Conference Session

COED: Skills for Moving from Computing Student to Professional

Collection

2023 ASEE Annual Conference & Exposition

Authors

Stephanie Jill Lunn, Florida International University; Veon Brewster, Florida International University

Tagged Divisions

Computers in Education Division (COED)

job seekers. The system, called VirtualInterview (VI)-Ready, offers an immersive role-play of interview scenarios with 3D virtual agentsserving as hiring managers. We applied Bandura’s concept of self-efficacy as we investigated: 1)overall impressions of the system; 2) the impact on students’ job interview preparedness; and 3)how internal perceptions of interview performance may differ from external evaluations by hiringmanagers. In our study, we employed a convergent parallel mixed methods approach.Undergraduate and graduate students (n = 20) underwent virtual job interviews using theplatform, each interacting with one of two different agents (10 were randomly assigned to each).Their interactions were video recorded. Participants then

Conference Session

First-Year Programs Division Technical Session 5A: Work-In-Progress: 5 Minute Postcard Session I

Collection

2016 ASEE Annual Conference & Exposition

Authors

Rachel McCord Ellestad, University of Tennessee - Knoxville

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

and metacognition. Thus this response is surprisingwhen looking at the clustering alone. The literature suggests a few possible reasons why thisresponse occurred. First, self-efficacy and test anxiety may play a more distinct role in gradeperformance than many of the other factors investigated in this particular study [12, 13]. Cluster3 participants reported higher levels of self-efficacy, lower levels of test anxiety when comparedto cluster 1. Future work will further investigate how these factors play a role in performance.Second, many SRL theorists believe that participants may have difficulty accurately assessingtheir levels of SRL skills [14-16]. A call for qualitative measures as well as studies conducted intrue learning contexts may

Conference Session

Clinical, Patient, and Innovation Experiences in BME

Collection

2017 ASEE Annual Conference & Exposition

Authors

Megan Huffstickler, Pennsylvania State University; Sarah E. Zappe, Pennsylvania State University, University Park; Keefe B. Manning, Pennsylvania State University, University Park; Margaret J. Slattery, Pennsylvania State University, University Park

Tagged Topics

Diversity

Tagged Divisions

Biomedical

, but were used for overall program evaluation. The three remaining scales included measures of creative self-efficacy, identity, and expectation. Creative self-efficacy refers to the “belief that one has the ability to produce creative outcomes” (p. 1138).18 Creative self-identity refers to the “overall importance that a person places on creativity in general as part of his or her self-definition” (p. 248).19 Creative self-expectation refers to students’ perceived expectations that they need to be creative within the academic setting, in this case the REU. Descriptions of the items included in these scales are given in Table 1. All three instruments used Likert-type scales. The number of anchor points corresponded to the

Conference Session

Out-of-school-time Engineering: Implications for Underrepresented Students

Collection

2016 ASEE Annual Conference & Exposition

Authors

Stephanie Luster-Teasley, North Carolina A&T State University; Radiah C. Minor, School of Agriculture and Envrinmental Sciences, North Carolina A&T State University; Vernal G. Alford III, North Carolina Agricultural and Technical State University

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering

. The program seeksto improve students’ competence and self-efficacy in science and engineering, stimulate an interestin pursuing STEM-related careers, and provide engaging “hands-on/mind-on activities.” Theprogram is divided into two initiatives which include an academic year and weekend academy. Atotal of 45 middle school students have participated in a 1-week Girls in Science Lab Camp andfive half-day Girls in Science and Engineering Weekend Academy activities. For the Girls inScience Lab program, the participants were divided into teams and assigned an environmentalscience and engineering themed case study to solve during guided laboratory experience. Studentswere taught how to collect and analyze water samples using university laboratory

Conference Session

First-Year Programs: Virtual Instruction in the First Year III

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Shannon Barker, University of Virginia

Tagged Divisions

First-Year Programs

]. It would seem that by including safe andconfirming environments for students to become competent in engineering skills in an engagingand enjoyable manner will have positive effects on a student’s engineering identity, and thereforeon their continued persistence in the engineering major.A person’s self-efficacy can be described as their judgment of their own capabilities to achievedesired outcomes [20]. Self-efficacy influences how well people motivate themselves in difficultsituations, and those with higher self-efficacy are more likely to execute behaviors that lead tosuccess. Self-efficacy has been shown to be a predictor of persistence within a program [22].Course design can help strengthen self-efficacy by creating opportunities for

