Conference Session

Conceptual Learning

Collection

2010 Annual Conference & Exposition

Authors

Aidsa Santiago Roman, University of Puerto Rico, Mayagüez; Ruth Streveler, Purdue Universtiy; Paul Steif, Carnegie Mellon University; Louis DiBello, University of Illinois at Chicago

Tagged Divisions

Educational Research and Methods

AC 2010-1674: THE DEVELOPMENT OF A Q-MATRIX FOR THE CONCEPTASSESSMENT TOOL FOR STATICSAidsa Santiago Roman, University of Puerto Rico, Mayagüez Aidsa I. Santiago Román is an Assistant Professor in the Department of Engineering Science and Materials and the Director of the Strategic Engineering Education Development (SEED) Office at the University of Puerto Rico, Mayaguez Campus (UPRM). Dr. Santiago earned a BA (1996) and MS (2000) in Industrial Engineering from UPRM, and Ph.D. (2009) in Engineering Education from Purdue University. Her primary research interest is investigating students’ understanding of difficult concepts in engineering science with underrepresented populations. She also

Conference Session

Works in Progress: Assessment and Research Tools

Collection

2016 ASEE Annual Conference & Exposition

Authors

Cheryl Q. Li, University of New Haven; Ronald S. Harichandran, University of New Haven; Maria-Isabel Carnasciali, University of New Haven; Nadiye O. Erdil, University of New Haven; Jean Nocito-Gobel, University of New Haven

Tagged Divisions

Educational Research and Methods

Paper ID #15139Development of an Instrument to Measure the Entrepreneurial Mindset ofEngineering StudentsDr. Cheryl Q. Li, University of New Haven Cheryl Qing Li joined University of New Haven in the fall of 2011, where she is a Senior Lecturer of the Industrial, System & Multidisciplinary Engineering Department. Li earned her first Ph.D. in me- chanical engineering from National University of Singapore in 1997. She served as Assistant Professor and subsequently Associate Professor in mechatronics engineering at University of Adelaide, Australia, and Nanyang Technological University, Singapore, respectively. In 2006

Conference Session

Concept Inventories and Assessment of Knowledge

Collection

2015 ASEE Annual Conference & Exposition

Authors

Brian Douglas Gane, University of Illinois at Chicago; Dana Denick, National Science Foundation; Natalie Jorion; Louis V DiBello; James W Pellegrino, University of Illinois, Chicago; Ruth A. Streveler, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

evidence that student thinking when completing the task (item) was consistentwith the type of reasoning that developers intended.12 Additionally, we completed two rounds ofdata collection with the full instrument (i.e., all items) and conducted quantitative analyses ofthese larger data sets to assess item and instrument performance.13, 14 These analyses resultshelped us revise items and update the domain model. Finally, we used a Q-matrix to documentthe mapping between item answers (correct and incorrect) with the normative concepts andmisconceptions specified in our evolving domain model.Examples of Redesign ProcessesQ-matrixTo provide more detail, we walk through examples of some of these critical redesign processes.First, one product that

Conference Session

Student Experiences with Undergraduate Research

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Wookwon Lee P.E., Gannon University; Nicholas B. Conklin, Gannon University

Tagged Divisions

Educational Research and Methods

were 3 female and 5 male students; 3 of them were domestic students and 5 of themwere international students. For a total of 40 questions in 10 categories, average scores andstandard deviations were calculated for individual questions and also for each category. The resultsare summarized in Table 1 where the survey categories are labeled by Roman numerals andindividual questions are sequentially labeled with a prefix Q. The average and standard deviationfor “Overall” are for the category. For a comparison between the results from the twoquestionnaires, the averages and standard deviations were presented in two sets of columns,denoted by “Perception” (questionnaire 1) and “Achievement” (questionnaire 2). For intuitive understanding from these

Conference Session

Beyond the Classroom

Collection

2015 ASEE Annual Conference & Exposition

Authors

Denise Rutledge Simmons PE, Virginia Tech; Chosang Tendhar, Virginia Tech; Rongrong Yu, Virginia Tech; Eric A. Vance, Virginia Tech; Catherine T. Amelink, Virginia Tech

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

measure undergraduate engineering students’ decisions toparticipate in out-of-class activities and the students’ outcomes from involvement in theseactivities. Specifically, this paper details the development of the items and face and contentvalidity for the Postsecondary Student Engagement Survey (PosSES).    The instrument development is guided by a thorough literature review, web searches, a Q-studyusing focus group meetings, a panel of experts, and finally, think aloud sessions to determineface and content validity. The instrument measures positive and negative involvement outcomesand factors that promote and prevent participation decisions in out-of-class activities; andengineering identification, sense of belonging, engineering major

