Conference Session

Concepts and Conceptual Knowledge

Collection

2015 ASEE Annual Conference & Exposition

Authors

Christian Anderson Arbogast, Oregon State University; Devlin Montfort, Oregon State University; Shane A. Brown P.E., Oregon State University

Tagged Divisions

Educational Research and Methods

pressure in the system? Person B: Why is there pressure? Interviewer: Yeah. Person B: Because the water’s flowing through it, and [pause]. I don’t know how to think about this. [long pause] Person B: Because the rate that the water’s flowing through the pipes is going to provide a force on the [pauses, laughs]. So you have a pressure, you have a velocity, and you have an elevation head, but I don’t [pause]. Everything has to equal, so if you increase your velocity on one side, then that would have a lower pressure, but they’ll be [pause] I think it [pause] yeah, I honestly don’t know. I don’t know where the pressure comes from. I just think of it in terms of Bernoulli’s equation.Frank

Conference Session

Classroom Practice II: Technology - and Game-Based Learning

Collection

2016 ASEE Annual Conference & Exposition

Authors

Camilo Vieira, Purdue University; Anindya Roy, Johns Hopkins University; Alejandra J. Magana, Purdue University, West Lafayette; Michael L. Falk, Johns Hopkins University; Michael J. Reese Jr., Johns Hopkins University

Tagged Divisions

Educational Research and Methods

simulated a one-dimensionalrandom walk.Data Collection Two main sources of data collection are considered for this study. The first source is theset of in-code comments students wrote as self-explanation of the worked-example. Two samplecommented codes submitted by the students are depicted in Figure 1. Note that the differences inthese two students’ approach to self-explaining are not limited to the extension of the comments.While student A did not describe the purpose of the function and each of the parameters, studentB did. Also, student A described the code in terms of the data structures (e.g. matrix, vector) andoperations between them, while student B consistently used science concepts (e.g. “…the overallvelocity to decrease if the

Conference Session

Alternatives to Traditional Assessment

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Lauren Singelmann, North Dakota State University; Enrique Alvarez Vazquez, North Dakota State University; Ellen M. Swartz, North Dakota State University; Mary Pearson, North Dakota State University; Ryan Striker P.E., North Dakota State University

Tagged Divisions

Educational Research and Methods

C. Ifstudents apply the knowledge to a project, they are at a B grade level. Finally, if students achievehigh external value with their project, they will receive the grade of an A.Choosing a Team and TopicAs students decide on learning objectives, most of the learning is based around an innovationproject that teams choose. At the beginning of the semester, students look atcardiovascular-related funding opportunity announcements from agencies like National ScienceFoundation and National Institute of Health to determine projects of interest. From there, studentspitch project ideas and form teams based around the projects [20]. Students are not evaluatedbased on their ability to solve the problem presented in the funding opportunity

Conference Session

Service Learning Courses

Collection

2007 Annual Conference & Exposition

Authors

Susan Maller, Purdue University; Tao Hong, Purdue University; William Oakes, Purdue University; Carla Zoltowski, Purdue University; Paul McDermott, University of Pennsylvania

Tagged Divisions

Educational Research and Methods

hasapplied cluster analytic techniques to derive normative typologies within the context ofservice-learning in engineering education area. Classification can provide critical insightinto the relationship between students’ perceptions of the program and other importantaspects of learning (e.g., academic achievement). Thus, profile analysis is useful for theEPICS program for at least two reasons: (a) for program evaluation to monitor howEPICS students perform on a variety of ABET criteria, and (b) to understand how EPICSstudents share common characteristics on ABET outcomes that may affect theireducational and professional experiences. By using the McDermott’s 12,13 three-stage cluster analysis strategy, the mainpurpose of current study was to

Conference Session

Using Technology to Enhance Education

Collection

2009 Annual Conference & Exposition

Authors

J. Shelley, United States Air Force

Tagged Divisions

Educational Research and Methods

togenerate grades are generally calculation-based problem solutions, difficulty withdynamics concepts that do not involve mathematical calculations cannot be assessedthrough student grades. Student grades appeared to correlate with DCI results only for those scoringabove class average on the DCI. The few students who scored more than one standarddeviation above average on both the initial and post-course DCIs were also among the topscoring students on the graded assessments. However, average scores or a lack ofimprovement from the initial to the post-course DCI did not correlate with student grades.Many students earning “B” grades did not show significant improvement on their DCIs.This lack of correlation between grades and DCI improvement

