Conference Session

Applied Frameworks

Collection

2017 ASEE Annual Conference & Exposition

Authors

Lori C. Bland, George Mason University; Margret Hjalmarson, George Mason University; Jill K. Nelson, George Mason University; Anastasia P. Samaras, George Mason University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

-study Scholar. She served as chair of S-STEP from 2013-2015 and is a current Co-PI of two National Science Foundation (NSF) funded grants: Designing Teaching: Scaling up the SIMPLE Design Framework for Interactive Teaching Development and a research initiation grant: Student-directed differ- entiated learning in college-level engineering education. Her research centers on facilitating and studying her role in faculty development self-study collaboratives. c American Society for Engineering Education, 2017 Applying Conjecture Mapping as a Design-Based Research Method to Examine the Design and Implementation of a Teaching Development Project for

Conference Session

Research Methods

Collection

2018 ASEE Annual Conference & Exposition

Authors

Cory Hixson, Rowan University; Ella Lee Ingram, Rose-Hulman Institute of Technology; Rachel McCord Ellestad, University of Tennessee, Knoxville; Julia M. Williams, Rose-Hulman Institute of Technology

Tagged Divisions

Educational Research and Methods

). Confusions and conventions: Qualitative research in engineering education. Journal of Engineering Education, 103, 1-7.Blair, E. E., R. B. Miller, M. Ong, and Y. V. Zastavker. (2017). Undergraduate STEM instructors' teacher identities and discourses on student gender expression and equity. Journal of Engineering Education, 106, 14-43.Blank, S. (2013). Why the lean start-up changes everything. Harvard Business Review, 91, 63-72.Borrego, M. (2007). Conceptual difficulties experienced by trained engineers learning educational research methods. Journal of Engineering Education, 96, 91-102.Case, J. M., and G. Light. (2011). Emerging research methodologies in engineering education research. Journal of Engineering Education, 100, 186-210

Conference Session

ERM Technical Session 5: Assessment

Collection

2019 ASEE Annual Conference & Exposition

Authors

Bahar Memarian, University of Toronto; Susan McCahan, University of Toronto

Tagged Divisions

Educational Research and Methods

. Black and D. Wiliam, “Assessment and classroom learning,” Assess. Educ. Princ. policy Pract., vol. 5, no. 1, pp. 7–74, 1998.[2] S. M. Brookhart, “Feedback that fits,” Engag. whole child Reflections best Pract. Learn. teaching, Leadersh., pp. 166–175, 2008.[3] K. E. Dunn and S. W. Mulvenon, “A critical review of research on formative assessment: The limited scientific evidence of the impact of formative assessment in education.,” Pract. Assessment, Res. Eval., vol. 14, no. 7, 2009.[4] H. Hattie, J., & Timperley, “The power of feedback,” Rev. Educ. Res., vol. 77, no. 1, pp. 81–112, 2007.[5] A. Kluger and A. DeNisi, “The effects of feedback interventions on performance: A historical review, a

Conference Session

Design Thinking and Creativity

Collection

2018 ASEE Annual Conference & Exposition

Authors

Suzanne Eyerman, Fairhaven Research and Evaluation; Sarah Hug, University of Colorado, Boulder; Emily McLeod; Tania Tauer, Techbridge Girls

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

andreferential language to communicate conceptual understandings. Finally, the holistic applicationof rubrics to interview data allowed for understandings of the engineering design process to beexpressed in multiple ways: both implicit and explicit understandings could be expressed byparticipants and then scored by analysts’ application of the rubrics to each participant’s interviewas a whole.References[1] E. P. Douglas, S. S. Jordan, M. Lande, and A. E. Bumbaco, “Artifact elicitation as a method of qualitative inquiry in engineering education,” in ASEE Annual Conference & Exposition, Seattle, WA, USA, June 2015.[2] Engineering Accreditation Commission. “Criteria for accrediting engineering programs,” Accreditation Board for