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 in Freshman and Sophomore Courses

Collection

2012 ASEE Annual Conference & Exposition

Authors

Gail Hohner, University of Michigan, Ann Arbor; Shanna R. Daly, University of Michigan; Jennifer Wegner, University of Michigan; Moses K. Lee, University of Michigan; Amy Frances Goldstein, University of Michigan

Tagged Divisions

Design in Engineering Education

also compare 35 incoming students who did not participate in the program. Thisprogram is the initial activity in an undergraduate multidisciplinary design program whichincludes many co-curricular enrichment activities as well as an academic minor. We intend tostudy this group of students through their engineering education and evaluate them periodically.We use both the self-efficacy survey from Carberry, Lee and Ohland (Measuring EngineeringDesign Self-Efficacy) as well as the concepts in design survey from Oehlberg and Agogino(Undergraduate Conceptions of the Engineering Design Process: assessing the Impact of aHuman-Centered Desgin Course – which is an extension of Mosborg S., et.al., Conceptions ofthe Engineering Design Process: An Expert

Conference Session

NSF Grantees Poster Session

Collection

2017 ASEE Annual Conference & Exposition

Authors

Stephanie Ruth Young M.Ed, University of Texas, Austin; Margo Cousins, University of Texas at Austin; Laura Suggs, University of Texas, Austin; Mia K. Markey, University of Texas, Austin

Tagged Topics

NSF Grantees Poster Session

statistical analysis of the pre- and post- measures ofscientific communication self-efficacy. Therefore, the results can only be interpreteddescriptively. Mean scores improved by a standard deviation or more on the Writing, Presenting,Speaking, and Total Scales, as shown in Table 1.Table 1. Pre- and Post-SCSE Means (Standard Deviations) Mean (SD) Baseline Post Writing Scale 35.5 (4.3) 39.8 (4.7) Presenting Scale 12.3 (3.3) 16.10 (2.5) Speaking Scale 27 (6.6

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Frank Andrasik, The University of Memphis; Bashir Morshed, Texas Tech University; Robert W Hewitt Jr., The University of Memphis

Tagged Topics

Professional Papers

always align with their actual abilities. Additionally, the samplesize for both the 2023 and 2024 camps was relatively small, which may limit confidence of theresults. Further research with larger cohorts and more objective measures of learning outcomes,such as coding assessments or project evaluations, would provide a more comprehensiveunderstanding of the camp's impact.Future iterations of the camp could explore a hybrid approach, combining the strengths ofbreakout room interactions with opportunities for independent problem-solving. The surveyinstrument could be modified to evaluate self-efficacy, which began to become more central tothe camp’s primary goals. Additionally, tracking students' long-term engagement with STEMfollowing the camp

Conference Session

CEED Technical Session II: Developing Research and Design Skills Through Experiential Learning

Collection

2019 ASEE Annual Conference & Exposition

Authors

Nicole Bowers, Arizona State University; Michelle Jordan, Arizona State University; Kate Fisher; Zachary Holman, Arizona State University; Mathew D. Evans, Arizona State University

Tagged Topics

Diversity

Tagged Divisions

Cooperative and Experiential Education

to theengineering CoP as well as their imagination of their current relationship to the CoP in the formof self-efficacy. Two data sources were used to operationalize participants imagination as a modeof belonging: pre-post administrations of a self-efficacy survey and post-program used to probefor how participants’ saw themselves in relation to the CoP. Self-efficacy. The self-efficacy measure focused on participants’ imagined sense of theirown current capabilities related to engineering. At two points in the program (pre and post), REUparticipants were asked to rate themselves on a scale from 0 (Completely Unconfident) to 100(Completely Confident) with respect to their current level of self-efficacy or confidence forinnovation and

Conference Session

Design in Engineering Education Division (DEED) Technical Session 7

Collection

2023 ASEE Annual Conference & Exposition

Authors

Sonia Travaglini, Stanford University; Sheri D. Sheppard, Stanford University; Helen L. Chen, Stanford University

