of social responsibility. Resultsshowed that, irrespective of the weighting system, volunteerism had poor to moderate correlationwith social responsibility attitudes. Looking specifically at the eight dimensions of the PSRDM,the strongest correlations existed between volunteerism and how engineering students weightedthe costs and benefits of volunteering and how they saw their professional obligation to helpothers as engineers or through their profession; though these had only weak correlations (0.3).BackgroundEngaging in volunteer activities has been shown to be very beneficial to students, not only intheir development of personal values and self-efficacy, but also having positive effects onacademic performance measures1. When tied to
J. E. Pizzolato, P. Chaudhari, E. D. Murrell, S. Podobnik, and Z. Schaeffer, “Ethnic Identity, Epistemological Development, and Academic Achievement in Underrepresented Students,” Journal of College Student Development, vol. 49, no. 4, pp. 301–318, 2008.18 J. E. Pizzolato, “Assessing self-authorship,” New Directions for Teaching and Learning, vol. 2007, no. 109, pp. 31–42, 2007.19 Masi, Barbara, “Impact on Freshman Design Experiences on Self-Efficacy in Engineering,” in the Proceedings of the 2009 ASEE Annual Conference, Session 2314. Austin, TX. Jun-2009.AppendixA1. Course content and structure Fall 2013 and 2014 Style Fall 2013 Style
using an online testing toolthey developed. They found there was no significant differences in performance, howeverstudents spent more time on the online test.Other studies have found some differences in on-line versus paper exams. Deutsch, Herrmann,Frese, and Sandholzer4 found gender differences in students taking online exams. These genderdifferences were attributed to differences in computer-self efficacy, but they found thedifferences were reduced considerably after students had a single experience taking an onlineexam. McDonald5 considered score equivalence between paper and computer-based assessmentsand concluded that individual differences in computer experience, computer anxiety, andcomputer attitudes could impact the potential of some
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
-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
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
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
Village, ILL: American Academy of Pedriatrics.[6] Seligman, M.E., “The Optimistic Child: A proven program to safeguard children against depression and buildlifelong resilience”, Mariner Books, 2007, ISBN: 978-0618918096[7] Seligman, M.E., “Learned Optimism: How to change your mind and your life”, Vintage, 2006, ISBN: 978-1400078394[8] Lopez, S. & Snyder, C.R., “The OxfordHandbook of Positive Psychology”, Oxford University Press, 2 nd edition 2009[18] Carver, C., Scheier, Mi., Miller, C. and Furlford, D.; "Optimism"; Lopez, S. & Snyder, C.R. (Eds.), TheOxford Handbook of Positive Psychology, Oxford University Press, 2nd edition 2009[21] Maddux, James E., "Self-Efficacy: The Power of Believeing you Can", Lopez, S. & Snyder, C.R. (Eds
implementation. In addition, exposingstudents to more challenging concepts, more productive brainstorming process and developingcooperative learning skills are also under investigation.Bibliography1. T. D. Fantz, T. J. Siller and M. A. DeMiranda, “Pre-collegiate factors influencing the self-efficacy of engineering students,” J. of Engineering Education, July 2011, vol. 100. No. 3, pp. 604-623.2. N. S. Salzman, G. D. Ricco, and M. W. Ohland, (2014), “Pre-college engineering participation among first-year engineering students”,Proc. of the 2014 American Society for Engineering Education Annual Conference, Indianapolis, IN, June 15-18.3. I. Jormanainen, Supporting Teachers Unpredictable Robotics Learning Environment, Dissertation in Forestry and
undergraduates. Economics Education Review 29: 935-946, 2010.6. Shotton, H.J., Oosahwe, E., Cintron, R. Stories of success: experiences of American Indian Page 26.1640.12 students in a peer-mentoring retention program. Rev higher Educ 31(1): 81-107, 2007.7. Amelink, C.T., Creamer, E.G., Gender differences in elements of the undergraduate experience that influence satisfaction with the engineeirng major and the intent to pursue engineering as a career. Journal Engineering Education 99(1): 81-92, 2010.8. Concannon, J.P., Barrow, L.H. A reanalysis of engineering majors' self-efficacy beliefs. J Science Education
