Conference Session

Pedagogy and Learning 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Waddah Akili, Iowa State University

Tagged Divisions

Educational Research and Methods

retention of new knowledge and acquisition of desirable personal traits.Any such method that engages students in the learning process is labeled as: “active learning”method. In essence, active learning requires doing meaningful learning activities in groups underthe guidance of an informed and experienced teacher. As stated by Christensen et al (1), “To teachis to engage students in learning.” The main point is that engaging students in learning isprincipally the responsibility of the teacher, who becomes less an imparter of knowledge andmore a designer and a facilitator of learning experiences and opportunities. In other words, thereal challenge in college teaching today is not covering the material for the students, but ratheruncovering the

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

faculty Page 24.1006.2members, who taught in both conditions, also completed reflection papers related to theirexperiences. The following describes guiding research questions for the study.Research questions: 1. Do students in inverted classrooms spend additional time actively working with instructors on meaningful tasks in comparison to those students in control classrooms? 2. Do students in inverted classrooms show higher learning gains as compared to students in traditional classrooms? 3. Do students in inverted classrooms demonstrate an increased ability to apply material in new situations as compared to students in

Conference Session

Trends in Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Maura J. Borrego, Virginia Tech; Michael J. Prince, Bucknell University; Christopher Evan Nellis, Virginia Tech; Prateek Shekhar, Virginia Tech; Cindy Waters, North Carolina A&T State University; Cynthia J. Finelli, University of Michigan

Tagged Divisions

Educational Research and Methods

their effectiveness, the adoption of these practices has beenslow and not necessarily persistent11-16. Our own research with instructors in electrical/chemicalengineering17 and introductory physics instructors18 confirms that more than one-third of facultywho have tried to implement one or more nontraditional teaching methods discontinue their use(e.g., Figure 1).Figure 1. The largest group of faculty (35%) have tried nontraditional teaching methods and Page 24.1120.2 then discontinued their use Research has identified a number of barriers to the use of these nontraditional teachingmethods, such as instructor concerns about

Conference Session

Assessment of Student Learning 1

Collection

2013 ASEE Annual Conference & Exposition

Authors

Kevin Rawson, University of California, Riverside; Tom Stahovich, University of California, Riverside

Tagged Divisions

Educational Research and Methods

identify students at risk of performing poorly in a course.1 IntroductionHomework exercises are a cornerstone of modern instruction, especially in engineering. In thiswork, we seek to understand how student homework habits correlate with course performance.This work is a first step toward building automated tools to identify students at risk for poorperformance in a course so that interventions can be employed.We provided LivescribeTM smartpens to an undergraduate statics class of over 140 students toobserve how the students solve statics problems. The students were given the smartpens at thebeginning of the course, and completed most of their homework, quizzes, and exams using them.These pens record each pen stroke of the work with a time stamp

Conference Session

Assessment of Student Learning 1

Collection

2013 ASEE Annual Conference & Exposition

Authors

Joe C. Guarino, Boise State University; James R Ferguson P.E., Boise State University; V Krishna C Pakala, Boise State University

Tagged Divisions

Educational Research and Methods

providing details on using results from the Fundamentals ofEngineering (FE) exam as metrics for meeting ABET program outcomes1. However,implementing an FE-based set of metrics poses challenges not limited to assessing validity ofresults. Programs using FE-based metrics must also determine the position of the metrics in theoverall assessment process. We present a method for using FE-based metrics as an integral partof the ABET program assessment process. The principle issues we address are: (1) The validityof using FE metrics for a group of graduating students when not all of them take the exam; (2)Establishing and quantifying levels of performance; and (3) Creating a trigger mechanism fortaking action based upon longitudinal results.The Department

Conference Session

Assessment of Student Learning 1

Collection

2013 ASEE Annual Conference & Exposition

Authors

James Herold, University of California, Riverside; Thomas Stahovich, University of California, Riverside; Kevin Rawson, University of California, Riverside

