Conference Session

Faculty Development Division Poster Session

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Steven Edalgo, Clemson University; Karen A. High, Clemson University; Gary Lichtenstein, Arizona State University; Cindy M. Lee, Clemson University; Joyce B. Main, Purdue University at West Lafayette

Tagged Divisions

Faculty Development Division

-existing factors, including demographic and personalgoals, with mentoring and self-efficacy for research, teaching, and mentoring graduate students.In the current (exploratory) phase, we developed a conceptual framework based on an extensiveliterature review, then interviewed 14, pre-tenured engineering education researchers in order toidentify themes that support or do not support the conceptual framework. In this paper, we reporton our preliminary conceptual framework, research design and future work for our project.Introduction/MotivationFaculty productivity is an important component in the tenure process and success for futureacademic careers. A report from the National Academies (2019) suggests mentoring has positiveeffects in Science

Conference Session

Entrepreneurship & Engineering Innovation Division Technical Session 7

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Vibhavari Vempala, University of Michigan; Jacob Frederick Fuher, University of Michigan; Heydi L. Dominguez, New Jersey Institute of Technology; Jeremiah Ogunbunmi, New Jersey Institute of Technology; Aileen Huang-Saad, Northeastern University; Prateek Shekhar, New Jersey Institute of Technology

Tagged Divisions

Entrepreneurship & Engineering Innovation

to pursue and persist in that task [21]. Self-efficacy is domain and task specific. In the context of entrepreneurship, Entrepreneurial Self-Efficacy (ESE) is a person’s belief in their ability to successfully perform entrepreneurshiprelated tasks and launch a successful entrepreneurial venture [22]. Research has shown ESE to bean important predictor of future entrepreneurial intent and behavior [10], [23], [24]. Severalinstruments to measure ESE are available. However, most of the measurements are empiricallyunderdeveloped and do not capture the various dimensions associated with entrepreneurialactivities and skills [25]. The ESE scale used in this study is developed by McGee [22].Compared to existing ESE measures, McGee’s scale is a multi

Conference Session

Industrial Engineering Division Technical Session 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

McKenzie Landrum, University of Florida; Austin Hayes, University of Florida; Josefina Giamichelle; Sima Sabahi, University of Florida; Sanaz Motamedi, University of Florida

Tagged Divisions

Industrial Engineering

researchwas originally conducted in 1997 and software tools and applications have grown significantlysince then. In addition, this study did not do any statistical analysis to evaluate the results oftheir work [6].To measure how students felt about the course, we measured self-efficacy - an individual's beliefin their capacity to execute behaviors necessary to produce specific performance attainments [7].If during the introduction of a new software the student becomes discouraged, they will likelydevelop a negative attitude towards the use of such software as well as a negative attitudetowards learning software in the future [8]. Discouraged students do not feel confident abouttheir knowledge and over time this leads to a decrease in their self

Conference Session

CoNECD Session : Day 3 Slot 1 Technical Session 3

Collection

2021 CoNECD

Authors

Casey Lynn Haney, Purdue University at West Lafayette (COE); Claudio Freitas, Purdue University at West Lafayette; Gregory John Gage, Backyard Brains; Jennifer Deboer, Purdue University at West Lafayette (COE)

Tagged Topics

CoNECD Paper Submissions, Diversity

, unlike the other measures, there was much more room forgrowth. However, there was no significant change detected. Thus, we cannot conclude that thelab kit and curriculum relate to self-beliefs.Table 4. Self-Efficacy results (N = 39) Initial Change Mean: 3.17 Change Mean = 0.17 Standard Deviation: 1.16 Change Standard Deviation =1.40 Conclusion and Future Directions Overall, the lab kit and neuroscience curriculum were most successful in the area ofimproving science aspirations for diverse students. Additional changes need to be made in futureiterations to the curricular materials

Conference Session

NSF Grantees Poster Session

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Robin A. M. Hensel, West Virginia University; Joseph Dygert, West Virginia University; Melissa Lynn Morris, University of Nevada - Las Vegas