Conference Session

Works in Progress I

Collection

2018 ASEE Annual Conference & Exposition

Authors

Malini Natarajarathinam, Texas A&M University; Lei Xie, Texas A&M University; Michael Beyerlein, Texas A&M University; Rodney Boehm, Texas A&M University; Jill Zarestky, Colorado State University

Tagged Divisions

Educational Research and Methods

expecting to see higher levels of student and agency motivation and engagement. With thismonetary award at stake, we also anticipate an improvement in the quality of this year’s projectproposals.References[1] R. G. Bringle and J. A. Hatcher, “A service-learning curriculum for faculty,” Michigan Journal of Community Service Learning, pp. 112-122, 1995.[2] S. J. Peterson and M. J. Schaffer, “Service learning: A strategy to develop group collaboration and research skills,” Journal of Nursing Education, vol. 38, no. 5, pp. 208-214, 1999.[3] C. I. Celio, J. Durlak, and A. Dymnicki, “A meta-analysis of the impact of service-learning on students,” Journal of Experiential Education, vol. 34, no. 2, pp. 164-181, 2011.[4] M. J. Gray, E. H

Conference Session

Data-informed Approaches to Understanding Student Experiences and Outcomes

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

John Chen, California Polytechnic State University, San Luis Obispo; Jenna Michelle Landy, California Polytechnic State University, San Luis Obispo; Matthew Scheidt, Purdue University, West Lafayette; Justin Charles Major, Purdue University, West Lafayette; Julianna Ge, Purdue University, West Lafayette; Camaryn Elizabeth Chambers, California Polytechnic State University, San Luis Obispo; Christina Grigorian; Michelle Kerfs, California Polytechnic State University, San Luis Obispo; Edward J. Berger, Purdue University, West Lafayette; Allison Godwin, Purdue University, West Lafayette; Brian P. Self, California Polytechnic State University, San Luis Obispo; James M. Widmann, California Polytechnic State University, San Luis Obispo

Tagged Divisions

Educational Research and Methods

declinein Cluster 3’s cumulative GPA (Fig. 2(b)).Research Question 3: Does retention vary across clusters? To test this research question, we examined three models for retention. Major retention, R1,is whether a student has switched their major since admission. This represents the university’sofficial recognition of a change of major. Engineering retention, R2, is whether a student hasswitched from their engineering major since admission but is still attending University A in anon-engineering major. Finally, university retention, R3, is whether a student is a current studentor not at the university as a whole. A chi-squared test for equal proportions was used to compareeach retention rate across clusters. We compare p-values of these tests to

Conference Session

Student Teams and Project-Based Learning

Collection

2007 Annual Conference & Exposition

Authors

Adam Carberry, Tufts University; Merredith Portsmore, Tufts University; Chris Rogers, Tufts University

Tagged Divisions

Educational Research and Methods

before administering the surveys. Futureassessment of the surveys and knowledge assessment will be performed using a group of expertsin the field ensuring interrater reliability. With the changes made, the results should show Page 12.1418.9ultimately how beneficial or not participation in a program like STOMP really is.Bibliography1. Chickering, A.W. and Z.F. Gamson, Seven principles of good practice, in AAHE Bulletin. 1987. p. 3-7.2. Brown, J.S., A. Collins, and S. Duguid, Situated cognition and culture of learning. Educational Researcher, 1989. 18(1): p. 32-42.3. Dewey, J., Education and experience. 1938, New York: Simon and

Conference Session

Cognitive and Motivational Issues in Student Performance I

Collection

2007 Annual Conference & Exposition

Authors

Dawn Williams, Howard University; Lorraine Fleming, Howard University; Marcus Jones, Howard University; Ashley Griffin, Howard University

