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

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

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

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

Choice and Persistence in Engineering Education and Careers

Collection

2014 ASEE Annual Conference & Exposition

Authors

Alana Unfried, North Carolina State University; Malinda Faber, North Carolina State University; Eric N. Wiebe, North Carolina State University

Tagged Divisions

Educational Research and Methods

design and directinterventions addressing the mechanisms that seem to be disconnecting ability and interest inSTEM careers.Social cognitive career theory suggests that self-efficacy and expectancy-value are criticalfactors in an individual’s career choice and persistence.7 Self-efficacy is a person’s belief in theirability to complete tasks and affect events that impact their lives.8 Expectancy-value theoriescomplement self-efficacy theories in the investigation of a larger social cognitive model forcareer aspirations and persistence. Expectancy-value theories posit that individuals regularlyassess the likelihood of attaining specific goals and the value they would gain or lose from suchattainment.9, 10 How self-efficacy in traditional academic

Conference Session

Engineering Student Experiences

Collection

2014 ASEE Annual Conference & Exposition

Authors

Louis Nadelson, Boise State University; Dee K. Mooney, Micron Foundation; Janine Rush-Byers, Micron Technology Foundation, Inc.; Nathan Dean, Boise State University

Tagged Divisions

Educational Research and Methods

of Mathematics. He earned his B.S. in Earth Science Education from Boise State University in 2011 with a minor in Physical Science and was a NSF Robert Noyce Scholar. Nathan’s research interests include STEM education, grading and assessment practices, self-efficacy, and student conceptions of science. Page 24.1379.1 c American Society for Engineering Education, 2014 Why I Am an Engineering Major: A Cross-Sectional Study of Undergraduate StudentsAbstractAccording to a recent report 1 K-12 students tend to like mathematics and science. Further, in

Conference Session

Innovative Use of Technology and the Internet in Engineering Education

Collection

2014 ASEE Annual Conference & Exposition

Authors

Erin Shaw, University of Southern California; Jihie Kim, University of Southern California; Jaebong Yoo, Samsung Electronics

Tagged Divisions

Educational Research and Methods

context of discussion forums (Table 1). Complete citations for theinstruments, and studies of their application, are provided in Appendix I. Page 24.896.2Table 1. Instruments investigated.Name ReferenceAcademic Confidence Scale (ACS) (Sander & Sanders, 2003; Bandura, 2001)Academic Self Efficacy Scale (ASES) (Elias & Loomis, 2000; Lent et al., 1997; 1986)Motivated Strategies for Learning (Pintrich et al., 1991)Questionnaire (MSLQ)Academic Locus of Control (LOC) (Rotter, 1966; Trice, 1985)Patterns of Adaptive Learning

Conference Session

Student Learning, Problem Solving, & Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Micah Lande, Arizona State University, Polytechnic campus

Tagged Divisions

Educational Research and Methods

that lacks certainty students often fumble at whattheir next step is, using their own developing judgment and sense of self efficacy to moveforward.We hypothesize that both the breadth and frequency of iterative steps in the design process givestudents more learning moments to apply their model of the design process, helping to rectifymisconceptions and realign their mental model of their design process. The author is building onpreliminary observations of student design activity and learning in ME310 and a pilot study of aqualitative content analysis of student design documentation from past years.18 The basicpedagogical approach as evidenced by course assignments and milestones to teaching design inthe ME310 course is comparable to the

Conference Session

Trends in Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Khairiyah Mohd-Yusof, Universiti Teknologi Malaysia; Fatin Aliah Phang, Faculty of Education, Universiti Teknologi Malaysia; Aziatul Niza Sadikin, Universiti Teknologi Malaysia; Syed Ahmad Helmi, Universiti Teknologi Malaysia; Mohd Johari Kamaruddin, Centre of Lipids Engineering & Applied Research (CLEAR), Faculty of Chemical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia.

Tagged Divisions

Educational Research and Methods

and affective memories are influenced by individuals’ perceptions of otherpeople’s attitudes and expectations for them, and by their own interpretations of theirprevious achievement outcomes8.According to another related theory on motivation, the social cognitive career theory(SCCT)9 explained that persistence is influenced by self-efficacy, goals, interest, contextualsupports/barriers and outcome expectations10. It is reported that outcome expectations andself-efficacy influence engineering students’ interest to study engineering10-13. Therefore,students’ expectation is one of the very important factors to retain students’ interest andpersistence in studying engineering and eventually to pursue career in engineering.In order to help first

Conference Session

Pedagogy and Learning 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Nancy K. Lape, Harvey Mudd College; Rachel Levy, Harvey Mudd College; Darryl H. Yong, Harvey Mudd College; Karl A. Haushalter, Harvey Mudd College; Rebecca Eddy, Cobblestone Applied Research & Evaluation, Inc.; Nancy Hankel, Cobblestone Applied Research & Evaluation, Inc.

