Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Anthony Bourne, Wright State University; Nathan W. Klingbeil, Wright State University; Frank W. Ciarallo, Wright State University

Tagged Divisions

Educational Research and Methods

SRI showed low correlation between the self-confidencemeasure and student success, while this study showed a strong correlation between high schoolGPA and academic self-confidence. Further study into specific self-confidence measures, suchas mathematics self-efficacy, may provide greater understanding of how self-confidence mayaffect academic success. Previous research has shown a strong link between mathematics self-efficacy and academic success, and tying this to the APCM could be beneficial for fulleridentification of differences across the engineering student population.Bibliography(1) Klingbeil, N.W., Bourne, A.L. (2012). The Wright State Model for Engineering Mathematics Education: A Longitudinal Study of Program Impacts

Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Nora B. Honken, University of Louisville; Patricia A Ralston, University of Louisville; Kate E. Snyder, University of Louisville

Tagged Divisions

Educational Research and Methods

the current study. Of these, 495 completed the survey(98% response rate). The final sample consisted of 479 students (95% participation rate) with Page 24.579.3complete data for all measures included in the analyses. Demographic information for thesample is provided in Table 1. Of note, gender composition for our cohort is relativelycomparable to national averages, but the cohort was less ethnically diverse than the nationalpopulation of engineering students.18 Average ACT composite score for the participants was28.5 (SD = 3.16) and the average ACT math score was 29.0 (SD = 3.16). Forty-one percent ofthe students had a weighted high school GPA

Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Courtney June Faber, Clemson University; Sarah Jane Grigg, Clemson University; Adam Kirn, Clemson University; Justine M. Chasmar; Lisa Benson, Clemson University

Tagged Divisions

Educational Research and Methods

-Level MotivationsSelf-efficacyBandura's work in self-efficacy examines motivations toward short-term tasks.14 Self-efficacyspeaks to students’ specific perceptions on how they will perform on a task.15 Self-efficacy hasbeen shown to influence the use of learning strategies on tasks related to students' courses.16While self-efficacy and expectancy are correlated constructs when examining goals with thesame time scale8, self-efficacy was developed to examine short-term tasks that require a highlevel of granularity17 and makes it more useful for examining motivations toward short-termgoals.For this work, problem solving items were adapted from the Attitudes and Approaches toProblem Solving survey18 to appropriately assess student self-efficacy for

Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Micah Stickel, University of Toronto; Siddarth Hari, University of Toronto; Qin Liu, University of Toronto

Tagged Divisions

Educational Research and Methods

questions on a 7-point Likert scale were asked to students toinvestigate their level of confidence in various aspects of the course materials and studyingengineering. Those related to Engineering Self-Efficacy were taken directly from theLongitudinal Assessment of Engineering Self-Efficacy instrument 20. Through factor analysisusing polychoric correlation, three factors were derived. Those questions and related factors arereported in Table 7.Table 7. Cronbach's Alpha and Loaded Factors of Measuring Self-Efficacy Cronbach’s Alpha Factors Traditional Cohort Inverted CohortSelf-efficacy related to explaining course

Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Adam Kirn, Clemson University; Courtney June Faber, Clemson University; Lisa Benson, Clemson University

Tagged Divisions

Educational Research and Methods

-1055950).References [1] Adam R. Carberry, Hee-Sun Lee, and Matthew W Ohland. “Measuring Engineering De- sign SelfEfficacy”. In: Journal of Engineering Education (2010), pp. 71–79. URL: http: / / onlinelibrary . wiley . com / doi / 10 . 1002 / j . 2168 - 9830 . 2010 . tb01043 . x / abstract. [2] A. Bandura. “Guide for constructing self-efficacy scales”. In: Self-efficacy beliefs of ado- lescents. Information Age Publishing, 2006, pp. 307–337. URL: http://books.google. com/books?hl=en\&lr=\&id=Cj97DKKRE7AC\&oi=fnd\&pg=PA307\&dq=GUIDE+FOR+ CONSTRUCTING+SELF-EFFICACY+SCALES\&ots=cF-Zx\_vHu5\&sig=onq0GKyPXkXj80f6IoboGeGDuYc. [3] MA Hutchison et al. “Factors influencing the self-efficacy beliefs of