Tagged Divisions

Educational Research and Methods

Education, 29(4) 425-450.10. Gladieux, L. E., and Swail , W. S. (1998). Financial aid is not enough: Improving the odds of college success. College Board Review, (185), 16-21, 30-32.11. Warburton, E. C., Bugarin, R., and Nunez, A. M. (2001). Bridging the gap: Academic preparation and Postsecondary success of first-generation students. Education Statistics Quarterly, 3(3) 73-77.12. National Postsecondary Education Cooperative. (2006). What matters to student success: A review of the literature. Commissioned report for the National Symposium on Post Secondary Student Success: Spearheading a dialogue on student success.13. Howe, D (1996). Too much homework? I tell my daughter to strike. New Statesman (129) 4471(22).14. Kuh, G.D. (1993). In

Conference Session

Tools for Teaching

Collection

2008 Annual Conference & Exposition

Authors

Alfred Ducharme, University of Central Florida; Ali Mehrabian, University of Central Florida; Diala Gammoh, University of Central FLorida

Tagged Divisions

Educational Research and Methods

at the viewing site. Figure 1shows the legacy FEEDS system. Figure1. Legacy FEEDS recording system.During the 1990’s, FEEDS had delivered over 5000 graduate and undergraduate engineeringcourses to numerous FEEDS sites through Florida, and more than 2,000 working engineers andtechnical managers had earned their Master’s degrees using FEEDS. In 20 years, over 50,000students have registered for FEEDS courses.The way the information was delivered was changed after the entry of the World Wide Web inthe mid-1990. It was not initially utilized for distance education in Florida. From 1995-2000,bandwidth limitations by end-users or students did not allow for video download and delivery asa viable means of delivering lecture

Conference Session

First Year Engineering

Collection

2013 ASEE Annual Conference & Exposition

Authors

Jennifer M Peuker, University of Alaska, Anchorage; Jennifer McFerran Brock, University of Alaska Anchorage; Steffen Peuker, University of Alaska Anchorage

Tagged Divisions

Educational Research and Methods

what the MC options are. Although more difficult toimplement because of the more sophisticated design and analysis of MC questions, it is possibleto give "partial credit" even for MC questions if, e.g., a MC question tests a different concept butthe answer is dependent on previous answer(s) of related MC question(s).As discussed above, MC distractors can give insight to student misconceptions in the same way Page 23.461.9that the traditional CR problems can provide the instructor information about commonmisunderstandings. The MC question approach also allows for very fast turn-around in terms ofgrading, and can be used to give feedback to the

Conference Session

Conceptual Learning

Collection

2010 Annual Conference & Exposition

Authors

Morris Girgis, Central State University

Tagged Divisions

Educational Research and Methods

Developing an Engineering TaxonomyIn 1956, Benjamin Bloom first published his widely known taxonomy5. He identified six levelswithin the cognitive domain: knowledge, comprehension, application, analysis, synthesis, andevaluation. The taxonomy advanced teaching and learning by motivating educators to create amore integrated method of educating students. During the 1990’s, a new group of cognitivepsychologists, led by Lorin Anderson, a former student of Bloom, updated the taxonomy toreflect relevance to 21st century work. Table 1 summarizes both old and new taxonomy levels6. Old Bloom’s Taxonomy Version ew Bloom’s Taxonomy Version Knowledge Define, duplicate, list, memorize, Remembering Can the

Conference Session

Trends in Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Jeffrey Wigdahl, The University of New Mexico; Gregory L. Heileman, University of New Mexico; Ahmad Slim, University of New Mexico; Chaouki T. Abdallah, University of New Mexico

Tagged Divisions

Educational Research and Methods

students in University 1’s engineer-ing departments are taking 138% of the hours that are needed to graduate.1 For this program, itmeans students are graduating with approximately 180 hours on average. It is also worth notingthe curriculum rigidity of the University 1 program. There are 1.48 edges per node, meaning eachclass has an average of one-and-a-half prerequisites. The longest path of nine is also significant,as it is longer than the number of semesters in a four year program, i.e., there are ten classes inthis pre/co-requisite chain that must be completed in eight semesters. Obviously there are severalco-requisites in this chain, meaning that two classes can be taken together, but this length makes afailure very costly in terms of timely

