Conference Session

K-12 Students and Teachers

Collection

2011 ASEE Annual Conference & Exposition

Authors

Micah S. Stohlmann, University of Minnesota; Tamara J. Moore, University of Minnesota, Twin Cities; Young Rae Kim, University of Minnesota, Twin Cities; Mi Sun Park, University of Minnesota, Twin Cities; Gillian Roehrig, University of Minnesota

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Educational Research and Methods

contest. Some flight characteristics that were tested were: (a) how far the planesflew, and (b) how long the planes stayed in the air. But, it was difficult to judge some of thesecharacteristics because the planes performance depended on which “pilots” tossed them. So, nextyear, the organizers of the paper airplane contest have decided that three “pilots” should fly eachplane, and that the same three pilots should fly all of the planes. The problem statement of thepaper airplane MEA asked students to write a letter to the judges of a paper airplane contest. Theletter needed to provide a procedure which would allow the judges to decide which airplane is:(a) the most accurate flier, and (b) the best floater. Teams of three to four students then

Conference Session

ERM Technical Session 7: Learning and Research in Makerspaces

Collection

2019 ASEE Annual Conference & Exposition

Authors

Lee Michael Martin, University of California, Davis

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Diversity

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Educational Research and Methods

interviews withstudents. Interview questions varied, but always asked students a) what they worked on that dayand b) if they encountered any sticking points in their work. These interviews constitute the datafor this paper. Data collection spanned two and a half school years.Participants in the full study were 40 students who enrolled for at least some portion of theschool year. This group was racially diverse: 2.5% were Asian, 25% were Black, 17.5% wereLatino/a, 35% were White, and 20% were two or more races; 47.5% were girls, 47.5% wereboys, and 5% were gender non-conforming. Across this full group, our data corpus consists ofapproximately 600 short interviews. For this paper, we analyze a subset of this data corpus,namely the data for 9 students

Conference Session

Works in Progress: Faculty Perspectives and Training

Collection

2016 ASEE Annual Conference & Exposition

Authors

Edward J. Berger, Purdue University, West Lafayette; Ryan R. Senkpeil, Purdue Engineering Education; Elizabeth K. Briody Ph.D., Cultural Keys LLC; Edward F. Morrison, Purdue University, West Lafayette

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Educational Research and Methods

their instructors accordingly.AcknowledgementThis material is based upon work supported by the National Science Foundation underGrant No. EEC-1519412 and the Revolutionizing Engineering Departments (RED)program. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References[1] T. A. Litzinger, S. H. Lee, J. C. Wise, and R. M. Felder, “A Psychometric Study of the Index of Learning Styles,” J. Eng. Educ., vol. 96, no. 4, pp. 309–319, 2007.[2] S. D. Gosling, P. J. Rentfrow, and W. B. Swann, “A very brief measure of the Big-Five personality domains,” J. Res. Pers., vol. 37, no. 6, pp. 504–528, Dec. 2003

Conference Session

Broadening Participation in Engineering

Collection

2015 ASEE Annual Conference & Exposition

Authors

Kevin O'Connor, University of Colorado Boulder; Frederick A. Peck, Freudenthal Institute, School of Education, University of Colorado; Julie Cafarella, University of Colorado, Boulder; Jacquelyn F. Sullivan PhD, University of Colorado, Boulder; Tanya D Ennis, University of Colorado, Boulder; Beth A Myers, University of Colorado Boulder; Daria A Kotys-Schwartz, University of Colorado Boulder; Beverly Louie, University of Colorado, Boulder

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Diversity

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Educational Research and Methods

contesting identities of expertise in a heterogeneous learning context. In S. Wortham & B. Rymes (Eds.), Linguistic Anthropology of Education (Vol. 37, pp. 61–91). Westport, CT: Praeger.5. Bowker, G. C., & Star, S. L. (1999). Sorting things out: Classification and it consequences. Cambridge, MA: MIT Press.6. Star, S. L., & Bowker, G. C. (1997). Of lungs and lungers: The classified story of tuberculosis. Mind, Culture, and Activity, 4(1), 3-23.7. Greeno, J. G. & The Middle School Mathematics Through Applications Project Group (1997). Theories and practices of thinking and learning to think. American Journal of Education, 106, 85– 126.8. Johri, A., Olds, B.M., and O’Connor, K. (2014). Situative frameworks for