Conference Session

College Industry Partnerships Division Technical Session 2

Collection

2014 ASEE Annual Conference & Exposition

Authors

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

Tagged Divisions

College Industry Partnerships

enrolled at four major universities: NortheasternUniversity, Rochester Institute of Technology, Virginia Polytechnic Institute and StateUniversity, and the University of Wyoming. It examines the effect of demographiccharacteristics, cooperative education, contextual support, and three dimensions of self-efficacyand their change over time on retention. It is based on a pathways model that links contextualsupport and cooperative education and other forms of student work experience to self-efficacy asa basis for retention in college and in the engineering major. As a longitudinal study, itincorporates measures at three time periods during the students’ academic experience: theirsecond, third, and fourth years.The original data pool constituted all

Conference Session

New Teaching Methods in Mechanics

Collection

2014 ASEE Annual Conference & Exposition

Authors

Sarah L. Billington, Stanford University; Sheri D. Sheppard, Stanford University; Robert C Calfee, Graduate School of Education, Stanford University; Peggy C. Boylan-Ashraf, Stanford University

Tagged Divisions

Mechanics

time. The developed web-based exercises are for a one-week segment on freebody diagrams and include video clips with opportunities for students to apply concepts boththrough multiple choice questions and interactive exercises. Class time during this week isdevoted to additional hands-on exercises with some supplemental lecture content. Pilot datahave been collected and results are reported on both the quantitative and qualitative information.Quantitative data include measures of performance on concept inventory questions and exams, aswell as self-efficacy data. Qualitative information includes individual homework and in-classwork as well as in-class pair work. In addition to presenting initial findings from our research,we will discuss how

Conference Session

Beyond Students: Issues of Underrepresentation among Parents and Professionals

Collection

2014 ASEE Annual Conference & Exposition

Authors

Scott Hofacker PE, US Army

Tagged Divisions

Minorities in Engineering

attainment and career opportunity, as suggested by social cognitive careertheory11. However, no data on the career self-efficacy of engineers in the workplace exists.During this study, career self-efficacy of black engineers was measured using an adapted 25-question Career Decision Self-efficacy Short Form2 (CDSE-SF) instrument, assessing careerself-efficacy subscales of self-appraisal, occupational information gathering, goal setting,planning, and problem solving. The results of a survey of 131 black engineers in a largegovernment engineering organization indicate that the career self-efficacy of black engineers ishigh. While the CDSE-SF is highly respected and widely used, the recommendation is made tofurther develop and validate the career self

Conference Session

Enhancing the Underrepresented Student Experience

Collection

2014 ASEE Annual Conference & Exposition

Authors

Kari L. Jordan, Ohio State University; Sheryl A. Sorby, Ohio State University

Tagged Divisions

Minorities in Engineering

significantly related to persistence. Their research showed reliableimprovement in persistence (p < 0.05) when motivation was included as a factor. Vogt et al. (28)measured self-variables including academic self-confidence and self-efficacy, as well as otherenvironmental and behavior variables to learn what influences a student’s academic achievement.They found that academic achievement was influenced by self-efficacy (p <= 0.01) and academicself-confidence (p <= 0.01). The results of these studies lead to a common conclusion. Self-regulation is essential inthe persistence of not only underrepresented minority students in engineering, but also allstudents. Self-regulation has also been found to result in improved student self

Conference Session

Diversity in K-12 and Pre-college Engineering Education

Collection

2014 ASEE Annual Conference & Exposition

Authors

Amelito G. Enriquez, Canada College; Wenshen Pong, San Francisco State University; Nilgun Melek Ozer, San Francisco State University; Hamid Mahmoodi, San Francisco State University; Hao Jiang, San Francisco State University; Cheng Chen, San Francisco State University; Hamid Shahnasser, San Francisco State University; Nick Patrick Rentsch, San Francisco State University

Tagged Divisions

K-12 & Pre-College Engineering

and implementing the curriculum; engaging industry partners and engineeringprofessionals; and encouraging family involvement in program activities. Program outcomesassessments include pre- and post-program student surveys that measure student interest inpursuing an engineering degree, academic self-efficacy and motivation, attitudes and enthusiasmof participants towards the program activities, knowledge of specific engineering topics, andawareness of resources and skills needed for success in engineering. A follow-up survey has alsobeen developed to track changes in student attitudes, interests, and educational plans years afterparticipating in the program. The paper presents the results and lessons learned from five yearsof implementation of

Conference Session

Student Learning, Problem Solving, and Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