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

Engineering Student Identity. International Journal of Engineering Education, 26(6),1550-1560.[4] Gee, J. P. (2000). Identity as an analytic lens for research in education. Review of Research in Education,25, 99-125.[5] Kittleson, J. M., S.A. Southerland. (2004). The Role of Discourse in Group Knowledge Construction: ACase Study of Engineering Students. Journal of Research in Science Teaching, 41(3), 267-293.[6] Allie, S., M.N. Armien, N. Burgoyne, J.M. Case, B.I. Collier-Reed, T.S. Craig, A. Deacon, Z. Geyer, C.Jacobs, J. Jawitz, B. Kloot, L. Kotta, G. Langdon, K. le Roux, D. Marshall, D. Mogashana, C. Shaw, G.Sheridan, N. Wolmarans. (2009). Learning as acquiring a discursive identity through participation in acommunity: Improving student learning

Conference Session

Understanding Our Students I

Collection

2012 ASEE Annual Conference & Exposition

Authors

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

Tagged Divisions

Educational Research and Methods

elements in the N-gram occur together.First we consider Dice’s coefficient, which is defined only for bigrams. Consider two sets ofbigrams: the set of bigrams in which a particular problem number, p1 , is the first element Page 25.305.9of each bigram and another set of bigrams in which some other problem number, p2 , is thesecond element of each bigram. Dice’s coefficient provides a measure of “similarity” forthese two sets, computed as: 2|X ∪ Y | S= (1) |X| + |Y |Here, |X| is the

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

(Eds.) Handbook of research design in mathematics and science education (pp. 591-645). Mahwah, NJ: Lawrence Erlbaum.2. Diefes-Dux. H. A, Hjalmarson, M., Miller, T., & Lesh, R. (2008). Chapter 2: Model-Eliciting Activities for engineering education. In J. S. Zawojewski, H. A. Diefes-Dux, & K. J. Bowman (Eds.) Models and modeling in Engineering Education: Designing experiences for all students. Rotterdam, the Netherlands: Sense Publishers.3. Salim, A. & Diefes-Dux, H. A. (2009). Problem identification during Model-Eliciting Activities: characterization of first-year students’ responses. Proceedings of the Research in Engineering Education Symposium, Palm Cove, QLD, Australia.4. Fry, A., Cardella, M

Conference Session

Before and After: Matriculants and Alumni

Collection

2012 ASEE Annual Conference & Exposition

Authors

Marisa K. Orr, Purdue University; Nichole M. Ramirez, Purdue University; Matthew W. Ohland, Purdue University, West Lafayette; Valerie Lundy-Wagner, New York University

Tagged Divisions

Educational Research and Methods

institution, an economic status variable, and the interaction of the two. Thisallows us to determine how much more variance is explained by including the economic statusvariable.Raudenbush and Bryk assert the importance of using hierarchical linear modeling (HLM), ormultilevel modeling (MLM), in education research, especially when using variables that areaggregated at a higher level than the outcome variable(s) 18. In our case, six-year graduation is astudent level outcome while PES and DES are variables that are aggregated at the school anddistrict levels, respectively. MLM takes into account the interrelatedness of variables at multiplelevels, which violates the assumption of independence in ordinary least squares (OLS) regression19 . While MLM

Conference Session

SPECIAL SESSION: Educational Methods and Tools to Encourage Conceptual Learning I

Collection

2011 ASEE Annual Conference & Exposition

Authors

Nancy K. Lape, Harvey Mudd College

Tagged Divisions

Chemical Engineering, Educational Research and Methods

guidance during formal class time 3, 4. It may be versions of PBL at theminimal-guidance extreme that led Kirschner et. al. 1 to name PBL as an example of an“instructional procedure that ignores the structures that constitute human cognitivearchitecture,” or more specifically, an instruction method that “proceed[s] with noreference to the characteristics of working memory, long-term memory, or the intricaterelations between them.” The tax on working memory during minimally guidedinstruction, Kirschner et al. argue, is great enough that students use all working memoryin their attempts to search for problem solutions, blocking their ability to truly learn thematerial via the accumulation of knowledge in long-term memory.However, as noted in Hmelo

