Conference Session

First-Year Programs: Design in the First Year

Collection

2017 ASEE Annual Conference & Exposition

Authors

James Blake Hylton, Ohio Northern University; Todd France, Ohio Northern University; Louis A. DiBerardino III, Ohio Northern University

Tagged Divisions

First-Year Programs

Annual Conference and Exposition.[3] Carberry, A. R., Lee, H.-S., & Ohland, M. W. (2010). Measuring Engineering Design Self-Efficacy. Journal of Engineering Education, (January), 71–79.[4] Daher, T., & Loehring, M. (2016). Shaping the Engineering Freshman Experience through active learning in a Flipped Classroom. In 123rd ASEE Annual Conference and Exposition (pp. 1–10).[5] Estell, J. K., Reeping, D., & Reid, K. “Workshop - Envisioning the First-Year Engineering Body of Knowledge”, Seventh Annual First Year Engineering Experience Conference, August 2-4, 2015.[6] Everett, J. W., Morgan, J. K., Stanzione, J. F., & Mallouk, K. E. (2014). A hybrid flipped first year engineering course. In 6th First Year

Conference Session

Engineering Leadership Skills Development Across the Undergraduate-to-Workforce Transition

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Dena Lang, Pennsylvania State University; Travis Gehr; Meg Handley, Pennsylvania State University; John Jongho Park, Pennsylvania State University; Andrew Michael Erdman, Pennsylvania State University

Tagged Divisions

Engineering Leadership Development

, 2018.Park, J., Lang, D.H., Handley, M.H., & Erdman, A.M. (2019) Developing undergraduates’ self- efficacy for engineering leadership: relations among leadership attributes, teamwork skills, and creativity. Conference Paper and Presentation: American Educational Research Association Annual Conference, Toronto, Canada, 2019.Powell, K. S., & Yalcin, S. (2010). Managerial training effectiveness: A meta-analysis 1952– 2002. Personnel Review, 39, 227–241.Reyes, D.L., Dinh, J, Lacerenza, C.N., Marlow, S.L., Joseph, D.L., and Salas, E. (2019) The state of higher education leadership development program evaluation: A meta-analysis, critical review, and recommendations. The Leadership Quarterly Vol. 30(5

Conference Session

NSF Grantees: Workforce Development (ATE)

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Mathew Kuttolamadom, Texas A&M University; Jyhwen Wang, Texas A&M University; DeDe Griffith, Northwest Louisiana Technical Community College; Cheri Greer, Northwest Louisiana Technical Community College

Tagged Topics

NSF Grantees Poster Session

. Taking guidelines for good evaluation plans [19], the formative andsummative evaluation plan utilizes a comprehensive and widely used CIPP (Context, Input,Process, Product Evaluation) model [20]. Given the relatively small sample size, statisticalanalysis is expected to be largely descriptive, both aggregate and by subgroup, to report onproject implementation and progress toward performance measures. T-tests will be used todetermine significant differences in teachers’ self-efficacy survey responses from pre- to post-test. Qualitative data collected through interviews, product review, and observation, will beanalyzed throughout the project. The outcomes that are being evaluated are briefly outlined:  Institution Outcomes: To strengthen a

Conference Session

Enhancing the Statics Classroom

Collection

2018 ASEE Annual Conference & Exposition

Authors

Kimberly B. Demoret P.E., Florida Institute of Technology; Jennifer Schlegel, Florida Institute of Technology; Matthew J Jensen, Florida Institute of Technology

Tagged Divisions

Mechanics

-copying-texas-tech-2/. [Accessed 30 Jan 2018].[9] A. Williams, "Online homework vs. traditional homework: Statistics anxiety and self- efficacy in an educational statistics course.," Technology Innovations in Statistics Education, vol. 6, no. 1, 2012.[10] V. Berandi, "The impact of using randomized homework values on student learning. The Journal of Effective Teaching. 2011; 11(2): 4-7.," The Journal of Effective Teaching, vol. 11, no. 2, pp. 4-7, 2011.[11] S. Condoor and S. Jayaram, "Learning Statics- A Foundational Approach," in Annual Conference of the American Society of Engineering Education AC 2008-2105, 2008.[12] T. Ji and A. J. Bell, "Seeing and touching structural concepts in class teaching," in The Proceedings of

