Conference Session

Works in Progress: Curricula and Pathways

Collection

2016 ASEE Annual Conference & Exposition

Authors

Lance C. Perez, University of Nebraska - Lincoln; Presentacion Rivera-Reyes, University of Nebraska - Lincoln

Tagged Divisions

Educational Research and Methods

framework of this study, andrepresentation mapping model proposed by Hahn and Chater [42]. The postdoc and theinvestigator independently analyzed the first interview identifying the episodes and the type ofreasoning used by the participants. Then, they met to discuss and revise the differences in coding,and any disagreements among coders were resolved for the first interview. Problems were codedand evaluated according to the following steps: a) The cognitive supply of the participant and the instructor of the course were assessed by parsing episodes of reasoning in the individual's explanation. b) The structure and logic of the episode were decomposed to determine the type of

Conference Session

Student Experiences and Motivation: ERM Roundtable

Collection

2015 ASEE Annual Conference & Exposition

Authors

Matthew J Jensen, Florida Institute of Technology; Anna KT Howard, North Carolina State University; Sherry Jensen, Florida Institute of Technology

Tagged Divisions

Educational Research and Methods

four-week time period (seven lectures) followed immediately by a midterm Page 26.781.4                                                                                                                i  A video capture of handwritten notes  exam covering only those two chapters. The 60 students were divided into two groups withsimilar demographics (sex, GPA, domestic versus international, etc.; see Table 1). StudentGroup A watched Dr. Howard’s videos for Chapter 5 and Dr. Jensen’s videos for Chapter 6.Student Group B

Conference Session

Student Approaches to Problem Solving

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Vanessa Svihla, University of New Mexico; Amber Gallup, University of New Mexico; Sung "Pil" Kang, University of New Mexico

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

mechanicalengineers. Future research will expand this to other engineering disciplines.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.EEC 1751369. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] J. F. Hair, W. C. Black, B. J. Babin, R. E. Anderson, and R. L. Tatham, Multivariate data analysis. Upper Saddle River, NJ: Pearson Prentice Hall, 2006.[2] Z. S. Roth, H. Zhuang, V. Ungvichian, and A. Zilouchian, "Integrating Design into the Entire Electrical Engineering Four Year Experience."[3] B. I. Hyman, "From capstone to cornerstone

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

STEM career areas, including engineering, in similar groupings or “clusters.”The analysis was run on every combination of gender or race/ethnicity, school-level, andinitiative, and findings revealed that all student groups perceived the STEM careers in either twoor three consistent clusters (see Appendix A-B for dendogram representations of results). Somestudent demographic sub-groups understood the careers in two, main clusters: a “core STEM” Page 24.1114.6career cluster and a “biological and medical sciences” career cluster. Other demographic sub-groups groups perceived the careers in three clusters: “core STEM,” “biological sciences

Conference Session

Engineering Identity 1

Collection

2013 ASEE Annual Conference & Exposition

Authors

Allison Godwin, Clemson University; Geoff Potvin, Clemson University; Zahra Hazari, Florida International University

Tagged Divisions

Educational Research and Methods

Engineer Identity: Campus Engineer Identities as Figured World. Cultural Studies of Science Education. 2006, 1, 273–307.(12) Capobioanco, B. M.; French, B. F.; Diefes-Dux, H. A. Engineering Identity Development Among Pre- Adolescent Learners. Journal of Engineering Education 2012, 101, 698–716.(13) Matusovich, H. M.; Barry, B. E.; Meyers, K.; Louis, R. A Multi-Institution Comparison of Identity Development as an Engineer. In American Society of Engineering Education Conference; 2011.(14) Beam, T. K.; Pierrakos, O.; Constantz, J.; Johri, A.; Anderson, R. Preliminary Findings on Freshmen Engineering Students ’ Professional Identity : Implications for Recruitment and Retention. In American Society of Engineering