Tagged Divisions

Educational Research and Methods

which theyused to complete their coursework. In this way, we collected a digital, time-stamped record of sixhomework assignments, seven quizzes, two midterms, and the final exam. Most homeworkassignments comprised eight problems, each of which would take approximately 30 minutes tosolve. An example of a typical problem is provided in Figure 1. Assignments were typically dueone week after they were assigned. Our present analysis excludes data from the first twohomework assignment and quizzes as they concerned basic math skills, rather than equilibriumanalysis, which is the primary focus of the course.Computing an Estimation of Student Effort Page

Conference Session

System 1 in Engineering Education and Research

Collection

2018 ASEE Annual Conference & Exposition

Authors

James L. Huff, Harding University; Kanembe Shanachilubwa, Harding University; Stephen Secules, University of Georgia

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

tobetter understand how engineering students experience shame, we used interpretative phenomenologicalanalysis (IPA) to critically examine the individual experience of shame in the case of a high-performing,White woman who was a junior mechanical engineering major at a faith-based university (n=1). Inparticular, we attended to the complex relationship between personal expectations that formed the contextfor her shame experiences: achieving excellence in performing tasks while maintaining strong socialrelationships with others. We discuss the implications of this single case study on broader narratives ofinclusion in the context of engineering education.Introduction I feel like, because I make good grades already, people know that, whether

Conference Session

System 1 in Engineering Education and Research

Collection

2018 ASEE Annual Conference & Exposition

Authors

Marisa K. Orr, Clemson University; Katherine M. Ehlert, Clemson University; Maya Rucks, Clemson University; Mitzi Desselles, Louisiana Tech University

Tagged Divisions

Educational Research and Methods

-makingcompetency.Theoretical FrameworkThe Self-Regulation Model of Decision-Making (SRMDM), posits that that self-regulateddecision-makers spend time in three phases: generation of options, evaluation of options, andlearning from the results. Additionally, adaptive decision-makers are aware of moderatingfactors (such as stress or lack of information) and work to overcome them [1]. The model isillustrated in Figure 1 and described in more detail below. Generation Evaluation Learning Phase Phase Phase Moderating factorsFigure 1. Byrnes’ Self-Regulation Model

Conference Session

System 1 in Engineering Education and Research

Collection

2018 ASEE Annual Conference & Exposition

Authors

Matthew Scheidt, Purdue University, West Lafayette; Allison Godwin, Purdue University, West Lafayette (College of Engineering); Ryan R. Senkpeil, Purdue University, West Lafayette (College of Engineering); Julianna Sun Ge, Purdue University, West Lafayette (College of Engineering); John Chen P.E., California Polytechnic State University, San Luis Obispo; Brian P. Self, California Polytechnic State University, San Luis Obispo; James M. Widmann, California Polytechnic State University, San Luis Obispo; Edward J. Berger, Purdue University, West Lafayette (College of Engineering)

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

atthree study sites to develop predictive models for student success.Motivation for this studyEngineering and computing education remains critical for U.S. workforce development andtechnological innovation now and into the future [1]–[3]. Many students recognize theimportance and opportunity associated with studying STEM majors, and engineering andcomputing programs today have a talented applicant pool [4]. As a consequence, manyinstitutions see relatively uniform and strong applicant credentials in terms of high school GPA,standardized test scores, and leadership experiences [5].Each admitted student has the clear potential for academic success in the undergraduatecurriculum. However, while some thrive at the university, many languish near the

Conference Session

System 1 in Engineering Education and Research

Collection

2018 ASEE Annual Conference & Exposition

Authors

S. Zahra Atiq, Purdue University, West Lafayette (College of Engineering)

Tagged Divisions

Educational Research and Methods

engineering. c American Society for Engineering Education, 2018 WIP - A Multi-Modal Method for Assessing Student Emotions During Programming Tasks1. IntroductionComputer programming is considered a necessary skill for engineering students [1]. As aconsequence, programming courses are introduced to undergraduates early in their engineeringeducation. However, learning programming is difficult [2]: it requires patience and persistence[3]. It is also challenging because novice students may not have accurate mental models ofcomputer programs [2]. Hence, students in a programming course may experience a wide arrayof emotions that may positively or negatively impact their performance and