Tagged Topics

Diversity, NSF Grantees Poster Session

]. Students who ultimately leave engineeringbefore their second year often begin their engineering journey with unrealistic views of theirability and the difficulty of the journey. Typically, they underestimate the demands of the major(and career) and overestimate their ability to succeed in the major with little extra effort [2], [3],[5]. This paper compares pre- and post-measures of characteristics believed to be influential orrelated to academic success and student retention in STEM fields for three cohorts (2017, 2018,and 2019) of the AcES program.2.0 MethodologyThree survey instruments: the Grit assessment [6], [7], the Longitudinal Assessment ofEngineering Self-Efficacy (LAESE) survey [8], [9], and the Motivated Strategies for

Conference Session

CoNECD Session : Day 3 Slot 3 Technical Session 2

Collection

2021 CoNECD

Authors

Sophia Lauren Plata, University of Southern California; Indhira María Hasbún, Florida International University ; Mauro Rodriguez Jr., California Institute of Technology; Dora Louise Renaud, Society of Hispanic Professional Engineers

Tagged Topics

CoNECD Paper Submissions, Diversity

captured by SHPE’s long-term NRP throughout the year.While several internal components of McCormick’s model have been validated, NILA’scurriculum serves as a unique opportunity to measure self-efficacy, a challenging aspect tomeasure [47-50], and validate in the context of Hispanic STEM professionals.Figure 2. McCormick’s Social Cognitive Model of Leadership [38], reproduced with permission from the publisher.3. SHPE’s Leadership and Chapter Programming Mapping to McCormick’s Model3.1 NILA’s Curriculum Mapped to Leader Cognitions Figure 3 shows the concept mapping of NILA’s 2019 curriculum to the leader cognitionportion of McCormick’s model [48]. Following the OGSM model presented in Section 2.1,NILA’s objective is captured by McCormick’s

Collection

2021 Fall ASEE Middle Atlantic Section Meeting

Authors

Ashley Lytle, Stevens Institute of Technology; Alexander John De Rosa, Stevens Institute of Technology (School of Engineering and Science); Frank T Fisher, Stevens Institute of Technology (School of Engineering and Science)

Tagged Topics

Diversity

; Tutwiller, 2017; Komarraju, Swanson, & Nadler, 2014). AmongSTEM students, self-efficacy predicts engagement, recruitment, and retention of STEM students(Lent et al., 2003; Wang, 2013).STEM self-efficacy is often measured using a modified 5-item scale originally created byMidgley et al. (2000) as a measure of academic self-efficacy. Participants answer on a 1(Strongly Disagree) to 7 (Strongly Agree) scale with sample items that include: “I can do almostall the work in my STEM classes if I don’t give up” and “I am certain I can figure out how to dothe most difficult class work in STEM.” This scale has been used in recent empirical workcharacterizing how psychosocial variables influences STEM outcomes (Lytle & Shin, 2020; Shinet al., 2016

Conference Session

Student Engagement, Socioemotional Needs, and Social Support During Pandemic

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sarah E. Zappe, Pennsylvania State University; Stephanie Cutler, Pennsylvania State University; Sam Spiegel, Colorado School of Mines; Deb Jordan, Colorado School of Mines; Ariana C. Vasquez, Colorado School of Mines

Tagged Divisions

Educational Research and Methods

Theories of Engineering Abilityscale, which is an 8-item Likert-type scale measuring the degree that engineering ability is moreof an innate, fixed trait, or consisting of skills that can be improved with training and practice. Wealso created a measure, which we call the Implicit Theories of Advanced ManufacturingCompetencies scale, that is intended to measure learners’ beliefs about the malleability of thecompetencies associated with advanced manufacturing.Self-efficacy within the course modules will be measured by the self-efficacy scale on Pintrichand colleagues’ (1991) Motivated Strategies for Learning Questionnaire (MSLQ). An additionalscale that was developed by the authors of this paper includes a domain-specific measure of self-efficacy