Conference Session

ERM Technical Session 11: Leadership and Collaborations in Engineering

Collection

2019 ASEE Annual Conference & Exposition

Authors

Medha Dalal, Arizona State University; Adam R. Carberry, Arizona State University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

innovation in engineering education necessitates research on ways of thinking. Wesought to gain this understanding based on four specific ways of thinking including futures,values, systems, and strategic thinking. The study builds on the existing body of knowledgeregarding these ways of thinking, while initiating a first step toward an ‘EER ways of thinking’model. We believe the resulting model could serve as an organizing and motivating structure toframe decisions throughout all engineering education endeavors.ReferencesBrown, T. A. (2015). Confirmatory factor analysis for applied research, 2nd edition. New York, NY: Guilford PublicationsCrawford, A. V., Green, S. B., Levy, R., Lo, W. J., Scott, L., Svetina, D., & Thompson, M. S. (2010

Conference Session

Academic Success and Retention

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Lisa Lampe, University of Virginia; Megan Harris, University of Colorado Boulder; Kayla Brooks, University of Colorado Boulder

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

3.4percent of females [13]. The Regents acknowledged student resource expansion and correctinginstitutional deficits improved student retention outcomes. However, when reporting theincreased retention rates, the Regents failed to report the outcome by ethnicity and sex.Institutional Background The institutions – University of Colorado at Boulder (A) and University of Virginia (B) –included in this study were public doctoral granting, Research I comprehensive universities withadmission offer rates around 30-40 percent in the engineering undergraduate school. These PWIinstitutions were located in A) the Midwest and B) the Mid-Atlantic. Academic probation andsuspension policies differed by institution. Institution A shifted its probation and

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

A B 54.85 Low Low A B 52.57 Low High B 52.14Commitment to College: Regression analysis in figure 10 shows that GPA is positivelycorrelated to commitment to college, the measure of students’ determination to stay in collegeand obtain a degree. Students with higher than average high school GPAs are more focused onlong-term success in college than their lower GPA peers. As with the Academic Self-Confidence measure, only high school GPA was significant in this analysis. Page 24.405.11 Figure 10. ANOVA

Conference Session

Classroom Engagement

Collection

2010 Annual Conference & Exposition

Authors

Joanna DeFranco, Pennsylvania State University; Colin Neill, Pennsylvania State University

Tagged Divisions

Educational Research and Methods

, however, that workingwithin a team actually generates its own set of problems: the difficulties associated withmanaging the diversity of those within a team, referred to as Problem B (in contrast to ProblemA: solving the actual problem on which the team is working)4.Diversity here refers to the difference in problem solving style preferences of the individualscomprising the team. In the A-I framework, one’s problem-solving preference reveals how onevisualizes, conceptualizes, and communicates about the problem the team is attempting to solve.An individual’s preference is at a point along a continuum from more adaptive to moreinnovative. A more adaptive problem solver seeks to refine or improve upon existing solutionswhereas more innovative

Conference Session

Professional Skills and the Workplace

Collection

2008 Annual Conference & Exposition

Authors

Johannes Strobel, Purdue University, West Lafayette; Monica Cardella, Purdue Engineering Education

Tagged Divisions

Educational Research and Methods

solving describes eleven different problem-types mapped ona four-dimensional scale. Real world problems are more likely to be compound problemsmeaning they contain a variety of different problem types. This paper describes the findings oftwo studies, (a) a single-case study of a steel engineer and (b) a multi-case study comparing thefindings to 90 problem-solving narratives of other engineers. Both studies are located in a US-American context. Results confirm that real-world problems are intertwined problems(compound problems) and that transitions from one problem type to another within a compoundproblem are a unique class of problems themselves. These ‘transition problems’ have properties,which are not represented in other problem types, and

Conference Session

Innovative Use of Technology and the Internet in Engineering Education

Collection

2014 ASEE Annual Conference & Exposition

Authors

Julian Ly Davis, University of Southern Indiana; Thomas McDonald, University of Southern Indiana

Tagged Divisions

Educational Research and Methods

Class vs. Homework Grade Page 24.952.4 The second analysis broke the homework grade down into the corresponding A – Fgrades using a standard grading scale (e.g., >=90 is an A, 80 – 89 is a B, etc.). The results of thesecond analysis show that there was a significant difference (p = 0.005) between the letter gradeon the homework and the final exam grade. Students having an ‘A’ average on the homework onaverage scored 14.4 points higher on the final exam than students having an ‘F’ average on thehomework.Discussion These data do support the idea that delivery methods for homework do not impact studentlearning. However the

