Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Megan Gray, Duke University; Ann Saterbak, Duke University; Sophia T. Santillan, Duke University; Michael Rizk, Duke University; Jessica Sperling, Duke University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

engineering design process to meet the needs of aclient; 2) iteratively prototype a solution; 3) work collaboratively on a team; and 4) communicatethe critical steps in the design process in written, oral, and visual formats. Students work on oneproject team for the entire semester, with the focus of delivering a built and tested solution to theclient. To better understand the effects of this course, we used a quantitative evaluation process.The survey addresses how the course contributes to students’ self-efficacy and commitment infour areas: professional development, professional skills, engineering/academics, and creativity.Using a repeated-measures design, all students taking the course in fall 2018 were invited toparticipate in a survey

Conference Session

First-Year Programs: Maker Spaces in the First Year

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Jennifer S Mullin, UC Davis

Tagged Divisions

First-Year Programs

where they think they can succeed.Students may have high-self efficacy in one area and lower self-efficacy in others. For example,some students may be very confident in their academic test taking skills but feel less so withtheir abilities to build a prototype. Carberry et al. [5] developed an engineering design self-efficacy survey instrument to assess student’s confidence, motivation, ability and anxiety toperform key steps in the design process.Experiences in overcoming specific obstacles or repeated failure can both influence one’s taskself-efficacy. Self-efficacy is not a fixed state nor a holistic measure. Therefore, introductorycurricular experiences intended to engage and retain engineering students are especially critical.Experiences

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Racheida S. Lewis, University of Georgia; Holly M. Matusovich, Virginia Polytechnic Institute and State University

Tagged Divisions

First-Year Programs

motivation withrespect to problem-based learning (PBL), using expectancy-value theory as a guiding framework.Although the original study used expectancy-value theory, it is important to note that in practice,expectancy and self-efficacy are similar enough to be empirically indistinguishable [9], [19], [20].Both self-efficacy and outcome expectations “stress the role of personal expectations as a cognitivemotivator” [9]. The measurement of expectancy typically includes the individuals’ beliefs abouttheir own ability in addition to their comparative sense of competence (i.e. their competence beliefscompared to others), whereas self-efficacy focuses more on the individuals’ beliefs of their abilitywith an emphasis placed on the ability to accomplish a

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Vanessa Svihla, University of New Mexico; Pil Kang, University of New Mexico; Yan Chen, University of New Mexico; Chen Qiu, University of New Mexico; Jordan Orion James, University of New Mexico

Tagged Divisions

First-Year Programs

baselinegroup in a first-year chemical engineering course at a Hispanic-serving research university in thesouthwest United States. Students completed measures of design self-efficacy, explicit designknowledge, and implicit design framing knowledge as a pre/post course measure. Usingexploratory factor analysis, we identified two explicit design knowledge factors ill-structuredness and framing. Using repeated measures ANOVA, we found that students in bothbaseline and implementation groups reported moderate design self-efficacy, with post-coursescores slightly but significantly higher. No difference was found by group or timepoint onstudents’ explicit knowledge of design. Compared to the baseline, the implementation groupshowed more growth in implicit

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Abigail M. Richards, Montana State University; Ryan Anderson, Montana State University; Carrie B. Myers, Montana State University

Tagged Divisions

First-Year Programs

, personal interest in studyingengineering (figure 5) and student’s reported academic self-efficacy (figure 6) related tounderstanding of engineering problems, ability to perform well on exams and overcomesetbacks. 5 5 4.5 4.5 4 4 3.5 3.5 3 3 2.5

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Jill Davishahl, Western Washington University; Sura Alqudah, Western Washington University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

in which to integrate newcontent in an effective manner. The total class time required for all three interventions ranges from 1-2 hourswhich equates, on the higher end, to one class session per quarter. The researchers and instructors of the courseagreed that the number of interventions and required time is reasonable without interfering with the core classmaterial. These interventions are hypothesized to improve engineering students’ sense of belonging and self-efficacy in their majors [14, 15].After considering course assignments and scheduling, the researchers chose a selection of ENGR 104 coursesin which to embed the interventions: Fall 17, Spring 18, and Fall 19. Each course was taught by a differentinstructor however, the content of

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Nisha Abraham, University of Texas at Austin; Nina Kamath Telang, University of Texas at Austin