Tagged Divisions

Design in Engineering Education Division (DEED)

communities of practice. This case study was completed as part of courseevaluation and feedback processes, in order to identify improvements to how the course kits andtools were implemented and supported. All processes were completed under the supervision andwith the approval of the course instructors. The survey questions, shown in Appendix 1 in Table2, included open-ended questions to explore students’ feedback on the benefits of kits and theirvalue in supporting their learning, and any barriers they experienced in using them. Questionswith Likert scale rating for students to rate an item on a 1-to-5 scale [12], were used fordetermining level of student engagement and measuring students’ self-efficacy in developingdesign, experimentation, analysis

Conference Session

NSF Grantees' Poster Session

Collection

2012 ASEE Annual Conference & Exposition

Authors

Amy Javernick-Will, University of Colorado, Boulder; Jessica Kaminsky, University of Colorado, Boulder; Cathy Leslie P.E., Engineers Without Borders - USA ; Kaitlin Litchfield, University of Colorado, Boulder

Tagged Topics

NSF Grantees Poster Session

. As a result, this research will consider an extendedSTEM pipeline that includes both undergraduates and professionals, recognizing the importanceof not only recruiting but also retaining diverse genders in STEM.Social cognitive theory proposes that self-efficacy and expected outcomes form the basis forprofessional identity and motivation. This research will test social cognitive theory as aframework for attracting diverse groups to engineering. Specifically, it proposes thatparticipation in EWB-USA changes the expected outcomes of engineering—from Dilbert to theengineer of 2020. In addition, it provides career scaffolding that helps members navigatecareers. Both of these aspects are hypothesized to be particularly attractive and beneficial

Conference Session

Undergraduate Student Issues II

Collection

2013 ASEE Annual Conference & Exposition

Authors

Ann Sharon Lourens, Nelson Mandela Metropolitan University (NMMU) Port Elizabeth South Africa

Tagged Divisions

Women in Engineering

well asacademic development to prepare WELA members for work and life. In 2013, in partnership with SCCDC colleagues, the university will embark on a longitudinalstudy to measure the self-efficacy of women engineering students before and after the WELAinterventions at the university. It is also envisaged that an international university will beinvolved in the study as from 2014. The longitudinal study will provide a clear indication of thesuccess of the WELA programme in influencing feelings of self-efficacy in women engineeringstudents who have taken part in it. To determine the success of the WELA LDP, several roleplayers will be asked to complete questionnaires, including the WELA LDP participants andtheir mentors.The results of the

Conference Session

First-Year Programs Division (FYP) - Technical Session 5: Supporting Success 2

Collection

2023 ASEE Annual Conference & Exposition

Authors

Pamela Bilo Thomas, University of Louisville; Campbell R. Bego, University of Louisville; Arinan De Piemonte Dourado, University of Louisville

Tagged Divisions

First-Year Programs Division (FYP)

of studying engineering, self-efficacy, and contingencies of Academic Competence, Academic Competence subscale. Example items and references for each of these scales are provided in Table 1, and 5. Retention, defined as enrollment in the engineering school in the fall of the second year.AnalysisTwo machine learning techniques were investigated in this work: a neural network and a decisiontree. A neural network works to learn patterns via an iterative process of trial and error to classifydata into categorical outputs [11], and the results are black box (it is not possible to tell why aclassification was made without the aid of explainable methods). For the neural network analysis, Table 1: EVT

Conference Session

Systems Engineering Division Technical Session 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Mark David Bedillion, Carnegie Mellon University; Karim Heinz Muci-Kuchler, South Dakota School of Mines and Technology; Cassandra M. Birrenkott, South Dakota School of Mines and Technology; Marsha Lovett, Carnegie Mellon University; Laura Ochs Pottmeyer, Carnegie Mellon University

Tagged Divisions

Systems Engineering

, with technical contentembedded in an online learning module and class time used to perform a group designactivity.An effective means of measuring students’ systems thinking / systems engineering skills isneeded to assess the effectiveness of the intervention. There have been several approaches in theliterature, ranging from comprehensive written / practical exams 9 to computerized tests thatmeasure specific systems engineering skills 10 . This paper uses a survey instrument called theSystems Thinking Skills Survey (STSS) 6 which includes both self-efficacy questions andtechnical questions to assess students systems engineering skills.This paper describes results of a flipped-classroom learning experience on systems engineeringgeared toward

Conference Session

Springfield's STEM Spectacle: Evaluating Engineering Excellence, D'oh!