Conference Session

Faculty and Student Perspective on Instructional Strategies

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Philip P. Graybill, Pennsylvania State University, University Park; Catherine G.P. Berdanier, Pennsylvania State University, University Park

Tagged Divisions

Educational Research and Methods

each behavior:1) student behavior without UORs, 2) instructors’ beliefs about students’ behavior without UORs,3) student behavior using UORs, and 4) instructors’ beliefs about students’ behavior using UORs(Fig 1a). Student and instructor responses for each item in List 2 were accrued (Fig 1b). (a) (b) (c)Fig. 1. Plots of survey results. (a) Histograms of student (left, red) and instructor (right, blue) responses for copying textbook homework solutions(List 1, question 7) without using UORs (top) and using UORs (bottom). The left and right vertical axes are normalized to the total number of validstudent and instructor surveys

Conference Session

Approaches to Encouraging Student Engagement

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Panagiotis Apostolellis, University of Virginia; Sitong Wang, University of Cincinnati

Tagged Divisions

Educational Research and Methods

expectedlearning outcomes mentioned above.To understand these tasks, let us describe a typical 2-day week: a) quiz on the reading of theweek followed by lecture with added examples on that topic (Tuesday); b) in-class activities(ICAs) where students practice the part of the UX process taught that week (Thursday); c)project group meetings with the facilitation of the TAs (in lieu of office hours). Lecture timeis augmented with complementary activities, such as ungraded polling questions (usingmentimeter.com [36]), real-world examples with some brief activity, and mini individualpresentations of good-bad-ugly UX examples (GBUX). In-class activities (ICAs) arecomplemented with sharing design artifacts to the whole class (using sharypic.com [37]) andmini

Conference Session

Knowing Ourselves: Research on Engineering Education Researchers

Collection

2011 ASEE Annual Conference & Exposition

Authors

Xin (Cindy) Chen, Purdue University; Nikitha Sambamurthy, Purdue University; Corey M. Schimpf, Purdue University, West Lafayette; Hanjun Xian, Purdue University, West Lafayette; Krishna Madhavan, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

W1 Conf1 Tag2 W2 Conf2 ... Sum of Last Name Weights2005 A assessment 50 0.8 accountable 10 0.7 … 1002005 B knowledge 40 0.8 research 10 0.8 … 1002005 C skill 60 0.8 soft 5 0.5 … 1002005 D diversity 35 0.7 learning 20 0.6 … 1002005 E difference 30 0.5 characteristics 10 0.5 … 100… … … … … … … … … … Table1. An example showing the tag spread sheet of one

Conference Session

Tools to Enhance Student Learning of Undergraduate Engineering Content

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Melissa Ann Gallagher, University of Houston; Jenny Byrd, University of Louisiana at Lafayette; Emad Habib P.E., University of Louisiana at Lafayette; David Tarboton, Utah State University; Clinton S. Willson, Louisiana State University

Tagged Divisions

Educational Research and Methods

problems), and (b) engineering as knowledge (comprising thespecialized knowledge that helps and motivates the process of problem-solving). Moreover,Streveler et al. [3] posit that gaining conceptual knowledge in engineering science is a vitalfactor in the development of competence and expertise as professional engineers.As recommended by the Accreditation Board for Engineering and Technology (ABET),technical skills are one of the attributes that an engineering student must obtain by the time ofgraduation [12]. The term technical skills encompass the knowledge and abilities required toperform a specialized task. These skills are practical and have real-world applications. Forstudents to develop these critical skills, engineering faculty must teach

Conference Session

ERM Technical Session 7: Learning and Research in Makerspaces

Collection

2019 ASEE Annual Conference & Exposition

Authors

Wendy Roldan, University of Washington; Jennifer A. Turns, University of Washington

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

betweensociocultural theories on equity and the practices we were observing in the makerspace. Aswe wrote this memo, we used Nasir’s work as a guide toward crafting the kinds of questionsthat called attention to the things that felt significant in our observations. We notice that theliterature guiding our understanding of equity in makerspaces is usually situated in thecontext of K-12 education and not oriented toward the design of university makerspaces.Thus, this paper offers an in-progress, practice-facing equity bifocals framework to help us:(a) make sense of the questions we come to when conceptualizing equity in universitymakerspaces and (b) name the design tensions present in university makerspaces.The motivation for this work is based on the rapidly