Conference Session

Design Mental Frameworks

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Devanshi Shah, University of Georgia; Elisabeth Kames, Florida Polytechnic University; Beshoy Morkos, University of Georgia

Tagged Divisions

Design in Engineering Education

The MSLQ survey used in the previous study was an adapted version of Pintrich’s MSLQconsisting of only five factors of motivation; cognition, intrinsic value, self-regulation,presentation anxiety, and self-efficacy. This is abbreviated compared to the original MSLQdesigned by Pintrich and his team which measured a total of fifteen factors of motivation. Whilethis approach is designed to target factors that are illustrated by Pintrich to influence the successof students in STEM fields, it is also important to understand and identify possibleinterdependency of the five factors in the adapted version. In this paper, we seek to study the dependency of earlier listed motivation factors to establishunderstanding at a finer resolution –to the

Conference Session

NSF Grantees Poster Session

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Tiffiny Antionette Butler, Worcester Polytechnic Institute; Katherine C. Chen, Worcester Polytechnic Institute; Kimberly Lechasseur, Worcester Polytechnic Institute

Tagged Topics

NSF Grantees Poster Session

their educational success. Quantitative methods are used in this study to assess students’ self-efficacy; a baseline ispresented here with plans to measure changes over time during students’ participation asCoMPASS Scholars. We administered a baseline survey to incoming CoMPASS Scholars usingthe Longitudinal Assessment of Engineering Self-Efficacy (LAESE). The LAESE is a validatedinstrument developed by the Assessing Women in Engineering project with NSF support (HRD0120642, HRD 0607081). This instrument has been validated to measure the self-efficacy ofundergraduate students studying engineering, their feelings of inclusion, and outcomesexpectations [4] - [7]. In addition, a satisfaction tracker was used to solicit student feedback

Conference Session

Perspectives on Engineering Education During COVID-19

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Ziyan Bai, University of Washington; Denise Wilson, University of Washington; Shruti Misra, University of Washington; Morgan Anderson, University of Washington, Seattle; Neha Kardam, University of Washington

Tagged Topics

Diversity

Tagged Divisions

New Engineering Educators

demographics were effect coded as dichotomous variables:gender (female = 1 vs. male = -1; other genders were present in very small numbers and wereeliminated from the analysis) and international status (U.S. citizen or permanent resident = -1 vs.international student = 1). Instructional modality was also effect coded as a dichotomous variable(remote = -1 vs. traditional = 1).Additional scales used in this study included those associated with task value, self-efficacy,participation, TA support, faculty support, and positive emotional engagement. Sample items,primary scales as well as the source of these scales are noted in Table 1.Table 1: Independent and Dependent Variables(𝛼 =Cronbach's Alpha measure of internal consistency) References Primary

Conference Session

Faculty Development 2: COVID-19 Impact on Faculty

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Jamie R. Gurganus, University of Maryland Baltimore County; Anita H. Komlodi; Neha B. Raikar, University of Maryland Baltimore County; Maria C. Sanchez, University of Maryland Baltimore County; Charles D. Eggleton, University of Maryland Baltimore County; Mariajose Castellanos, University of Maryland Baltimore County; Mark Berczynski, University of Maryland Baltimore County; Olivia M. Bailey, University of Maryland Baltimore County

Tagged Divisions

Faculty Development Division

development on the faculty, a mixed-methodapproach was adopted. This included interviewing faculty who participated in the PIVOT+ seriesusing well-formulated questions and a validated survey instrument that assesses the faculty’sattitudes, perceptions, and self-efficacy towards online teaching and learning. This web-basedsurvey, hosted through Qualtrics, was borrowed, with permission, from a previous study thatexamined online teaching self-efficacy of faculty [10]. Self-efficacy items included instructionalstrategies, use of computers, classroom management and student engagement. Faculty attitudesand perceptions were also examined measuring satisfaction, perceptions of student learning,future interest in teaching online and their computer skills