K. Jo Min, Iowa State University; John Jackman, Iowa State University; Jason C.K. Chan

Tagged Divisions

Educational Research and Methods

Abstract Concepts towards Better Learning Outcomes and Self-Efficacy AbstractWe constructed and analyzed an evidence-based practice case to see if visual models helpstudents develop a better understanding of abstract concepts and enhance their self-efficacywhen solving engineering problems. Abstract concepts without corresponding physicalphenomena are often found in the domains of industrial engineering, engineeringmanagement, and systems engineering. In this study, we focus on inventory control of asupply chain, which is typically a junior level undergraduate production systems course in anindustrial engineering program. Visual models of inventory behaviors were designed tocomplement the

Conference Session

NSF Grantees’ Poster Session

Collection

2014 ASEE Annual Conference & Exposition

Authors

Noah Salzman, Purdue University, West Lafayette; Matthew W. Ohland, Purdue University and Central Queensland University; Monica E. Cardella, Purdue University, West Lafayette

Tagged Topics

NSF Grantees Poster Session

Tagged Divisions

Division Experimentation & Lab-Oriented Studies

Designing andConducting Mixed Methods Research by J.W. Creswell & V.L. Plano Clark, 2007.ParticipantsThis study will focus on the experiences of first-year engineering students. These students areable to inform our research questions because they are the least removed from their precollegeengineering experiences and from the transition to college engineering programs. To the extentthat self-efficacy is important to persistence in engineering4, the mastery experiences of first-yearstudents will be more closely tied to their precollege experiences, whereas the masteryexperiences of upper-level engineering students will be derived from their college engineeringexperiences.Qualitative Data CollectionWe administered a survey on students’ demographic

Conference Session

California on the Move: A Robust Array of Student Success Initiatives

Collection

2014 ASEE Annual Conference & Exposition

Authors

Sharnnia Artis, University of California, Berkeley; Catherine T. Amelink, Virginia Tech

Tagged Divisions

Two Year College Division

centered, andcommunity centered activities [15] is designed to develop the self-efficacy of community collegestudents that participate, specifically as it relates to research skills.MethodologyA mixed-methods approach using formative and summative evaluation measures was used toassess impact of the summer experience on students’ self-efficacy specifically as it pertains to Page 24.1227.3research. A pre-survey was administered to the students one week prior to their arrival on theBerkeley campus. The survey included questions to solicit information on: degree aspirations,knowledge about the admissions process for enrollment at a four-year institution

Conference Session

The Nature of Innovation and Entrepreneurship Session 4

Collection

2014 ASEE Annual Conference & Exposition

Authors

Sarah E. Zappe, Pennsylvania State University, University Park

Tagged Divisions

Entrepreneurship & Engineering Innovation

faculty to publish educational research. Her research interests primarily involve creativity, innovation, and entrepreneurship. Page 24.337.1 c American Society for Engineering Education, 2014 Creative Go-Getters: Antecedents of Entrepreneurial Activities in Engineering UndergraduatesAbstract:The purpose of this study is to examine characteristics of incoming engineering students aspossible predictors of later participation in entrepreneurial activities. Four characteristics wereexamined: 1) locomotion, 2) self-evaluation, 3) creative self-efficacy and 4

Conference Session

Engineering Student Experiences

Collection

2014 ASEE Annual Conference & Exposition

Authors

Denise Wilson, University of Washington; James J. Pembridge, Embry-Riddle Aeronautical Univ., Daytona Beach; Caitlin H. Wasilewski, Seattle Pacific University

Tagged Divisions

Educational Research and Methods

Significant Differences in Student Affective ExperienceAbstractThis study looks at differences in non-intellective measures expressed by two engineeringstudent populations, one at a large public university in the pacific northwest and the other a smallprivate aerospace institution in the southeast. Both student populations are in their first year ofstudy in their respective engineering majors. Previously validated, Likert scale items were usedto measure self-efficacy, task value, peer support, two forms of faculty support, and two forms ofbelonging using a survey instrument. Students at the small private university reported that theirinstitution was friendlier and had a greater sense of togetherness than the public institution.However, no significant

Conference Session

Entrepreneurship & Engineering Innovation Research Technical Session 7

Collection

2014 ASEE Annual Conference & Exposition

Authors

Philip M. Reeves, The Pennsylvania State University; Sarah E. Zappe, Pennsylvania State University, University Park; Elizabeth C. Kisenwether, Pennsylvania State University, University Park; D. Jake Follmer, The Pennsylvania State University; Jessica Menold, Pennsylvania State University, University Park