Conference Session

Educational Research

Collection

2010 Annual Conference & Exposition

Authors

Cindy Waters, North Carolina A&T State University; Helen Chen, Stanford University; Sheri Sheppard, Stanford University

Tagged Divisions

Educational Research and Methods

Engineering Education (CAEE). Page 15.344.10REFERENCES1 .Sheppard, S.D., Atman, C.J., Stevens, R., Fleming, L., Streveler, R., Adams, R.S., & Barker, T. 2004. Studying theengineering experience: Design of a longitudinal study. In Proceedings of the American Society for EngineeringEducation Annual Conference, Salt Lake City, Utah.2 Clark, M., Sheppard, S.D., Atman, C.J., Fleming, L., Miller, R., Stevens, R., Streveler, R. & Smith, K. 2008.Academic Pathways Study: Processes and realities. In Proceedings of the American Society for EngineeringEducation Annual Conference, Pittsburgh, PA.3 Donaldson, K., Chen, H.L., Toye, G., & Sheppard, S

Conference Session

New Learning Paradigms I

Collection

2010 Annual Conference & Exposition

Authors

Kendra Seniow, Oregon State University; Eric Nefcy, Oregon State University; Christine Kelly, Oregon State University; Milo Koretsky, Oregon State University

Tagged Divisions

Educational Research and Methods

reasoning in order to make decisions within the project.Once identified, the full mathematical expression or model descriptor is added to the ModelRepresentation. Quantitative Model Components, those characterized by mathematicalequations, are placed inside squares while Qualitative Model Components, those characterizedby descriptive mechanisms and responses, reside in circles. Additionally, a model componentcan be designated as either statistical or empirical in nature by an ‘S’ or ‘E’ in the modelcomponent box. Figure 2 shows the different types of model components and an example ofhow they could appear together in the Model Representation. Figure 2. Primary and Secondary Model Components. Part (a) shows both qualitative (circle) and

Conference Session

Student Learning, Problem Solving, & Critical Thinking 3

Collection

2014 ASEE Annual Conference & Exposition

Authors

Megan Kenny Feister, Purdue University, West Lafayette; Carla B. Zoltowski, Purdue University, West Lafayette; Patrice Marie Buzzanell, Purdue University, West Lafayette; William C. Oakes, Purdue University, West Lafayette; Qin Zhu, Purdue University

Tagged Divisions

Educational Research and Methods

work where ethics may be present but goes unnoticed or under-scrutinized. Thisline of research will contribute both to our theoretical and methodological efforts to understandteams and ethics in an engineering context, but could also be useful to engineering educators asthey consider how to present ethics and team work to engineering students.AcknowledgementsThis work was made possible by a grant from the National Science Foundation (DUE-112374).Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the authors and do not necessarily reflect the views of the National Science Foundation.References[1] Rest, J., Narvaez, D., Bebeau, M., & Thoma, S. (1999). A neo-Kohlbergian approach: The DIT and

Conference Session

Issues in Advising and Mentoring

Collection

2013 ASEE Annual Conference & Exposition

Authors

Nathan Dolenc, University of Virginia

Tagged Divisions

Educational Research and Methods

thecorrect way to perform an engineering design process, but it strips away opportunities by notallowing students to be more engaged and learn by doing it themselves. Students in theapprentice model learn by observing, while students in the autonomous model learn by doing.Furthermore, as these groups of students continue to develop, we can suggest that those whoparticipated in a more heavily mentor team may become dependent and mold into a teammember, whereas a student who participated in a less mentorship team is more likely to becomeindependent and develop into a team leader. Page 23.1130.12References1. Barker, S. B., Ansorge, J. (2007). Robotics