Conference Session

System 1 in Engineering Education and Research

Collection

2018 ASEE Annual Conference & Exposition

Authors

Elif Miskioglu, Bucknell University; Kaela M Martin, Embry-Riddle Aeronautical University, Prescott

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

phase of this work will be alarger-scale study of engineering intuition across multiple disciplines and institutions that willpropel us towards developing classroom interventions for “teaching” intuition.IntroductionAs technology-aided problem solving has become standard practice, an engineers’ ability to“intuit” the results obtained through technology grows increasingly urgent. Studies on classroomlearning gains from technology use report both shallow learning [1] and deeper learning [2-5].The technology that aids today’s engineers in problem solution is not without limitations, asthese tools are based on underlying assumptions that may or may not hold true. Thus,engineering students must learn to use technology intelligently and critically

Conference Session

Student Learning, Problem Solving, & Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Oluwatosin Alabi, Purdue University, West Lafayette; Alejandra J. Magana, Purdue University, West Lafayette; R. Edwin Garcia, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

Figure 1. Vygostky’s activity theory model for this study. Page 24.582.4Research Design and MethodsInstructional ContextThe course entitled “Introduction to Rechargeable Batteries” is an elective course for upper levelundergraduate and graduate students interested in developing an understanding on the materialsscience of rechargeable batteries. This course included an introduction to basic electrochemistry,principles of electrochemical devices, and electroactive materials as used in rechargeable batterysystems. The instructional goal for the course was to provide students expertise regarding thefundamental analytical and computational modeling

Conference Session

Methodological & Theoretical Contributions to Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Scottie-Beth Fleming, Georgia Institute of Technology

Tagged Divisions

Educational Research and Methods

community of practice. Consequently, theseresearchers may be unable to adopt best practices from and exchange relevant information withthe greater community. Page 24.279.21. IntroductionResearch collaboration often occurs between colleagues working within similar as well asdifferent disciplines. Collaboration is known to boost creativity, increase access to relevant skillsand knowledge, provide intellectual companionship, and grow researcher network size.1-3Through collaborations, social capital is leveraged as a transfer of information and knowledge isfacilitated through formal and informal networks.4 Additionally, future opportunities

Conference Session

Student Learning, Problem Solving, & Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Sean Moseley, Rose-Hulman Institute of Technology; Rachel McCord, Virginia Tech

Tagged Divisions

Educational Research and Methods

engineering problems” 1.While many courses in different engineering curriculums have a focus on problem solving,statics is typically the first course in many students’ undergraduate engineering coursework thatrequires them to use an engineering problem solving process. Many researchers have spentsignificant resources investigating how students learn in statics and how to effectively teachproblem solving in statics courses. For instance, Steif, Lobue, Kara, and Fay developed anintervention where students where engaging in talk about salient features of the statics problem2.Steif and team found that students that were engaged in body centered talk were better atrepresenting unknown forces on free body diagrams than students that did not participate in

Conference Session

Methodological & Theoretical Contributions to Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Lauren D. Thomas, University of North Carolina at Chapel Hill

Tagged Divisions

Educational Research and Methods

revised theoretical understanding is gained through the researchprocess. This framework does need additional exploration within engineering and thephysical sciences. Additional findings will contribute to engineering education’s currentdiscourse on graduate education and identity.!!!![1] Mann, L., P. Howard, F. Nouwens, F. Martin (2008). Professional identity: A framework for research inengineering education. Proceedings from 2008 Australasian Association for Engineering Education,Yeppoon.[2] Case, J. M., G. Light. (2011). Emerging methodologies in engineering education research. Journal ofEngineering Education, 100(1), 186-210.[3] Meyers, K. L., M. W. Ohland, A.L. Pawley, C.D. Christopherson. (2010). The Importance of FormativeExperiences for

Conference Session

Methodological & Theoretical Contributions to Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Jennifer A Turns, University of Washington; Brook Sattler, University of Washington; Ken Yasuhara, Center for Engineering Learning & Teaching (CELT); Jim L. Borgford-Parnell, University of Washington; Cynthia J. Atman, University of Washington

