Conference Session

K-12 & Pre-College Engineering Division: Evaluation: Impact of Curriculum for PreK-12 Engineering Education

Collection

2016 ASEE Annual Conference & Exposition

Authors

Joseph E. Michaelis, University of Wisconsin - Madison; Mitchell Nathan, University of Wisconsin - Madison

Tagged Divisions

Pre-College Engineering Education Division

Paper ID #16242Observing and Measuring Interest Development Among High School Stu-dents in an Out-of-School Robotics CompetitionJoseph E. Michaelis, University of Wisconsin - Madison Joseph E Michaelis is a Ph.D. student in Educational Psychology in the Learning Sciences area at the University of Wisconsin - Madison. His research involves studying interest in STEM education, focusing on the impact of learning environments, feedback, and influence of social constructs and identities. This research includes developing inclusive learning environments that promote interest in pursuing STEM fields as a career to a broad range

Conference Session

Measuring the Impact of Community Engagement on Students

Collection

2015 ASEE Annual Conference & Exposition

Authors

Matthew Siniawski, Loyola Marymount University; Sandra G. Luca, Loyola Marymount University; Jeremy S. Pal, Loyola Marymount University; Jose A. Saez, Loyola Marymount University

Tagged Topics

Diversity

Tagged Divisions

Community Engagement Division

StudentsAbstractFirst-year engineering students at Loyola Marymount University (LMU), a primarily liberal artsprivate undergraduate institution, can participate in service-learning projects through anengineering living-learning community. In addition, service-learning projects were recentlyoffered at LMU for first-year engineering students not participating in this living-learningcommunity. The impact of service-learning on students’ engineering design self-efficacy andengineering learning outcomes were assessed. An instrument was adapted from a combination ofpreviously validated instruments that measure engineering design self-efficacy and interventionalimpacts on technical and professional engineering learning outcomes. The instrument alsoincludes a

Conference Session

Computers in Education Division Technical Session 4: Digital Learning Part II

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Fadi Castronovo, California State University, East Bay; Jesus Oliver Ph.D., California State University, East Bay; Andrew Stanciulescu, California State University, East Bay

Tagged Divisions

Computers in Education

utilizingseveral validated questionnaire instruments. The total number of questions for the instrumentwas 20, 8 for self-efficacy, 3 for task attraction, 4 for perceived usefulness, 3 for user-experience,and 2 for effort regulation. The instrument was administered at the end of the differenttreatments. In addition to the following questions, the research team asked the participants fordemographic information such as age, grade point average, gender, and current year of study. The questions that measured the students’ self-efficacy, perceived usefulness, and effortregulation were based on the instrument developed by Boekaerts ​[26]​ titled the OnLineMotivation Questionnaires. These instruments included questions such as: “​How do you feel justafter

Conference Session

Mentoring Graduate Students, Diversity, and Assessment

Collection

2010 Annual Conference & Exposition

Authors

Stephen Thompson, University of South Carolina; Joy Watson, University of South Carolina; Jed Lyons, University of South Carolina

Tagged Divisions

Graduate Studies

been widely used to measurethe Science teaching efficacy of various teacher groups. A modified version of the STEBI-B wasused in this study. STEBI-B pre and post-study results (25-item survey) were obtained for 23GK-12 Fellows (13 in 2007-8 and 10 in 2008-9). Pre and post focus group data were alsoanalyzed using qualitative data analysis techniques. The STEBI-B contains two subscales.Personal Science Teaching Efficacy (PSTE) which captures the construct of self-efficacy andScience Teaching Outcome Expectancy (STOE) which measures outcome expectancy regardingScience teaching and learning. A dependent t-test, using an alpha of .05, was computed for thetwo subscales to determine if there was a significant difference between the mean scores for