Conference Session

Misconceptions

Collection

2013 ASEE Annual Conference & Exposition

Authors

Dana Denick, Purdue University, West Lafayette; Aidsa I. Santiago-Román, University of Puerto Rico, Mayaguez Campus; James W Pellegrino, University of Illinois, Chicago; Ruth A. Streveler, Purdue University, West Lafayette; Louis V DiBello, Universtify of Illinois at Chicago

Tagged Divisions

Educational Research and Methods

Confirmation CE1: Failure to clarify body in equilibrium Q-1,3,17,18,19 Moderate CE2: Failure to treat parts as single system Q-1,3,4,5,14,15, 17,18,19 Weak CE3: Leaving force off FBD Q-1,3,14,15,17,18,19 No Evidence CE4: Including internal force in FBD Q-1,3 Strong CE5: Including non-acting force in FBD Q-1,3 Strong CE6: Failure to account for force pair between separated bodies Q-4,5,7,8 Moderate CE7: Couple between bodies Q-7,8,27 No

Conference Session

Research in Engineering Education II

Collection

2012 ASEE Annual Conference & Exposition

Authors

Dana Denick, Purdue University, West Lafayette; Aidsa I. Santiago-Román, University of Puerto Rico, Mayaguez Campus; Ruth A. Streveler, Purdue University, West Lafayette; Natalie Barrett, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

differing by Page 25.1457.3degree).3 The model is based on a Q-matrix approach in which the Q-matrix is a binaryrepresentation of the underlying cognitive attributes required for correct item responses.5Additionally, the Fusion Model uses residual information from a continuous attribute to uniquelydetermine a student’s probability for correctly performing each task. The Fusion Model employsa Bayesian approach to estimate the model parameters and estimations are made based on aMonte Carlo Markov Chain (MCMC) parameter estimation algorithm. The Fusion Model hasshown promising results when applied to real educational assessment data and in the

Conference Session

ERM Potpourri

Collection

2006 Annual Conference & Exposition

Authors

Nadia Kellam, University of South Carolina; Veronica Addison, University of South Carolina; Michelle Maher, University of South Carolina; Mann Llewellyn, University of Queensland; David Radcliffe, University of Queensland; Walter Peters, University of South Carolina

Tagged Divisions

Educational Research and Methods

e l l e a c h e q u i p

Conference Session

Educational Research & Methods Poster Session

Collection

2010 Annual Conference & Exposition

Authors

Qaiser Malik, Michigan State University; Punya Mishra, MSU; Michael Shanblatt, MSU

Tagged Divisions

Educational Research and Methods

(six per category): standard problems and inferential problems. The problems in both the categories were small and simple; they did not require complicated mathematical formulas or calculator to solve them. a. Standard problems: The standard or textbook type problems were similar to the ones covered during the course in class assignments, home assignments and exams, with minor variations in numerical values and problem setup. Students were given sufficient practice on like problems. Two typical standard problems are given below: Q#25 Find ‘Vout’, as indicated, for the following circuit: Note: A typical voltage-divider-network; students had sufficient

Conference Session

Practice III: Multimedia Learning

Collection

2018 ASEE Annual Conference & Exposition

Authors

John T. Solomon, Tuskegee University; Eric Hamilton, Pepperdine University; Vimal Kumar Viswanathan, San Jose State University; Chitra R. Nayak, Tuskegee University; Firas Akasheh, Tuskegee University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

the student population responded that they are more satisfied with KACIE incomparison to other courses. The other half had the opinion that they are satisfied with KACIEjust like any other course. Finally, nearly all responded that KACIE sheets were useful for betterunderstanding and learning the concepts. TABLE IV STUDENT SURVEY DATA TABLE Completely Somewhat Disagree (%) agree (%) agree (%) Q.1 The supplementary videos provided helped to 50 50 0 understand the course material in better manner Q.2 These videos equipped