Tagged Divisions

Educational Research and Methods

of each course were administered a pretest and posttest attitude survey. The surveycontained selected items from three established instruments: Research on the Integrated ScienceCurriculum (RISC), Motivated Strategies for Learning Questionnaire (MSLQ), and the STEMQuestionnaires developed by the STEM team at the Higher Education Research Institute (HERI).The pretest survey contained nine items from RISC and the remaining items were from theMSLQ (18 items). The posttest contained the same items but added an additional 27 (for a totalof 54) survey items from the HERI questionnaires. The survey items used from the MSLQcontained constructs for self-efficacy for learning, metacognitive self-regulation, peer learning,and help seeking. The survey

Conference Session

Student Learning, Problem Solving, & Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Stephanie Marie Kusano, Virginia Tech; Aditya Johri, George Mason University

Tagged Divisions

Educational Research and Methods

.4,9,12,13,14 In regards to informal learning environments,this implies that the students should have the opportunity, and be encouraged to participate ininformal activities during the entirety of their engineering education, because despite thelimitations, design experiences have unique and valuable benefits to engineering students. Themost notable benefits that literature has illustrated include improved student retention, studentengagement, multidisciplinary skills, communication skills, and student self-efficacy.4,5,6,7,8,15,16,17 Although not necessary, this same literature implies that design experiencescan be effective in informal learning environments. A common characteristic of successfuldesign experiences described in the literature is that

Conference Session

Student Learning, Problem Solving, & Critical Thinking 2

Collection

2014 ASEE Annual Conference & Exposition

Authors

Nathan M. Hicks, University of Florida; Amy Elizabeth Bumbaco, University of Florida; Elliot P. Douglas, University of Florida

Tagged Divisions

Educational Research and Methods

, and importance.70,78,112,113,118,120A number of studies have compared critical thinking ability to various demographic variablesand learning orientations. According to one study, a student’s cultural background stronglyimpacts the expression of critical thinking skills.121 The same study reported that students atpredominantly black universities experienced more widespread development and that Asianstudents struggled to think critically. Another study reported higher levels of critical thinking formales than females.122 Other studies have indicated positive correlations between criticalthinking and information literacy,110 self-efficacy, and effort,122 no correlation between criticalthinking and problem based learning,73 and a negative

Conference Session

Engineering Student Experiences

Collection

2014 ASEE Annual Conference & Exposition

Authors

Scott Blum, University of Colorado, Colorado Springs

Tagged Divisions

Educational Research and Methods

throughout the literature that includeddropout prevention, academic motivation, self-determination, achievement, self-efficacy, andintrinsic motivation. They explain the different definitions in the contexts of the associatedbehavioral, emotional, and cognitive perspectives taken by different research disciplines. Theyemphasized that as any consideration of the impact and policy making implications wascontemplated, it was critical to understand that the definition of engagement was foundational tothe question being asked.12 Engagement as a construct has manifested itself in many forms. Within the theoreticalframework of Astin’s4 foundational work, it was established as “the amount of physical andpsychological time and energy the student

Conference Session

Pedagogy and Learning 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Laura Hirshfield, Oregon State University; Jaynie L. Whinnery, Oregon State University; Debra M. Gilbuena, Oregon State University; Milo Koretsky, Oregon State University

Tagged Divisions

Educational Research and Methods

with aninstructor that is acting as an industry supervisor and project coach to discuss their progress.Students must work together to define an optimal set of process parameters (e.g., temperatures,flow rates, and times) while managing a set of applicable measurement tools and a self-generated, coach-approved budget. In order to complete the process optimization process, thestudents must develop their own strategy for all aspects of the project and produce fivedeliverables. The major components of the Virtual Laboratory project and details aboutopportunities for feedback are summarized in Table 1.Table 1. Overview of the Virtual Laboratory project structure with feedback opportunities Timeline Key Project Milestones Student

Conference Session

Choice and Persistence in Engineering Education and Careers

Collection

2014 ASEE Annual Conference & Exposition

Authors

Joanna Wolfe, Carnegie Mellon University; Beth A. Powell, Tennessee Tech University

Tagged Divisions

Educational Research and Methods

, Z. Dangerous Curves. 2013 February 12, 2013 [cited 2014 22 March]; Available from: http://www.insidehighered.com/news/2013/02/12/students-boycott-final-challenge-professors-grading- policy-and-get.14. Eliot, A.J. and M.A. Church, A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 1997. 72(1): p. 218-232.15. Hutchison, M.A., et al., Factors Influencing the Self‐Efficacy Beliefs of First‐Year Engineering Students. Journal of Engineering Education, 2006. 95(1): p. 39-47.16. Patrick, H., A. Ryan, and P. Pintrich, The differential impact of extrinsic and mastery goal orientations on males' and females' self-regulated learning. Learning and Individual