Conference Session

ERM Technical Session 8: Survey and Instrument Development

Collection

2019 ASEE Annual Conference & Exposition

Authors

Dina Verdin, Purdue University-Main Campus, West Lafayette (College of Engineering); Jessica Mary Smith, Colorado School of Mines; Juan C. Lucena, Colorado School of Mines

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

, “First-Generation and Continuing-Generation College Students: A Comparison of High School and Postsecondary Experiences (NCES 2018- 009),” Washington, DC, 2017.[9] J. Engle and V. Tinto, “Moving beyond access: College success for low-income, first- generation students,” Pell Inst. study Oppor. High. Educ., pp. 1–38, 2008.[10] S. E. Whitley, G. Benson, and A. Wesaw, “First-generation Student Success: A Landscape Analysis of Programs and Services at Four-year Institutions,” Washington, DC, 2018.[11] N. C. for E. S. U.S. Department of Education, “Students Whose Parents Did Not Go to College: Postsecondary Access, Persistence, and Attainment, NCES 2001-126,” Washington, DC, 2001.[12] V. B. Saenz, S. Hurtado, D

Conference Session

Research Methods

Collection

2018 ASEE Annual Conference & Exposition

Authors

Max William Blackburn, University of Michigan; Aaron W. Johnson, University of Michigan; Cynthia J. Finelli, University of Michigan

Tagged Divisions

Educational Research and Methods

, DC: American Society for Engineering Education.[8] Gilbuena, D. M., Sherrett, B. U., Gummer, E. S., Champagne, A. B., & Koretsky, M. D. (2015). Feedback on professional skills as enculturation into communities of practice. Journal of Engineering Education, 104(1), 7-34.[9] Yuksel, D. (2014). Teachers’ treatment of different types of student questions. Classroom Discourse, 5(2), 176-193.

Conference Session

Academic Success and Retention

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Heather Lee Perkins, North Carolina State University; Justin Charles Major, Purdue University, West Lafayette; Julianna S. Ge, Purdue University, West Lafayette; Matthew Scheidt, Purdue University, West Lafayette; Allison Godwin, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

Individual Differences, 71, 66-76.[11] Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological bulletin, 130[12] Kuncel, N. R., Credé, M., Thomas, L. L., Klieger, D. M., Seiler, S. N., & Woo, S. E. (2005). A meta-analysis of the validity of the Pharmacy College Admission Test (PCAT) and grade predictors of pharmacy student performance. American Journal of Pharmaceutical Education, 69(3).[13] Fan, X., & Chen, M. (2001). Parental involvement and students' academic achievement: A meta- analysis. Educational psychology review, 13(1), 1-22.[14] Grove, W. A., & Wasserman, T

Conference Session

Conceptual Learning

Collection

2010 Annual Conference & Exposition

Authors

Bill Brooks, Oregon State University; Milo Koretsky, Oregon State University

Tagged Divisions

Educational Research and Methods

, respectively.Table 2. Distribution of student responses to multiple-choice portions of the exercises Exercise Correct % Wrong A % Wrong B % Wrong C % Throttling Valve - pre 13 61 25 1 Throttling Valve - post 10 81 9 0 Consensually Wrong Equilibrium - pre 10 48 38 5 Equilibrium - post 7 60 33 0 Spray Can - pre 56 31 9 4

Conference Session

Tools for Teaching

Collection

2008 Annual Conference & Exposition

Authors

Kyu Yon Lim, Pennsylvania State University; Roxanne Toto, Pennsylvania State University, University Park; Hien Nguyen, Pennsylvania State University; Sarah Zappe, Pennsylvania State University; Thomas Litzinger, Pennsylvania State University; Mark Wharton, Pennsylvania State University; John Cimbala, Pennsylvania State University