Conference Session

NSF Grantees Poster Session

Collection

2017 ASEE Annual Conference & Exposition

Authors

Kristi J. Shryock, Texas A&M University; Jeffrey E. Froyd, Texas A&M University

Tagged Topics

NSF Grantees Poster Session

in the project: identification and self-efficacy. Further,it presents results responses from approximately 2,000 first-year engineering students at a largepublic institution. The paper addresses two questions: 1) How do engineering students respond totwo scales related to identity frameworks; and 2) What has been learned by giving these twoscales to first-year engineering students.IntroductionThe importance of increasing the number and diversity of B.S. graduates with degrees in science,technology, engineering, and mathematics (STEM) has been highlighted in several nationalreports1,2 . Increasing retention of students, including retention of students traditionallyunderrepresented in engineering is one approach to addressing this challenge

Conference Session

Addressing Diversity Issues in Engineering Education

Collection

2016 ASEE Annual Conference & Exposition

Authors

Anna Marbella Camacho, Cañada College; Denise Hum, Cañada College

Tagged Topics

Diversity

Tagged Divisions

Two Year College Division

capability to complete specific tasks or goals) a self-efficacy instrument was administered as part of the pre- and post-program surveys. Studentswere asked 18 of the 34 question Mathematics Self Efficacy Scale developed by Nancy Betz andGail Hackett to measure student self-efficacy related to math both at the very beginning of MathJam and again on the last day of the program. The questions related to math tasks that studentsmight encounter in day-to-day life. The analysis of the responses is shown in Table 8. Overall,students in STEM math classes increased their math self-efficacy. It is important that studentsbelieve in their capacity to complete math tasks because “there is evidence linking STEMattrition to such attitudinal factors as motivation

Conference Session

Issues of Persistence in Engineering

Collection

2009 Annual Conference & Exposition

Authors

Matthew Ohland, Purdue University; Michelle Camacho, University of San Diego; Richard Layton, Rose-Hulman Institute of Technology; Russell Long, Purdue University; Susan Lord, University of San Diego; Mara Wasburn, Purdue University

Tagged Divisions

Women in Engineering

the female populations tend to have lower eight-semester persistence rates forthe same six-year graduation rate. Men, conversely, will derive self-efficacy from a diverse set ofachievements, including simply passing their classes. Attributing failures to the professor, badluck, or other sources bolsters the self-efficacy of men at times beyond reasonable limits,resulting in their languishing in degree programs and, at times, exhausting their options. We willcontinue our work to test this hypothesis by examining the populations with high eight-semesterpersistence rates but low six-year graduation rates to determine if they do indeed have feweroptions available to them when they leave engineering as measured by their academic standing attheir

Conference Session

Graduate Student Writing and Communication

Collection

2019 ASEE Annual Conference & Exposition

Authors

Juan M. Cruz, Virginia Tech; Mayra S. Artiles , Virginia Tech; Holly M. Matusovich, Virginia Tech; Gwen Lee-Thomas, Quality Measures LLC; Stephanie G. Adams, Old Dominion University

Tagged Topics

Diversity

Tagged Divisions

Graduate Studies

intended to imply a degree of severity or sequential progression. The first obstacle categorywas the task of writing the dissertation. Students facing this obstacle were commonly in the veryfinal stages and described experiencing ‘writer’s block’ or inability in expressing their researchresults in writing. The second category was students who believed they lacked motivation.These students expressed a lack of self-efficacy in being able to commit to the work necessary tocomplete the degree. They described often procrastinating because they no longer wanted toconduct the research (or related activities), and in more advanced cases, inability to communicateclearly with the doctoral advisor. The third category was students that struggled in

Conference Session

Industrial Engineering Division Technical Session 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Behin Elahi, Indiana University Purdue University, Fort Wayne

Tagged Divisions

Industrial Engineering

factors and found the best setting forfactor level which results in higher yield. In the second project, they were asked to determine apotential optimized structure of 3D-printed material to be used for future space suits. Theydesigned different structures and analyzed the fabric strength versus fabric shape and structureusing tensile test. The uniqueness of this project learning paper is the key findings from the studyand the associated survey. They demonstrate that the project-based learning approach improvesthe students’ attitudes towards engineering, results in higher-order cognitive learning, booststheir self-efficacy, enhances learning through high retention of the learning material and thesubject matter, strengthens team working and