Conference Session

Assessment II: Learning Gains and Conceptual Understanding

Collection

2016 ASEE Annual Conference & Exposition

Authors

Kristen Bethke Wendell, Tufts University; Jessica Watkins, Tufts University; Aaron W. Johnson, Tufts Center for Engineering Education and Outreach

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Educational Research and Methods

Paper ID #16265Noticing, Assessing, and Responding to Students’ Engineering: Exploring aResponsive Teaching Approach to Engineering DesignKristen Bethke Wendell, Tufts University Kristen Wendell is Assistant Professor of Mechanical Engineering and Adjunct Assistant Professor at Tufts University, where she is also a Faculty Fellow at the Center for Engineering Education and Outreach.Jessica Watkins, Tufts UniversityDr. Aaron W. Johnson, Tufts Center for Engineering Education and Outreach Aaron W. Johnson is a postdoctoral research associate at the Tufts University Center for Engineering Education and Outreach. He received his

Conference Session

Works in Progress: Learning and Engagement

Collection

2016 ASEE Annual Conference & Exposition

Authors

Nicholas D. Fila, Purdue University, West Lafayette; Senay Purzer, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

learning curriculum: From an activity theory perspective. International Journal of Engineering Education, 29(1). 5. Ferrari, A., Cachia, R., & Punie, Y. (2009). Innovation and creativity in education and training in the EU member states: Fostering creative learning and supporting innovative teaching. JRC Technical Note, 52374. 6. Bowden, J. A., & Green, P. (2005). Doing developmental phenomenography. Melbourne, Australia: RMIT Press. 7. Marton, F., & Booth, S. A. (1997). Learning and awareness. Psychology Press. 8. Zoltowski, C. B., Oakes, W. C., & Cardella, M. E. (2012). Students' Ways of Experiencing Human‐Centered Design. Journal of Engineering Education,101(1), 28-59. 9. Mann, L

Conference Session

Educational Research and Methods Division Poster Session

Collection

2017 ASEE Annual Conference & Exposition

Authors

William E. Genereux, Kansas State University Polytechnic Campus

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Educational Research and Methods

). Retrieved from Proquest dissertations and theses - full text. (UMI No. 3408757).7. Benkler, Y. (2006). The Wealth of Networks: How Social Production Transforms Markets and Freedom. In Wealth of Networks (pp. 356–487). New Haven, CT: Yale University Press.8. Kvavik, R. B., & Caruso, J. B. (2005). Students and information technology, 2005 : Convenience, connection, control, and learning. Boulder, CO: Educause. Retrieved from https://net.educause.edu/ir/library/pdf/ers0506/rs/ERS0506w.pdf9. Schmidt, H. (2013). Media literacy education from kindergarten to college : A comparison of how media literacy is addressed across the educational system. Journal of Media Literacy Education, 5(1), 295–309.10. O’Neal, J. (1990). The humanities

Conference Session

Knowing Our Students, Faculty, and Profession

Collection

2009 Annual Conference & Exposition

Authors

Marisa Orr, Clemson University; Zahra Hazari, Clemson University; Philip Sadler, Science Education Department, Harvard-Smithsonian Center for Astrophysics; Gerhard Sonnert, Science Education Department, Harvard-Smithsonian Center for Astrophysics

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Educational Research and Methods