Conference Session

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

Collection

2019 ASEE Annual Conference & Exposition

Authors

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

Tagged Divisions

Educational Research and Methods

𝑞 (𝜋𝑎𝑘 + 𝜋𝑏𝑘 )2 𝑎1 𝑏1 𝑎2 𝑏2 𝑝𝑒 = ∑ = ( + )2 + ( + )2 (3) 4 2𝑛 2𝑛 2𝑛 2𝑛 𝑘=1Where q is the number of categories, a corresponds to Rater A and b to Rater B, the subscripts 1and 2 correspond to categories and 𝜋𝑥𝑘 is the probability of Rater x categorizing a subject to thekth category defined as the ratio of number of subjects in category k and total number of subjects.However, this method assumes that the chances of raters randomly assigning an item to samecategory is based on rater’s average distribution for each category which is not

Conference Session

Knowing Ourselves: Research on Engineering Education Researchers

Collection

2011 ASEE Annual Conference & Exposition

Authors

Junaid A. Siddiqui, Purdue University, West Lafayette; Robin S. Adams, Purdue University, West Lafayette; Lorraine N. Fleming, Howard University; Alison A. Dingwall, Howard University

Tagged Divisions

Educational Research and Methods

participants considered themselves to be familiar with these issuesto some extent but not to a level of “very familiar”. Adams et al.7 made a similar observationthat engineering faculty face difficulty with education research because of the differences indisciplinary language and the use of qualitative data in education research. Choosing anappropriate conceptual framework for education research (Q 1.5) was rated the lowest. Thisconforms to Borrego’s13 finding that when learning educational research methods, groundingresearch in a theoretical framework is among the conceptual issues that engineering faculty findless familiar. As Borrego observes, the scientific and engineering theories these faculty use areuniversal and often do not need to be

Conference Session

Trends in Engineering Education 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

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

Tagged Divisions

Educational Research and Methods

regular class session?Q. Are there any courses where these expectations were challenged, in other words, where yourexpectations of your involvement during class were different?Q. When you think about a typical engineering lecture-based course, what expectations do youthink faculty have of you in terms of your involvement in the class session. In other words, whatdo you think faculty expects you to do during a regular class session?Q. Are there any courses where these expectations were challenged, in other words, wherefaculty expectations of your involvement during class were different?Q. How do you respond when a faculty member tries an instructional style that requires yourinvolvement in class, for example, working with a partner or a team to

Conference Session

Knowing our Students, Faculty, and Profession

Collection

2010 Annual Conference & Exposition

Authors

Samantha Brunhaver, Stanford University; Russell Korte, University of Illinois, Urbana-Champaign; Micah Lande, Stanford University; Sheri Sheppard, Stanford University

Tagged Divisions

Educational Research and Methods

CoworkersAs with managers, new engineers at every company reported varying degrees of help from thecoworkers. Many participants said that their coworkers helped them understand what is expectedof them and helped them accomplish their work. Other participants said that their coworkerswere too busy or too new to the work group to provide much help. Q: Did your [coworker] give you this assignment? A: Yes. Q: I assume he gave you background information? A: Yes and no. We both were new to this [name] system, so we pretty much were on the same page in terms of understanding the system. So it was like we both learned it at the same time. I found some information, I talked to him about it, he found some more information

Conference Session

Classroom Practice I: Active and Collaborative Learning

Collection

2016 ASEE Annual Conference & Exposition

Authors

Ray Essick, University of Illinois, Urbana-Champaign; Matthew West, University of Illinois, Urbana-Champaign; Mariana Silva, University of Illinois at Urbana-Champaign; Geoffrey L. Herman, University of Illinois, Urbana-Champaign; Emma Mercier, University of Illinois at Urbana Champaign

Tagged Divisions

Educational Research and Methods

). Collaborative and cooperative learning in higher education: A proposed taxonomy. Cooperative Learning and College Teaching, 2, 2-5.[9] Dillenbourg, P. (1999). What do you mean by collaborative learning. In Collaborative learning: Cognitive and computational approaches (Vol. 1, pp. 1–19). Retrieved from http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:What+do+you+mean+by+’collaborative+l earning'?#0[10] Facer, K. (2014). What is space for? Towards a politics and a language for the human in education. Technology, Pedagogy and Education, 23(1), 121-126. doi:10.1080/1475939X.2013.839229[11] Florman, J. C. (2014). TILE at Iowa: Adoption and Adaptation. New Directions for Teaching and Learning, (137), 77

Conference Session

Efforts to Understand and Support Students' Socioemotional Factors

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Olufunso Oje, Washington State University; Olusola Adesope, Washington State University; Adurangba Victor Oje, University of Georgia