Conference Session

Continuing Professional Development Division (CPD) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mary Grace Golden, Purdue University ; Emeline Anne Ojeda-Hecht, Purdue University ; Savannah Meier, Purdue University ; Eric Holloway, Purdue University; Jennifer S. Linvill, Purdue University

Tagged Topics

Diversity

Tagged Divisions

Continuing, Professional, and Online Education Division (CPOED)

careerdevelopment, was founded by Robert Lent, Steven Brown, and Gail Hackett [21]. The theory isbased on Bandura’s general social cognitive theory and self-efficacy theory [22], [23]. Bandura[24] describes self-efficacy as dependent on four main factors: personal performanceaccomplishments, vicarious learning, social persuasion, and physiological and affective states.SCCT draws on Bandura’s theories to argue that interests develop from outcomes expectationsand self-efficacy and acknowledges the dynamic nature of interests and expectations asindividuals have new experiences [25]. SCCT is often utilized to understand “why people chooseand persist in their career paths” [26, p. 4]. Additionally, SCCT considers both environmentaland individual factors that

Conference Session

Pre-college Engineering Education Division Poster Session

Collection

2017 ASEE Annual Conference & Exposition

Authors

Alison K. Polasik, The Ohio State University; Alexandria Julius, The Ohio State University

Tagged Divisions

Pre-College Engineering Education Division

Moderate or Considerable 0.50 Communicative Interactions - SEC Moderate or Considerable 0.00 0.00 1.00 2.00 3.00 4.00 Journal Average Coded ScoreFigure 3: Comparison of SEC scores and Journal scores. SEC scores are calculated both as average (circle data points) andthe number moderate or considerable (X data points). The measurements are compared for procedural knowledge (blue) andcommunicative interactions (orange)In the 2016 – 2017 school year, the same tools are being used to measure teachers’ use of hands-onactivities and self-efficacy. In addition, focus

Conference Session

Examining "Big" Data

Collection

2015 ASEE Annual Conference & Exposition

Authors

Issam Wajih Damaj, American University of Kuwait; Ashley Ater Kranov, Washington State University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

Paper ID #12549A Framework for Measuring the Sustainability of Academic Programs in theTechnical Fields: Initial Validity Study FindingsDr. Issam Wajih Damaj, American University of Kuwait Dr. Issam W. Damaj (Ph.D. M.Eng. B.Eng.) is an Associate Professor of Computer Engineering at the American University of Kuwait (AUK). He is the Chairperson of the Department of Electrical and Computer Engineering. His University service experience is focused around assessment, quality assur- ance, program development, accreditation, and institutional effectiveness. His research interests include hardware/software co-design

Conference Session

Mental Health of Graduate Students

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Sarah Jane Bork, University of Michigan; Joi-lynn Mondisa, University of Michigan

Tagged Topics

Diversity

Tagged Divisions

Graduate Studies

literature points to aspects of the student’s social environment, such as feelings ofconnectedness, a sense of belonging, social self-efficacy, and social support, influencingstudents’ reported mental health measures in addition to lasting academic impacts. It is stillunclear, however, to the extent which of these concepts are present in current surveys used toassess graduate student mental health. The research question guiding this study is, Whatunderlying factors are important when looking at the mental health of science, engineering, andmathematics graduate students?This study will look specifically at the Healthy Minds Study (HMS), conducted by the HealthyMinds Network (HMN): Research on Adolescent and Young Adult Mental Health group, to tryand

Conference Session

Pathways to Success in STEM through Computer Science and Making

Collection

2016 ASEE Annual Conference & Exposition

Authors

Alicia Nicki Washington, Winthrop University; Shaefny Grays, North Carolina State University ; Sudipta Dasmohapatra, North Carolina State University

