscale of Engineering MajorConfidence were measured on a five-point Likert scale (i.e., Strongly Disagree to StronglyAgree). Example items included, “I can succeed in an engineering major” and “Someone like mecan

Conference Session

Mechanical Engineering Division Technical Session 5

Collection

2018 ASEE Annual Conference & Exposition

Authors

Nolan Tsuchiya P.E., California State Polytechnic University, Pomona; Zhaoshuo Jiang P.E., San Francisco State University; Alec William Maxwell, San Francisco State University; Zahira H. Merchant

Tagged Divisions

Mechanical Engineering

students’ self-efficacy on critical engineering concepts using a five-point Likert-type scale from strongly agree to strongly disagree [15]. In this context, self-efficacyis defined as the ability of students to learn concepts and perform tasks efficiently [16]. Summer2017Results:Self-efficacy,FrequencyResponse Measures Mean Pre/Post T-test p value Q1 1.94/1.50 3.259 0.03 Q2 2.19/1.75 3.458 0.02 Q3 2.47/1.81 4.116 0.000 Q4 2.13/1.66 3.695

Conference Session

Women in Engineering Division Technical Session 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Jennifer Blue, Miami University; Amy Summerville, Miami University; Brian P. Kirkmeyer, Miami University; Brielle Nikole Johnson

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

mindset, self-efficacy,and on the regrets that they may feel after they take their first exam. These measures of self-perception often have enough of an effect on students that they affect student performance andpersistence in a major and, sometimes, in a career.A. Mindset People can have either fixed or growth mindsets. Someone with a fixed mindset believesthat intelligence is both stable and uncontrollable, while someone with a growth mindsetbelieves that intelligence can improve [3]. Students with fixed mindsets may interpret one lowexam grade as evidence that they are not smart enough to learn the material in a course, whilethose with growth mindsets are more likely to keep trying to learn. Consequently, people with1 Miami

Conference Session

Entrepreneurship & Engineering Innovation Division Technical Session 2

Collection

2018 ASEE Annual Conference & Exposition

Authors

Leon Szeli, Stanford University; Shannon Katherine Gilmartin, Stanford University; Helen L. Chen, Stanford University; Sheri Sheppard, Stanford University

Tagged Divisions

Entrepreneurship & Engineering Innovation

) patterns of predicted external correlates, and (d) convergence betweenself and observer ratings“[1]. The TIPI is asking the following question on a 7-point likert-scale(1 = disagree strongly; 7 = agree strongly): I see myself as… • Extraverted, enthusiastic. • Critical, quarrelsome. • Dependable, self-disciplined. • Anxious, easily upset. • Open to new experiences, complex. • Reserved, quiet. • Sympathetic, warm. • Disorganized, careless. • Calm, emotionally stable. • Conventional, uncreative.For Entrepreneurial Self-Efficacy, we used the 4-item measure (α = .792) developed by Zhaoet al. [14], which is asking the participants how

Conference Session

ET Peripherals

Collection

2018 ASEE Annual Conference & Exposition

Authors

Osazuwa John Okundaye Jr, Texas A&M University; Mathew Kuttolamadom, Texas A&M University; Malini Natarajarathinam, Texas A&M University; Sharon Lynn Chu, Texas A&M University; Francis Quek, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

Engineering Technology

://teilab.tamu.edu c American Society for Engineering Education, 2018 Motivating STEM Participation through a “Making as Micro- Manufacture (M3)” ModelAbstractThe objective of this paper is to outline a new model for motivating STEM participation anddeveloping self-efficacy among high-schoolers, and to detail the major implementation activitiesinvolved, preliminary impressions/results, and lessons learned.In this model titled, “Making as Micro-Manufacture (M3),” high-variability low-volumeproducts were manufactured in real-world settings and for a real-life purpose. The modelcombined “Making” with engineering concerns attendant to manufacturing at micro scales (tensto hundreds of parts) along with

Conference Session

Design Assessment

Collection

2018 ASEE Annual Conference & Exposition

Authors

Martina Margaret Moyne, University College Dublin; Maxwell Herman, Harvard University; Conor Walsh P.E., Harvard University; Donal Padraic Holland, University College Dublin