Tagged Divisions

First-Year Programs

enrolled students attended regularly; EE 307E showed even higher ratesof attendance, with 75% of enrolled students being in the SI group. These results mirror the datawe have seen in past semesters for these courses and match what other programs have presented.One criticism of accurately determining the impact of a voluntary support program like SI is thedifficulty in extricating any self-selection bias. For example, highly prepared freshmen either usethese services at higher rates or do not make use of any supports, yet still perform well in thecourse. Using one type of college prediction measure (SAT scores), all enrolled students in thetwo courses were divided into five groups, each with a 50-60 point range of SAT scores and thenfurther

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

MSLQ X X X X X X X XThe GRIT survey was developed by Angela Duckworth and consists of 12 Likert Scale questions[2]. Grit, defined as “perseverance and passion for long term goals”, was recognized as a trait byDuckworth [3].The LAESE survey was developed at Penn State University with support from the NationalScience Foundation. The LAESE was designed to measure the self-efficacy of undergraduateengineering students by using 31 Likert scale questions. Self-Efficacy aspects of studentsmeasured by the survey include outcomes expected from studying engineering, the process ofselecting a major, expectations about workload, coping strategies in challenging situations, careerexploration, and the

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Peter M. Ostafichuk, University of British Columbia, Vancouver; Susan Nesbit, University of British Columbia, Vancouver; Naoko Ellis P.Eng., University of British Columbia, Vancouver; Gerald Tembrevilla, University of British Columbia, Vancouver

Tagged Divisions

First-Year Programs

academic transition to university witha series of optional, easy-to-access, and inexpensive-to-deliver resources implemented within thecontext of a core first-year course. Ultimately, a series of online interactive videos (“universitylearning screencasts”) were developed and deployed starting in 2018.To assess the impacts of these screencast resources, a mixed methods study design was adopted.Several approaches to measure changes in student metacognition were used, including theMetacognitive Awareness Inventory, a qualitative interview process, a beliefs questionnaire, andcorrelation between utilization and course performance. Other aspects of effectiveness of thescreencasts were assessed through exploration of student perceptions and usage

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Cara Mawson, Rowan University; Cheryl A. Bodnar, Rowan University; Scott Duplicate Streiner, Rowan University

Tagged Divisions

First-Year Programs

, anonparametric one-way ANOVA test was completed using SPSS in order to compare thecategories. The effect size for this study was calculated using Cohen’s D. For the secondresearch question, the average number of attempts for each student was compared to each of thefive components of the MUSIC model by calculating the Pearson correlation coefficients usingSPSS[19].​ ​Data was then compiled into RADAR plots in order to evaluate the relationshipbetween academic motivation and the number of attempts needed to complete a quest. Data wascategorized as being from three categories: all students, the top 20 performing students, and thebottom 20 performing students as measured by the average number of attempts. The differencein populations was analyzed using an

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

Tagged Divisions

First-Year Programs

, M.R. Blais, N.M. Briere, C. Senecal, and E.F. Vallieres, “The Academic Motivation Scale: A measure of intrinsic, extrinsic, and amotivation in education,” Educational and Psychological Measurement, vol. 52, no. 4, pp. 1003-1017, 1992. [6] A. Bandura, “Human agency in social cognitive theory.” American Psychologist, vol. 44, no. 9, pp. 1175-1184, 1989. [7] D.H. Schunk, “Self-efficacy and academic motivation,” Educational Psychologist, vol. 26, nos. 3 & 4, pp. 207-231, 1991. [8] T.R. Mitchell and D.M. Nebeker, “Expectancy theory predictions of academic effort and performance,” Journal of Applied Psychology, vol. 57, no. 1, pp. 61-67, 1973. [9] V.H. Vroom, Work and motivation. New York, NY: John Wiley and Sons, 1964.[10

Conference Session

First-Year Programs: Assessment in the First Year

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Jamie R. Gurganus, University of Maryland, Baltimore County; Shannon M. Clancy, University of Michigan; Richard Olaf Blorstad, DeMatha Catholic High School; Ryan Reinhardt; Charles D. Eggleton, University of Maryland, Baltimore County; L. D. Timmie Topoleski, University of Maryland, Baltimore County