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering

Computer Science Education. 6. Goode, J. 2008. Computer science segregation: Missed opportunities. The Voice. 4(2). 7. Graham, J. M., & Caso, R. (2002). Measuring engineering freshman attitudes and perceptions of their first year academic experience: The continuing development of two assessment instruments. In the Proceedings of the 32nd Annual Frontiers in Education Conference. 8. Gushue, G.V. and Whitson, M.L. (2006). The relationship among support, ethnic identity, career decisions and self-efficacy, and outcome expectations in African-American high school students. Journal of Career Development, 33(2), 112-124. 9. Hilpert, J. C., Stump, G., & Husman, J. (2010). Pittsburgh engineering

Conference Session

The Best of Computers in Education Division (COED)

Collection

2024 ASEE Annual Conference & Exposition

Authors

Phyllis J. Beck, Mississippi State University; Mahnas Jean Mohammadi-Aragh, Mississippi State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

formative times in their computing education [6, 8]. There have been many attempts at developing novel approaches to support various aspects of programming metacognition, improve self-efficacy, and provide automated feedback and assessment for students in introductory programming courses [5, 6, 8]. Programming metacognition can be broadly defined as how students think about programming and the problem-solving strategies they employ to achieve a goal when given a programming task [9]. However, most of these methods have yet to be successfully scaled and applied in the classroom. Previous studies suffer from issues such as being too small, difficult to validate or replicate, and software that is not shared or is abandoned

Conference Session

WIED: Support for All in the WIED Community

Collection

2022 ASEE Annual Conference & Exposition

Authors

Ilknur Aydin; Mary Villani, State University of New York, College of Technology at Farmingdale; Lisa Cullington, State University of New York, College of Technology at Farmingdale

primarily occur at residential colleges and can span from a few days in length toseveral weeks in the summer before students’ first year [10]. Programs that focused on students’academic skills and academic self-efficacy have contributed to their effectiveness [11].Despite the struggling enrollment and retention of women in computer science bachelor's degreeprograms, much of the research on summer bridge programs focus on STEM majors in general.Authors of [12] identified several factors that impacted enrollment, retention and success ofminority students and women specifically in computer science majors. These included studentsreporting less information regarding computer science degrees before starting college andwomen computer science majors

Conference Session

Pre-College: Organizing Instruction Around a Theme

Collection

2017 ASEE Annual Conference & Exposition

Authors

Kristin Kelly Frady, Clemson University; Ikenna Q. Ezealah, Clemson University; Christopher Ciuca, SAE International; Meghan M. Stoyanoff, SAE International

Tagged Divisions

Pre-College Engineering Education Division

quantified attitude and motivationintegrating frameworks of self-efficacy theories with outcome expectancy theories. Self-efficacyis social cognitive approach with roots in self-determination theory and describes a person’sperception or beliefs about their capabilities to produce effects (Bandura, 1986). This is closelytied with outcome expectancy which is a person’s expectations about the consequences of anaction (or outcome of a task). The combination of these frameworks, in the context of STEMeducation, have been shown to influence motivation and persistence in an academic track(Unfried, Faber, Stanhope, & Wiebe, 2015). However; in order to situate student attitudes,interests, and experiences within a larger career context, the social

Conference Session

NSF Grantees Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Holly M Golecki, University of Illinois Urbana-Champaign; Karin Jensen, University of Michigan; Karen T. Klebbe, Centennial High School, Champaign IL; Thomas Tran, University of Chicago; Elizabeth Ann McNeela, University of Illinois Urbana-Champaign

Tagged Topics

NSF Grantees Poster Session

a pathway to recruit students to robotics and engineering careers.IntroductionPre-college robotics programs are common precursors to majoring in engineering [1]. However,gender disparities persist across engineering disciplines. The fact that girls do not participate inpre-college robotics at the same rate as boys has been proposed as a bottleneck for girls enrollingin engineering majors [2]. When girls are not part of extracurricular robotics programs, they missvital opportunities to develop tinkering self-efficacy and join engineering majors includingmechanical and electrical engineering [3]. Alternatively, bioengineering and biomedicalengineering (BME) programs graduate ~40% women students each year [4]. Diversity in BME iswell studied