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

Science, 1998.[11] Pezdek, K., Berry, T., and Renno, P. A. Children’s mathematics achievement: The role of parents’ perceptions and their involvement in homework. Journal of Educational Psychology, 94, 771–777, 2002.[12] Romero, C., Romero, J., Luna, J., and Ventura S. Mining Rare Association Rules from e-Learning Data. In Proceedings of the Third International Conference on Educational Data Mining, 2010.[13] Singh, K., Granville, M., and Dika, S. Mathematics and science achievement: Effects of motivation, interest, and academic engagement. Journal of Educational Research, 95, 323–332, 2002.[14] Oviatt, S., Arthur, A., and Cohen, J. Quiet interfaces that help students think. In Proceedings of the 19th annual

Conference Session

Preparing Engineering Students for Their Professional Practice

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Shiuan-Huey Yen, Institute of Engineering Education Taiwan; Jessica Fan, Institute of Engineering Education Taiwan; Mandy Liu, Institute of Engineering Education Taiwan; Liang-Jenq Leu, Institute of Engineering Education Taiwan

Tagged Divisions

Educational Research and Methods

, Japan is constantly improving itshigh-level talent training programs and innovative initiatives.Cultivating interdisciplinary skills among high-level talents in the U.S.As universities are considered a source of advanced knowledge in science and technology(S&T), innovation initiatives in the U.S. have emphasized technology transfer. Beginning withthe Bayh-Dole Act, intellectual property (IP) rights were transferred to universities. Thisgradually diversified the role of universities from doing research only to commercializing theresearch results [23]. R&D activities and patent applications have increased due to UIC [24],which also stimulates regional R&D activities [25]-[26].For training talent in the U.S., Wang [27] addressed two

Conference Session

Assessing Hard-to-Measure Constructs in Engineering Education: Assessment Design and Validation Studies

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Madison E. Andrews, University of Texas at Austin; Priyadarshan N. Patil, University of Texas at Austin

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

Electromagnetic Induction Problems. International Journal of Science and Mathematics Education, 13(1), 215.Borrego, M., Foster, M. J., & Froyd, J. E. (2014). Systematic Literature Reviews in Engineering Education and Other Developing Interdisciplinary Fields. Journal of Engineering Education, 103(1), 45-76. doi:10.1002/jee.20038Ferretti, R. P., MacArthur, C. A., & Dowdy, N. S. (2000). The effects of an elaborated goal on the persuasive writing of students with learning disabilities and their normally achieving peers. Journal of Educational Psychology, 92(4), 694.Gainsburg, J., Fox, J., & Solan, L. M. (2016). Argumentation and decision making in professional practice. Theory Into Practice, 55(4

Conference Session

Assessment II: Learning Gains and Conceptual Understanding

Collection

2016 ASEE Annual Conference & Exposition

Authors

Kevin Lewis Van De Bogart, University of Maine; MacKenzie R. Stetzer, University of Maine

Tagged Divisions

Educational Research and Methods

% Mathematical calculation 5% 6% 4% No phase shift 49% 19% 50% Explicit justification of unchanged phase 2% 6% 4% Phase shift of ±90° or 180° 32% 63% 38% Explicit justification of specified phase shift 17% 31% 12% Non-sinusoidal output 15% 13% 4% frequency to the calculated 3dB frequency. As an example of the latter kind of reasoning, onestudent wrote, “ω3dB = 1/RC = 1/(10 kΩ)(15.9 nF) = 6.3 * 103 s-1. f3dB = ω3dB / 2π = 1001 Hz ≈1 kHz. So the input voltage is attenuated by a

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

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

the author(s) and do not necessarily reflect the views of the NationalScience Foundation. The authors wish to thank the STRIDE team and survey participants fortheir engagement with this study.References [1] M. Credé and N. R. Kuncel, “Study habits, skills, and attitudes: The third pillar supporting collegiate academic performance,” Perspectives on Psychological Science, vol. 3, no. 6, pp. 425-453, 2008. [2] A. Godwin, “Unpacking Latent Diversity,” in American Society for Engineering Education (ASEE) Annual Conference and Exposition, Columbus, OH, 2017. [3] J. J. Lin, P. K. Imbrie, K. J. Reid, and J. Wang, “Work in progress—Modeling academic success of female and minority engineering students using the student attitudinal