Conference Session

Pre-College Engineering Education Division Technical Session 6

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Francisco Cima, Old Dominion University; Pilar Pazos, Old Dominion University; Jennifer Jill Kidd, Old Dominion University; Kristie S. Gutierrez, Old Dominion University; Stacie I. Ringleb, Old Dominion University; Orlando M. Ayala, Old Dominion University; Krishnanand Kaipa, Old Dominion University

Tagged Divisions

Pre-College Engineering Education

Beliefs about engineering Methods integration (BEI) Collaboration 3 Self-efficacy for integrating Elementary Science Methods + Fluid engineering (SEI) MechanicsInstrumentsTwo survey instruments were used to assess the variables of interest. The Attitudes Surveymeasured PSTs’ beliefs about integrating engineering into their future teaching. The instrumentwas adapted from existing scales [22], [23], incorporating elements of social cognitive theory[24] to measure PSTs’ beliefs about engineering integration (BEI) and self-efficacy forintegrating engineering (SEI). Beliefs refer to one’s mental representations of reality that

Conference Session

The Role of Peers in Promoting Learning and Persistence

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Thien Ngoc Y Ta, Arizona State University; Gary Lichtenstein, Arizona State University; Cody D Jenkins, Arizona State University; Karl A. Smith, University of Minnesota - Twin Cities; Ryan James Milcarek, Arizona State University; Samantha Ruth Brunhaver, Arizona State University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

of URG students [13],[14].We hypothesize that PLSGs will effectively provide engineering transfer students with socialsupport that, in turn, promotes institutional and major persistence in ways consistent with socialcognitive career theory (SCCT).Study DesignTreisman’s approach has been implemented at several institutions [15], [16], [17]. Our projectdiffers in four critical ways: we (1) utilize the PEERSIST model in an engineering context, (2)extend beyond student achievement to also measure self-efficacy beliefs, (3) employ a virtualplatform to accommodate the unique work and personal circumstances of transfer students and(4) compare PLSG results to a TA-led study group.After piloting the method with four students in Spring 2020, the

Conference Session

Design Across Curriculum 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sheri Sheppard, Stanford University; Helen L. Chen, Stanford University; George Toye, Stanford University; Felix Kempf, King's College London; Nada Elfiki, Stanford University

Tagged Divisions

Design in Engineering Education

5 1.8% Missing 7 2.6%2.2 Survey Design and Key VariablesThe research team worked closely with the course teaching team to align the pedagogical goals,milestones, strategies, and assignments to the survey measures and questions. The surveyinstrument addressed three general topics related to: 1) education and career pathways; 2)innovation, entrepreneurship, and design self-efficacy measures; 3) the learning experience ofthe course. This paper primarily addresses the first two areas.Education and Career Pathways (31 survey items)One major challenge faced by our research team was how to efficiently ask about the careerpaths and plans that students have pursued since

Conference Session

Women in Engineering Division Technical Session 7

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Victoria Beth Sellers, University of Florida; Idalis Villanueva, University of Florida

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

measures to determine mismatches between how efficacious a woman in engineeringthinks she is versus the strategy she chooses and if it depends on the type of HC or who thecommunicator of the HC is. Our future work will compare the strategies used by people withother gender identities in engineering to see how:(1) others work to overcome HC inengineering, and (2) see how different others’ strategies are to those that women employ. We alsoplan to analyze responses to a self-advocacy item to determine how women extend their self-efficacy into advocating for themselves and others in engineering. With these findings, we aredeveloping professional development workshops to support women engineers’ advocacymentoring capacity within engineering

Conference Session

Pre-College Engineering Education Division Technical Session 4

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Amanda M. Gunning, Mercy College; Meghan E. Marrero, Mercy College; Kristen V. Larson, Mercy College

Tagged Topics

Diversity

Tagged Divisions

Pre-College Engineering Education

science teacher fellows. Gunning presents her research on science teacher self-efficacy, vertical learning communities for teacher professional develop- ment and family STEM learning at international conferences every year since 2009 and is published. She is the Co-Director and Co-Founder of Mercy College’s Center for STEM Education.Dr. Meghan E. Marrero, Mercy College Dr. Meghan Marrero is a Professor of Secondary Education at Mercy College, where she also co-directs the Mercy College Center for STEM Education, which seeks to provide access to STEM experiences for teachers, students, and families. Dr. Marrero was a 2018 Fulbright Scholar to Ireland, during which she implemented a science and engineering program for