Conference Session

Addressing Diversity Issues in Engineering Education

Collection

2016 ASEE Annual Conference & Exposition

Authors

Jackie Perez, Texas A&M University - Dwight Look College of Engineering; So Yoon Yoon, Texas A&M University; Teri Kristine Reed, Texas A&M University; Cecelia Diane Lawley, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

Two Year College Division

engineering education research as a psychometrician, program evaluator, and institutional data analyst. As a psychometrician, she revised the PSVT:R for secondary and undergraduate students, developed the TESS (Teaching Engineering Self-efficacy Scale) for K-12 teachers, and rescaled the SASI (Student Attitudinal Success Inventory) for engineering students. As a program evaluator, she evaluated the effects of teacher professional development (TPD) programs on elementary teachers’ attitudes toward engineering and students’ STEM knowledge through a NSF DRK-12 project. As an institutional data analyst, she is investigating engineering students’ diverse pathways to their success.Dr. Teri Reed, Texas A&M University Teri

Conference Session

Modeling and Simulation

Collection

2016 ASEE Annual Conference & Exposition

Authors

Elif Miskioglu, Bucknell University; Kaela M Martin, Embry-Riddle Aeronautical University, Prescott

Tagged Divisions

Computers in Education

instructionalsoftware emphasized lower-level cognitive processes,9 but a larger number report learning gainswhen implementing technology in the classroom through virtual experiments or onlineinstruction.10-13 Additionally, incorporating simulations into the classroom can increasevisualization and problem-solving processes,14,15 as well as show positive gains in student self-efficacy with respect to engineering skills.16Virtual experiments offer an opportunity to provide students with valuable experience at a lowcost (no laboratory space or consumables, only computer facilities, required), high flexibility(can be performed outside of class, does not require direct supervision, safety is not a directconcern), and great breadth (some disciplines may have

Conference Session

Visualization Within Engineering Design Graphics Education Session 2

Collection

2015 ASEE Annual Conference & Exposition

Authors

Michael Johnson, Texas A&M University; So Yoon Yoon, Texas A&M University

Tagged Divisions

Engineering Design Graphics

undergraduate students, developed the TESS (Teaching Engineering Self-efficacy Scale) for K-12 teachers, and rescaled the SASI (Student Attitudi- nal Success Inventory) for engineering students. As a program evaluator, she has evaluated the effects of teacher professional development (TPD) programs on K-6 teachers’ and elementary students’ attitudes to- ward engineering and STEM knowledge. As an institutional data analyst, she is investigating engineering students’ pathways to their success, exploring subgroup variations. Page 26.707.1 c American Society for Engineering Education, 2015

Conference Session

First-year Programs Division Technical Session 10: Paying Attention to Retention

Collection

2015 ASEE Annual Conference & Exposition

Authors

Steffen Peuker, California Polytechnic State University; Nova Alexandria Glinski Schauss, Oregon State University

Tagged Divisions

First-Year Programs

-19 Volume 3, 20023. Veenstra, Cindy P., Dey, Eric L., Herrin, Gary D., "A Model for Freshman Engineering Retention", AEE, Volume 1, Issue 3, Winter 20094. Meyers, Kerry L., Silliman, Stephen, E., Gedde, Natalie, L., Ohland, Matthew, W., "A comparison of engineering students’ reflections on their first year experiences.", J. Engineering Education, April 20105. Hutchison, Mica A., Follman, Deborah K., Sumpter, Melissa, Bodner, George M., "Factors influencing the self- efficacy beliefs of first year engineering students", J. Engineering Education, January 20066. Landis, R. B., "Student Development: An Alternative to 'Sink or Swim'", Proceedings of 1994 ASEE Annual Conference, June 19947. Lotkowski, Veronica A., et al. "The Role of