Tagged Topics

Diversity

Tagged Divisions

Design in Engineering Education

’ conceptual understanding ofengineering concepts [13-15]. Other tools collect intermittent peer evaluations [16], andstudent self-efficacy in design skills [17]. However, these tools do not give a direct measureof students’ design process learning, nor do they collect the process-related data needed foreducators to investigate the effect of the students’ experiential learning of design processes.There are also instructor self-efficacy tools that cover general teaching tasks [18], specificacademic areas such as science [19] and the teaching of design engineering within STEM andthird level education [20, 21]. However, these tools are only intended to measure instructors’perception of their own teaching abilities and cannot provide a direct measure of

Conference Session

Postcard Session: Experiential Learning as a High-Impact Student Experience

Collection

2018 ASEE Annual Conference & Exposition

Authors

Glenda D. Young Collins, Mississippi State University ; Reuben F. Burch V, Mississippi State University

Tagged Divisions

Cooperative and Experiential Education

, goals, and actions. We will leverage the framework by deeming the internship as the learning experience thatshapes interns’ self-efficacy and outcome expectations related to working in a data analyticsand/or sports industry career post-graduation. Levering the SCCT framework, we have designedour assessments to explore student beliefs as well as contextual (and environmental) variables byexploring the supervisor’s perspective. Figure 1. Social Cognitive Career Theory [12]Assessment methods To capture the individual student experience as well as the organizational context, we aredeveloping an assessment plan to measure changes in student learning and perceptions, as well ascollect data on program elements, including

Conference Session

Civil Engineering Division Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Zhaoshuo Jiang P.E., San Francisco State University; Alec William Maxwell, San Francisco State University; Zahira H. Merchant, San Francisco State University; Philip Scott Harvey Jr., University of Oklahoma; Nolan Tsuchiya P.E., California State Polytechnic University, Pomona; Cheng Chen, San Francisco State University

Tagged Divisions

Civil Engineering

. To further evaluate itseffectiveness in a larger scale, the mobile learning module is implemented in three dynamics andvibration classes in three different universities. The classes are carefully selected to evaluate theadaptability and expandability of the module and its effectiveness in advancing the learning ofstudents from various backgrounds and knowledge levels (junior, senior, undergraduate, smallsize, and large size class). Three measures namely Smart Tablet Readiness Measure, EngineeringConcepts Achievement Test, and Engineering Concepts Self-Efficacy Test, are developed toperform the evaluation. Results clearly demonstrated the student readiness of using mobiledevice as a tool for learning activities, and that the mobile learning

Conference Session

Design Assessment

Collection

2018 ASEE Annual Conference & Exposition

Authors

Jennifer S. Mullin, University of California, Davis; Jean S. VanderGheynst, University of California, Davis

Tagged Topics

Diversity

Tagged Divisions

Design in Engineering Education

the design project and overarching goal of growing the course, aneducational research plan was initiated during fall 2017 in order to better understand thestudents’ educational needs and interests around the communication and design objectives.Data collection included two instructor-developed surveys, one to determine the students’ in-coming technology skills and prior experience working with a design team. The other instructor-developed survey asked students to self-rate their technology skills and to share particularproblems on the farm they found interesting to help with the team assignments.Students were invited to take the Engineering Design Self-Efficacy (EDSE) instrument, a 36-item instrument designed to measure individuals' self

Conference Session

Engineering Design Graphics Division Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Jeremy V. Ernst, Virginia Tech; Shelley Glimcher, North Carolina State University; Daniel P. Kelly, North Carolina State University; Aaron C. Clark, North Carolina State University

Tagged Topics

Diversity

Tagged Divisions

Engineering Design Graphics

. 7, no. 1, pp. 9, 2016.[9] N. Honken, P. S. Ralston, “Freshman engineering retention: A holistic look,” Journal of STEM Education: Innovations & Research, vol. 14, no. 2, pp 29-37, 2013.[10] M. W. Ohland, C. E. Brawner, M. M. Camacho, R. A. Layton, R. A. Long, S. M. Lord, and M. H. Wasburn, “Race, gender, and measures of success in engineering education,” Journal of Engineering Education, vol. 100, no. 2, pp. 225, 2011.[11] T. D. Fantz, T. J. Siller, and M. A. Demiranda, “Pre-Collegiate Factors Influencing the Self- Efficacy of Engineering Students,” Journal of Engineering Education, vol. 100, no. 3, pp. 604–623, 2011.[12] S. Freeman, S. L. Eddy, M. Mcdonough, M. K. Smith, N. Okoroafor, H. Jordt, and M. P