: A follow-up study of the job attitudes of business school graduates. Organizational Behavior & Human Performance, 6(1), 36-49.11. Mitchell, T., & Knudsen, B. (1973). Instrumentality theory predictions of students' attitudes towards business and their choice of business as an occupation. Academy of Management Journal, 16(1), 41-52.12. Lawler III, E., Kuleck, W., Rhode, J., & Sorensen, J. (1975). Job choice and post decision dissonance. Organizational Behavior & Human Performance, 13(1), 133-145.13. Mitchell, T., & Beach, L. (1976). A review of occupational preference and choice research using expectancy theory and decision theory. Journal of Occupational Psychology, 49(4), 231-248.14. Brooks

Conference Session

Assessment and Evaluation in Engineering Education II

Collection

2007 Annual Conference & Exposition

Authors

Erol Ozan, East Carolina University; Mohammad Tabrizi, East Carolina University; Karl Wuensch, East Carolina University; Shahnaz Aziz, East Carolina University; Masao Kishore, East Carolina University

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Educational Research and Methods

Dr. Tabrizi is a professor in the Department of Computer Science at East Carolina University. He received his Ph. D. degree in Automatic Control and Systems Engineering, his M.Sc. degree in Automatic Control and Systems Engineering, and his B. Sc. degree in Computer Science. His research interests include Modeling and Simulation, Computer Vision, Signal and Image Processing, Software Engineering, Internet and Multimedia, Software Process Modeling, Object Oriented Analysis and Design, Computer Science Education.Karl Wuensch, East Carolina University Dr. Wuensch received his B.A. from Elmira College, M.A. from East Carolina University, and Ph.D. from Miami University. He is currently a professor and ECU

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

instructor, and the group's repeatability of the error (on the specificassignment) is plotted in Figure 2. Page 24.26.5 Figure 2. Plot of the probability distribution functions.For the study, the values of the coefficients from Equation 3 and the weights, , from Equation 1are shown in Table 1. These values were optimized by using the data discussed in the followingsections. Content Priority Prior Experience Repeatability Coefficients i=1 i=2 i=3 a 0 1 0 b

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

,” Scientific Reports, vol. 3, no. 1, 2013. [17] C. M. Ganley and S. A. Hart, “Shape of Educational Data: Interdisciplinary Perspectives,” Journal of Learning Analytics, vol. 4, no. 2, pp. 6-11, 2017. [18] Kirn, A., Godwin, A., Benson, L., Potvin, G., Doyle, J., Boone, H., & Verdin, D. (2016). “Intersectionality of Non-normative Identities in the Cultures of Engineering,” in American Society for Engineering Education (ASEE) Annual Conference and Exposition, New Orleans, LA, 2016.[19] A. Godwin, D. Verdín, B. S. Benedict, R. A. Baker, T. J. Milton, and J. T. Yeggy, “Board 51: CAREER: Actualizing Latent Diversity: Building Innovation through Engineering Students' Identity Development,” in American Society for Engineering

Conference Session

Student Attitudes and Perceptions

Collection

2009 Annual Conference & Exposition

Authors

Debbie Chachra, Franklin W. Olin College of Engineering; Deborah Kilgore, University of Washington

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Educational Research and Methods

completion of their degrees. Fulldetails of the development, administration, and preliminary results of the survey can be foundelsewhere.18, 19 For the purposes of this paper, we will be focusing on three constructs thatmeasure different aspects of academic self-confidence. Each construct comprises two or moreitems (questions). Page 14.614.3  I. Confidence in math and science skills: a) math ability b) science ability II. Confidence in open-ended problem-solving skills: a) Creative thinking is one of my strengths. b) I am skilled in solving problems that can have multiple solutions

Conference Session

Mentoring Practices and Project Teams

Collection

2018 ASEE Annual Conference & Exposition

Authors

Ying Cao, Oregon State University; Christina Smith, Brown University; Benjamin David Lutz, Oregon State University; Milo Koretsky, Oregon State University