Conference Session

Engineering Education During the COVID-19 Pandemic

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Chadia A. Aji, Tuskegee University; M. Javed Khan, Tuskegee University

Tagged Divisions

Educational Research and Methods

hands-on problemsolving and group work using zoom breakout rooms. The virtual in-class active-learning wasimplemented through solving of appropriately scaffolded problems at varying levels of Bloomstaxonomy. Virtual peer-to-peer interactions were implemented through the use of Zoom breakoutrooms.Assessment Instruments: The impact on the students’ motivation as a result of the learningenvironment, was measured using the Motivational Strategies and Learning Questionnaire(MSLQ) [14]. This instrument measures the dimensions of self-efficacy (5 items), intrinsic value(9 items), test anxiety (4 items), cognitive strategies (13 items) and self-regulation (9 items) on a5-point Likert scale (1- Strongly Disagree, 2 - Disagree, 3 -Neutral, 4- Agree, 5

Conference Session

Pre-College Engineering Education Division Technical Session 9

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Mariel Kolker, Morris School District

Tagged Topics

Diversity

Tagged Divisions

Pre-College Engineering Education

domain during the pre-college yearsthat is one of the strongest predictors of intent to pursue or persist in a STEM major in college.This exploratory case study examined the lived experiences of eight high school girls whoexhibited strong STEM identities. This work reports on the role that all-female STEM spacesinfluenced participants’ intent to pursue STEM majors in college. Eight junior and senior girlswere interviewed over the course of an eight-week period during fall 2019 regarding theirperceived feelings of self-efficacy, their feelings of recognition in STEM, and their interest inSTEM domains. This qualitative research was framed using Godwin’s 2016 Engineering IdentityFramework, adapting it to accommodate a broader STEM Identity and

Conference Session

CoNECD Session : Day 2 Slot 6 Technical Session 2

Collection

2021 CoNECD

Authors

Ekundayo Shittu, George Washington University; Jennifer Dashiell-Shoffner, North Carolina A&T State University; Hyung Nam Kim, North Carolina A&T State University

Tagged Topics

CoNECD Paper Submissions, Diversity

constructs in the population. The constructs are all positively correlated, withmagnitude of correlation corresponding to the size of the bubble. This is shown by the checkedbubbles intersecting any two pairs of measures in Figure 2. It is evident that Anticipatory Cognitionis correlated and significant to several of the measures, but lacks significance against stereotypethreat, isolation, extant knowledge and future anticipation. For example, the weaker theparticipants infer the stereotype threat, the higher is their attention and focus to solving theirresearch problem. It is also evident from this Figure that Academic Self Efficacy is predominantlycorrelated

Conference Session

Design Across Curriculum 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Christopher Rennick, University of Waterloo; Carol Hulls P.Eng., University of Waterloo; Andrew Gryguć, University of Waterloo

Tagged Divisions

Design in Engineering Education

affect, is self-efficacy asdescribed in Bandura’s Social Cognitive Theory [5]. According to this theory, peoples’ beliefs intheir capabilities vary across domains and situations, and can develop through 4 mechanisms: 1. Mastery experiences: achieving success on a challenging task 2. Social modeling: seeing similar people achieve success 3. Social persuasion: being convinced by others that one can succeed; and 4. Physical and emotional statesSelf-efficacy can have significant impacts on student resilience, persistence, and attitude during aproblem solving session; as Bandura describes: “How people perceive the structuralcharacteristics of their environment—the impediments it erects and the opportunity structures itprovides

Conference Session

Engineering Design Graphics Division Technical Session 4: A Potpourri of Ideas

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Daniel P. Kelly, Texas Tech University; Jeremy V. Ernst, Embry-Riddle Aeronautical University; Aaron C. Clark, North Carolina State University at Raleigh; Erik Schettig, North Carolina State University at Raleigh