Tagged Divisions

Entrepreneurship & Engineering Innovation

multiple entrepreneurial situations including idea generation, problemsolving, and opportunity recognition. While educators are still working on the best method ofdeveloping and measuring creativity, it is possible to gauge an individual’s creative self-efficacy,which Tierney and Farmer defined as ‘the belief that one has the ability to produce creativeoutcomes’ (p . 1138)7. For this study, permission was granted to use Tierney & Farmer’s Creative Self-EfficacyMeasure7. The measure contains three items (with a Cronbach’s alpha, internal consistencyreliability, coefficient of α=.574) on a 7 point Likert scale (1= very strongly disagree through 7=very strongly agree). The scale has been used in numerous research studies and

Conference Session

K-12 Teacher Pre-Service and Undergraduate Instructor Training

Collection

2014 ASEE Annual Conference & Exposition

Authors

Howard L. Greene, The Ohio State University; Xi Zhan, Department of Educational Studies, The Ohio State University; Anika Anthony, The Ohio State University; Paul E. Post, The Ohio State University; Andrew James Parkhurst, Ohio state university

Tagged Divisions

K-12 & Pre-College Engineering

in engineering and preparing practicing teachers and engineering students tointroduce middle school students to the engineering design process. This paper describes theTEK8 university-school partnership and presents results from a preliminary study conducted toexamine the partnership’s effectiveness for preparing teachers and engineering students tointerest middle school students in engineering. Data were collected using interviews,observations, and a teacher self-efficacy survey. The survey was appropriated to focus onteachers’ and engineering students’ self-efficacy to interest middle school students inengineering. Methods of analysis included discourse analysis, the constant comparative method,and the nonparametric 1-tailed Wilcoxon

Conference Session

Impacts on K-12 Student Identity, Career Choice, and Perceptions of Engineers

Collection

2014 ASEE Annual Conference & Exposition

Authors

Kimberly A.S. Howard, Boston University; Jacob William Diestelmann, University of Wisconsin - Madison; Tsu-Lun Huang; Lauren E. Aneskavich; Kevin Cheng; Benjamin Bryan Crary, University of Wisconsin - Madison; Jean DeMerit, UW–Madison; Tam Mayeshiba, University of Wisconsin-Madison; Amy K. Schiebel, Edgewood College; Susan C. Hagness, University of Wisconsin, Madison; Steven M. Cramer P.E., University of Wisconsin, Madison; Amy E. Wendt, University of Wisconsin - Madison

Tagged Divisions

K-12 & Pre-College Engineering

135Male 235 130White 315 192Hispanic/Latino 72 30African American 64 29Asian/Pacific Islander 11 11Native American 0 1Multi-racial or Other 1 2Low Income 221 121Not Low Income 242 144Middle School Self-Efficacy Scale (MSSE). At present, no validated engineeringefficacy/outcome expectation measures exist that are appropriate for use with middle school-aged youth. Further, measures of social cognitive variables focus on individuals

Conference Session

NSF Grantees’ Poster Session

Collection

2014 ASEE Annual Conference & Exposition

Authors

Jianyu Dong, California State University, Los Angeles; Pearl Chen, California State University, Los Angeles

Tagged Topics

NSF Grantees Poster Session

Tagged Divisions

Division Experimentation & Lab-Oriented Studies

engineeringstudents [5]. However, up to date research on this aspect is still not adequate to generate acomprehensive understanding of PBL in engineering context. In 2013, California StateUniversity Los Angeles received a RIGEE grant from NSF to conduct an interdisciplinaryresearch to study the impact of collaborative project-based learning (CPBL) on the self-efficacyof traditionally underrepresented minority groups in electrical engineering courses. The projectgoals include: 1) Improve the understanding of the factors that affect the self-efficacy of minoritystudent groups in Engineering; 2) Develop better ways to measure the impact of collaborativelearning in the developmental stages of the student learning process in addition to the learningoutcomes; 3

Conference Session

Systems Engineering Division Technical Session 3

Collection

2014 ASEE Annual Conference & Exposition

Authors

Yue Bi, University of Virginia; Reid Bailey, University of Virginia; Michael C. Smith, University of Virginia

Tagged Divisions

Systems Engineering

feedback they received on their cases, and their generalexperiences with the course SYS 2001. Three major categories of surveys were used to assessstudents’ perceptions (timeline of the use of the technologies included in Figure 1): Page 24.547.7 Self-efficacy surveys were modified based on an instrument measuring engineeringdesign self-efficacy by Carberry and Lee24. The surveys were believed to identify students’self-concepts to engineering design tasks24. Students were asked to rate on a scale of 0-100their confidence, motivation, success, and anxiety in completing each of the 10 tasks whichrepresent a systems approach. Grading surveys