Conference Session

Data Analysis and Assessment

Collection

2015 ASEE Annual Conference & Exposition

Authors

David B. Knight, Virginia Tech, Department of Engineering Education; Cory Brozina, Virginia Tech; Eric M. Stauffer, Virginia Tech; Chris Frisina, Virginia Tech; Troy D. Abel, Virginia Tech

Tagged Divisions

Computers in Education

is an investigation of how studentsinteract with data or how faculty can use data to change teaching.3 Practices that select relevantdata traces and develop dashboards with learners instead of for learners may lead to strongerstudent self-efficacy, build on existing social learning theory, and benefit from perspectivesfound within human centered design practices.Our interdisciplinary team of faculty and graduate students from engineering education,computer science, human computer interaction, human centered design, learning sciences, andvisual communications are following a mixed-methods, human centered approach to dashboarddevelopment that breaks new ground in learning analytics by involving the end users throughoutthe dashboard design and

Conference Session

NSF Grantees’ Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

Milo Koretsky, Oregon State University; Jana Bouwma-Gearhart, Oregon State University; Shane A. Brown P.E., Oregon State University; Thomas Dick, Oregon State University; Susie J Brubaker-Cole, Oregon State University; Ann Sitomer, Oregon State University; Kathleen Quardokus Fisher, Oregon State University; Julie Risien, Oregon State University ; David L. Little II, Oregon State University; Christina Smith, Oregon State University; john David ivanovitch, Oregon State university

Tagged Topics

NSF Grantees Poster Session

student growth concerning: conceptual learning via concept inventory and Concept Warehouse questions; student measures of interactive engagement and frequent formative assessment viewed through the Interactive, Constructive, Active, and Passive framework (ICAP);15 student social network development related to participation in ICAP activities; and other student outcomes measures (such as content self-efficacy) based on faculty particular interest in students in their classrooms.7. Utilize and facilitate individualized portions of above data collection processes with faculty regarding student growth to inform reflection and change to practice.8. Develop ICAP and social network student instrument mentioned above utilizing established

Conference Session

First-year Programs Division Postcard Session 1: Retention and Student Success Strategies

Collection

2018 ASEE Annual Conference & Exposition

Authors

Suzanne Zurn-Birkhimer, Purdue University, West Lafayette; Mayari I. Serrano, Purdue Polytechnic Institute; Beth M. Holloway, Purdue University, West Lafayette; Rachel Ann Baker, Purdue University, West Lafayette

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

participants’ spatialperception, mental rotation, and spatial visualization skills, both the experimental group and acontrol group will complete the Purdue Spatial Visualization Test (PSVT) before the onlineworkshop, in the middle of the semester, and after completion of the workshop. Results of this pilotstudy will be analyzed to determine the value of offering online spatial reasoning content to allincoming engineering students. It is our hope to understand how to best increase spatial skills forwomen engineering students, and doing so early in their college careers might lead to increasedretention, success, and self-efficacy. This research also aims to expand representation of women inengineering by creating resources that properly address specific

Conference Session

Graphics and Visualization

Collection

2007 Annual Conference & Exposition

Authors

Jianping Yue, Essex County College

Tagged Divisions

Engineering Design Graphics

Educational Research Association, April, Boston, Massachusetts (ERIC Document Reproduction Service No. ED189166.)28. Battista, M. The Interaction between Two Instructional Treatments of Algebraic Structures and Spatial- Visualization Ability. Journal of Educational Research, 74(5), May/June 1981, 337-341.29. Towle, E., et al. Assessing the self efficacy and spatial ability of engineering students from multiple disciplines. 35th ASEE/IEEE Frontiers in Education Conference, October 19-22, 2005, Indianapolis, Indiana.30. Hamlin, A., Boersma, N., & Sorby, S. Do spatial abilities impact the learning of 3-D solid modeling software? Proceedings of the 2006 ASEE Annual Conference & Exposition, June 18-21, Chicago

Conference Session

Technological Literacy - Courses, Educational and Accreditation Standards

Collection

2010 Annual Conference & Exposition

Authors

Yoojung Chae, Purdue University; Senay Purzer, Purdue University; Monica Cardella, Purdue University