Conference Session

ERM Technical Session 5: Assessment

Collection

2019 ASEE Annual Conference & Exposition

Authors

Aaron W. Johnson, University of Michigan; Jessica E. S. Swenson, University of Michigan; Max William Blackburn, University of Michigan; Cynthia J. Finelli, University of Michigan

Tagged Divisions

Educational Research and Methods

Facilitation—each with anumber of sub-category codes. When coding question-initiated dialogue within a transcript, asingle code is applied to each utterance from an instructor or student. If a single utterance coversmultiple codes, it may be divided into a set of utterances, each with its own code. When codingquestion-initiated dialogue, a researcher also indicates whether the speaker of each utterance isthe instructor or a student. Furthermore, a researcher can indicate when a new student is speakingby numbering the students within each set of question-initiated dialogue. Two examples ofdialogue from a small section of a 200-level chemical engineering course are presented inAppendix B. Table I. Final TENOR Protocol Categories and Sub

Conference Session

Practice III: Multimedia Learning

Collection

2018 ASEE Annual Conference & Exposition

Authors

Faye Linda Wachs, California State Polytechnic University, Pomona; Juliana Lynn Fuqua, California State Polytechnic University, Pomona; Paul Morrow Nissenson, California State Polytechnic University, Pomona; Angela C. Shih, California State Polytechnic University, Pomona; Michael Pavel Ramirez, California State Polytechnic University, Pomona; Laura Queiroz DaSilva, California State Polytechnic University, Pomona ; Nguyen Nguyen; Cheyenne Romero, California State Polytechnic University, Pomona

Tagged Divisions

Educational Research and Methods

approximately 15-60 minutes; (b) At the first in-class meeting, students weregiven a concept quiz to ensure they watched the videos, and the remaining class time wasdedicated to reviewing the solutions to the quiz, reviewing the concepts in the videos, andsolving example problems; (c) After the first in-class meeting, students were provided with anoptional zero-credit practice quiz to prepare them for a second, more challenging quiz at thebeginning of the second in-class meeting; (d) After taking the challenging quiz and reviewing thesolutions during the second meeting, the remaining class time was dedicated to an active learningexercise called a "Team Battle" in which students competed in teams to complete problems asquickly as possible. Students in

Conference Session

ERM Technical Session 5: Assessment

Collection

2019 ASEE Annual Conference & Exposition

Authors

Timothy Ryan Duckett, Acumen Research and Evaluation, LLC; Matthew W. Liberatore, University of Toledo; Uchenna Asogwa, University of Toledo; Gale A. Mentzer, Acumen Research and Evaluation; Amanda Portis Malefyt, Trine University

Tagged Divisions

Educational Research and Methods

the ratings on student B. This provides furtherexplanation for the variation in the 95% CI of the ICC coefficient.Figure 7. Plot of the student problem-solving ability level used for the ICC coefficientDiscussionThis study estimated the reliability of scores from a rubric designed to measure chemicalengineering problem-solving ability. The analyses mark an important step in the validation of thePROCESS itself which has only been validated previously using traditional correlationaltechniques. The many-facet Rasch model (MFRM) was used to explore a set of rater-mediateddata. This evaluative approach and choice of measurement models was designed to meet theincreasing demands of accountability in engineering, and in this case specifically

Conference Session

Use of Technology to Improve Teaching and Learning

Collection

2006 Annual Conference & Exposition

Authors

K-Y Daisy Fan, Cornell University; Clare van den Blink, Cornell University

Tagged Divisions

Educational Research and Methods

register theresponses—a, b, c, etc.—transmitted from the students’ clickers. The countdown timer,shown in the bottom right hand corner of the slide on Figure 1, can be activated at anytime by the instructor. After the countdown, the receiver stops accepting answers and candisplay the student responses as a histogram or a pie chart, as shown in Figure 2. In thisstudy, the resulting histogram was always displayed after a clicker question. Morediscussion on the questions used will follow below in Section 3.2. % Given an nr-by-nc matrix M for r= 1: nr for c= 1: nc A(c,r)= M(r,c); end

Conference Session

Assessing Student Learning

Collection

2011 ASEE Annual Conference & Exposition

Authors

Byron G. Garry, South Dakota State University

Tagged Divisions

Educational Research and Methods

ABET Student Learning Recommended IDEA Learning Objectives that faculty courses Outcomes measured should mark as Important/Essential 118 a, b, c, o 1, 2, 3, 4 220 a, b, d 1, 2, 3, 6 (emphasize “designing” to students) 230 a, b 1, 2, 3, 4 230L a, h 4, 12 330 a, j 1, 2, 4, 10 472 h, f, p, j 3, 10, 12 320 b, h, m, c, d 2, 4, 6 (emphasize “designing” to students), 12 470 a, h, m, d, f, k, l, o, p, e