Tagged Divisions

Educational Research and Methods

AiChE Concept Warehouse: A web-based tool to promote concept-based instruction," Advances in Engineering Education, vol. 4, no. 1, pp. n1, 2014.[9] J. Trevelyan, The making of an expert engineer, CRC Press, 2014.[10] E. Wenger-Trayner, M. Fenton-O'Creevy, S. Hutchinson, C. Kubiak and B. Wenger-Trayner eds, Learning in landscapes of practice: Boundaries, identity, and knowledgeability in practice-based learning, Routledge, 2014.[11] D. M. Gilbuena, B. U. Sherrett, E. S. Gummer, A. B. Champagne, and M. D. Koretsky, "Feedback on professional skills as enculturation into communities of practice," Journal of Engineering Education, vol. 104, no. 1, pp. 7-34, 2015.[12] J. Trevelyan, "Technical coordination in engineering practice," Journal

Conference Session

Educational Research and Methods Division Poster Session

Collection

2019 ASEE Annual Conference & Exposition

Authors

Zachariah J. Beasley, University of South Florida; Les A. Piegl, University of South Florida; Paul Rosen, University of South Florida

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Educational Research and Methods

(worst), 3.01 (average:a ‘B’), and 4.3 (excellent: an ‘A+’).The process has resulted in two different review forms to date. The seed form was designed basedon teaching style, the students and their preparation, and the courses. The second iteration removedtwo questions and added thirteen leveraging our process for capturing sentiment. Since these factorsvary widely, our particular form may not be appropriate for other courses. Although the questionsare not solely limited to the field of engineering, they do reflect feedback from students in ourdiscipline. We do not believe there is a one-size-fits-all review form — it is a mistake to use onetuned to a specific course/discipline without going through the process of iteratively mining

Conference Session

Innovative Pedagogies Afforded Through Technology and Remote Learning

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Chadia A. Aji, Tuskegee University; M. Javed Khan, Tuskegee University

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Diversity

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Educational Research and Methods

the basic concepts taught in thecore STEM courses is a strong contributing factor to student attrition. Strategies to improvelearning experiences in STEM courses by all students at colleges and universities are thereforeneeded so that they persist in the STEM career pipeline. A group of STEM faculty members at aHistorically Black University is committed to this important need through the far-reaching use ofVirtual Reality (VR) in its STEM courses and investigating its impact on learning outcomes,engagement and persistence in STEM.The two big questions that continue to be examined by STEM education experts are: (a) Why dostudents change their majors from a STEM to a non-STEM major? and, (b) Why do studentsstruggle with STEM concepts leading

Conference Session

Efforts to Understand and Support Students' Socioemotional Factors

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Madasamy Arockiasamy, Florida Atlantic University; Sudhagar Nagarajan, Florida Atlantic University; Hassan Mahfuz, Florida Atlantic University; Michael R. Maniaci, Florida Atlantic University; Ishwarya Srikanth, Florida Atlantic University; Stephen Michael Castillo; Reinaldo L. Dos Santos, Florida Atlantic University

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Diversity

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Educational Research and Methods

used for the purpose ofmapping and geo-spatial analysis. This software enables students to use the GPS application forasset management showing natural as well as in-built assets on the ground. The students werealso exposed to learning opportunities though mobile museums organized in the schools bySouth Florida Science Center and Aquarium (Figures 4b and 4c). a) b) c)Figure 4. Student Learning Activities: a) Asset Mapping of School Playground usingArcGIS Collector App, b) Mobile Museum in Middle School, c) Mobile Museum Set-up inHigh School Gymnasiumiv) Family Café events for the Middle and High SchoolsParental involvement in a student’s education has a

Conference Session

Student Learning

Collection

2009 Annual Conference & Exposition

Authors

Kathryn Jablokow, Pennsylvania State University-Great Valley; Pamela Vercellone-Smith, Penn State Great Valley; Sally Sue Richmond, Penn State Great Valley

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Educational Research and Methods

theowners of those differences as “inferior”), leading to the undervaluation and poor utilization ofpotentially critical contributions to the team. In general, when any team comes together to solvea problem, they automatically inherit another problem: the management of cognitive diversitywithin that team. Kirton refers to these two problems as “Problem A” (the original problem thatbrought the team together) and “Problem B” (managing their individual differences),respectively19; successful teams spend more time on Problem A than Problem B, but this may beno easy feat!It is also important to note that some scholars (and many practitioners) have become particularlyenthralled with Innovation (“radical, breakthrough change”) in recent years, which