Tagged Divisions

First-Year Programs

in 1993to evaluate the efforts to improve engineering education at the University of Pittsburgh. “ThePFEAS was constructed to measure many of Seymour and Hewitt’s primary reasons studentsleave engineering. The PFEAS attitudinal subscales were administered to assess students’attitudes about engineering” [17]). Seven factors identified by the original authors werepostulated to underlie the attitudinal items: general impressions, financial influences,contributions to society, perceptions of work, enjoyment of math and science, engineering asexact science, and family influences. The LAESE (longitudinal assessment of engineering self-efficacy) instrument was usedto measure the self-efficacy of women studying engineering, including feelings

Conference Session

The Best of First-year Programs Division

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Campbell R. Bego, University of Louisville; Jason Immekus, University of Louisville; Jeffrey Lloyd Hieb, University of Louisville

Tagged Divisions

First-Year Programs

Research Paper examines non-cognitive predictors of first-year engineeringretention for students who received a C in their first semester mathematics course at theUniversity of Louisville. Scores across eight non-cognitive measures served as model predictors,obtained at the beginning of the first year, including: value interest in engineering, perceivedeffort, opportunity, and psychological costs, perceived belonging uncertainty, contingencies ofself-worth: academic competence, test anxiety, and self-efficacy. Using least absolute shrinkageand selection operator regression, we found that value interest and test anxiety were the strongestpredictors of C-student retention. The results from this study inform research on the decision-making of

Conference Session

First-Year Programs: Major Choice

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Laura Hirshfield, University of Michigan; Stacie Edington, University of Michigan; Michael Dailey, University of Michigan

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

elements of affect. For example, feelings can often beconsidered to be measured by a students’ physiological state [20]; and one contributor to self-efficacy (an aspect of a student’s affect) is physiological state [5]. If a student has an upsetstomach or dizziness – in other words, symptoms of anxiety – they may experience reduced self-efficacy. Whereas if they experience an elevated heart rate or increased blood rush to the head,symptoms that can be associated with being excited, they may experience an increase in self-efficacy. In other words, a student’s most basic feelings will both be influenced by and, in turn,influence, their self-efficacy.Therefore, while it is recognized that it is important to study how different elements of

Conference Session

First-Year Programs: Maker Spaces in the First Year

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Brian Scott Robinson, University of Louisville; James E. Lewis, University of Louisville; Nicholas Hawkins, University of Louisville; Teresa Lee Tinnell, University of Louisville

Tagged Divisions

First-Year Programs

students [27]. The principles ofthe competency-belief component of this theory are similar to Shavelson’s self-concept of ability[28] and Bandura’s self-efficacy construct [29]. While by definition, these three concepts aredifferent, they have proven difficult to isolate empirically [30-34] and are usually measured in thesame manner [27]. Competency beliefs are frequently grounded in self-efficacy theory [22], whichfacilitates the connection between positive feedback and better academic achievement [35]. Valuebeliefs, on the other hand, have been studied less often but are by no means less vital. Whilecompetency beliefs focus on a person’s ability to do a task or engage in an activity, value beliefsfocus on an individual’s desire to engage in an

Conference Session

The Best of First-year Programs Division

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Laurel Whisler, Clemson University; Abigail T. Stephan, Clemson University; Elizabeth Anne Stephan, Clemson University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

”responses related to strategies students realize they were not using effectively.A single researcher scored the responses; thus our study did not have the benefit of a more robustreview of the data or the benefit of inter-rater reliability.Conclusion and Implications for Future ResearchWe propose that a course environment that focuses on increasing metacognitive awarenessthrough self-directed learning in individual and collaborative settings may positively impactstudents’ self-efficacy. As students focus on attaining goals that are important to them, in settingswhere the challenge is not beyond their capability, in a social setting that supports persistence,students’ self-efficacy should be enhanced [16]. This is an area ripe for future

Conference Session

First-year Programs: Core Skills

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Wujie Zhang, Milwaukee School of Engineering; Gina Elizabeth Mazzone, Milwaukee School of Engineering; Anne Alexander, Milwaukee School of Engineering; Jill Meyer, Milwaukee School of Engineering