Tagged Divisions

Educational Research and Methods

Hands-on Effect on MotivationAll nine experiments on motivation reported a positive hands-on effect size ranging from0.19 to 0.90. Using the random effect model, the overall mean effect size was moderate andstatistically significant (d = 0.52, p = 0.05), indicating a positive hands-on effect onmotivation. The heterogeneity statistic was highly significant, Q = 15.76, df = 8, p = 0.05.This result shows that the hands-on learning effect had a significant positive impact onstudent motivation. Figure 2 shows the forest plot of the hands-on effect on motivation.Figure 2 Hands-on effect on Motivation (Forest Plot)The Hands-on Effect on Self-EfficacyThirteen out of the 15 experiments on self-efficacy reports a positive hands-on effect sizeranging from

Conference Session

Qualitative Research Methods

Collection

2017 ASEE Annual Conference & Exposition

Authors

Elliot P. Douglas, University of Florida

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

, I’m just, no …Q … So does that …A … So we value a student from Michigan or Georgia Tech or Stanford …Q … Right …A … right? And those are not historically Black …Q … No …A … but if they produce you know, a Black or a Hispanic teacher ….Q … But if you don’t know that an HBCU does not produce such a student, why, I guessmy question is why do you, why is the reaction the same? ….A … Yeah, so was that an inherent bias on my part? Maybe. Because I just, I haven’texplored that, that space yet.Much of his discussion of recruiting focused on standards. Earlier in the interview he saidabout faculty searches,…we need to be color blind and gender blind, at some stage. So for example you set yourcriteria for your

Conference Session

Digital Technologies and Learning

Collection

2011 ASEE Annual Conference & Exposition

Authors

Michael Hergenrader, University of Southern California, Information Sciences Institute; Joanna Drummond, University of Pittsburgh; Jihie Kim, University of Southern California

Tagged Divisions

Educational Research and Methods

tools to assist online dialogue in the context of a discussion board. Page 22.716.1 c American Society for Engineering Education, 2011 F irst Impressions: T he F irst Two Posts and their Influence on the Development of O nline Q uestion-A nswer Discussion T hreads1. IntroductionWith universities nationwide challenged to provide funding for increasing engineering courseenrollment, it seems natural that online courses are becoming more popular1, cutting costs whilestill providing students with a college-level education. The switch to these distance learningenvironments provides not only

Conference Session

Communication and Literacy

Collection

2015 ASEE Annual Conference & Exposition

Authors

Chad M Gotch, Washington State University; Quinn Langfitt, Washington State University; Brian F French, Washington State University; Liv Haselbach, Washington State University

Tagged Divisions

Educational Research and Methods

our energy future. Retrieved from http://www.neefusa.org/pdf/roper/Roper2002.pdf13. Bittle, S., Rochkind, J., & Ott, A. (2009). The energy learning curve. Retrieved from http://www.publicagenda.org/media/the-energy-learning-curve14. Southwell, B. G., Murphy, J. J., DeWaters, J. E., & LeBaron, P. A. (2012). Americans' perceived and actual understanding of energy. (RTI Press peer-reviewed publication No. RR-0018-1208). Research Triangle Park, NC: RTI Press. Retrieved from http://www.rti.org/rtipress15. Langfitt, Q., Haselbach, L., & Hougham, R.J. (2014). Artifact-based energy literacy assessment utilizing rubric scoring. Journal of Professional Issues in Engineering Education and Practice. Retrieved from

Conference Session

Works in Progress: Facilitating Student Success and Inclusion

Collection

2016 ASEE Annual Conference & Exposition

Authors

Julie P. Martin, Clemson University; Samuel S. Newton, Clemson University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

the University and beyond. West Lafayette, IN; 2012:59-85.3. Pawley AL. Drawing the line: Academic engineers negotiating the boundaries of engineering. 2007.4. Pawley AL. Universalized Narratives: Patterns in How Faculty Members Define “Engineering.” J. Eng. Educ. 2009;98(4):309-319. Available at: http://dx.doi.org/10.1002/j.2168-9830.2009.tb01029.x.5. Riley D. Engineering and Social Justice: Synthesis Lectures on Engineering, Technology, and Society #7.6. Mcintosh P. White Privilege : Unpacking the Invisible Knapsack. Cyrus V, ed. Work 1990;49(1988):1-5. Available at: http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:White+Privilege:+Unpacking+the+Invisi ble+Knapsack#0.7. Mcintosh P