Conference Session

Faculty Development II: Building Community Among STEM Educators

Collection

2016 ASEE Annual Conference & Exposition

Authors

Jana Bouwma-Gearhart, Oregon State University; Ann Sitomer, Oregon State University; Kathleen Quardokus Fisher, Oregon State University; Christina Smith, Oregon State University; Milo Koretsky, Oregon State University

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Educational Research and Methods

organizational change in response to postsecondary education improvementinterventions? We identify the need for a multi-theoretical research model that allows us to morerigorously describe the potential for organizational change at the start of an educational changeintervention in higher education and to document change over time. To accomplish the first purpose, weset the stage by describing characteristics of educational change interventions targeting formalpostsecondary education organizations. Next, we detail findings from a targeted literature reviewconcerning: (a) the nature of formal postsecondary education organizations upon which we grounded ourontological perspective of these organizations, and (b) literature on organizational change that

Conference Session

Methodological & Theoretical Contributions to Engineering Education 3

Collection

2014 ASEE Annual Conference & Exposition

Authors

Rachel Louis Kajfez, Ohio State University; Elizabeth G. Creamer, Virginia Polytechnic Institute and State University

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Educational Research and Methods

Letter Enhancing the "to complement observations […] survey data were 2011 Comparison A Quality… collected"; "a synthesis of the findings" Incorporating a No 2011 no discussion of why MM was used B Systems… Justification AEE Service

Conference Session

Innovations in Teaching and Learning

Collection

2007 Annual Conference & Exposition

Authors

Monica Cardella, Center for the Advancement of Scholarships on Engineering Education (CASEE); Cynthia Atman, University of Washington

Tagged Divisions

Educational Research and Methods

” indicate that theparticipant spent a relatively large amount of time in a particular design activity while skinnyticks indicate that the participant spent a brief amount of time in a particular design activitybefore transitioning to a different activity. By looking at students’ design processes depicted intimelines, we can see whether a student tended to transition frequently between design activities(as was the case with Senior A) or spend large amounts of time in an activity (as was the casewith Senior B and Freshman A). We can also note when (chronologically) a participant engagedin a particular design activity—for example, Senior A engaged in Gather Information morefrequently during the first thirty minutes of the design process, but did

Conference Session

ERM Poster Session

Collection

2009 Annual Conference & Exposition

Authors

Dazhi Yang, Purdue University; Ruth Streveler, Purdue University; Ronald Miller, Colorado School of Mines; Aidsa Santiago Roman

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Educational Research and Methods

fundamental engineering concepts. Such a study could lead totransformational approaches to repair students’ misconceptions by applying and testing thatontological schema training methods can help repair robust misconceptions, which are resistantto repair by traditional teaching methods.AcknowledgementsWe wish to thank the National Science Foundation for supporting this project: DevelopingOntological Schema Training Methods to Help Students Develop Scientifically Accurate MentalModels of Engineering Concepts (EEC-0550169).References1. Miller, R. L., Streveler, R. A., Olds, B., Chi, M. M. T. H., Nelson, A., and Geist, M. R., “Misconceptions about rate processes: preliminary evidence for the importance of emergent conceptual schemas in thermal and

Conference Session

Cognitive Engagement

Collection

2018 ASEE Annual Conference & Exposition

Authors

Petr Johanes, Stanford University

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Educational Research and Methods