Conference Session

Approaches to Assessment and Student Reflection

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Jes Barron, U.S. Military Academy; Brad C. McCoy, U.S. Military Academy; Jakob C. Bruhl, U.S. Military Academy; John J. Case, U.S. Military Academy; John Andrew Kearby, U.S. Military Academy

Tagged Divisions

Educational Research and Methods

. Table 1: Treatment Group Test Matrix No. of No. of Group Activity Activity Grade Type of students sketches Course Instructor ID location frequency value students (n students) (n sketches) I-A Engineering Every Sophomore 16 91 A In class None Mechanics class - Senior II-B

Conference Session

SPECIAL SESSION: Describing the Engineering Student Learning Experience Based on CAEE Findings: Part 2

Collection

2008 Annual Conference & Exposition

Authors

Russell Korte, The University of Texas-Tyler; Sheri Sheppard, Stanford University; William Jordan, CRL-Stanford University

Tagged Divisions

Educational Research and Methods

ofmanagement, and learn the values and mission of the organization1, 18. Van Maanen and Schein2described the socialization process by three domains of (a) learning what to do, (b) learning howto do it, and (c) learning why it is done this way.From the perspective of the learner in a social context, social cognitive theory views learning asa complex process, which is affectively and socially constituted19. This is consistent with recenttheories of learning, which incorporate cognitive, emotional, and social factors into a moreintegrated system of interdependent factors19, 20. For example, Yang20 proposed a theory ofknowledge comprising interactions between technical knowledge (what to do), practicalknowledge (how to do it), and affectual knowledge

Conference Session

Concepts and Conceptual Knowledge

Collection

2015 ASEE Annual Conference & Exposition

Authors

Lauren Suzanne Wallace; Floraliza Bornilla Bornasal, Oregon State University; Shane A. Brown P.E., Oregon State University

Tagged Divisions

Educational Research and Methods

Paper ID #12186Concepts in roundabout resources: A comparison between academic andpractical text using content analysisLauren Suzanne WallaceFloraliza Bornilla Bornasal, Oregon State University Floraliza B. Bornasal is a doctoral candidate in the School of Civil and Construction Engineering at Oregon State University. Her research explores engineering practice and learning in workplace contexts. She received her bachelor’s degree in civil engineering from Saint Martin’s University and her master’s degree in civil engineering - with a focus in transportation - at Oregon State University. Address: School of Civil and

Conference Session

Data-informed Approaches to Understanding Student Experiences and Outcomes

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Mariem Boujelbene, University of Louisville; Khalil Damak, University of Louisville; Asuman Cagla Acun Sener, University of Louisville; Jeffrey Lloyd Hieb, University of Louisville; Campbell R. Bego, University of Louisville; Patricia A. Ralston, University of Louisville; Olfa Nasraoui , University of Louisville

Tagged Divisions

Educational Research and Methods

and even third year, these labelings have both false positives and falsenegatives. Our study which seeks to identify, using a data science approach, a consistent wayto label all students as either ​retained​ or ​not retained​, ​enjoys the following advantages: a) It does not rely on the requirement of earning a degree in engineering, b) It is not based on enrollment at a fixed point in time, and c) It can be used as the data set continues to grow.Using a data science pipeline, we analyze student enrollment gaps to determine a reasonablelabeling of ​not-retained.​ In the following, we start by describing our methods, then presentour findings and finish with a discussion and conclusions.MethodsA Data-driven Pipeline for Retention

Conference Session

Understanding the Discipline of Engineering

Collection

2017 ASEE Annual Conference & Exposition

Authors

Andrea Mazzurco, University of Queensland; Brent K. Jesiek, Purdue University, West Lafayette (College of Engineering)

Tagged Divisions

Educational Research and Methods

collection and analysis processes for this phase and the final framework, which was thenintegrated in the information sheets presented at the end of the paper.Data collection. To ensure that a large enough sample of methods was gathered, we used asystematized literature review process. As suggested by Borrego and colleagues20, wefollowed the PRISMA selection process to search for and select potentially relevant papers.First, we defined three inclusion criteria:1. The papers needed to focus on the social or procedural aspects of small scale HE projects, such as: a. Frameworks, methodologies, processes, approaches, principles, or collections thereof, b. Methods, tools, techniques, dimensions, mindsets, c. Lessons learned, and/or d. Case

