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 Division Technical Session 2A: Using Alternative Measurements to Look at Students and Their Success

Collection

2016 ASEE Annual Conference & Exposition

Authors

Nicholas Andres Brake, Lamar University; James C. Curry

Tagged Divisions

First-Year Programs

students during the first andfinal week of the semester to assess the gains in each of the mentioned categories. The surveywas comprised of questions from the questionnaire published by Mamaril19 and Carberry et al.20that are used to measure general, skills, tinkering, and design self-efficacy, and students’engineering design motivation and confidence, respectively. The first 18 items were taken fromCarberry et al.20 which uses a 11 point Likert scale ranging from 0 to 100 with ten pointincrements; and shown to have excellent internal group reliability (Cronbach alpha of 0.96 and0.95, respectively) and significantly differentiate motivation, anxiety, and confidence. Thefollowing 14 items were taken from Mamaril19, which uses a six point Likert

Conference Session

First-year Programs Division: Self Efficacy

Collection

2018 ASEE Annual Conference & Exposition

Authors

Joshua L. Hertz, Northeastern University

Tagged Divisions

First-Year Programs

naturally uncomfortable towork on open-ended problems, because it feels risky to proceed along an ambiguous solutionpath. Nevertheless, some students seem to be more confidently uncomfortable, ready and willingto begin working on open-ended problems. We sought in this study to understand the factors thatmake a student better able to begin work on these projects without directed guidance from theinstructor. Here, this student ability is ascribed to, in part, a student’s ambiguity tolerance andself-efficacy on open-ended problems. A survey instrument to measure ambiguity tolerance and self-efficacy on open-endedproblems was created and subject to internal validation. Students taking a 2-course sequence ofrequired, foundational courses over

Conference Session

First-year Programs Division: Self Efficacy

Collection

2018 ASEE Annual Conference & Exposition

Authors

Stacey Leigh Kelly, Virginia Tech; Darren K. Maczka, Virginia Tech; Jacob R. Grohs, Virginia Tech

Tagged Divisions

First-Year Programs

has shown to be related to students’ choice to leaveengineering. Jones et al. [8] found that engineering belonging was the most significant predictor of first-yearengineering students’ intention to remain in their selected engineering major.Engineering program expectancy. Expectancy is a subjective evaluation of one’s competence in a particulardomain.19 Self-perceptions of competence are central to many theories in the field of motivation, such as self-concepttheory,20 self-efficacy theory,21 and expectancy-value theory.16 An individual’s expectancy beliefs are influenced bymany factors including past experiences (e.g. how well they performed in a high school math class), the influences ofsocializers (e.g., parents, teachers and peers) and

Conference Session

First-year Programs Division: Self Efficacy

Collection

2018 ASEE Annual Conference & Exposition

Authors

Brenda Read-Daily, Elizabethtown College; Kurt M. DeGoede, Elizabethtown College; Stacey L. Zimmerman, Elizabethtown College

Tagged Divisions

First-Year Programs

] [7].Other tools that are helpful in developing self-awareness are the Myers-Briggs Type Indicator(MBTI), the DiSC profile, and the Kolb Learning Style Inventory. These inventories all measuredifferent aspects of an individual; CSF measures natural talent, MBTI measures preferred modesof psychological processing, DiSC measures behavioral style, and Kolb measures individuallearning styles [8]. Our campus chose to utilize the CSF as our primary tool because of Gallup'sspecific focus on college students with their StrengthsQuest platform. This platform utilizes thesame inventory (CSF), but the information provided after taking the inventory is geared towardstudents.Within the Engineering education community, MBTI has been widely used in team

Conference Session

First-year Programs Division: Self Efficacy

Collection

2018 ASEE Annual Conference & Exposition

Authors

Tanya Dugat Wickliff, Texas A&M University; So Yoon Yoon, Texas A&M University; Jacques C. Richard, Texas A&M University; Noemi V. Mendoza Diaz, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

. AcknowledgementThis work was conducted under the auspices of the National Science Foundation (NSF) undergrant number EEC-1640521. However, any items expressed in this paper do not necessarilyrepresent the views of NSF or its affiliates.ReferencesBandura, A. (1977). Self-Efficacy: Toward a Unifying Theory of Behaviorial Change. Psychological Review, 84(2), 191-215.Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147.Engineering Accreditation Commission (2015). Criteria for accrediting engineering programs: Effective for reviews during the 2016-2017 accreditation cycle. Baltimore, MD: ABETFantz, T. D., Siller, T. J., & DeMiranda, M. A. (2011). Pre-collegiate factors influencing the self