math self-efficacy).In all cases, KA was used as a supplemental resource in a blended learning model. Blendedlearning as a term emerged in 19993 and refers to the blending of "text-based asynchronousInternet technology with face-to-face learning,"4 where the primary role of ICT is tocomplement student learning as opposed to replace face-to-face time.5 One form of blendedlearning that is becoming increasingly common in tertiary science and engineering educationis the combined use of Flipped Classroom (FC) and Just-in-Time Teaching (JiTT). FC refersto a teaching structure where students receive their first exposure to the subject material priorto class so that class time can be freed up to work with the material, which is the reverse orderto
Education, 369-387.9) Molitor, S.C., Kaderavek, J.N., Dao, H., Liber, N.J., Rotshtein, R., Milewski, G., & Czerniak, C.M. (2014). Engineering Teaching Behaviors in PK-3 classrooms. Proceedings of the ASEE Annual Conference and Exposition, June 2014, Indianapolis, IN.10) Yoon Yoon, S., Evans, M.G., & Strobel, J. (2012). Development of the Teaching Engineering Self-Efficacy Scale (TESS) For K-12 Teachers. Proceedings of the ASEE Annual Conference and Exposition, June 2012, San Antonio, TX.11) Wang, H.-H., Moore, T. J., Roehrig, G. H., & Park, M. S. (2011). STEM integration: The impact of professional development on teacher perception and practice. Journal of Pre-College Engineering Education Research, 1(2), 1-13.12
in the PreK-12 setting was acceleratedwith the release of A Framework for K-12 Science Education: Practices, Crosscutting Conceptand Core Ideas and the subsequent standards document, The Next Generation ScienceStandards.1,7,8 Engineering is still, however, a recent and complex challenge for teachers, Page 26.592.3particularly those at the elementary level, who often lack self confidence and self efficacy withregard to teaching engineering.1,2 Teachers’ self confidence in a subject is linked to both howthey perceive it and their knowledge of the subject itself.19 Elementary teachers receive little tono training in engineering in either pre
motivating modern learners indicates that it is important to enable“the millennials” to overcome anxiety and believe that they can learn content and achieve theoutcomes; they must build self-efficacy and take responsibility for their own learning.According to Pryce, some of the best ways to motivate the millennial student are through guidedpractice, repeated and distributed practice, and early and frequent “low stakes formativeassessment with developmental feedback, as well as repeated and distributed practice built intothe course structure.”10 Thus, the development of appropriate class components and assessmentsis essential, especially for a course aimed at first-year students. The assessments must: 1) beperceived as both relevant and valuable to
attitudesurveys completed during the same time frame also showed positive outcomes, supporting thenotion of high self-efficacy. Briefly, with respect to the SVM, the majority of students (n=149)agreed with statements concerning value (94%), interest (62%), and cost (78%). According tothe BSS survey, all engagement strategies were favorable with opinions of the pencaststatistically higher than the rest of the interventions (0.9/1, n=132 students) and the flippedclassroom statistically lower than the other interventions (0.69/1, n=132 students). In terms ofachievement, pre-instruction data of the concept quiz yielded a score of 44% (n=82) for Fall2014 and post-instructions scores were 75% for Spring 2014 (n=33) and 76% for Fall 2014(n=49). Analysis of the
Education, pp. 267-274, July 2002.4. R. Talbert, “Learning MATLAB in the Inverted Classroom,” Proceedings of the ASEE Conference, San Antonio, TX (2012).5. K. M. Kecskemety, B. Morin, “Student Perceptions of Inverted Classroom Benefits in a First-Year Engineering Course,” Proceedings of the ASEE Conference, Indianapolis, IN (2014).6. M. Stickel, S. Hari, Q. Liu, “The Effect of the Inverted Classroom Teaching Approach on Student/Faculty Interaction and Students’ Self-Efficacy,” Proceedings of the ASEE Conference, Indianapolis, IN (2014). Page 26.1698.127. N. K. Lape, R.L. Levy, D. H. Yong, K. A. Haushalter, R. Eddy, N
, 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.Dr. Monica M Cortez, Texas A&M University Monica M. Cortez, Ph.D., is the Director of the Texas A&M Engineering Academy and Workforce De- velopment Programs at Texas A&M University. She received her Ph.D. and M.S