Conference Session

First-Year Programs Division Technical Session 7: Retention & Success

Collection

2024 ASEE Annual Conference & Exposition

Authors

Navid Yaghoubisharif, Oregon State University; Shane A. Brown P.E., Oregon State University; Natasha Mallette P.E., Oregon State University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs Division (FYP)

influencing the self‐efficacy beliefs of first‐year engineering students,” J. Eng. Educ., vol. 95, no. 1, pp. 39–47, 2006.[2] M. W. Ohland, S. D. Sheppard, G. Lichtenstein, O. Eris, D. Chachra, and R. A. Layton, “Persistence, engagement, and migration in engineering programs,” J. Eng. Educ., vol. 97, no. 3, pp. 259–278, 2008.[3] J. J. Appleton, S. L. Christenson, D. Kim, and A. L. Reschly, “Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument,” J. Sch. Psychol., vol. 44, no. 5, pp. 427–445, 2006.[4] J. L. Meece, P. C. Blumenfeld, and R. H. Hoyle, “Students’ goal orientations and cognitive engagement in classroom activities.,” J. Educ. Psychol., vol. 80, no. 4, p. 514, 1988.[5] R

Conference Session

Analysis of Feedback Loops, Understanding the Impact of a LSAMP Scholar Program, Sustainable and Equitable Infrastructure, and Indigenous Innovators

Collection

2023 ASEE Annual Conference & Exposition

Authors

Martha Lucia Cano-Morales, Rowan University; Michael Corey Weinberg; Eduardo Rodriguez Mejia; Juan M. Cruz, Rowan University; Gwen Lee-Thomas, Quality Measures, LLC; Holly M. Matusovich, Virginia Tech; Mayra S. Artiles, Arizona State University; Abimelec Mercado Rivera, Arizona State University; Stephanie G. Adams, University of Texas at Dallas

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering Division(MIND)

of the relationship between the student and the student’s advisor andthe support received from this advisor. Some of these factors are productivity, self-efficacy, andcommitment. The second category, Student experience, grouped the factors related to theExpectancy Value Theory [8], such as the perceived cost, the intrinsic and extrinsic motivation,and the sense of belonging. The Faculty-Student interaction refers to factors that come from thefaculty professors, besides the advisor. The latter category includes factors such as receivingadvice, mentorship, or special attention from a professor. Finally, the academic support categoryincluded factors that are related to the institution, for example, participation in research projectspreviously

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

Articles which did not focus on McConnell and Dickerson (2017) Engineering undergraduate engineering students consider student arguments about or undergraduate engineering subject the function of external structures matter. on animals for survival. The subjects are fourth-grade students. Examine Process Articles which examined the process Purzer (2011) studied student rather than of argumentation, rather than the arguments, self-efficacy and Product products of argumentation (e.g. a individual student achievements. writing

Conference Session

Track 5: Technical Session 2: Revisiting Assessment Tools Used to Measure the Impact of Summer Program Interventions on Perceptions and Interest in Engineering Among Underrepresented Pre-College Students – A Work in Progress

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Zeynep Ambarkutuk, Virginia Polytechnic Institute and State University; Jesika Monet McDaniel, Virginia Tech Department of Engineering Education; Cynthia Hampton Ph.D., Virginia Polytechnic Institute and State University; Kim Lester, Virginia Polytechnic Institute and State University

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

as theSTEM-CIS (STEM Career Interest Survey) [15] tool measures self-efficacy and interest inSTEM classes and careers. The surveys included a pre-survey before arriving on campus, asurvey at the end of week 1 and week 2 to capture feedback on specific activities, and a post-survey at the end of BETA. All surveys were available via QR code for mobile devices. Thepost-surveys include whether students found material in the individual program sessions relevantto their goals, contained new knowledge, and presented in a learning-conducive way. The surveyof activities spanned departments in engineering [16].Additionally, we conducted pre- and post-camp focus groups. These focus groups involvedmeeting with a groups of 12-15 students in a room