Tagged Divisions

Educational Research and Methods

in lieu of a textbook at the beginning of the semester andthen posted annotated notes immediately after each class. In Course B, the instructor postedrough outline notes as pre-notes before each class, but posted the annotated notes under twothree-week long alternating time conditions. In the first condition the instructor did not post theannotated notes until several days prior to assessment. In the second condition the instructorposted annotated notes after class. The authors applied both qualitative and quantitative methodsto investigate the research questions. The research findings reveal that classroom attendancedecreased gradually in both courses as the semester progressed, regardless of the difference innote-posting strategy. The

Conference Session

Student Success I: Interventions and Programs

Collection

2016 ASEE Annual Conference & Exposition

Authors

Sara Hahler, Louisiana Tech University; Marisa K. Orr, Louisiana Tech University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

counted as an “F” in the class. In most cases, studentsdrop classes when they are in danger of failing the courses, and if dropped then the student willhave to take the course again before moving on to the next class. Additionally, other studies havegrouped these cases similarly [29, 30]. As a result, the Pre-Calculus model included 3,280participants and the engineering class model included 2,735 participants. Grades were changed toa 4.0 scale (4 replaced “A”, a 3 replaced “B”, and so on). Table 1. Study Variables Variable (Abbreviation) Range/Values Sex (Sex) 0 = Male 1 = Female Race (Race) 0 = White

Conference Session

Knowing Ourselves: Research on Engineering Education Researchers

Collection

2011 ASEE Annual Conference & Exposition

Authors

Krishna Madhavan, Purdue University, West Lafayette; Hanjun Xian, Purdue University, West Lafayette; Aditya Johri, Virginia Tech; Mihaela Vorvoreanu, Purdue University; Brent K. Jesiek, Purdue University, West Lafayette; Phillip C. Wankat, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

FIE conference from 1991 to 2009 – a massive amount of data toanalyze manually. The resulting visualization34 showed that through the papers presented at thisconference, a larger community of researchers was being united into a powerful network. Thisnetwork showed not only the characteristics of significant capacity – but also the size of thelargest network showed tremendous potential to propagate pedagogical and theoreticalinnovations. Key points in the growth of the network fostered by the FIE conference are shownin Figure 10. (a) (b) (c) Figure 10. The growth of the co-author network in FIE: snapshots of the network in (a) 1991, (b) 2000, and (c

Conference Session

Assessment of Student Work

Collection

2017 ASEE Annual Conference & Exposition

Authors

Lori C. Bland, George Mason University; Stephanie Marie Kusano, University of Michigan; Xingya Xu, George Mason University; Aditya Johri, George Mason University

Tagged Divisions

Educational Research and Methods

student outcomes withinan engineering competition. We specifically examined student discourse as related to the ABET(2013) technical outcomes including (outcome a) content knowledge, (outcome b)experimentation, (outcome c) design, outcome (e) problem solving, and outcome (k) use of tools.These outcomes are critical to becoming an engineer (Balascio, 2014). Our research questionsincluded:1. How do students describe their learning experiences within engineering competitions?2. What is the nature of their reflective discourse that revealed their learning?This paper is a work in progress has not yet been completed.Methods. The design for the study was qualitative. Qualitative methods provided the means tounderstand students’ learning using students

Conference Session

Student Motivation, Identity, and Resilience

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Matthew J. Ford, Cornell University; Hadas Ritz, Cornell University; Elizabeth M. Fisher, Cornell University

Tagged Divisions

Educational Research and Methods

years in which motivation and identity are so important to persistence. Our study addressesthis question by measuring motivational constructs in a cohort of mechanical engineering studentsmultiple times across several different course contexts.MethodsData was collected from students in three concurrent Mechanical Engineering courses during theFall 2019 semester (“Course A”: Introductory Fluid Mechanics, “Course B”: Mechanics ofMaterials, and “Course C”: Mechatronics). These three courses have been targeted by ourlearning initiative because they reach every student enrolled in the mechanical engineeringprogram (courses A and B are required while course C is taken by almost all students to satisfy amajor requirement), and because we have

Conference Session

Concepts and Conceptual Knowledge

Collection

2015 ASEE Annual Conference & Exposition

Authors

Gina Cristina Adam, University of California, Santa Barbara; Brian P. Self, California Polytechnic State University; James M Widmann, California Polytechnic State University; Alexa Coburn, California Polytechnic State University, San Luis Obispo; Baheej Nabeel Saoud, California Polytechnic State University, San Luis Obispo