Conference Session

DEED Melange

Collection

2014 ASEE Annual Conference & Exposition

Authors

Sara A. Atwood, Elizabethtown College; Matthew T. Siniawski, Loyola Marymount University; Adam R. Carberry, Arizona State University

Tagged Divisions

Design in Engineering Education

hashigher value (2.94 + 0.87) than cost (2.03 + 0.78) on a 4-point scale (p <0.001). Students at thesmall, liberal arts college responded with generally higher ratings for both value and cost, with alarger average difference between combined value and cost (1.0 and 0.81, respectively), thanstudents at a large, public university. Additionally, students reported higher self-efficacy indesign-based objectives after the course, with an average self-efficacy increase of 15-20 pointson a 100-point scale.IntroductionStandards-based grading (SBG) is an alternative grading system that involves and depends ondirectly measuring the quality of students’ proficiency on well-defined course learning outcomes,i.e., standards.1-3 Student development toward

Conference Session

International Division Technical Session 7

Collection

2014 ASEE Annual Conference & Exposition

Authors

Irene B Mena, Pennsylvania State University, University Park; Thomas A. Litzinger, Pennsylvania State University, University Park; Sarah E. Zappe, Pennsylvania State University, University Park

Tagged Divisions

International

these scales had a strong internal consistency (see results below). Finally, t-testswere conducted on each of the subscales, for both surveys, to determine any significantdifferences in experiences or perceptions between international and domestic students.ResultsIn this section, we describe results from the first-year survey and from the second-year survey.First-year surveyOur first-year survey consisted of seven scales: 1) Self-efficacy: This scale consisted of eight items, all related to students’ perceived levels of self-efficacy. It had the goal of revealing students’ levels of confidence in their abilities to succeed in engineering. 2) Knowledge of the engineering profession: The five items in this scale asked students

Conference Session

NSF Grantees’ Poster Session

Collection

2014 ASEE Annual Conference & Exposition

Authors

Kimberly Warren, University of North Carolina, Charlotte; Chuang Wang, University of North Carolina, Charlotte

Tagged Topics

NSF Grantees Poster Session

Tagged Divisions

Division Experimentation & Lab-Oriented Studies

measured the students’ degree of self-efficacy to remember and understand course content as well as to solve, analyze, evaluate, andcreate a problem related to soil structure, seepage, effective stress, consolidation, and shearstrength. Students were asked to rate on a five-point Likert scale where ‘1’ stands for “cannot doat all” and ‘5’ stands for “certainly can do”. Second, the ‘Student Self-Efficacy for theApplication of Knowledge’ survey included 21 questions developed by the researchers tomeasure the student’s self-efficacy to accomplish tasks associated with the content in the course.Students were asked to rate the same five-point Likert scale. Lastly, the ‘Self-RegulatedLearning Strategies’ survey included 13 questions that were developed

Conference Session

NSF Grantees’ Poster Session

Collection

2014 ASEE Annual Conference & Exposition

Authors

Nathan W. Klingbeil, Wright State University; Anthony Bourne, Wright State University

Tagged Topics

NSF Grantees Poster Session

Tagged Divisions

Division Experimentation & Lab-Oriented Studies

performance in calculus, studentperformance in core engineering courses, and ultimate graduation rates. The current paper willprovide a longitudinal analysis of student perception data, as measured by end-of-course surveys.In particular, the extent to which reported increases in student motivation and self-efficacy havecontributed to the previously reported increases in ultimate graduation rates will be investigated.The Wright State ModelIt is well known that student success in engineering is highly dependent on student success inmath, and perhaps more importantly, on the ability to connect the math to the engineering1-6.However, first-year students typically arrive at the university with virtually no understanding ofhow their pre-college math

Collection

2014 ASEE Zone 1 Conference

Authors

Mohammadjafar Esmaeili; Ali Eydgahi

. In order to test this satisfaction of students in project-based classes, there is notrelationship this study utilizes TAM as a core model to assess the enough evidence to show any attitude changes toward STEMeffect of active learning based classes on students’ intention and course.attitude toward STEM course. Moreover, this study hasexamined the effects of external factors such as social influences,and internal factors such as anxiety and self-efficacy toward This study is attempting to examine the relationship betweenSTEM courses. active learning methodology that has been introduced in one of