Conference Session

Faculty Development I

Collection

2015 ASEE Annual Conference & Exposition

Authors

Martha Cleveland-Innes, Athabasca University; Stefan Stenbom, KTH Royal Institute of Technology; Stefan Hrastinski, KTH Royal Institute of Technology

Tagged Divisions

Educational Research and Methods

presence.Teaching presence is available to the instructor and the students. It is created through the design,facilitation, and direction of cognitive and social processes such that personally meaningful andeducationally worthwhile learning outcomes are realized. See Appendix B for a chart of courseactivities.Ensuring educationally worthwhile outcomes in engineering education requires usingpedagogical methods that are instructional themselves. According to Yigit, Koyun, Yuksel, &Cankaya (2014) 16, “algorithmic thinking abilities of students who enrolled in the Algorithm andProgramming course in blended and traditional education are close” (p. 1). While not specific toengineering curriculum, these thinking abilities emerge in the learning environment and

Conference Session

Learning From Experts

Collection

2011 ASEE Annual Conference & Exposition

Authors

Alejandra J. Magana, Purdue University, West Lafayette; Ruth A. Streveler, Purdue University, West Lafayette; Natalie Barrett, Purdue University

Tagged Divisions

Educational Research and Methods

have implications that relate to a) the advancementof effective nanotechnology education in higher education and b) the use of PCK as atheoretical framework to investigate aspects of teaching in engineering education.IntroductionThe ability to explore the physical world at the nanoscale has opened up a wealth ofresearch opportunities. New marvels of design seem to appear each day and the potentialof nanoscale devices to improve human life is staggering. In the last twenty yearsnanotechnology has revolutionized technological devices and has impacted medicine,biotechnology, electronics, and has contributed to the creation of innovative tools andmaterials. The promise of nanotechnology is enormous, but producing enough trainedscientists

Conference Session

Model Eliciting Activities

Collection

2012 ASEE Annual Conference & Exposition

Authors

Heidi A. Diefes-Dux, Purdue University, West Lafayette; Monica E. Cardella, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

company has many 0 hour late times but all the late times are extremely big. … And the dataset2 i created emphasize a situation in which the shipping company has rarely any 0 late times…” [Student 2680] “Dataset A: is very unique because there are very small standard deviations from the mean. …Dataset B: there are many delays but very consistent and in the same range.” [Student 2736] “…I create two columns data sets which have more non-late data and small late hours number. …” [Student 2717]Four students provided a somewhat more quantitative description of their data sets. However,their quantification was often tied to the way in which the data set was generated and not to theresulting data set. “The two data sets were generated

Conference Session

Research on Diversity, Equity, and Inclusion

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Kristen Moore, University at Buffalo; Nathan R. Johnson, University of South Florida; Fernando Sánchez, University of St. Thomas; Walter R. Hargrove

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

citationpractices belie a more complex system of relationships. Historically, they have established powerrelationships among authors, ideas, and larger sociotechnical systems within the university[26].Our citations reflect our reading practices while establishing field boundaries and contours andultimately funneling into the larger economy of the university. They undergird this universityeconomy in a number of ways: (a) we form communities of practice/discourse communities inhow we cite, excluding and including particular ways of knowing; (b) we give particular ideaspower and visibility in how we cite; (c) we decide whose work matters, who should be tenuredand promoted, who belongs; and (d) we teach ethics and intellectual property through citations.These

Conference Session

Problem Solving, Adaptive Expertise, and Social Engagement

Collection

2018 ASEE Annual Conference & Exposition

Authors

Hieu-Trung Le; Aditya Johri, George Mason University; Aqdas Malik, George Mason University

Tagged Divisions

Educational Research and Methods

Paper ID #21513Situated Information Seeking for Learning: A Case Study of EngineeringWorkplace Cognition among Cybersecurity ProfessionalsHieu-Trung LeDr. Aditya Johri, George Mason University Aditya Johri is Associate Professor in the department of Information Sciences & Technology. Dr. Johri studies the use of information and communication technologies (ICT) for learning and knowledge shar- ing, with a focus on cognition in informal environments. He also examine the role of ICT in supporting distributed work among globally dispersed workers and in furthering social development in emerging economies. He received the