Tagged Divisions

Technological Literacy Constituent Committee

their learning experienceas and how to promote students' learning who show giftedness in the Engineering and Technology areas.Senay Purzer, Purdue University Senay Purzer is an Assistant Professor in the School of Engineering Education at Purdue University. She is also the Co-Director of Assessment Research for the Institute for P-12 Engineering Research and Learning (INSPIRE). She received a Ph.D. and a M.A in Science Education, Department of Curriculum and Instruction from Arizona State University. Her creative research focuses on collaborative learning, design & decision-making, and the role of engineering self-efficacy on student achievement.Monica Cardella, Purdue University

Conference Session

Writing and Communication I

Collection

2004 Annual Conference

Authors

Roberta Harvey

#### 1. Affective: how we feel, our engagement, including values, self-esteem, and self-efficacy 2. Conative: what we do, our action, including skills and aptitudes, pace or “tempo” of learning, and degree of desire for autonomy or for social interaction 3. Cognitive: what we think, our understanding, including multiple intelligences, internal reflection, level of abstraction, and prior experience7Learners experience these three dimensions through four patterns of mental processes, each ofwhich engages affect, conation, and cognition in distinct ways. The extent to which a learnerexhibits each of the four patterns is captured in an instrument called the Learning ConnectionsInventory (formerly the Learning Combination Inventory) or

Conference Session

FPD III: Innovation in Design in the First Year

Collection

2012 ASEE Annual Conference & Exposition

Authors

Ann Saterbak, Rice University; Mark Embree, Rice University; Maria Oden, Rice University

Tagged Divisions

First-Year Programs

with many common tools andbecome more familiar with the OEDK and its resources. During the prototyping phase of ENGI120, the fabrication mentors offer office hours in the OEDK to help the design teams constructand test their prototypes.Assessment of ENGI 120 ProgramStudent SurveysAssessment was conducted at the end of the semester. In the survey, student perception onimprovements in skills, including engineering design, problem-solving, technical writing, andteamwork was probed. Student’s self-efficacy toward engineering and their decision-makingregarding an engineering major were also probed. The authors recognize that these data are self-reported, and may not reflect actual improvement in skills.The students’ perceptions of how they are

Conference Session

New Trends in ECE Education II

Collection

2012 ASEE Annual Conference & Exposition

Authors

Craig J. Scott, Morgan State University; Petronella A. James, Morgan State University; Yacob Astatke, Morgan State University; Jumoke O. Ladeji-Osias, Morgan State University

Tagged Divisions

Electrical and Computer

2.0. Thispolicy is a minimal attempt to identify those students that may not possess the proper study skillsor self-efficacy traits, needed to master an online course offering. Figure 4 depicts the average ofthe final course grades received by all the online courses and the complementing non-web basedsections. The average scores are notably higher for the online sections. 4 3.61 3.47 3.49 GPA 3.5 N=109 N=777 N=886 3 WEB

Conference Session

Biomedical Engineering Division (BED) Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Casey Jane Ankeny, Northwestern University; David P O'Neill, Northwestern University; Ken Gentry, Northwestern University; Philippa Eshun, Northwestern University

Tagged Divisions

Biomedical Engineering Division (BED)

surveys versus “reflection while doing” in the form of notebooks. Although thestudy was not definitive, these reflective notebooks may promote increased achievement earlierin the quarter. Further, the students viewed the reflective practice favorably.To increase student engagement with the SBG system, we implemented a co-creation processwith the rubric [15]. The use of co-created rubrics is an inclusive teaching practice that canimprove confidence and self-efficacy [5]. It speeds up future detailed feedback, as the studentsand instructors have a similar understanding about the elements of the rubric and may enhanceself-regulated learning [5]. In our course, proficiency in the standards was evaluated accordingto the co-created rubric (as shown in

Conference Session

Student Engagement in Construction Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Hariharan Naganathan, Wentworth Institute of Technology; John Cribbs Ph.D., Wentworth Institute of Technology