. First, our participants, all of whom were persisting inengineering majors at the time of this study, expressed high levels of self-efficacy, and self-identified as someone who seizes opportunities and combats self-doubt with a fierce work ethic.We call this type of student an “active agent.” Second, emerging across all domain categorieswas a strong sense of responsibility toward kin, and community and support from theseoftentimes-nontraditional sources. In identifying and analyzing these two seeminglycontradictory characteristics – strong individual drive and interdependent, relational orientation –we hope to inform diversity advocates in engineering about the unique attributes that helpstudents from low socioeconomic standpoints persist and
studentswith a higher probability of failure) reduce attrition through improving self-efficacy and skilllevel in mathematics. Moses et al.6, in an article devoted to math readiness and personality, stressthe need to examine math readiness to in order to improve retention of first-year students. Thisstudy consisted of participation from 129 freshman engineering majors, and used logisticregression as a means of evaluating the data. Moreover, research in engineering education has indicated that pre-university assessment of“student readiness” might be used to inform best practices in teaching first-year engineeringcourses. A substantial portion of the literature considered in this paper was devoted to theevaluation of mathematical and other pre
STAR Legacy cycle11 which guidesstudents through six phases entitled The Challenge (problem definition), Generate Ideas(brainstorming), Multiple Perspectives (open inquiry), Research and Revise (guided inquiry,lecture, textbook), Test Your Mettle (formative assessment), and Go Public (summativeassessment, presentation).A decision was made to use CBI as the framework for the development and implementation ofthe fourth year curriculum for the outreach program. The decision was based on the previoussuccess of integrating projects into the curriculum in the TexPREP program and studies showingpositive results, especially in self-efficacy and adaptive expertise12, associated with theimplementation of CBI. The development of four courses using CBI
modified from severalvalidated instruments related to the 21st Century Skills listed above 33, 34. In addition to 21stCentury Skills, student engagement and self- efficacy were also measured. This instrument,developed by researchers at Georgia Tech for this project, included forty-five items on a 5-pointLikert-type rating scale (e.g., ranging from “Strongly Agree” to Strongly Disagree”), with aCronbach’s α of 0.91, and internal consistency for each of the five scales ranging from 0.84 to0.95. Engineering design portfolio assessment. In addition to affective data, studentachievement data were collected using an engineering design portfolio assessment (EDPA). Foreach project, students used a digital log to document their progress through the
research interests are engineering self-efficacy, creativity, and decision making.Dr. Kevin Andrew Richards, Northern Illinois University K. Andrew R. Richards is currently a visiting assistant professor at Northern Illinois University. Prior to his current post, Richards was a post-doctoral research associate with the Center for Instructional Ex- cellence at Purdue University, USA. His post-doctoral position focused on the evaluation of a large-scale course transformation project that sought to increase active learning and student-centered pedagogies in university-level teaching. Prior to post-doctoral studies, Richards completed his Master’s degree and PhD at Purdue University, and Bachelor’s degree at Springfield
because it is linked to student success and persistence in STEM degrees30,33–39.Students’ self-efficacy in mathematics and science is also related to student success andpersistence in STEM degrees10,20,35,37,40–42.MethodsSelf-Determination TheoryI used Ryan and Deci’s self-determination theory of motivation as the theoretical framework formy study. Self-determination theory takes into consideration intrinsic and extrinsicmotivations43–46. ANSEP makes public the extrinsic motives they provide to their high schoolstudents, such as scholarships, to motivate them to complete advanced mathematics and sciencecourses19. Due to ANSEP’s high levels of success at motivating high school students to takeadvanced mathematics and science course19,21,22, ANSEP