Tagged Topics

Diversity

Tagged Divisions

Engineering Design Graphics

, including student scoreon the pretest three-dimensional modeling self-efficacy (3DSE) assessment, gender, age, andwhether or not the student had a parent with professional engineering backgrounds. The three-dimensional self-efficacy instrument consisted of nine questions, each being a 7-point Likerttype item, designed to measure students’ self-efficacy related to modeling three-dimensionalobjects [11]. Logistic regression could not identify for which subgroups of students the variableswere most significant. For these reasons, machine learning analytics software was used toexamine the predictors, and their interactions, that led to persistence in engineering degreeprograms. Machine learning has gained popularity over recent years due to its ability

Collection

2021 ASEE St. Lawrence Section Conference

Authors

Matthew Jordan Ford, Cornell University; Soheil Fatehiboroujeni, Cornell University; Hadas Ritz, Cornell University

. 1c.One measure of whether or not an activity supports student agency is the diversity of solutionsgenerated by students [3]. We analyzed 36 reports from the final guided-inquiry lab and coded theexperimental procedure on five key decisions such as the type of experiment performed, specimengeometry, and measurement method. We identified 29 unique approaches to the problem, with noone approach accounting for more than three submissions.Analysis of student outcomes. Student outcomes were measured by a survey of students’attitudes and self-efficacy administered directly after every lab activity except for the first one.The fraction of students endorsing statements related to a sense of agency increased dramaticallybetween the “traditional” labs and

Conference Session

STEM Issues

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Laura Kasson Fiss, Michigan Technological University; John L. Irwin, Michigan Technological University; Sarah Tan, Michigan Technological University

Tagged Topics

Diversity

Tagged Divisions

Engineering Technology

, extrinsic goal orientation, task value, control of learning beliefs, self-efficacy forlearning and performance, critical thinking, and metacognitive self-regulation; 2) the Change-Readiness Assessment [10] which assess 7 subscales, including adventurousness, confidence,adaptability, drive, optimism, resourcefulness, and tolerance for ambiguity; 3) PersistenceMeasures [11] which measures 3 responses including graduate study, career, and intent to changemajor; and 4) the Longitudinal Assessment in Engineering Self-Efficacy [12] which providesresults in six subscales, including self-efficacy, sense of belonging, and career expectations. Allof the questions are related to the course and/or learning environment. These questionnairesemploy 7-point Likert

Conference Session

Design Methodologies 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

J. Blake Hylton, Ohio Northern University; Patrick James Herak, Ohio State University; Todd France, Ohio Northern University; Sherri Youssef, Ohio State University

Tagged Divisions

Design in Engineering Education

(strongly agree). The instrument is scored by simple summationof student responses. Scores on the individual scales and subscales should be compared to themaximum possible score, which is seven times the number of items in the scale. All items, broken downby scale and subscale, are listed in the Appendix.The 2014 Standards for Educational and Psychological Measurement (AERA, APA, & NCME, 2014) wereused as a framework for gathering evidence of validity for the self-efficacy instrument, following thevalidation process presented by Cook (2016). A summary of validity evidence used is presented in Table1 and discussed in detail below. Table 1: Evidence of validity, definitions from Cook (2016, p3) Type of Evidence Definition

Conference Session

CoNECD Session : Day 2 Slot 3 Technical Session 3

Collection

2021 CoNECD

Authors

Mary E. Fitzpatrick, University of Wisconsin - Madison; Manuela Romero, University of Wisconsin - Madison; James A. Yonker

Tagged Topics

CoNECD Paper Submissions, Diversity

specified). In addition, we assessed social cognitive variables related to educationaland career decision making, including engineering self-efficacy, expectations for the field ofengineering, commitment to major and degree completion. In 2019, students were asked if theyidentified as a member of the LGBTQ+ community, allowing for a better understanding of thesestudents’ experiences. Data from all three survey years were combined to investigate trends oncritical measures related to persistence in engineering. We found that students’ assessment of theeducational environment (professors and student interactions) were relatively stable, while otheraspects of the environment (experiences of stereotyping and harassment) significantly increasedacross the