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jose Capa Salinas, Purdue University; Manuel Salmeron, Purdue University; Gaurav Chobe, Purdue University; Herta Montoya, Purdue University at West Lafayette (COE); Morgan R Broberg, Purdue University at West Lafayette (COE)

Tagged Divisions

Pre-College Engineering Education Division (PCEE)

[1]. FET is a framework designed to evaluate ToLthrough the factors that impede or facilitate the transfer. In contrast with other methods that focuson determining the factors (see, for example, [9], [16], [17]), the FET model aims to assess them[1]. Furthermore, the FET’s framework encompasses evaluating multiple dimensions influencingthe ToL. Specifically, the FET model's categories include transfer dimensions, achieved learning,and intent to transfer. The transfer dimensions are: 1. Trainee, which includes factors related to the participants’ reactions to a training program, such as motivation of transfer, self-efficacy, and locus of control; 2. Training, that evaluates the training itself and its design, and includes factors

Conference Session

FPD3 -- Professional Issues for First-Year Courses

Collection

2007 Annual Conference & Exposition

Authors

Jennifer Light, University of Washington; Russell Korte, University Of Minnesota; Ken Yasuhara, University of Washington; Deborah Kilgore, University of Washington

Tagged Divisions

First-Year Programs

parental education and SATscores, better study skills, and participated in classes specifically designed to reduce or eliminatefactors purported to work against women in the classroom, yet still did not persist at greater ratiosthan men. In fact, men did better, especially at the upper end of the grade spectrum.These and other research studies show that while self-confidence is one of many positiveoutcomes for college students, its relationship to successful outcomes is not a simple positive one.Bandura’s12 concept of self-efficacy may be a better construct when examining students’perceptions of their capabilities and their likelihood to perform well on an engineering task.Self-efficacy is widely used to mean one’s perception of one’s own

Conference Session

Best In DEED

Collection

2019 ASEE Annual Conference & Exposition

Authors

Elizabeth Marie Starkey, Pennsylvania State University; Scarlett Rae Miller P.E., Pennsylvania State University; Samuel Todd Hunter

Tagged Divisions

Design in Engineering Education

self-efficacy surveys to measure one’s belief in theirengineering [27] and creative [28] ability, since self-efficacy is a strong predictor of futurebehavior [29]. While Table 2 identifies the prior work in the area of product dissection, theimplementation of product dissection in the engineering classroom has not been systematic,leaving us to question how variations in product dissection impact learning, creativity, or bothfor students when used in the classroom. In order to fill this gap in the literature, our researchgroup has conducted numerous studies over the last four years in order to systematicallyinvestigate variations in deployment of product dissection in an engineering classroom. Throughthese studies, a research driven

Conference Session

Research and Assessment

Collection

2011 ASEE Annual Conference & Exposition

Authors

Andrew Borchers, Kettering University; Sung Hee Park, Kettering University

Tagged Divisions

Entrepreneurship & Engineering Innovation

Attitude direction and strength toward the targeted behaviors (e.g., being an entrepreneur)Skill-Based Proficiency to use the entrepreneurship knowledge and business acumen, referred as procedural knowledge, skill compilation and automaticityCurrently, the authors do not have any outcome measure for the Behavioral Outcome Dimension.However, it is commonly believed that behavioral intention could be a good surrogate forbehavior. The authors employ Intention to Start a Business (ITSB), a 5 item measure adaptedfrom Chen et al. [11] to measure student behavior intention. The authors also employEntrepreneurial Self Efficacy (ESE) – a 22 item measure that speak

Conference Session

First-Year Programs Division Technical Session 10: Best of First-Year Programs Division