Conference Session

Information and Network Security

Collection

2014 ASEE Annual Conference & Exposition

Authors

Richard Scott Bell, Kansas State University; Eugene Y. Vasserman, Kansas State University; Eleanor C. Sayre, Kansas State University

Tagged Divisions

Computing & Information Technology

studentcharacteristics that have been shown to lead towards success in the classroom and influencestudent career selection. These characteristics include self-efficacy in relation to cybersecurity,student interest in further coursework, and research or jobs that involve cybersecurityconcepts 3,12 . By interviewing students enrolled in a cybersecurity course, at multiple pointsduring the semester, we are able to identify student interests and perceptions of cybersecurity anddocument changes in student self-efficacy and interest that occur as the semester progresses.Furthermore, we identify pedagogical practices which students found most useful through thissemester-long investigation. The results from this study will be used to construct a Likert-typescale survey

Conference Session

Industrial Engineering Division Technical Session 2

Collection

2014 ASEE Annual Conference & Exposition

Authors

Imelda Olague-Caballero, New Mexico State University; Delia J. Valles-Rosales, New Mexico State University

Tagged Divisions

Industrial Engineering

team; communicate effectively; and knowledge of contemporaryissues while building students' self-efficacy through direct interactions with industryprofessionals. This model will increase the students' employability by facilitating the creation ofmeaningful connections to the real world of work, and will develop the students' ability tonavigate and negotiate the social, political, and practical dimensions of a workplaceThe model allows teams of 4 students to participate in this experience; they work under thesupervision and guidance of a graduate students acting as peer mentor, who is responsible toassist and support the team during the completion of their project. It is required that the teamspend two hours a day during twelve weeks

Conference Session

Addressing the NGSS, Part 2 of 3: Supporting K-12 Science Teachers in Engineering Pedagogy and Engineering-Science Connections, Part 2 of 3

Collection

2014 ASEE Annual Conference & Exposition

Authors

Christine Schnittka, Auburn University; George Edward Turner Jr., Auburn University; Randall William Colvin, Auburn University; Mary Lou Ewald, Auburn University

Tagged Divisions

K-12 & Pre-College Engineering

mathematical concepts in the context of engineering design challenges, teacherswork in teams on design projects that involve constraints, optimization, and predictive analysis.In this study, we measure not only changes in science content knowledge, but changes inattitudes toward engineering and changes in self-efficacy to teach engineering. Theoretical Framework Learning is not an individual, isolated process; it involves the interchange of ideas Page 24.106.6   5  between teacher and student and among peers

Conference Session

Methodological & Theoretical Contributions to Engineering Education 2

Collection

2014 ASEE Annual Conference & Exposition

Authors

So Yoon Yoon, Texas A&M University; P.K. Imbrie, Texas A&M University; Joe J.J. Lin, Purdue University, West Lafayette; Kenneth Reid, Ohio Northern University

Tagged Divisions

Educational Research and Methods

to persistence, and academic self-efficacy andachievement motivation were the best predictors of cumulative GPA over pre-college cognitiveindicators, such as standardized achievement test scores and high school GPAs. This implies thatsolely depending on traditional cognitive measures may not be sufficient to predict collegestudents’ performance, so embracing noncognitive measures may increase the predictive powerof students’ persistence and future performance in college.As students’ noncognitive attributes have gained more attention in academic performance andretention studies in higher education, this study describes a validation procedure for the extendedversion of the Student Attitudinal Success Inventory (SASI) to assess engineering

Conference Session

NSF Grantees’ Poster Session

Collection

2014 ASEE Annual Conference & Exposition

Authors

Jennifer E. LeBeau, Washington State University; Denny C. Davis, Washington State University; Noah L. Schroeder, Washington State University; Brian F. French, Washington State University ; Shane A. Brown P.E., Washington State University; Howard P. Davis, Washington State University

Tagged Topics

NSF Grantees Poster Session

Tagged Divisions

Division Experimentation & Lab-Oriented Studies

, critical thinking assessments,and metacognition measures. Approximately 72 instruments comprise the Attitudes domain.Thirty (30) instruments are classified in the Behavior domain, including instruments related tomotivation, engineering design self-efficacy, and team effectiveness. The Professional Skillsdomain is comprised of 33 instruments related to critical thinking, writing, teamwork, anddesign. Nine instruments are related to Learning Environment, and four instruments fall underthe Institutional Data domain. Certain instruments, such as the Achievement MotivationInventory, are categorized in more than one domain.Within ASSESS, instruments are searchable by domain as well as by other filtering criteria,including ABET Student Learning Outcomes