Tagged Topics

Diversity

Tagged Divisions

Construction Engineering Division (CONST)

benchmarks. It details an XRframework that can be implemented by CM institutions that follow ACCE accreditation as part oftheir student learning outcomes and program objectives.XR in Construction EducationExtended Reality (XR) technologies, such as virtual reality (VR), augmented reality (AR), andmixed reality (MR), can provide significant benefits in the field of construction education. Theyhelp improve understanding of AEC subdisciplines, enhance the visualization of complexconcepts, and increase student engagement and self-efficacy [6]. XR is particularly useful forsafety training and risk management, with VR being the most used tool [7]. Integrating deeplearning and XR technologies in construction engineering and management presents

Conference Session

Understanding Engineering Design

Collection

2005 Annual Conference

Authors

Penny Hirsch; Ann McKenna

Conference & Exposition Copyright © 2005, American Society for Engineering Educationconfidence, how that element can be related to the learning goals of EDC, and whether ourfreshman design course increases students’ confidence.Many researchers have focused on the role of confidence and motivation on learning. Forexample, Hynd and coworkers explain that persistence and effort are outcomes of motivatinginfluences such as “self efficacy, interest, a desire for good grades and a belief that theinformation is relevant and useful” (p. 55)2. Hynd and coworkers argue that, in order to supportlearning at the conceptual change level, students should be encouraged to engage in reflectionabout the role of their self-perceptions in

Conference Session

Transfer issues between 2-year colleges and 4-year Engineering and Engineering Technology programs 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Heather Dillon, University of Washington; EC Cline, University of Washington Tacoma; Emese Hadnagy, University of Washington Tacoma ; Sarah L Rodriguez, Virginia Polytechnic Institute and State University; Amanda K Sesko, University of Washington Tacoma; Rebecca N Sliger, Tacoma Community College; Noelle Wilson

Tagged Topics

Diversity

Tagged Divisions

Two-Year College Division (TYCD)

Lents, N. H., 2016, “Cultivating Minority Scientists: Undergraduate Research Increases Self-Efficacy and Career Ambitions for Underrepresented Students in STEM,” J. Res. Sci. Teach.[8] Watkins-Lewis, K. M., Dillon, H. E., Sliger, R., Becker, B., Cline, E. C., Greengrove, C., James, P. A., Kitali, A., and Scarcella, A., 2023, “Work In Progress: Multiple Mentor Model for Cross-Institutional Collaboration and Undergraduate Research,” American Society for Engineering Education, Baltimore MD.[9] Lopatto, D., Hauser, C., Jones, C. J., Paetkau, D., Chandrasekaran, V., Dunbar, D., MacKinnon, C., Stamm, J., Alvarez, C., Barnard, D., Bedard, J. E. J., Bednarski, A. E., Bhalla, S., Braverman, J. M., Burg, M

Conference Session

Pedagogy and Learning 1

Collection

2014 ASEE Annual Conference & Exposition

Authors

Nancy K. Lape, Harvey Mudd College; Rachel Levy, Harvey Mudd College; Darryl H. Yong, Harvey Mudd College; Karl A. Haushalter, Harvey Mudd College; Rebecca Eddy, Cobblestone Applied Research & Evaluation, Inc.; Nancy Hankel, Cobblestone Applied Research & Evaluation, Inc.

Tagged Divisions

Educational Research and Methods

of each course were administered a pretest and posttest attitude survey. The surveycontained selected items from three established instruments: Research on the Integrated ScienceCurriculum (RISC), Motivated Strategies for Learning Questionnaire (MSLQ), and the STEMQuestionnaires developed by the STEM team at the Higher Education Research Institute (HERI).The pretest survey contained nine items from RISC and the remaining items were from theMSLQ (18 items). The posttest contained the same items but added an additional 27 (for a totalof 54) survey items from the HERI questionnaires. The survey items used from the MSLQcontained constructs for self-efficacy for learning, metacognitive self-regulation, peer learning,and help seeking. The survey