Tagged Divisions

Educational Research and Methods

, we were able to gain abetter idea of student understanding of each desired proposition. For the first three scenarios inthe IBLA, the student was asked to (a) predict the correct answer and explain his/her reasoning,(b) perform the hands-on experiment depicted in the Scenario, and (c) explain how the results ofthe experiments compared with their original prediction. In order to emphasize conceptualunderstanding, students were instructed to “think aloud” during the activities in order to maketheir learning explicit and use as little mathematical tools as possible. Page 26.858.6 Figure 4. The four scenarios utilized for the IBLA (see Appendix A

Conference Session

Assessment I: Developing Assessment Tools

Collection

2016 ASEE Annual Conference & Exposition

Authors

Leroy L. Long III, Embry-Riddle Aeronautical University, Daytona Beach

Tagged Divisions

Educational Research and Methods

at Wright State University. He is a native of Dayton, OH and a graduate of Dayton Public Schools. Dr. Long’s research interests include: (a) technology use, (b) diversity and inclusion, and (c) retention and success, with a particular focus on students in STEM fields. He has conducted and published research with the Movement Lab and Center for Higher Education Enterprise at OSU. Dr. Long has taught undergraduates in the First-Year Engineering Program and Department of Mechan- ical Engineering at OSU and served as a facilitator for both the University Center for the Advance- ment of Teaching and Young Scholars Program at OSU. Furthermore, he has worked in industry at Toyota and has a high record of service with

Conference Session

Works in Progress: Learning and Engagement

Collection

2016 ASEE Annual Conference & Exposition

Authors

Justin Charles Major, University of Nevada, Reno; Adam Kirn, University of Nevada, Reno

Tagged Divisions

Educational Research and Methods

Test18 was run to determine normality of thedata. Results of this comparison test were considered significant at the 0.05 level. These pre- andpost- results were plotted within a box plot to provide visual representation of each test.Qualitative Data Collection and AnalysisAt the conclusion of the course, students were offered five points of extra credit in the class, on a1000-point scale, to complete a 15 to 30-minute short-answer journal entry. Students completedthe entry outside of class via Learning Management Software. The journal protocol, shown inAppendix B, consisted of 12 short answer questions requiring students to answer each with aminimum of two sentences to receive extra credit. Students were provided the list of designsubcategories

Conference Session

Measurement Tools

Collection

2010 Annual Conference & Exposition

Authors

Laura L. Pauley, Pennsylvania State University; Jonna M. Kulikowich, Pennsylvania State University; Nell Sedransk, National Institute of Statistical Sciences; Renata Engel, Pennsylvania State University

Tagged Divisions

Educational Research and Methods

mathematics tested is Construct (M2) that applies a physical meaning to thevariables in the equation. An example of Construct (M2) is shown below. A second example canbe found later in the paper as Figure 6.________________________________________________________________________ M2.1.  If h represents the height of water in a tank and t represents time, what does the following  equation tell you about the height of the water in the tank?  dh = −5 dt      a.   The height of the water is negative.  b.  The height of the water does not change with time.  c.  The height of

Conference Session

Assessment I: Developing Assessment Tools

Collection

2016 ASEE Annual Conference & Exposition

Authors

Curtis Cohenour Ph.D., P. E., Ohio University; Audra Hilterbran, Ohio University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

contemporary automated grading tools common to undergraduate MSExcel® training courses with large student enrollments. Specifically, the program was guided bya two-fold objective of (a) increasing formative assessment opportunities in preparation forsummative exams, and (b) facilitating an accelerated student-teacher feedback loop throughprompt and specific feedback.The uniqueness of the proposed method is grounded in the simple set up and the efficient use ofActiveX Com controls in Matlab® to grade the Paradigm Education Solutions Benchmark SeriesMicrosoft® Excel 2013 (BM)1 text workbooks. For this particular training course, the BM Textwas organized into two levels with eight chapters within each level. Each chapter included anassessment. A unit