Conference Session

Engineering Cultures and Identity

Collection

2016 ASEE Annual Conference & Exposition

Authors

Allison Godwin, Purdue University, West Lafayette

Tagged Topics

ASEE Diversity Committee

Tagged Divisions

Educational Research and Methods

, June 26, 2011 - June 29, 2011. In: ASEE Annual Conference and Exposition, Conference Proceedings. Virginia Tech, United States Department of Civil and Mechanical Engineering, U.S. Military Academy, West Point, United States College of Engineering, University of Notre Dame, United States Department of Engineering Education, United States: American Society for Engineering Education; 2011.4. Tonso KL. On the Outskirts of Engineering: Learning Identity, Gender, and Power via Engineering Practice. Rotterdam, Netherlands: Sense; 2007.5. Jorgenson J. Engineering Selves: Negotiating Gender and Identity in Technical Work. Manag Commun Q. 2002;15(3):350-380. doi:10.1177/0893318902153002.6. Du X-Y. Gendered

Conference Session

ERM Potpourri I

Collection

2007 Annual Conference & Exposition

Authors

Elif Kongar, University of Bridgeport; Tarek Sobh, University of Bridgeport

Tagged Divisions

Educational Research and Methods

students’future success to evaluate the performance criteria fed into the model.To achieve these objectives, the data for all 107 applicants (n = 107) for the Masters of Science(M.S.) in Computer Science program in the School of Engineering for Fall 2004 semester iscollected. According to the office of admissions records, the acceptance rate of the ComputerScience graduate program for the Fall 2004 semester is approximately 34 percent, with 36 accepted,and 71 rejected students.Following data collection, a DEA model to evaluate the relative efficiency of each candidate isemployed with six performance criteria, viz., the Bachelors of Science (B.S.) GPA, TOEFL andGRE Quantitative (-Q) scores, number of years of work experience, number of

Conference Session

Makers, Making, and the Maker Movement

Collection

2017 ASEE Annual Conference & Exposition

Authors

Aditya Johri, George Mason University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

discussion forums, including social question and answer (Q&A) sites, arebecoming increasingly popular for problem-solving and help-asking. Users of these sites askquestions, post responses, or search information from existing threads to satisfy theirinformational needs. One popular use of online discussion forums is to provide help witheducational content [26]. Research shows that online forums are robust platforms for learning 1as they evolve over time and become a rich source of information for participants due to theinterpersonal exchange they. For instance, van De Sande [26] examined an online help forumfor mathematics and found that learners receive general forms of help that orient the

Conference Session

Approaches to Curriculum and Policy

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Afroditi Vennie Filippas, Virginia Commonwealth University; Rebecca Segal, Virginia Commonwealth University ; Alen Docef, Virginia Commonwealth University

Tagged Divisions

Educational Research and Methods

faculty interactions with math facultyOf the faculty who responded to the survey, two had met with mathematics faculty (Q.3). Bothhad attended the special meeting we held in the spring of 2017 and had participated in theclassroom observation opportunity, and one of them had also participated in one-on-onemeetings with math faculty (Q.4). In both cases, these meetings only changed their perceptionson faculty engagement (Q.5). The interaction that was listed as being the most impactful was themeeting/classroom observation, but the one-on-one visits also ranked high on the list (Q.6). Itdoes seem, though, that building in opportunities for faculty socialization and active exchange ofideas is important.Questions 8: Have you provided feedback or input

Conference Session

Motivation, Identity, and Belongingness

Collection

2018 ASEE Annual Conference & Exposition

Authors

Jacqueline Ann Rohde, Purdue University; Lisa Benson, Clemson University; Geoff Potvin, Florida International University; Adam Kirn, University of Nevada, Reno; Allison Godwin, Purdue University, West Lafayette (College of Engineering)

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

pattern was distinguished by the phrase “I feel” as well as the word“just.” The use of “just” seemed to reference an innate feeling the student had about theirattitudes and beliefs, rather than a specific affinity towards some trait such as creativity or actionsuch as problem solving. Students expressed two kinds of emotional responses to belongingness:comfort and enjoyment. An excerpt from Candace’s interview transcript is an example ofstudents’ comfort towards being in engineering. Q: Do you feel like you belong in engineering? Candace: Yes. I don't know, I've just never felt like I wasn't in the right place or I wasn't- I guess I've never felt like I didn't belong, so I don't know why I feel like I do belong, but