. Elby, R. E. Scherr, and E. F. Redish, “Resources, framing, and transfer,” in Transfer of Learning from a Modern Multidisciplinary Perspective, J. P. Mestre, Ed. Greenwich, CT: Information Age Publishing, 2005, pp. 89–120.[19] A. A. DiSessa, “Knowledge in Pieces,” in Constructivism in the Computer Age, G. Forman and P. B. Pufall, Eds. New Jersey: Lawrence Erlbaum Publishers, 1988, pp. 49–70.[20] S. A. Ambrose, M. W. Bridges, M. DiPietro, M. C. Lovett, and M. K. Norman, How learning works: Seven research-based principles for smart teaching, 1st ed. John Wiley & Sons, 2010.[21] E. J. Hansen, Idea-based learning: A course design process to promote conceptual understanding. Stylus Publishing, LLC., 2012.[22] B. Rogoff, J

Conference Session

ERM Technical Session 16: Faculty Development and Teaching Contexts

Collection

2019 ASEE Annual Conference & Exposition

Authors

Eleazar Marquez, Rice University; Samuel Garcia Jr., Texas State University

Tagged Divisions

Educational Research and Methods

and after class; 3) learnstudent names; and 4) pose non-intuitive questions that spark curiosity (Figure 1).This emerging model, termed ECNQ (e.g., acronym for Engage, Communicate, Names,Questions), is an active and dynamic approach to engaging students in the engineering classroomand works towards disrupting traditional normalized, ineffective teaching practices that limitand/or stifle student participation by helping to engender conditions for deep learning, activeparticipation, and engagement. Three main sources provided the foundation for development andrefinement of the model proposed by the authors: a) teaching practices employed by the authorduring lecture sessions; b) post course analysis of teaching experiences; c) literature

Conference Session

Student Motivation and Faculty Development

Collection

2015 ASEE Annual Conference & Exposition

Authors

Lisa Huettel, Duke University; Michael R. Gustafson II, Duke University; Joseph C. Nadeau P.E., Duke University; David Schaad, Duke University; Michael M Barger, Duke University; Lisa Linnenbrink-Garcia, Michigan State University

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Educational Research and Methods

not provide information about the gender or race. Participants were asked tocomplete surveys in class at the beginning (Week 2) and end of the semester (Week 15) to assesstheir thoughts and feelings about engineering. The survey took approximately 15 minutes tocomplete.4.2 MeasuresIn addition to standard demographic variables, we also collected measures of (a) students’ self-assessed ability to achieve the outcomes listed in ABET Criterion 3, (b) situational interest inengineering that emerged as a function of the course, and (c) individual interest in engineering asa profession/discipline. These measures, described in detail below, were highly reliable, withCronbach’s alphas above 0.80.Student Outcomes (ABET Criterion 3). Students rated the

Conference Session

Survey and Assessment Development

Collection

2015 ASEE Annual Conference & Exposition

Authors

Chrystal A. S. Smith, University of South Florida; Hesborn Wao, University of South Florida; Julie P Martin, Clemson University; George T. MacDonald, University of South Florida; Reginald S Lee, University of South Florida; Gladis Kersaint, University of South Florida

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Diversity

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Educational Research and Methods

Methods, 17(4), 331–355.10. Daniulaityte, R. (2004). Making sense of diabetes: Cultural models, gender and individual adjustment to Type 2 diabetes in a Mexican community. Social Science & Medicine (1982), 59(9), 1899–1912.11. Smith, C. A. S. (2011). Living with sugar: Influence of cultural beliefs on type 2 diabetes self-management of English-speaking women. Journal of Immigrant and Minority Health, 14(4), 640-647.12. Ahorlu, C. K., Koram, K. A., & Weiss, M. G. (2007). Children, pregnant women and the culture of malaria in two rural communities of Ghana. Anthropology & Medicine, 14(2), 157-181.13. Lopez, T. M. T., Hoyos, R. C., Salas, J. H. B., & Paredes, J. J. R. (2006). Cultural conceptions about dengue

Conference Session

Professional Skills and the Workplace

Collection

2008 Annual Conference & Exposition

Authors

Ashley Ater Kranov, Center for Teaching, Learning & Technology; Robert Olsen, Washington State University; Carl Hauser, Washington State University; Laura Girardeau, Washington State University