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

FPD IX: Research on First-Year Programs and Students, Part II

Collection

2011 ASEE Annual Conference & Exposition

Authors

Rachelle Reisberg, Northeastern University; Joseph A. Raelin, Northeastern University; Margaret B. Bailey, Rochester Institute of Technology; Jerry Carl Hamann, University of Wyoming; David L. Whitman, University of Wyoming; Leslie K. Pendleton, Virginia Tech

Tagged Divisions

First-Year Programs

allengineering students have some form of work experience, though not necessarily provided bytheir colleges. Contextual support was measured as the support provided to students in their firstyear through a number of mechanisms, in particular, financial aid, mentors, advisors, family,friends, teachers, profession, campus life, and living-learning communities.This paper first presents the background, conceptual framework, and methodology of the study.Next, we describe the results to date regarding the effect of contextual support, in conjunctionwith descriptive measures of respondent demographics, on self-efficacy. We then conclude byreviewing significant findings of the study thus far and describe future plans of this ongoingstudy of pathways to

Conference Session

FPD and DEEDs Joint Postcard Sessions

Collection

2018 ASEE Annual Conference & Exposition

Authors

Jessica Daniels; Sophia T. Santillan, Duke University; Ann Saterbak, Duke University

Tagged Topics

Diversity

Tagged Divisions

Design in Engineering Education, First-Year Programs

aspirations, level of motivation, andacademic accomplishments” [8]. In the context of engineering, this is essential as students navigatetechnically challenging coursework and rigorous workloads. Self-efficacy has a strong relationshipto both learning and achievements. As Mamaril et al. state, it is most effective to measure self-efficacy at both the general engineering field level and the specific technical skill level [9].Evaluating at these different levels yields a more comprehensive understanding of a student’sconfidence in their overall engineering abilities. A major contributor to a student’s self confidence in completing engineering tasks is theirperceived proficiency in technical skills. Usher et al. investigated students in

Conference Session

First-Year Programs: Focus on Student Success I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Matthew Cavalli, Western Michigan University; Anetra Grice, Western Michigan University

Tagged Divisions

First-Year Programs

Western Michigan University’s College of Engineering and Applied Sciences for since 2010. American c Society for Engineering Education, 2021 Self-Efficacy, Mathematical Mindset, and Self-Direction in First-Year Engineering StudentsIntroductionIncoming first-year students in engineering, engineering technology, and computer science atWestern Michigan University (WMU) are placed into cohorts according to their preferred majorand initial math placement level. Cohort members share at least two courses (usually three orfour) during each of their first two semesters with the goal of encouraging study group formationand peer support. Peer tutoring and

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

FPD9 - First Year Learning & Assessment

Collection

2008 Annual Conference & Exposition

Authors

Gary Halada, State University of New York at Stony Brook

Tagged Divisions

First-Year Programs

a scenario-based, task-specific on-line assessmentinstrument, the Self-Efficacy Assessment Survey (SEAS), and evaluated its use for pre- andpost-assessment of students in a first year Introduction to Engineering course. Through acombination of the SEAS and other quantitative and qualitative assessment tools, incorporationof problem-based and active learning activities are found to enhance student self-belief in theirability to learn engineering-related material and accomplish certain engineering-related tasks.Use of scenario-based questions to measure student confidence levels (as has been done in theSEAS) provides a unique mechanism to gain insight into student self-efficacy, though questionsmust be carefully designed to limit the impact

Conference Session

The Best of First-Year Programs Division

Collection

2017 ASEE Annual Conference & Exposition

Authors

Jan DeWaters, Clarkson University; John C. Moosbrugger, Clarkson University; Pankaj Sharma, Clarkson University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

online at http://caeeaps.stanford.edu/phpESP/admin/manage.php.[20] LAESE (Longitudinal Assessment of Engineering Self-Efficacy) survey versions 3.0 (copyright 2006) and 3.1 (copyright 2007), which are products of AWE (Assessing Women and Men in Engineering), available online at www.aweonline.org.[21] DeVellis, R. F. (1991). Scale Development: Theory and Applications. Newbury Park, California: Sage Publications.[22] Armstrong, J.B., and Impara, J.C. (1991). The impact of an environmental education program on knowledge and attitude. Journal of Environmental Education, 22(4):36-40.[23] Barrow, L. H., and Morrisey, J. T. (1987). Ninth-grade students' attitudes toward energy: A comparison between Maine and New Brunswick. Journal of