Collection

2022 ASEE Annual Conference & Exposition

Authors

Campbell Bego, University of Louisville; Pamela Thomas; Xiaomei Wang, Texas A&M University; Arinan Dourado, University of Louisville

interventions. Here, threemachine learning tools, namely, clustering, principal component analysis (PCA), and decisiontrees, were applied to data from two cohorts of engineering students at a large public university.Concerning the SEVT framework, student responses to surveys given at the beginning and endof the first semester, containing established scales for self-efficacy and contingencies of academiccompetence self-worth (expectancies), and interest in engineering and perceived costs of studyingengineering (subjective task values) were used. Demographic data including race, gender, and Pelleligibility, alongside performance data in the form of introductory course grades, GPA, and per-sistence into Year 2, complete the set of gathered information

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

Thinking Outside the STEM Box: Equity, Culture & Social Justice in Education Division Technical Session 1

Collection

2022 ASEE Annual Conference & Exposition

Authors

Jan Fertig, Milwaukee School of Engineering; Subha Kumpaty, Milwaukee School of Engineering

persistence and perceived level ofprogram fairness (e.g., lack of discrimination based on race, gender, sexual orientation or anybasis). High discrimination/low fairness departments were characterized by notable prejudiceand discrimination, while low discrimination/high fairness departments were characterized bygender-blindness, equity, respectful treatment of students and greater trust. The relationshipbetween program fairness and persistence was moderated by level of individual empathy. Inother words, individual empathy enhanced or buffered the effect of program discrimination onpersistence. (Individual empathy scores did not differ by engineering program). Under conditionsof low fairness and low STEMpathy, engineering self-efficacy was low

Conference Session

Global Engineering Models: Curriculum Development, Improvements, and Partnerships

Collection

2012 ASEE Annual Conference & Exposition

Authors

Teri Kristine Reed, Purdue University, West Lafayette; P.K. Imbrie, Purdue University, West Lafayette; Qu Jin, Purdue University, West Lafayette; Joe J.J. Lin, Purdue University, West Lafayette

Tagged Divisions

International

(predictor) variables collected in this study include: 1) eight items fromstudent’s high school performance measures, and 2) eight affective and attitudinal self-beliefconstructs from SASI survey. The high school performance measures include: standardized testresults (verbal and math), average high school grades in mathematics, science, and Englishclasses, and also the number of semesters in mathematics, science, and English in high school.The eight attitudinal and affective self-beliefs applied include Leadership, Deep Learning,Surface Learning, Teamwork, Self-efficacy, Meta-cognition, Expectancy-value, and Majordecision. The construct Motivation from original SASI was not used in this study, due to a veryhigh correlation (0.80) with Self-efficacy

Conference Session

Teaching & Learning Statics and Mechanics of Materials

Collection

2016 ASEE Annual Conference & Exposition

Authors

Andrew Lee, Arizona State University; Haolin Zhu, Arizona State University; James A Middleton, Arizona State University

Tagged Divisions

Mechanics

studies to validatetheir results due to the short length of their research or small classroom size. In addition, many ofthese studies do not measure student attitudes, such as self-efficacy, or the difference in timespent out of class on coursework.The objective of this research is to determine the effectiveness of the flipped classroom system incomparison to the traditional classroom system (TC) in a large mechanics of materials course.Specifically, it aims to measure student performance, student self-efficacy, student attitudes onlecture quality, motivation, attendance, hours spent out of class, practice, and support, anddifference in impact between high, middle, and low achieving students. In order to accomplishthis, three undergraduate

Collection

2020 Gulf Southwest Section Conference

Authors

Chadia Affane Aji; M. Javed Khan

. The study was based on a quasi-experimental within-subject design. Theindependent variables (dimensions) were Self-Efficacy, Intrinsic Value, Test Anxiety, CognitiveStrategies Use, and Self-Regulation. A semester-long intervention which consisted of active-learningpedagogy was implemented in selected lower level math and aerospace engineering courses.Participants. The participants were undergraduate students at an HBCU who had registered in thecourses in Spring 2019 in which the intervention was implemented. There were 48, 38, 21, 25, and 9students registered in the MATH107 Pre-Calculus, MATH108 Pre-Calculus Trigonometry,MATH207 Calculus I, AENG200 Introduction to Aerospace Engineering, and AENG242 AerospaceStructures I courses respectively