Collection

2013 North Midwest Section Meeting

Authors

Cristinel Ababei; Anca M. Miron

format of our summer camp, which we project would helpeven more our main goal, is to organize follow-up summer camps (in the following year)with the same participants. Exposing girls repeatedly to engineering concepts will providethe necessary reinforcement of the main topics and will foster the desire to pursueengineering careers. In addition, it is also desirable to maintain a database of participantsand their contact info (with parental consent) to keep track of their careers later in theirlives. Such data would present concrete statistics about how many participants willeventually pursue careers in engineering.To measure the improvement in perceived self-efficacy, we plan to update the exitquestionnaire with an additional question, “I

Conference Session

Graduate Studies Division Technical Session 3

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Chi-Ning Chang, The University of Kansas; Guan Kung Saw, Claremont Graduate University; Uriel Lomelí-Carrillo, The University of Texas at San Antonio; Mingxia Zhi, Northside Independent School District; Kahlí Romano, Claremont Graduate University ; Ryan Culbertson, The University of Texas at San Antonio

Tagged Topics

Diversity

Tagged Divisions

Graduate Studies

, to estimate the expected total numberof delayed months, including: 1-3 months, 4-6 months, 7-9 months, 10-12 months, and morethan one year. In terms of the career outcome, we evaluated students’ job search self-efficacy byasking three questions [25]: “Since the COVID-19 outbreak occurred, how confident have youbecome in finding (1) the job for which you are qualified? (2) a job in a company/institution thatyou prefer? (3) the job for which you are prepared?” The 5-point Likert scale was from -2 (muchless confident) to 2 (much more confident). The Cronbach’s alpha for these three job search self-efficacy items is .906. The measure for mental health outcome, which focused on symptoms ofdepression and anxiety, asked students if in the last 7

Conference Session

Women in Engineering Division Technical Session 7

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Leanne Kallemeyn, Loyola University Chicago; Gail Baura, Loyola University Chicago; Francisca Fils-Aime, Loyola University Chicago; Jana Grabarek; Pete Livas Jr, Loyola University Chicago

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

participants to report these findings. The remainder of theanalyses focused on gender.Similar rates of persistence existed for women and men, even though when they began theprogram there were statistically significant difference between mean scale scores for freshmenwomen and men on some measures of self-efficacy. For the Self-Efficacy Scale II, t(66) = 2.63,p = .011; Career Success Scale, t(66) = 3.03, p = .004, and Math Scale t(66) = 2.49, p = .015,men averaged higher scores than women (see Table 2 for averages). Although men scored higherthan women on the Self-Efficacy I Scale and Coping Self-Efficacy Scale, these results were notsignificantly different. Women and men scored similarly on the Inclusion Scale. The means onself-efficacy scales at the

Conference Session

NSF Grantees Poster Session

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Indira Chatterjee, University of Nevada, Reno; Kelsey Scalaro, University of Nevada, Reno; Ann-Marie Vollstedt, University of Nevada, Reno; Jeffrey C. LaCombe, University of Nevada, Reno; Julia M. Williams, Rose-Hulman Institute of Technology; Adam Kirn, University of Nevada, Reno

Tagged Topics

Diversity, NSF Grantees Poster Session

students to enter graduate school. Quantitative measurableoutcomes will include increased student retention; increased cohort self-efficacy and identitystatistics; higher-than-average graduation rate for the cohorts through evidence-based programs;and successful placement in industry or graduate school. CREATE will have a broad impact onlow-income, academically talented students in two key ways (1) Support of 32 students withscholarships; and (2) Implementation and assessment of academic and professional developmentsupport mechanisms that are tuned to the needs of these students. Both impacts achievestate/federal strategic workforce diversification goals. Qualitative measurable outcomes willinclude attaining academic and personal goals; increased