Conference Session

First-Year Programs Division Technical Session 2A: Using Alternative Measurements to Look at Students and Their Success

Collection

2016 ASEE Annual Conference & Exposition

Authors

Mark Schar, Stanford University; Angela Harris, Stanford University; Robert J. Witt, University of Wisconsin - Madison; Robert Rice, University of California - Merced; Sheri Sheppard, Stanford University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

) and have shown that self-expansion can have many benefits includingsharing of resources and greater self confidence. We call this “closeness,” and have used Aron’sscale to measure student closeness to “others” in the engineering classroom – Professor, TA, LabGroup, Classroom and Friend. A total of 571 complete observations were obtained at threeuniversity locations among students enrolled in the local equivalent course, Introduction to SolidMechanics or Statics. Classroom sizes varied from Large (~400 students) to Medium (125-150students) to Small (75-90 students).Results show that closeness plays an important role in classroom performance, particularly incombination with mechanics self-efficacy (or personal confidence in your mechanics

Conference Session

First-Year Programs Division Technical Session 9: Evaluating and Measuring Recruiting and Major Selection Strategies

Collection

2016 ASEE Annual Conference & Exposition

Authors

Juan David Ortega, Universidad EAFIT, Medellin - Purdue University, West Lafayette; S. Zahra Atiq, Purdue University, West Lafayette; Hector Enrique Rodriguez-Simmonds, Purdue University, West Lafayette

Tagged Divisions

First-Year Programs

Major? A Qualitative Study of Values and Expectations    1. Introduction    Decision making is a complex phenomenon which has been studied by researchers in variousfields like sociology, psychology, and neurology1. In STEM education, student decision makingis often linked to persistence. Hence, theories like the Social Cognitive Theory (SCT)2,3 andMotivation theory4 are often employed to investigate students’ decision to enroll in a certainmajor. Such studies repeatedly discuss ideas like interest, values, and expectations as factors thatdrive student decision making process.Bandura classifies expectations into performance (self-efficacy) and outcome expectations2. Inturn, outcome expectations comprise anticipation of physical (e.g. monetary

Conference Session

First-Year Programs Division Technical Session 2A: Using Alternative Measurements to Look at Students and Their Success

Collection

2016 ASEE Annual Conference & Exposition

Authors

Jack Bringardner, New York University; Christopher Leslie, New York University; Gunter W. Georgi, New York University; Alyssa Marie D'Apice, New York University

Tagged Divisions

First-Year Programs

primary motivator for emphasizing teamwork in the classroom. It has been shown thatteamwork assignments can increase self-efficacy for most students.5 Improving student efficacyis a critical component to success in education as well as success in industry. A number ofmethods for improving student self-confidence in succeeding have been tested. Two commontechniques that have been implemented in first-year engineering courses are a teamwork trainingsession and the use of teamwork agreements. Teamwork training, seminars, or orientationsattempt to provide students without teamwork experience the knowledge necessary to practiceteam skills. Teamwork agreements, charters, or contracts are used to provide the guidelines thatwould exist in the

Conference Session

First-Year Programs Division Technical Session 8: Ways to Measure "Things" About Your Course(s)

Collection

2016 ASEE Annual Conference & Exposition

Authors

Lilianny Virguez, Virginia Tech; Kenneth Reid, Virginia Tech; Tamara Knott, Virginia Tech

Tagged Divisions

First-Year Programs

a desirable trend1,2. Specifically, a study involving one cohort of first-yearengineering students from a large public university showed that first-year engineering students’expectancy-related beliefs, including expectations for success in engineering and self-efficacy inengineering, as well as value related beliefs, including identification with engineering, interest, cost, andutility value decreased over their first year for both male and female students. Within this population,male students reported a higher level of expectation for success than female students; higher expectationfor success tended to predict a higher academic performance over the first year3.Engineering programs have seen a wave of revisions in their first-year programs