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Educational Research and Methods

instructions thatencouraged students to discuss the implications of the problem and develop approaches toaddress it, rather than immediately develop solutions. After all, practicing engineers mustapproach problems holistically, working as a team to assess data sources, address contextualissues, and communicate with stakeholders before deciding on solutions. “The scenario assignment is not intended to measure a student’s scientific knowledge. Rather, it is a realisticopen-ended task that draws on a student’s critical thinking skills as well as problem formulationand management expertise.”17 See Appendix B for instructions and sample scenarios.The Student DiscussionBefore each of the 45-minute curricular debriefs, a CTLT facilitator informed students

Conference Session

Classroom Engagement

Collection

2009 Annual Conference & Exposition

Authors

Sarah Zappe, Pennsylvania State University; Robert Leicht, Pennsylvania State University; John Messner, Pennsylvania State University; Thomas Litzinger, Pennsylvania State University; Hyeon Woo Lee, Pennsylvania State University

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Educational Research and Methods

purposes. The response rate for this survey was80.2%. A total of 80 students responded to Course Survey 2 and provided consent. Theresponse rate for this survey was 83.3%. Select results from Course Survey 1 are displayed intables below. In addition, Appendix B displays the frequency data and descriptive statistics forthe rating scale items from Course Survey 1. Appendix C displays the frequency data anddescriptive statistics for all items administered during Course Survey 2.How do students use the video lectures?The overwhelming majority of the students reported watching each video that was availableonline. Most students (92%) reported watching the video one time, although many studentsreported reviewing unclear portions of the video. Figure 2

Conference Session

Undergraduate Students' Development of Computational and Programming Skills

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Geoffrey L. Herman, University of Illinois at Urbana-Champaign; Sofia Meyers, University of Illinois at Urbana-Champaign; Sarah-Elizabeth Deshaies, University of Illinois at Urbana-Champaign

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Educational Research and Methods

bring to their early learningexperiences.References[1] L. Kaczmarczyk, E. Petrick, J. P. East, and G. L. Herman, “Identifying studentmisconceptions of programming,” in Proceedings of the Forty-First ACM Technical Symposiumon Computer Science Education, 2010, Conference Proceedings, pp. 107–111.[2] R. Lister, B. Simon, E. Thompson, J. L. Whalley, and C. Prasad, “Not seeing the forestfor the trees: Novice programmers and the solo taxonomy,” in Proceedings of the 11th AnnualSIGCSE Conference on Innovation and Technology in Computer Science Education, ser.ITICSE ’06. New York, NY, USA: Association for Computing Machinery, 2006, p. 118–122.[Online]. Available: https://doi.org/10.1145/1140124.1140157[3] J. D.Bransford, A. L.Brown, and

Conference Session

Practice III: Multimedia Learning

Collection

2018 ASEE Annual Conference & Exposition

Authors

Qi Dunsworth, Penn State Behrend; Yi Wu, Penn State Behrend

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Educational Research and Methods

students to the higher order thinking skills such as analysis, synthesis, and creative problem solving. Simple questions asking students to list facts or identify among given choices will not be very valuable to achieving the goal.4. We recommend review videos to include the must-have features as students elected. In addition to giving control of how they want the video to be played, students should have access to the handouts used by the review video so that they can take their own notes. An example problem should be included at the end of the video to explain to students what they are expected to understand upon a successful review.References[1] B. Honeycutt, “Ready to flip: three ways to hold students accountable for pre-class work

Conference Session

Approaches to Assessment and Student Reflection

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

Tagged Divisions

Educational Research and Methods

situations wecreate, we may find additional paths forward.This paper is organized as follows. In the next section we offer three vignettes to concretize thework. We follow these vignettes with a traditional section devoted to related work. We thendescribe the activities that led to the findings section including (a) the context of the surveydevelopment efforts, (b) specific details of the survey development effort during a four monthperiod, and (c) the processes that led to the findings presented in this paper. Then, afterpresenting the findings, we turn to discussion and implications. MotivationAs part of our work on promoting reflection in engineering education, we have hadconversations with