Conference Session

Student Success II: Self-Regulatory, Metacognitive, and Professional Skills

Collection

2016 ASEE Annual Conference & Exposition

Authors

Aubrey Wigner, Arizona State University; Micah Lande, Arizona State University, Polytechnic campus; Shawn S. Jordan, Arizona State University, Polytechnic campus

Tagged Divisions

Educational Research and Methods

software forthe following categories.20 Table 3: ABET Criteria 3 - Student Outcomes a) an ability to apply knowledge of mathematics, science, and engineering b) an ability to design and conduct experiments, as well as to analyze and interpret data c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability d) an ability to function on multidisciplinary teams e) an ability to identify, formulate, and solve engineering problems f) an understanding of professional and ethical responsibility

Conference Session

Approaches to Assessment and Student Reflection

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Catherine Marie Hamel, University of Maryland; W. Ethan Eagle, University of Maryland

Tagged Divisions

Educational Research and Methods

” technique, where the higher of the two attempt scores,by question, was kept and summed together for a final “superscore.” An example of how the finalscores are calculated is shown in Table 1 below, where a “1” represents a conceptually correctsolution to a problem and a “0” represents a conceptually incorrect solution. Table 1: Mean exam scores. Question Exam A Exam B Superscore 1 1 1 1 2 1 0 1 3 0 1 1 4 0 0 0 5 1 0 1

Conference Session

Assessment Instruments

Collection

2011 ASEE Annual Conference & Exposition

Authors

Laura L. Pauley, Pennsylvania State University, University Park; Jonna M. Kulikowich, Pennsylvania State University; Nell Sedransk, National Institute of Statistical Sciences; Renata S. Engel, Pennsylvania State University, University Park

Tagged Divisions

Educational Research and Methods

included: a) aerospaceengineering; b) architectural engineering; c) electrical engineering, and, d) industrial engineering.For students in aerospace engineering and architectural engineering, the Thermal Science course isa required course taken in fourth semester. For students in civil engineering, this course is taken insixth semester. The Thermal Science course is used as a technical elective in the electrical andindustrial engineering programs. Most students were enrolled in a dynamics course at the timethey completed the survey. Most students had enrolled previously and completed coursework inboth Engineering Design as well as Calculus and Analytic Geometry. Reported grades for thesecourses were also available for analysis along with self

Conference Session

Works in Progress: Curricula and Pathways

Collection

2016 ASEE Annual Conference & Exposition

Authors

Bingbing Li, California State University - Northridge; Robert G. Ryan, California State University - Northridge; Nancy Warter-Perez, California State University - Los Angeles; Yong Gan, Cal Poly Pomona; Hadil Mustafa, California State University - Chico; Helen Cox, Institute for Sustainability, California State University - Northridge; Li Ding, California State University - Northridge

Tagged Divisions

Educational Research and Methods

and the goals of this program. a. identify existing GE Paths that would be a good fit for our objectives b. if only a subset of courses in a path is desirable, identify that subset c. if new courses need to be added to a path work with faculty to meet Student Learning Objectives (SLOs) and include in path d. identify any new courses that should be created for a path, and develop these 3) Create new minor in Sustainable Innovation and incentivize engineering students to take it through advisement 4) Identify engineering courses with potential for liberal arts integration and adopt a variety of strategies (team teaching, FLC development, online modules) for accomplishing this. 5

Conference Session

Student Teams and Design Skills

Collection

2006 Annual Conference & Exposition

Authors

Susan Mohammed, Pennsylvania State University; Gül Okudan, Pennsylvania State University; Madara Ogot, Pennsylvania State University

Tagged Divisions

Educational Research and Methods

overthe course of the semester. Because the first project was guided and straightforward, whereas thesecond was industry-sponsored and much more open-ended, it was expected that tolerance forambiguity would have a greater impact on the variables measured for the second project. In otherwords, the personality trait of tolerance for ambiguity was proposed to be more relevant whenthe project demands involved a higher degree of uncertainty and abstractness. Specifically, thefollowing hypotheses were proposed:(1). Individuals with higher tolerance for ambiguity will report higher levels of: a. self-efficacy, b. collective efficacy, c. satisfaction with the team, and d. conflict resolution.(2). Task ambiguity will impact the