Tagged Divisions

First-Year Programs

an understanding of students' chemistry education backgroundas well as their intent of study to be able to analyze the results based on their majors (majors willbe clustered and included in the drop-down list). The questions related to motivation assessmentare selected from the attached reference to mainly focus on the three factors of motivation: self-efficacy (Q4 and 5), active learning strategies (Q6-8), and science learning value (Q9-11). Q11looks particularly at whether the response is major-dependent. The questions with the highestloading of these three factors have been chosen. Moreover, to ensure the survey quality, a reversequestion has also been included (Q5).Voluntary Qualtrics surveys containing an informed consent statement were

Conference Session

First-Year Programs: Retention & Bridge Programs #2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Zahrasadat Alavi, California State University, Chico; Kathleen Meehan, California State University, Chico; Kevin Buffardi, California State University, Chico; Webster R. Johnson, California State University, Chico; Joseph Greene, California State University, Chico

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

• I am confident with Precalculus • I am confident with Calculus • I enjoy math • I can apply my math skills to computing and engineering projectsThe post-bootcamp survey included these same ratings so we could investigate potential changesin their attitudes. Fourteen (n=14) of the seventeen bootcamp participants (82%) completed bothsurveys and consented to include their data in our formative assessment. We performed aWilcoxon-Mann-Whitney test to compare pre- and post-bootcamp ratings to test the hypothesisthat the bootcamp would improve students’ self-efficacy. Table 1 shows the mean (M) andstandard deviation (sd) for each item’s rating, as well as the p-value of the hypothesis test.Overall, the average

Conference Session

First-year Programs: Teams and Teamwork

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Emma Tevaarwerk DeCosta, Northwestern University; Kathleen Carmichael, Northwestern University; Lisa M. Davidson, Northwestern University; Ordel Brown, Northwestern University; Elise Gruneisen, Northwestern University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

concept guided thedevelopment of survey questions that measured students’ perceived abilities, in alignment withliterature on project-based teams in engineering educational contexts [24]. The inclusive team-based learning items used the same response scale as the General Self-efficacy Scale, given theevidence of high reliability and cross-cultural validity [25]. Additionally, the survey askedstudents to rate how easy or difficult the 16 inclusive team-based learning activities felt, giventhat team-based activities can involve intercultural exchange. This strategy was informed by theconcept of intercultural effort [19], which explains that measuring students’ intergroupengagement without also measuring the effort required to engage across such

Conference Session

First-year Programs: Focus on Students

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Ahmed Ashraf Butt, Purdue University, West Lafayette; Saira Anwar, Purdue University, West Lafayette; Muhsin Menekse, Purdue University, West Lafayette

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

theirrelationship with academic performance. Second, longitudinal studies to identify the relationshipand impact of employed study strategies on the students' academic performance over the courseof their engineering degree should be conducted. Finally, the researchers may includemotivational factors to discuss the relationship between the students' study strategies and theiracademic performance.AcknowledgmentThe authors would like to thank Dr. Heidi Diefes-Dux and Dr. Morgan Hynes for access tostudent data.References[1] M. C. W. Yip, “Learning strategies and self-efficacy as predictors of academic performance: a preliminary study,” Qual. High. Educ., vol. 18, no. 1, pp. 23–34, 2012, doi: 10.1080/13538322.2012.667263.[2] N. Rosenberg and R. R. Nelson

Conference Session

The Best of First-year Programs Division

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Chao Wang, Arizona State University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

punishment avoidance.SDT also postulates that individuals will adopt more internalized/autonomous forms ofmotivations, resulting in more optimal learning outcomes, when three basic psychological needsare satisfied: autonomy, a sense of choice and control; relatedness, a sense of positive andsupportive connections to others; and competence, a sense of mastery and self-efficacy [18].In a real-world setting, individuals express multiple forms of motivation to varying degrees inany given activity, instead of appearing as either autonomous/internalized orcontrolled/externalized. Examining the learner’s motivation across the whole continuum ofamotivation, external regulation, identified regulation and intrinsic motivation, i.e.,characterizing it into a

Conference Session

ENT Division Technical Session: First-year Experiences

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Scott Duplicate Streiner, Rowan University; Cheryl A. Bodnar, Rowan University; Kaitlin Mallouk, Rowan University; Bruce Oestreich, Rowan University; Kevin D. Dahm, Rowan University