Conference Session

Student Recruitment and Retention

Collection

2008 Annual Conference & Exposition

Authors

Elif Kongar, University of Bridgeport; Mahesh Baral, University of Bridgeport; Tarek Sobh, University of Bridgeport

Tagged Divisions

Educational Research and Methods

program in the School of Engineering for Fall 2004 semester iscollected.After reading in the relevant data, a DEA model is employed to evaluate the relative efficiency ofeach candidate using six performance criteria, viz., the Bachelors of Science (B.S.) GPA (BS GPA),TOEFL and GRE Quantitative (GRE-Q) scores, number of years of work experience, number ofundergraduate semesters till B.S. degree completion, and the number of below-B grades in math-related and technical courses in the B.S. degree transcript.4.1 DEA model for the evaluation processFollowing the retrieval of the complete application materials, related data is entered into theapplications database. The office of admissions then sends each applicant a confirmation e-mail withan assigned

Conference Session

ERM Potpourri

Collection

2012 ASEE Annual Conference & Exposition

Authors

Russ Pimmel, University of Alabama; Roger K. Seals, Louisiana State University; Stephanie M. Beard, Louisiana State University

Tagged Divisions

Educational Research and Methods

the presenter summarized the views of a group of NSF ProgramDirectors that were developed earlier through a similar exercise.Each IWBW was divided into two 60-minute segments with a 15-minute break inbetween them. Typically, each segment had about four TPSR activities with a fewshorter ones included to break the routine. The format allotted six minutes for eachTPSR activity. Usually, two Q&A sessions were included in each segment with one inthe middle and one at the end. Since the presenter had no control once a TPSR activitywas initiated and could not react to question or provide guidance, the task statementsneeded to be clear and precise and describe challenging but doable tasks that fit withinthe time constraints. Local facilitators

Conference Session

Trends in Engineering Education 2

Collection

2014 ASEE Annual Conference & Exposition

Authors

Conrad Tucker, Pennsylvania State University, University Park; Kathy Schmidt Jackson, Pennsylvania State University, University Park; Linda C. Schmidt, University of Maryland, College Park; Gül E. Okudan Kremer, Pennsylvania State University, University Park; Peifeng Yin

Tagged Divisions

Educational Research and Methods

large sample size for engineering disciplines.4.2 Data collection instrumentAs part of the data collection, in addition to providing demographic data, students were askedspecific questions pertaining to their future academic aspirations and their preferences towardsdigital/tactile learning. We present the specific questions in Table 3 for EDSGN 100 and Table 4for IE 466.Table 3: EDSGN 100 Survey Questions Pertaining to Virtual/Tactile Preferences Q# Introduction to Engineering Design (EDSGN 100) 1 My knowledge about the environmental impact of a product. 2 I find it useful to be able to virtually manipulate products (using tools like Solid Works/CAD, HTML/Google

Conference Session

Motivation, Goal Orientation, Identity, and Career Aspirations

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Robert M. O'Hara, Clemson University; Lisa Benson, Clemson University; Jennifer Harper Ogle, Clemson University; Candice W. Bolding, Clemson University

Tagged Divisions

Educational Research and Methods

likelihood estimator. Initial descriptive statisticalanalysis was conducted and used to test normality of data. Dependent variables and hypothesizedcovariates showed significant p-values (p>.05) on Shapiro-Wilk test of normality (refer to Table3). This indicated violations of normality in the data; however, large samples are sensitive toviolations of normality (Azen & Walker, 2011; Pituch & Stevens, 2016). As a result, visualinspections of histograms and normality Q-Q plots indicated acceptable normality in the data[36]-[37]. Table 3 Test of normality of data for each survey construct Shapiro-Wilk

Conference Session

Medley of Undergraduate Programming and Pedagogies

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Gretchen A. Dietz, University of Florida; Leann Wishah, University of Florida; Elliot P. Douglas, University of Florida; Erica D. McCray, University of Florida

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

their early experiences leading to the Bridge program. The secondinterview explored their experiences in the Bridge program and their aspirations for their co-op.Interviews were professionally transcribed and pseudonymized.Data were analyzed using a narrative approach that includes multiple readings [19]. Themultistep process included reading for: familiarization with the transcripts, identifying contentsuch as individuals mentioned and major storylines, detecting identity of the participant andothers, and uses of CCW and funds of knowledge. After the readings, a narrative case waswritten for each participant.Quality was considered internally and externally. Internally, we used the Q 3 framework [20],[21] as a reflexive tool to guide each phase