Conference Session

ERM Technical Session 7: Learning and Research in Makerspaces

Collection

2019 ASEE Annual Conference & Exposition

Authors

Juan Torralba, University of Miami; Rob Rouse, Southern Methodist University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

and influencing makers, we position (a)accountable disciplinary knowledge as the changes in what counts as engineeringknowledge throughout the IDC, as determined by experienced members of the space, (b)identification as the process of students identifying themselves, as well as beingidentified by others, as engineers, and (c) navigation as the ways in which studentsbecome experienced users of the space. To better understand the specifics of theframework and their theoretical underpinnings, a brief overview of each componentfollows. Figure 1. Adapted framework positioning makerspaces as communities of practice [19] where, students' development of an engineering identity [13] can be analyzed.Situated

Conference Session

Educational Research and Methods Poster Session

Collection

2012 ASEE Annual Conference & Exposition

Authors

Lisa K. Davids, Embry-Riddle Aeronautical University, Daytona Beach

Tagged Divisions

Educational Research and Methods

percentage of students fromthe experimental group earned A and B grades on the final exam, and a smaller group earned Dand F grades.The percentage increase in A grades from the control group to experimental group was 75%(control – 8%, experimental – 14%) and for B grades the percent increase was 31% (control –16%, experimental – 21%). Commensurate with the increase for the A and B grades, there was acorresponding decrease in the D and F grades. The percent decrease in D grades from thecontrol group to experimental group was 14% (control – 14%, experimental – 12%) and for Fgrades, the percent decrease was 30% (control – 30%, experimental – 21%). Interestingly, the

Conference Session

Digital Technologies and Learning

Collection

2011 ASEE Annual Conference & Exposition

Authors

Debra Gilbuena, Oregon State University; Ben Uriel Sherrett, Oregon State University; Milo Koretsky, Oregon State University

Tagged Divisions

Educational Research and Methods

80% 500Word Count 400 60% 300 40% 200 20% 100 0 0% Team A Team B Team C Team D Team A Team B Team C Team DFigure 3. Comparison of Material Balance episodes: (left) word counts for episode components, (right) word count percentages for episode componentsTwo of the four teams, (Team C

Conference Session

Research Methods

Collection

2018 ASEE Annual Conference & Exposition

Authors

Alexandra Coso Strong, Franklin W. Olin College of Engineering; Courtney S. Smith-Orr, University of North Carolina, Charlotte; Cheryl A. Bodnar, Rowan University; Walter C. Lee, Virginia Tech; Courtney June Faber, University of Tennessee, Knoxville; Erin J. McCave, University of Houston

Tagged Divisions

Educational Research and Methods

Education as a Field of Scientific Inquiry,” in Cambridge Handbook of Engineering Education Research, A. Johri and B. Olds, Eds. Cambridge University Press, 2014, pp. 3–28.[2] L. D. Gonzales and R. Rincones, “Interdisciplinary scholars: negotiating legitimacy at the core and from the margins,” J. Furth. High. Educ., vol. 36, no. 4, pp. 495–518, 2012.[3] S. K. Gardner, “‘What’s Too Much and What’s Too Little?’: The Process of Becoming an Independent Researcher in Doctoral Education,” J. Higher Educ., vol. 79, no. 3, pp. 326–350, 2008.[4] S. C. Narendorf, E. Small, J. A. B. Cardoso, R. W. Wagner, and S. W. Jennings, “Managing and Mentoring: Experiences of Assistant Professors in Working with Research Assistants,” Soc

Conference Session

Epistemic Research

Collection

2012 ASEE Annual Conference & Exposition

Authors

Ji Hyun Yu, Purdue University, West Lafayette; Johannes Strobel, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

- examination of the role of knowledge in learning and instruction. Educational Psychologist, 31, 89-92.31. Vosniadou, S., & Brewer, W. F. (1987). Theories of knowledge restructuring in development. Review of Educational Research, 57, 51-67.32. Buehl, M., & Alexander, P. A. (2001). Beliefs about academic knowledge. Educational Psychology Review, 13, 385-418.33. Hofer, B. K. (2000). Dimensionality and disciplinary differences in personal epistemology. Contemporary Educational Psychology, 25, 378-405.34. Vosniadou, S. (2002). On the nature of naive physics. In M. Limon & L. Mason (Eds.), Reconceptualizing conceptual change. Issues in theory and practice (pp. 61-76). Dordrecht, The Netherlands: Kluwer Academic.35. Vosniadou