Tagged Divisions

Entrepreneurship & Engineering Innovation, First-Year Programs

three broad learning domains –affective (i.e., self-efficacy), thinking patterns (i.e., developing connections in the pursuit ofvalue creation), and content knowledge/skills [14]. Included in EML content knowledge/skillscan be design iteration and prototyping, which is the assessment focus of this paper and is anelement not seen in many of other first-year engineering design projects that harnesses EML.In the College of Engineering at Rowan University, we set out to foster EM in our first-yearengineering students by transforming a project that leverages Universal Design Principles as aframework for creating toys for children to include EM-related outcomes inspired by KEEN’sthree tenets: Curiosity, Connections, and Creating Value (the 3Cs). In

Conference Session

First-year Programs: Retention and Bridge Programs #1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Scott Martin Hanson, North Dakota Established Program to Stimulate Competitive Research (EPSCoR); Austin James Allard, Turtle Mountain Community College; Robert V. Pieri, North Dakota State University; Paula Jean Comeau, North Dakota State University; North Dakota State College of Science; Megan Even, North Dakota Established Program to Stimulate Competitive Research; Daniel John Luecke, North Dakota State University; Jean Ostrom-Blonigen, North Dakota Established Program to Stimulate Competitive Research; Kelly A. Rusch, North Dakota EPSCoR and North Dakota State University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

been caused by the participants’ unfamiliarity with the 3D printing software/hardware,inadequate supplementary instruction material, and/or the complexity of the device (anintermediate level project). The purpose of the second face-to-face session was to prepare theparticipants adequately for their independent project, and in retrospect, more hands-onexperience with the hardware/software is necessary for participant success. Future individualengineering projects should start with a simpler model that could be upgraded to a moreadvanced design for participants that are more skilled. The authors believe this shift inphilosophy would boost participant success and self-efficacy, as they would be more likely toconstruct their initial device

Conference Session

First-Year Programs: Peer Mentoring

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Noah Salzman, Boise State University; Ann E. Delaney, Boise State University; Catherine Rose Bates; Donna C. Llewellyn, Boise State University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

expand a student’s personal and professional networks,and provide validation and critical feedback on their academic progress. For these reasons,faculty and student interactions are critical to the undergraduate student experience. Additionalstudies done by Crisp and Cruz have found that mentoring can help with student persistence incollege and overall adjustment [14].Impact on Underrepresented StudentsSeveral studies indicate the critical role mentoring and social support networks play specificallyin the educational progress of students from racial and ethnic groups who have been traditionallyunderrepresented in the STEM fields [15], [16]. Studies have demonstrated that mentoring canlead to higher grade point averages, increased self-efficacy

Conference Session

First-Year Programs: Peer Mentoring

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Lakshmy Mohandas, Purdue University; Nathan Mentzer, Purdue University; Aparajita Jaiswal, Purdue University; Shawn Farrington, Purdue University

Tagged Divisions

First-Year Programs

. McKeegan, “Using undergraduate teaching assistants in a research methodology course,” Teach. Psychol., vol. 25, no. 1, pp. 11–14, Feb. 1998, doi: 10.1207/s15328023top2501_4.[5] K. A. Ritchey and S. Smith, “Developing a Training Course for Undergraduate Teaching Assistants,” Coll. Teach., vol. 67, no. 1, pp. 50–57, Jan. 2019, doi: 10.1080/87567555.2018.1518891.[6] M. Komarraju, “Ideal Teacher Behaviors: Student Motivation and Self-Efficacy Predict Preferences,” Teach. Psychol., vol. 40, no. 2, pp. 104–110, Apr. 2013, doi: 10.1177/0098628312475029.[7] J. W. Herrman and J. K. Waterhouse, “Benefits of Using Undergraduate Teaching Assistants Throughout a Baccalaureate Nursing Curriculum,” J. Nurs. Educ. Thorofare, vol. 49

Conference Session

First-year Programs: Retention and Bridge Programs #1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Kamau Wright, University of Hartford

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

engineering students, increasing it from near87% in recent years to 90% after the block scheduling year [5].Diversity in retention effortsWhat has also been reported in literature is that unfortunate disparities and barriers related torace must also be overcome [4, 7, 8]. Studies have focused on barriers to the success of Blackand Latino STEM students [7, 8], including academic, social [7], and institutional barriers [8].Strategies have been described for helping with student retention and success, includingencouragement and maintenance of attributes like academic self-efficacy, confidence andresilience [9]. Traditional theories on retention such as that of Tinto [10], focus on the impact ofadjustment, and adaptation to the dominant culture of an