Conference Session

Minorities in Engineering Division Technical Session 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Mayra S. Artiles Ph.D., Arizona State University; Juan M. Cruz, Rowan University; Sarah Anne Blackowski, Virginia Polytechnic Institute and State University; Holly M. Matusovich, Virginia Polytechnic Institute and State University; Stephanie G. Adams, University of Texas at Dallas; Gwen Lee-Thomas, Quality Measures LLC

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering

Attrition: Lessons from Four Departments. The Journal of Higher Education, 76(6), 669–700. https://doi.org/10.1080/00221546.2005.11772304Holbrook, A., Shaw, K., Scevak, J., Bourke, S., Cantwell, R., & Budd, J. (2014). PhD candidate expectations: Exploring mismatch with experience. International Journal of Doctoral Studies, 9, 329–346.Holloway-Friesen, H. (2019). The Role of Mentoring on Hispanic Graduate Students’ Sense of Belonging and Academic Self-Efficacy. Journal of Hispanic Higher Education, 153819271882371. https://doi.org/10.1177/1538192718823716Jaeger, A. J., Mitchall, A., O’Meara, K. A., Grantham, A., Zhang, J., Eliason, J., & Cowdery, K. (2017). Push and pull: The influence of race

Conference Session

First-Year Programs Division Technical Session 2A: Using Alternative Measurements to Look at Students and Their Success

Collection

2016 ASEE Annual Conference & Exposition

Authors

Mark Schar, Stanford University; Angela Harris, Stanford University; Robert J. Witt, University of Wisconsin - Madison; Robert Rice, University of California - Merced; Sheri Sheppard, Stanford University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

) and have shown that self-expansion can have many benefits includingsharing of resources and greater self confidence. We call this “closeness,” and have used Aron’sscale to measure student closeness to “others” in the engineering classroom – Professor, TA, LabGroup, Classroom and Friend. A total of 571 complete observations were obtained at threeuniversity locations among students enrolled in the local equivalent course, Introduction to SolidMechanics or Statics. Classroom sizes varied from Large (~400 students) to Medium (125-150students) to Small (75-90 students).Results show that closeness plays an important role in classroom performance, particularly incombination with mechanics self-efficacy (or personal confidence in your mechanics

Conference Session

First-Year Programs Division Technical Session 9: Evaluating and Measuring Recruiting and Major Selection Strategies

Collection

2016 ASEE Annual Conference & Exposition

Authors

Juan David Ortega, Universidad EAFIT, Medellin - Purdue University, West Lafayette; S. Zahra Atiq, Purdue University, West Lafayette; Hector Enrique Rodriguez-Simmonds, Purdue University, West Lafayette

Tagged Divisions

First-Year Programs

Major? A Qualitative Study of Values and Expectations    1. Introduction    Decision making is a complex phenomenon which has been studied by researchers in variousfields like sociology, psychology, and neurology1. In STEM education, student decision makingis often linked to persistence. Hence, theories like the Social Cognitive Theory (SCT)2,3 andMotivation theory4 are often employed to investigate students’ decision to enroll in a certainmajor. Such studies repeatedly discuss ideas like interest, values, and expectations as factors thatdrive student decision making process.Bandura classifies expectations into performance (self-efficacy) and outcome expectations2. Inturn, outcome expectations comprise anticipation of physical (e.g. monetary

Conference Session

First-Year Programs Division Technical Session 2A: Using Alternative Measurements to Look at Students and Their Success

Collection

2016 ASEE Annual Conference & Exposition

Authors

Jack Bringardner, New York University; Christopher Leslie, New York University; Gunter W. Georgi, New York University; Alyssa Marie D'Apice, New York University

Tagged Divisions

First-Year Programs

primary motivator for emphasizing teamwork in the classroom. It has been shown thatteamwork assignments can increase self-efficacy for most students.5 Improving student efficacyis a critical component to success in education as well as success in industry. A number ofmethods for improving student self-confidence in succeeding have been tested. Two commontechniques that have been implemented in first-year engineering courses are a teamwork trainingsession and the use of teamwork agreements. Teamwork training, seminars, or orientationsattempt to provide students without teamwork experience the knowledge necessary to practiceteam skills. Teamwork agreements, charters, or contracts are used to provide the guidelines thatwould exist in the