Conference Session

Teaching Materials Science Using Innovative Methods

Collection

2013 ASEE Annual Conference & Exposition

Authors

Stephen J Krause, Arizona State University; Dale R Baker, Arizona State University; Adam R Carberry, Arizona State University; Milo Koretsky, Oregon State University; Bill Jay Brooks, Oregon State University; Debra Gilbuena, Oregon State University; Cindy Waters, North Carolina A&T State University; Casey Jane Ankeny, Arizona State University

Tagged Divisions

Materials

to which students' competency beliefs and thevalues of the specific subject predict the quality of their learning and the amount of effort theywill invest in learning the subject6,7. For example, students perceiving short term value of thematerial will engage in quick learning strategies, instead of mastery. An increase in socialinteraction would foster idea brainstorming and information gathering that could result in deeperthinking about the material.9 Page 23.916.4Self EfficacyThe self-efficacy is an impressive measure of human behavior as it offers both “cognitive andmotivational drive”10. One factor that affects self-efficacy is gender

Collection

2020 Gulf Southwest Section Conference

Authors

M. Javed Khan; Chadia Affane Aji

noted thatin 2011 Blacks were 11% of the total workforce, but only 6% were employed in STEM-relatedcareers. This was in contrast to Whites who were 71% of the workforce with 67% of them in STEMcareers. It is pertinent to point out that according to the 2015 census12, Blacks/African-Americanswere 13% of the US population and Whites were 72% of the population. While there are severalstructural reasons for this disparity13, one of the challenges is the retention of underrepresentedstudents in STEM disciplines in college. A literature study14 in 2013 identified six factors resultingin students to leave engineering, these being (i) classroom and academic climate, (ii) grades andconceptual understanding, (iii) self-efficacy and self-confidence, (iv

Conference Session

Undergraduate Track - Technical Session VII

Collection

2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference

Authors

James Burton Dorsey, University of Washington

Tagged Topics

Undergraduate Education

Support  Transfer credit assistance  Orientation Course  Academic Excellence Workshop  Academic advising/counseling  Dedicated Student study center and Tutoring  Professional and Career development  Links with Engineering Professional Student Orgs  Industry advisory partnerships & Internships www.WashingtonMESA.orgResearch Questions 7  What influences do MESA Community College Program activities have on early college student STEM self- efficacy?  What activities are most influential? Academic vs Social?  MCCP influence on persistence & completion of STEM degrees

Conference Session

NSF Grantees: Student Learning 1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Patricia Ann Maloney, Texas Tech University; Weilong Cong, Texas Tech University; Meng Zhang, Kansas State University; Bingbing Li, California State University, Northridge

Tagged Topics

NSF Grantees Poster Session

UniversitiesWIP: Implementation and Assessment of ProjectAbstract: This paper documents the effects of an additive manufacturing course on two sets ofstudents: (1) the undergraduates who took the course and (2) the middle and high school studentswho visited our labs. At the time of the conference, nine semesters of data (three years at threeschools) will have been collected, as well as data from the middle and high school students whovisited our labs. Overall, our research questions were: (1) what is the effect of this course on thecontent knowledge of (a) enrolled undergraduates and (b) middle and high school students? And(2) what is the effect of this course on the attitudes towards engineering and self-efficacy inengineering for (a) enrolled

Conference Session

Biomedical Engineering Division (BED) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jacquelynn Ann Horsey, University of Arkansas; Thomas Hudnall McGehee, University of Arkansas; Mostafa Elsaadany, University of Arkansas; Timothy J. Muldoon, University of Arkansas

Tagged Topics

Diversity

Tagged Divisions

Biomedical Engineering Division (BED)

context of such available resources isof broad interest to the engineering community. This study sought to measure the effectivenessof a junior-level clinical observations course designed for a major land-grant, public universitywithout proximity to a medical school. We compared IP generation and pre- and post-classsurveys were used to quantify students’ self-efficacy, motivations, and ability to makeconnections to real-world problems. The total number of IP applications increased more thantwo-fold following the adoption of the course, and survey results indicated students’ collectiveimproving understanding of the design process and increased confidence in engineering-relatedskills. This study included a sample size of 75 undergraduate students