Conference Session

ERM Technical Session 12: Creativity and Problem Framing

Collection

2019 ASEE Annual Conference & Exposition

Authors

Caleb Sean Cunningham, Bucknell University; Kaela M. Martin, Embry-Riddle Aeronautical University, Prescott; Elif Miskioglu, Bucknell University

Tagged Divisions

Educational Research and Methods

variability in scoring. We areparticularly interested if there is a discrepancy between the judged creativity in the first-year and senior-year students.AcknowledgementsWe would like to thank the capstone instructors at Embry-Riddle Aeronautical Universityand the Institutional Review Board at Bucknell University for supporting and making ourwork possible.References[1] Davis, K. A., and C. T. Amelink, “Exploring differences in perceived innovative thinkingskills between first year and upperclassmen engineers,” JEEE Frontiers in EducationConference (FIE), Erie, PA, 2016.[2] Kazerounian K, Foley S., “Barriers to Creativity in Engineering Education: A Study ofInstructors and Students Perceptions,” Journal of Mechanical Design, vol. 129, no. 7, 2007,pp

Conference Session

ERM Potpourri II

Collection

2007 Annual Conference & Exposition

Authors

Shane Brown; Devlin Montfort; Kip Findley

Tagged Divisions

Educational Research and Methods

of MaterialsAbstractStudents often have far less conceptual understanding in core engineering courses thanfaculty assume. The first wide-spread application of the Force Concept Inventory in theearly 1980’s highlighted students’ lack of understanding in fundamental physicsprinciples. Recently, educators have been reevaluating student understanding of conceptsin the standard science and engineering curriculum using concept inventory instrumentsin topics such as thermodynamics, mechanics, and fluid mechanics. The objective of thisstudy is to develop a methodology to observe specific examples of difficulty inconceptual understanding which could be used to infer specific student misconceptions.To achieve this task a pilot study was undertaken

Conference Session

New Models for Teaching and Learning

Collection

2007 Annual Conference & Exposition

Authors

Malgorzata Zywno, Ryerson University; Mary Frances Stewart

Tagged Divisions

Educational Research and Methods

AC 2007-1608: A SUMMARY ANALYSIS OF ENGINEERING STUDENTS'INTERACTIONS WITH AN ONLINE LEARNING OBJECT IN THE CONTEXT OFTHEIR LEARNING STYLESMalgorzata Zywno, Ryerson University MALGORZATA S. (GOSHA) ZYWNO Gosha Zywno, M.Eng. (U. of Toronto), Ph.D. (Glasgow Caledonian U.), is a Professor of Electrical and Computer Engineering at Ryerson University. Dr. Zywno is a recipient of several university, national and international teaching excellence and achievement awards, including the 2005 ASEE Sharon Keillor Award, 2002 3M Teaching Fellowship and 2005 Canadian Engineers’ Medal for Distinction in Engineering Education. Her research interests are in active, collaborative learning with technology. She has

Conference Session

The Critical First Year in Engineering Education

Collection

2007 Annual Conference & Exposition

Authors

Linda Lindsley, Arizona State University; Veronica Burrows, Arizona State University

Tagged Divisions

Educational Research and Methods

AC 2007-750: DEVELOPMENT OF AN ONLINE TEXTBOOK AND RESEARCHTOOL FOR FRESHMAN ENGINEERING DESIGNLinda Lindsley, Arizona State UniversityVeronica Burrows, Arizona State University Page 12.527.1© American Society for Engineering Education, 2007 Development of an Online Textbook and Research Tool for Freshman Engineering DesignAbstractIn many engineering design texts, the solution(s) to design problems are provided along with theproposed problem. Therefore, the student will read about the solution rather than take the time tothink about the problem being presented. This paper explores the development of and pilot studydone on an online textbook and