Tagged Divisions

Educational Research and Methods

experience as an intentional form of thinking where aperson revisits an experience with a specific meaning making lens. While reflection has nothistorically received a great deal of attention in engineering education scholarship, we aremotivated by calls for greater consideration of reflection. For example, in her NationalAcademies piece calling for curricular change in undergraduate engineering, Ambrose notes that“…students learn by doing, but only when they have time to reflect—the two go hand in hand.Why, then, don’t engineering curricula provide constant structured opportunities and time toensure that continual reflection takes place?” (p.1).30 There is opportunity for more research onand efforts to support reflection in engineering education

Conference Session

Methodological & Theoretical Contributions to Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Yakut Gazi, Texas A&M University

Tagged Divisions

Educational Research and Methods

the value of heutagogyin academic versus workforce development environments in science, technology, andengineering. Page 24.830.2Andragogy, Self-Directed Learning, and HeutagogyAndragogy is a theory that holds a set of assumptions about how adults learn. Accordingto American Council on Education, adult learners are learners over the age 25 and oftenreferred to as non-traditional learners. These individuals usually have additionalresponsibilities such as family, career, military or community and are seeking a degree oreducational offering to enhance their professional or personal lives (American Council onEducation, n.d.)[1]. According to National

Conference Session

Methodological & Theoretical Contributions to Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Gurlovleen K. Rathore, Texas A&M University

Tagged Divisions

Educational Research and Methods

. Page 24.834.1 c American Society for Engineering Education, 2014 Judging the Quality of Operationalization of Empirical- Analytical, Interpretive and Critical Science Paradigms in Engineering Education ResearchIntroductionParadigms are basic sets of beliefs that guide disciplinary inquiry. They can be constructed froma proponent’s responses to basic questions of ontology, epistemology, and methodology. Thethree basic questions are1: 1. Ontological: What is the nature of the “knowable”? Or, what is the nature of “reality”? 2. Epistemological: What is the nature of the relationship between the knower (the inquirer) and the known (or

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

doing (problem formulation and problem solving), and design andengineering learning (focused on change in the student’s conceptual understanding of design).Research Methods and ParticipantsTo best address the research questions, this study uses multiple methodologies to collect andanalyze data around engineering students’ learning. Empirical evidence of what design andengineering thinking looks like and how it changes over time, and how students conceptualizedesign and engineering, comes from two participant groups: (1) a spread of undergraduateengineering students across fields of engineering, and (2) a homogeneous group of MechanicalEngineering graduate students in a project-based learning course in design and innovation forMaster’s students

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

institution, which is home to studentengineering design teams, such as a Formula design team. We found that these experiencesenhanced students’ self-directed autonomy and allowed them to take control of their learningtrajectory. We discuss implications for future research and educational practices.IntroductionIt has been estimated that over a human lifespan about 90% of a person’s learning occurs in non-formal environments, that is, people learn through informal experiences.1 As part of theircollege-based undergraduate degree experience, a large portion of engineering students areinvolved in different informal learning experiences, such as co-curricular design teams, studentorganizations, undergraduate research, or studio-based environments. However

Conference Session

Student Learning, Problem Solving, & Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Youyi Bi, School of Mechanical Engineering, Purdue University; Tahira N. Reid, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

adopt appropriate teaching methods for different students.Key words: engineering problem-solving, eye gaze data, visual attentionI. IntroductionSolving complex problems is an important symbol of human intelligence and has alwaysfascinated researchers. Though mental problem-solving studies originated in psychology, todaysome of their methods and techniques are applied and developed in other areas such asmathematics [1], computer science [2], engineering [3], and medicine [4]. Although theseresearchers come from different backgrounds, the questions of common interest are how exactlypeople solve problems and how their performance may be improved.According to Budny’s research on freshman performance in engineering courses at Purdue

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

increase in the use of visual Page 24.1363.2models for abstract concepts in textbooks, DVDs, and online resources.To our knowledge, however, there has been little systematic research on whether and howvisual models help engineering students better understand abstract concepts especially in theareas of industrial engineering, engineering management, and systems engineering. Toaddress this issue from an engineering education research perspective, two essential questionsare (1) to what extent do visual models of such concepts help students develop a completemental model and (2) whether better mental models lead to better understanding of thedomain