Conference Session

First-Year Programs Division Technical Session 2A: Using Alternative Measurements to Look at Students and Their Success

Collection

2016 ASEE Annual Conference & Exposition

Authors

Nora Honken, University of Cincinnati; Patricia A Ralston, University of Louisville; Thomas Tretter, University of Louisville

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

impacted by his/her competency, self-efficacy, andtheir perceived level of control over the task31. Weiner32 states that expectancy will be lower ifthe individual’s perceived ability is low or his/her perceived difficulty of the task is high. Healso states that if an individual assumes that conditions will remain the same and that his pastsuccess was due to ability, he will anticipate success in another similar task. Since manystudents measure success by GPA, first semester GPA was used as a measure of expectancy inthe current study. Further support for using GPA to measure expectancy is given in the literaturereview section.Value Value is related to the incentive or gain from doing or completing a task31. Eccles andWigfield31 list four

Conference Session

Projects and Problems in First-Year Courses

Collection

2009 Annual Conference & Exposition

Authors

Senay Purzer, Purdue University

Tagged Divisions

First-Year Programs

instructors takingstudents’ gender, ethnicity, engineering skills, science backgrounds, and leadership skills intoconsideration. All teams were composed of three or four members. Two of the teams weremixed-gender and each one included two male and two female members. Students’ initial andfinal self-efficacy scores were measured using an engineering self-efficacy instrument designedin alignment with the course objectives. Page 14.1188.4Selection of Case StudiesThree students, Bryan, Eric, and Alex (the most supportive, the most responsive, and the mostdisruptive) were chosen for in-depth analysis. All student names reported in this paper

Conference Session

First-Year Programs: Sunday 5-Minute Work-in-Progress Postcard Session

Collection

2017 ASEE Annual Conference & Exposition

Authors

Philip Reid Brown, Rutgers, The State University of New Jersey

Tagged Divisions

First-Year Programs

on programming activities, facilitated by both graduate and undergraduate teachingassistants. Students would then have to complete homework assignments based on recitation modules.Motivation and Self-Efficacy OutcomesDesired ResultsThe development of this course was also informed by motivation and self-efficacy theory, and high-levelcourse outcomes were set to increase both student motivation in the course and their self-efficacy as aprogrammer. Motivation was measured using the five constructs of the MUSIC Model of AcademicMotivation[9]: Empowerment, Usefulness, Success, Interest, and Caring. These constructs are defined inTable 2. Table 2: The MUSIC Model MUSIC Letter Name

Conference Session

First-Year Programs: Focusing on Student Success

Collection

2019 ASEE Annual Conference & Exposition

Authors

Melissa Lynn Morris, West Virginia University; Robin A. M. Hensel, West Virginia University; Joseph Dygert, West Virginia University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

administered X X X MSLQ X X X X XThe GRIT survey is a questionnaire consisting of 12, 5-point Likert scale (1 = not gritty to 5 =very gritty) questions that were developed by Angela Duckworth from the Department ofPsychology at the University of Pennsylvania. [23]. Duckworth has identified grit as a unique trait,defining it as “perseverance and passion for long term goals” [22].During the first-year, students’ academic self-efficacy has been directly related to academicperformance [10]. Among other things, the LAESE survey measures a student’s academic self-efficacy. The LAESE survey instrument is a validated instrument developed via the NSF

Conference Session

First-year Programs Division Technical Session 16: That Important Decision - Which Engineering Major?

Collection

2015 ASEE Annual Conference & Exposition

Authors

Frank Blubaugh, Purdue University; Joyce B. Main, Purdue University, West Lafayette

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

Using asimilar approach of measuring cultural consumption and preferences by proxy, we examinestudent music genre preference  as  a  potential  mediating  factor  in  engineering  students’  disciplinechoice.We situate our examination in the context of self-efficacy, which has been shown to have asignificant impact on student behavior, including major choice. Self-efficacy, the belief in one'sabilities, plays a central role in the achievements of individuals throughout their careers.Differing levels of self-efficacy has been documented to impact student behavior from academicachievement to the success in a job search.2 Furthermore, self-efficacy has been shown to have asignificant impact  on  students’  decisions  to major in engineering