women’sprofessional outcome expectations using the same data.22 They found, after controlling forstudents’ demographic and academic background characteristics, pre-college self-efficacy andself-confidence, learning experience, academic and social contextual influence, and fourth yearself-confidence, participation in the living learning program positively influenced students’overall professional outcome expectation, as well as achieving career success and combining aprofessional career with having a balanced personal life.To sum, these studies reported positive influences of LLC on student engagement, connectionwith engineering programs, and career expectations. The LLC involvement affects studentdevelopment through interactions with peers and faculty and the
choosing betweenchoice of 4b. Connect modules to boost self-efficacy in an 4b. Students identifymajor engineering with engineering skill area engineering skills students' personal 4c. Mentors talk about their own they enjoy or have values majors and process of choosing learned 4c. Introduce students 4c. Student can to faculty in their explain the societal potential majors value of their
, “Effects of process-oriented worked examples on troubleshooting transfer performance,” Learn. Instr., vol. 16, no. 2, pp. 154–164, Apr. 2006.[6] M. Ward and J. Sweller, “Structuring effective worked examples,” Cogn. Instr., vol. 7, no. 1, pp. 1–39, 1990.[7] K. J. Crippen and B. L. Earl, “The impact of web-based worked examples and self-explanation on performance, problem solving, and self-efficacy,” Comput. Educ., vol. 49, no. 3, pp. 809–821, Nov. 2007.[8] A. Renkl, R. Stark, H. Gruber, and H. Mandl, “Learning from worked-out examples: The effects of example variability and elicited self-explanations,” Contemp. Educ. Psychol., vol. 23, no. 1, pp. 90–108, Jan. 1998.[9] B. M. Mclaren, S. Lim, and K. R. Koedinger
were two questionnaires administered in fall 2012, spring2013, fall 2013, and spring 2014: one for the Current pathway scholars and one for the potentialtransfer students who attended Shadow Day (the Anticipating students). Both questionnairesassessed demographic information and information regarding their choice and feelings forchoosing engineering as a career. The questionnaires also assessed any hurdles they expect toface by transferring to LSU or continuing in the program. The responses to these questions werecompared between the two groups to determine potential effects of actually transferring to LSU.The results from the self-efficacy questions suggests that anticipating students rated this more Table 4. The cumulative GPA’s for
autonomy. The learner can stop,rewind, and replay a screencast as many times as she wants and move with her own pace. Shecan watch the screencast at any location and time on a world-wide-web browser that can be on apersonal computer, a tablet, or a smart phone. The initial learning is fast since students do not Page 26.737.3spend time in interpreting the steps and avoid the laborious trial-and-error process. Since astudent learns by observing the desired behavior of an expert on the screencast, it aids learnerswith low self-efficacy in exploring the demonstrated behaviors1. Teaching how to use CAD software with the screencasts has additional
. Educational areas of interest are self- efficacy and persistence in engineering and development of an interest in STEM topics in K-12 students.Dr. Chris Geiger, Florida Gulf Coast University Chris Geiger is an Associate Professor and Chair of the Department of Bioengineering in the U.A.Whitaker College of Engineering at Florida Gulf Coast University. He received his M.S and Ph.D.degrees in Biomedical Engineering from Northwestern University in 1999 and 2003, respectively,and his B.S. in Chemical Engineering from Northwestern University in 1996. Page 26.799.1 c American Society for
Paper ID #13326Go Team! The Role of the Study Group in Academic SuccessDr. Denise Wilson, University of Washington Denise Wilson is a professor of electrical engineering at the University of Washington, Seattle. Her research interests in engineering education focus on the role of self-efficacy, belonging, and other non- cognitive aspects of the student experience on engagement, success, and persistence.Dr. Cheryl Allendoerfer, University of Washington Dr. Allendoerfer is a Research Scientist in the College of Engineering at the University of Washington.Prof. Rebecca A Bates, Minnesota State University, Mankato