making. 1 The SCCT model posits thatperson-centered variables of domain-specific self-efficacy coupled with interests and realisticoutcome expectations about the field propel individuals to pursue particular careers. Careerchoice is further influenced by a combination of supportive and inhibiting contextual factors.Supportive factors associated with pursuing computing include: early exposure, access to highquality learning experiences, supportive parents, and peer groups.2, 3 Inhibiting factors includelimited access, subtle and not-so-subtle racism and sexism, geographic location, and lower socio-economic status.3, 4 Importantly, SCCT incorporates gender and race/ethnicity explicitly in its model, whichrenders it appropriate for work with
. Three research questions are asked:RQ1: How does student STEM SC relate to their design performance in parametricbuilding design? In this study, “design performance” refers to the ability of students to generatesolutions that have good performance in quantitative metrics such as low energy usage. Previousresearch shows that student self-efficacy and performance are positively related both outside ofSTEM [11] and in STEM [12]. However, this study evaluates performance specifically in abuilding design exercise with quantitative goals that are simulated within a parametric designtool. This relationship can reflect potential student effectiveness in technical building design, butit does not fully reflect student behavior. The extent of their
IntroductionThere is substantial evidence that most K-12 science and math teachers who aim to incorporateengineering design processes into their courses acquire these skills through extracurricularprofessional development (PD) programs or self-directed learning [1-4]. Research has shownthat PD programs are valuable in increasing teachers' engineering self-efficacy and thelikelihood of implementing engineering processes in the classroom [5-7]. These programs offerflexibility in introducing engineering design to teachers in diverse formats (e.g., in-person versusvirtual) [8], using various theoretical frameworks [9]. They often provide participation incentivessuch as stipends [9, 10]. However, despite the value of these PD programs, teachers areusually
, social responsibility, ethics, and diversity. c American Society for Engineering Education, 2018 Perceived Importance of Leadership in their Future Careers Relative to Other Foundational, Technical and Professional Skills among Senior Civil Engineering StudentsAbstractMany demands are placed on undergraduate students to possess a broad range of foundational,technical, and professional knowledge and skills when they graduate. Expectancy value theory(EVT) indicates that students will be more motivated to learn topics that they believe will beimportant in their future, due to utility value. Self-efficacy beliefs also contribute to learning.Given this framework, the research
. Page 12.1080.7Table 1 Factor Questions Asked Dreaming to get Did you think you were going to be admitted in the UPRM? admission to engineering Did people talk about the UPRM when you were in High School? Did you have any doubts about completing the application Self-efficacy beliefs Do you think you were good in math? What came to your mind when you completed your college application? In which IE specialty area you see yourself working? Cultural biases and
-Year EngineeringIt is critical that first-year engineering programs have a plan to assess the objectives and outcomes.Continuous improvement will allow a program to make adjustments along the way to meet theirobjectives and outcomes for students. Recently, Spurzer, Douglas, Folkerts, and Williams (2017)developed an assessment framework for the first-year introduction to engineering courses whichfocuses on student-learning objectives. While this is much needed, there is an opportunity toexpand beyond assessing only student-learning objectives to include student-growth objectives(e.g., motivation, identity, self-efficacy, integration). The term student-growth objective is coinedfrom the ever-expanding research and instruments used to measure
, which focuses on a start-of-semester half-day training.MethodsTo understand the main challenges faced by CS GTAs and to inform the development of atraining program that makes the most effective use of limited resources (specifically funding,GTA time, and instructor time), the CS department surveyed GTAs, as well as instructors whosecourses were supported by GTAs, at the end of the Fall 2020 semester. GTAs were asked whatskills they view as most important to their success in fulfilling their responsibilities and theirperceived level of preparation/skill for those responsibilities. GTAs’ perceived level ofpreparation provides a window into their teaching self-efficacy, which can be measured overtime to track teaching development [1]. GTAs were
, practical abilityand intuition about physical phenomenon remain important. In fact, the NAE cites “practicalingenuity” as one of the key attributes of the engineer of 20201. Because students today are lesslikely to have grown up in rural communities than their predecessors, they have probably hadfewer opportunities to tinker. Instead of fixing the family tractor or the hay bailer, theengineering students of today and tomorrow will have lived a cocooned virtual life of videogames and online chat forums. While facility with computers is advantageous, our curricula donot provide adequate opportunities for many students to overcome this tinkering deficit. Moreimportantly, there is some evidence that low self-efficacy with respect to tinkering may even