Conference Session

Student Learning, Problem Solving, and Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Jeffrey A. Davis, Grant MacEwan University; Shelley Lorimer, Grant MacEwan University

Tagged Divisions

Educational Research and Methods

, theresults tend to be context specific[1],[2],[3]. One possible cause of this is the exclusion of any linkof human errors to cognitive processes.The starting point for the present research is based on Action theory. This is a goal-directedtheory that assumes the existence of a conscious choice that guides a person's behaviour to someoutcome[4],[5].In this theoretical context, an error implies that through some intended action, thegoal was not attained[1]. Rooted in this theory, two models of human error taxonomy commonlycited in the literature are: the Generic Error Modeling System model[1] and the Skill-Rule-Knowledge (SRK) model[6]. These models further classify errors as being either the failure ofactions to go as intended (slips, lapse) or as

Conference Session

Student Learning, Problem Solving, and Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Cynthia B. Paschal, Vanderbilt University

Tagged Divisions

Educational Research and Methods

. Forresponse rates of 40% to 90%, in steps of 10%, 40 survey trials at each rate were simulated. Ineach trial at each response rate, the corresponding number of respondents was randomly selectedfrom the 300 member dataset. For example, if the response rate was 60%, 240 students wererandomly selected as respondents for each trial. From the respondents, the percent of studentsheaded to industry vs. graduate or professional school vs. other activity as well as the percent ofthose students headed to industry who were successfully placed were computed. The results forthe % of graduates headed to industry are illustrated in Figure 1 and those for % of graduatesheaded to industry who were successfully placed are illustrated in Figure 2. The collection

Conference Session

Student Learning, Problem Solving, and Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Natasa S. Vidic, University of Pittsburgh; Nur Ozge Ozaltin; Mary E. Besterfield-Sacre, University of Pittsburgh; Larry J. Shuman, University of Pittsburgh

Tagged Divisions

Educational Research and Methods

?Through the qualitative analysis the research team was able to gain a more in-depthunderstanding of why students selected certain solution paths.1. Introduction and BackgroundThe overall purpose of this research is to determine if the use of model eliciting activities (MEAs)in the classroom helps to improve students’ ability to solve engineering problems. Model ElicitingActivities are open-ended realistic problems constructed around a few main concepts1-8. Originallydeveloped by mathematics educators, and used at the pre-college level, we have been refocusingMEAs for use in upper division engineering courses. MEAs require the team to develop ageneralizable, mathematical model to solve the problem and to present both the solution methodand the

Conference Session

Student Learning, Problem Solving, and Critical Thinking 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Claudia Elena Vergara, Michigan State University; Mark Urban-Lurain, Michigan State University; Jon Sticklen, Michigan State University; Abdol-Hossein Esfahanian, Michigan State University; Hannah McQuade, The Center for Engineering Education Research; Andrew League, Michigan State University; Chris John Bush, The Center for Engineering Education Research; Michael Cavanaugh, Michigan State University, Center for Engineering Education Research

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Educational Research and Methods

CPACE computational competencies. • Brief discussion of our efforts to develop and validate assessments to measure computational competencies for engineering students.Introduction The learning sciences have influenced repeated calls for improving engineering educationthat focus on providing students with the opportunities to integrate their knowledge acrossdisciplines through authentic problem solving 1- 6. Computation for engineering cannot simply beaddressed with one or two courses in computing or a few examples scattered in the curriculum,but must be integrated as part of an engineer’s training to become a “Holistic Engineer” 7. One of the challenges of preparing engineers for the rapidly changing workplace is to providethe

Conference Session

ERM Technical Session 1: Methods Refresh: Approaches to Data Analysis in Engineering Education Research

Collection

2019 ASEE Annual Conference & Exposition

Authors

Allison Godwin, Purdue University, West Lafayette; Aaron Robert Hamilton Thielmeyer, Purdue University, West Lafayette; Jacqueline Ann Rohde, Purdue University, West Lafayette; Dina Verdin, Purdue University, West Lafayette; Brianna Benedict McIntyre, Purdue University, West Lafayette; Rachel Ann Baker; Jacqueline Doyle, Harvard-Smithsonian Center for Astrophysics