Conference Session

First-Year Programs Division (FYP) - Technical Session 8: Skill Building

Collection

2023 ASEE Annual Conference & Exposition

Authors

Samantha Yanosko; Grant Valentine; Matthew W. Liberatore, The University of Toledo

Tagged Divisions

First-Year Programs Division (FYP)

. 11[6] AIChE. "Spreadsheet related resources as part of the AIChE Academy." https://www.aiche.org/academy/search/spreadsheet (accessed July, 2020).[7] K. Stratvert. "Kevin Stratvert Master Technology YouTube channel." https://www.youtube.com/@KevinStratvert (accessed January, 2023).[8] L. Gharani. "Leila Gharani Advance Your Career YouTube Channel." https://www.youtube.com/@LeilaGharani (accessed January, 2023).[9] M. D. Miller, Minds Online: Teaching Effectively with Technology. Harvard University Press, 2014.[10] A. Singh, V. Bhadauria, A. Jain, and A. Gurung, "Role of gender, self-efficacy, anxiety and testing formats in learning spreadsheets," Computers in Human Behavior, vol. 29, no. 3

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

is also regarded as acomplex repository of knowledge and skills for planning, implementing, monitoring, evaluating,and continually improving the learning process. Self-regulated learning has been studied over morethan two decades in general classroom settings and various assessment methods exist in theliterature. It is commonly agreed that self-regulation is a good predictor of student’s academicsuccess. For instance, relationships were examined in [1] among motivational orientation, self-regulated learning, and classroom academic performance, and their regression analyses revealedthat self-regulation, self-efficacy, and test anxiety emerged as the best predictors of performance. In recent years, studies on SRL have been extended to

Conference Session

ABET Accreditation, Assessment and Program Improvement in ECE.

Collection

2013 ASEE Annual Conference & Exposition

Authors

Mark William Redekopp, University of Southern California; Gisele Ragusa, University of Southern California

Tagged Divisions

Electrical and Computer

California (USC). She is jointly appointed in the Viterbi School of Engineering’s Division of Engineering Education and the Rossier School of Education. Her research interests and areas of expertise include: engineering education, STEM college access, teacher education and retention, literacy education, content literacy, special education and deaf education as well as assessment and measurement in STEM education. She teaches courses in sci- ence education, measurement, literacy and language development, courses in learning and instructional theory, and teacher education research courses. She extensive expertise in assessment, psychometrics, advanced quantitative analyses, and multimodal research design

Conference Session

Environmental Engineering Division (ENVIRON) Technical Session 1 - Sustainability & Environmental Justice

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jeffrey M. Bielicki, The Ohio State University; Yun-Han Weng, The Ohio State University; Emily T. Creamer, The Ohio State University; Matthew Judkins Mayhew, The Ohio State University

Tagged Topics

Diversity

Tagged Divisions

Environmental Engineering Division (ENVIRON)

widespread adoption ofsustainable, decarbonized energy systems. The goals of the Ohio State EmPOWERmentProgram were developed by twelve faculty in departments across six colleges within theuniversity, in consultation with external stakeholders who work in industry, U.S. nationallaboratories, and non-profit organizations. These stakeholders are ensconced in various aspectsof the field of sustainable energy. Together, this process identified important attitudes,experiences, and core competencies necessary to support three-overarching program goals: 1. Prepare a diverse cohort of versatile graduates with the innovation capacity, self-efficacy, and collaborative capacity to influence positive change in the transition to environmentally

Conference Session

ELOS Technical Session 3 - Diversity

Collection

2024 ASEE Annual Conference & Exposition

Authors

Blessing Isoyiza Adeika, Morgan State University; Adedayo Ariyibi, Morgan State University; Pelumi Olaitan Abiodun, Morgan State University; Oludare Adegbola Owolabi P.E., Morgan State University