Conference Session

Modeling, Inquiry, Engineering Literacy & Argumentation

Collection

2018 ASEE Annual Conference & Exposition

Authors

Katherina V. Tarnai-Lokhorst, Camosun College

Tagged Topics

Diversity

Tagged Divisions

Pre-College Engineering Education

applications can make the world a better place.This paper presents an alternative to additive outreach programs prevalent in universities andengineering societies. The proposed teaching paradigm is demonstrably simple to implement,eases teacher workload, enhances student learning and creates a significant improvement inperceptions and beliefs about self-efficacy in physics, an indicator of student success andmotivation. The research identifies an unanticipated impact of introducing engineering designprinciples into Physics 11 classrooms. Physics 11 teachers participated in developing a lessonplan that guides facilitators of learning through the discovery- or inquiry-based activity. Themixed methods research methodology included surveys, observations

Conference Session

Making, Hacking, and Extracurricular Design

Collection

2018 ASEE Annual Conference & Exposition

Authors

Victoria Bill, New York University, Tandon School of Engineering; Anne-Laure Fayard, New York University, Tandon School of Engineering

Tagged Divisions

Design in Engineering Education

.[11] Carberry, A. R., Lee, H. S., & Ohland, M. W. (2010). Measuring engineering design self‐efficacy. Journal ofEngineering Education, 99(1), 71-79.[12] Martinez, L. J., & Sullivan, P. A., & Pines, E. (2017, June), Integration of Engineering Capstone within aMakerspace Environment Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio.[13] Nickols, F. (2003). Communities of practice. A start-up kit.

Conference Session

Making, Hacking, and Extracurricular Design

Collection

2018 ASEE Annual Conference & Exposition

Authors

Ethan Hilton, Georgia Institute of Technology; Megan Tomko, Georgia Institute of Technology; Wendy C. Newstetter, Georgia Institute of Technology; Robert L. Nagel, James Madison University; Julie S. Linsey, Georgia Institute of Technology

Tagged Topics

Diversity

Tagged Divisions

Design in Engineering Education

Makerspaces," presented at the International Symposium on Academic Makerspaces, Cleveland, USA, 2017.[8] M. Tomko, R. L. Nagel, M. W. Aleman, W. C. Newstetter, and J. S. Linsey, "Toward Understanding the Design Self-Efficacy Impact of Makerspaces and Access Limitations," in 2017 ASEE Annual Conference & Exposition, 2017.[9] R. Morocz, B. D. Levy, C. R. Forest, R. L. Nagel, W. C. Newstetter, K. G. Talley, et al., "University Maker Spaces: Discovery, Optimization and Measurement of Impacts," in ASEE Annual Conference and Exposition, Seattle, WA, 2015.[10] E. C. Hilton, M. Tomko, A. Murphy, R. L. Nagel, and J. Linsey, "Impacts on Design Self- efficacy for Students Choosing to Participate in a University

Conference Session

Environmental Engineering Division Technical Session 3

Collection

2018 ASEE Annual Conference & Exposition

Authors

Bettina Jeanine Casad, University of Missouri, St. Louis; Monica Palomo P.E., California State Polytechnic University, Pomona; Natalie Mladenov, San Diego State University

Tagged Topics

Diversity

Tagged Divisions

Environmental Engineering

American Chemical SocietyAnnual Spring Meeting, and at the international Dresden Nexus Conference in Germany .(3)MeasuresThe pre- and post-questionnaires included the following quantitative measures.Academic self-efficacy. An 8-item measure (Chemers et al., 2001) assessing students’ beliefsregarding their ability to successfully achieve their academic goals was rated on a scale from 1(Very Untrue) to 6 (Very True). Items included statements such as, “I know how to study toperform well on tests” and “I usually do very well at school and at academic tasks.” The scalehad adequate internal consistency (Time 1 or T1 Cronbach’s α = .70, Time 2 or T2 α = .94).Items were averaged so that higher scores indicated higher levels of academic self