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Diversity

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Educational Research and Methods

high variability among engineering studentswere used in the TDA to map students’ latent diversity. The results of this map indicate six distinctdata progressions as well as a sparse group of students whose responses were not similar to themajority of the dataset. This work illustrates the opportunities for using TDA and provides adiscussion of the different researcher decisions that are involved in this statistical technique.IntroductionRecent quantitative research in social science and engineering education has begun to focus notjust on a single aspect of participants’ experiences or psycho-socio processes but rather aconstellation of aspects that are important for particular outcomes like retention or academicsuccess [1]-[4]. For example

Conference Session

ERM Technical Session 1: Methods Refresh: Approaches to Data Analysis in Engineering Education Research

Collection

2019 ASEE Annual Conference & Exposition

Authors

Manoj Malviya, Pennsylvania State University; Catherine G.P. Berdanier, Pennsylvania State University; Natascha Trellinger Buswell, University of California, Irvine

Tagged Divisions

Educational Research and Methods

interraterreliability (IRR) and compares them with statistical methods for calculating IRR. Across fields,establishing quality in the qualitative data analysis process involves calculating a measure ofagreement between the human researchers interpreting the data: If researchers cannot agree to anacceptable level, then a coding schema cannot be considered sound and results cannot beconsidered meaningful, transferrable, or conclusive. The extent to which the classification patternsof two or more coders coincide represents the interrater reliability, sometimes known as interrateragreement. Methods for calculating IRR have been established across the social sciences, such asthose documented by Eckes [1], Zhao [2], Krippendorff [3], and Carletta [4], typically

Conference Session

ERM Technical Session 1: Methods Refresh: Approaches to Data Analysis in Engineering Education Research

Collection

2019 ASEE Annual Conference & Exposition

Authors

Nicholas D. Fila, Iowa State University; Carla B. Zoltowski, Purdue University, West Lafayette ; Justin L. Hess, Indiana University Purdue University, Indianapolis; Dayoung Kim, Purdue University, West Lafayette; Alison J. Kerr, University of Tulsa; Andrew O. Brightman, Purdue University, West Lafayette; Michael C. Loui, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

quality. Although qualitativeresearchers often conduct phenomenography collaboratively, most often a single individual leadsthe data collection and analysis; others primarily serve as critical reviewers. However, qualitymay be enhanced by involving collaborators as data analysts in “sustained cycles of scrutiny, de-bate and testing against the data” [1, p. 88], thus interweaving unique perspectives and insightsthroughout the analysis process. Nonetheless, collaborating in this intensive data analysis processalso presents unique challenges. In this paper, we (1) describe the processes we are applying inan integrated team-based phenomenographic study, (2) identify how the team approach affectsresearch quality, and (3) reflect on the challenges

Conference Session

SPECIAL SESSION: Describing the Engineering Student Learning Experience Based on CAEE Findings: Part 1

Collection

2008 Annual Conference & Exposition

Authors

Cynthia Atman, University of Washington; Lorraine Fleming, Howard University; Sheri Sheppard, Stanford University; Ronald Miller, Colorado School of Mines; Karl Smith, University of Minnesota; Reed Stevens, University of Washington; Ruth Streveler, Purdue University; Christine Loucks-Jaret, University of Washington; Dennis Lund, University of Washington

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Educational Research and Methods

engineering education programs. The Academic Pathways Study is providing a rich set of Page 13.908.13insights and tools to support these changes and ultimately to strengthen effective teaching of ourfuture engineers.AcknowledgmentsThis material is based on work supported by the National Science Foundation under Grant No.ESI-0227558, which funds the Center for the Advancement of Engineering Education (CAEE).CAEE is a collaboration of five partner universities.End Notes:a The Longitudinal Cohort (Fall 2003—Spring 2007) was initially called Cohort 1; the twoBroader Sampling Cohorts using the APPLE Surveys were referred to as Cohorts 3 and 4.; andthe