Tagged Divisions

Experimentation and Laboratory-Oriented Studies Division (DELOS)

effectively.After identifying these concepts, experiments utilizing electronic instruments are developed andimplemented. The Motivated Strategies for Learning Questionnaire (MSLQ) was used to assesskey constructs related to student success, such as motivation, epistemic and perceptual curiosity,and self-efficacy [34], [35]. Student success was determined by the academic performance ofstudents who received ECP doses in different classes and across the gender spectrum.Furthermore, the fundamentals of ECP and the classroom observation protocol are implementedto effectively integrate ECP into the Biology Discipline.Student participation in ECP was evaluated using the Classroom Observation Protocol forUndergraduate STEM(COPUS), developed by Smith et al. [36

Conference Session

Minorities in Engineering Division Technical Session 6

Collection

2022 ASEE Annual Conference & Exposition

Authors

Amy Walker, University of Texas at Dallas; Laura Gelles, University of Texas at Dallas

research suggests that engineering students do not leave solely because they are notperforming well academically [4], [6], [10] and that historically marginalized populations inengineering leave at higher rates [11]–[13]. Geisinger and Raman found six broad factors thatinfluence retention or attrition including: grades and conceptual understanding, student self-efficacy and confidence, interest and career goals, identity, and climate [3]. They found that overhalf of the studies they explored in their extensive literature review mentioned climate as a factorfor students’ leaving engineering programs.Climate includes the attitudes, perceptions, and expectations associated with an institution andcan be informed by interactions with individuals within

Conference Session

Insights and Practices for Engineering Leadership Development

Collection

2017 ASEE Annual Conference & Exposition

Authors

Ricky T. Castles, East Carolina University

Tagged Divisions

Engineering Leadership Development Division

microprocessors course. Pre and post data on students’ self-assessment of theircollaborative behaviors, ability to work with others to achieve a common purpose, ability tomaintain positive working relationships while respectfully disagreeing, ability to divide labor,fostering of a positive work environment, self-efficacy and reflection, approaching work withhonesty and integrity, commitment to task completion, empathy and understanding of others,along with self-assessment of their work to achieve technical competency are presented.Observations from a recorded hands-on lab period are also presented to categorize the behaviorsobserved by studentsThe following sections survey the literature on leadership skills necessary for success inengineering, discuss

Conference Session

First-Year Programs Division Technical Session 6: Design and Design Chanllenges

Collection

2016 ASEE Annual Conference & Exposition

Authors

Haolin Zhu, Arizona State University; Benjamin Emery Mertz, Arizona State University

Tagged Divisions

First-Year Programs

apply what they learn immediately in the context of the project. Theseelements of just-in-time learning and increased emphasis on a “discipline project” level projectbased learning strategy were added to the course in an attempt to increase student motivation toapply these fundamental design concepts in a manner that would improve their ability to applythem and transfer this knowledge into other contexts14-16.To assess the effectiveness of these changes, the students’ knowledge of the design processneeds to be evaluated. Different instruments are available in the literature to assess differentaspects of the engineering design process. For example, Carberry et al.17 developed aninstrument to measure engineering design self-efficacy. McKenna and

Conference Session

K-12 Professional Development II

Collection

2013 ASEE Annual Conference & Exposition

Authors

So Yoon Yoon, INSPIRE, Purdue University, West Lafayette; Yi Kong, Purdue University, West Lafayette; Heidi A. Diefes-Dux, Purdue University, West Lafayette; Johannes Strobel, Purdue University, West Lafayette

Tagged Divisions

K-12 & Pre-College Engineering

and contexts of TPD by analyzing teachers’ responses to theschools and staffing survey (SASS). Garet et al. (2001)7 identified the features that influencedthe effectiveness of TPD based on teachers’ responses from a teacher activity survey. Lowden(2005)14 evaluated TPD and its impact on teacher change by applying a designed survey.Posnanski (2002)15 analyzed the TPD model that was developed by Haney, Czerniak, and Lumpe(1996)16 and elementary science teachers’ self-efficacy beliefs based on the data collected froman evaluation form and a survey that included open-ended questions.C. Previous Studies about Teachers’ Evaluations of Engineering TPDFor TPD in engineering, only a few studies have investigated the evaluations of TPD fromteachers