Conference Session

First-Year Programs Division Technical Session 8: Ways to Measure "Things" About Your Course(s)

Collection

2016 ASEE Annual Conference & Exposition

Authors

Lilianny Virguez, Virginia Tech; Kenneth Reid, Virginia Tech; Tamara Knott, Virginia Tech

Tagged Divisions

First-Year Programs

a desirable trend1,2. Specifically, a study involving one cohort of first-yearengineering students from a large public university showed that first-year engineering students’expectancy-related beliefs, including expectations for success in engineering and self-efficacy inengineering, as well as value related beliefs, including identification with engineering, interest, cost, andutility value decreased over their first year for both male and female students. Within this population,male students reported a higher level of expectation for success than female students; higher expectationfor success tended to predict a higher academic performance over the first year3.Engineering programs have seen a wave of revisions in their first-year programs

Conference Session

First-Year Programs Division Technical Session 2A: Using Alternative Measurements to Look at Students and Their Success

Collection

2016 ASEE Annual Conference & Exposition

Authors

Nora Honken, University of Cincinnati; Patricia A Ralston, University of Louisville; Thomas Tretter, University of Louisville

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

impacted by his/her competency, self-efficacy, andtheir perceived level of control over the task31. Weiner32 states that expectancy will be lower ifthe individual’s perceived ability is low or his/her perceived difficulty of the task is high. Healso states that if an individual assumes that conditions will remain the same and that his pastsuccess was due to ability, he will anticipate success in another similar task. Since manystudents measure success by GPA, first semester GPA was used as a measure of expectancy inthe current study. Further support for using GPA to measure expectancy is given in the literaturereview section.Value Value is related to the incentive or gain from doing or completing a task31. Eccles andWigfield31 list four

Conference Session

Best of Computers in Education Division

Collection

2012 ASEE Annual Conference & Exposition

Authors

Autar Kaw, University of South Florida; Ali Yalcin, University of South Florida; Gwen Lee-Thomas, Old Dominion University and Quality Measures, LLC; Duc T. Nguyen, Old Dominion University; Melinda R. Hess; James A. Eison, University of South Florida; Ram Pendyala, Arizona State University; Glen H. Besterfield, University of South Florida; Corina M. Owens, Battelle Memorial Institute

Tagged Divisions

Computers in Education

p=0.44 After N=29, µ=3.0, σ 2 =0.7 The statistical results of the UASQ prototype study also revealed that overall students’learning styles, self-efficacy, pre-requisite grades, number of attempts, and time duration withUASQs did not have a significant relationship to the students’ UASQ scores. This is possibly apositive outcome of the UASQ environment because regardless of the students pre-coursedisposition, they can be successful with demonstrating knowledge of SLE if they have unlimitedaccess and time with UASQs. Focus groups and surveys exploring the experience with the UASQs also were conducted.Overall, the students indicated that they really enjoyed working with UASQs for several reasons. • UASQs

Conference Session

Technical Session IV

Collection

2018 FYEE Conference

Authors

Christopher McComb, Pennsylvania State University, University Park; Catherine G.P. Berdanier, Pennsylvania State University, University Park; Jessica Dolores Menold, Pennsylvania State University, University Park

Tagged Topics

Diversity, FYEE Conference Sessions

], [16] and scales have beendeveloped in a myriad of fields. With respect to engineering design in particular, Carberry, Lee,and Ohland [17] validated a scale for design self-efficacy that measures student’s self-efficacy,motivation, outcome expectancy, and anxiety across the breadth of activities involved in thedesign process. The correlation between skill and self-efficacy in first-year engineering designcourses is typically studied outside of an assessment context; however, we posit that self-efficacymeasures embedded within open-ended design challenges can add insight into the developmentof students’ skills, both as perceived by the students and as assessed by engineering instructors.To investigate this proposition, this paper presents an