an issue not only with competency,but also with a lack of self-efficacy in math, science, and engineering which creates anxiety. According to Beck-Winchatz and Riccobono (2007), the majority of students with VI arefollowing general education curricula. However, less than 30 individuals with VI earned ascience and engineering research doctorate on average each year from 2001 to 2009 compared to25,600 people without a disability on average per year during the same time period (NSF, 2012).Lack of higher level degrees in the science and engineering fields do not reflect the fact thatstudents with VI have the same spectrum of cognitive abilities as sighted peers (Kumar,Ramasamy, & Stefanich, 2001) and with appropriate accommodations can
. Theinitiative was assessed by participant engagement with the topics and qualitative journalresponses to the discussion prompts.Our effort for this project consists of two main goals: Goal 1: To encourage female students to remain in STEM fields through supportivedialogue. Goal 2: To promote collaboration, self-efficacy and leadership while providing strategiesfor females to change the culture.Each of these goals are in line with new ABET criteria focused on educating the “wholeengineer.” To measure our progress toward these goals, we have begun to capture studentengagement via qualitative journal responses. In the future, we plan an additional survey and alimited number of interviews about the project. Journal data is derived from
they are capable of achievement in a given learningsituation, as expressed on the MLSQ); and control-of-learning beliefs (a student’s belief that acourse’s content is indeed learnable at all, also expressed on the MLSQ).Our quantitative evidence of the relationship between students’ intrinsic and extrinsicmotivations and the three measures of perception of competence can be seen in Figure 5. Acrossthe 432 survey respondents whose scores were complete enough to characterize, there was astatistically significant relationship between intrinsic goal orientation and writing apprehension,self-efficacy for learning, and control-of-learning beliefs, which can be modeled as a linearcorrelation. There was also a statistically significant linear
“grit”, self-determination and social cognitive careertheories are used to explore self-efficacy, goal orientation and perception of institutionalculture as mediators of academic achievement. A significant part of this paper analyzesresponses to interventions designed to support retention of students lacking the mathbackground to “hit the ground running” upon entering a large, public predominantlywhite institution (PWI)’s college of engineering, with a disproportionate number ofminorities in the underprepared category. Targeted retention interventions for first yearstudents yielded statistically significant improvement in math course progression,particularly for minority students. Overall attrition decreased by 10% in two successiveyears
this data is quite timely, because this course isunique among offerings across the country. The pre-service teachers in the class represented avariety of backgrounds, but generally displayed lower self-efficacy than engineering students oftheir age. The general lack of understanding of such students with regards to engineering,including the differences and similarities among the various STEM disciplines as well as theirown feelings of fear and/or inadequacy when faced with problem solving tasks may represent asignificant barrier to the potential recruiting success of future engineering students. This paperwill describe the results of self-efficacy assessments, the methods used in presentation of thecourse material and the ways in which the
Design self- Efficacy. Journal of Engineering Education. pp. 71 - 79. 6. Eris, Ozgur, Chachra, Debbie, Chen, Helen, Sheppard, Sheri, Ludlow, Larry, Rosca, Camelia, Bailey, Tori, Toye, George. 2010. Outcomes of Longitudinal Administration of the Persistence in Engineering Survey. Journal of Engineering Education. pp. 371-395. 7. Hartman, Harriet, Hartman, Moshe. 2006. Leaving Engineering: Lessons from Rowan University’s College of Engineering. Journal of Engineering Education. pp. 49 – 61. 8. Hutchison, M. A., Follman, D. K., Sumpter, M., and Bodner, G. M. 2006. Factors Influencing the Self- Efficacy Beliefs of First-Year Engineering Students. Journal of Engineering Education. 91:1, pp. 39
and diversity,equity, and inclusion (DEI). The authors described how these subcategories would need to becategorized properly in future revisions, but the idea is they heavily dictated a student’sconfidence and sense of belonging.Summarizing this listing, we concluded with a motivational category list of interventionsubcategories as follows: task-value interventions (e.g., utility-value, communal value), framinginterventions (e.g., self-efficacy, belonging), personal value interventions (e.g., valueaffirmations), mitigating stereotype threat, and changing attributions, as shown in Table 1.Donker et al (2014) conducted a meta-analysis on teaching strategies that help studentmetacognition and self-regulation to find which specific tactics
on curriculum development, etc.) both during their research experience and the academic year; 4. Create strong communication between the teachers, the RET Site project faculty team and the industrial advisory board during the academic year to provide the teachers with support as they refine their curriculum modules utilizing inquiry methodology; 5. Increase teacher self-efficacy related to manufacturing content knowledge and inquiry-based teaching needed to inspire their students to consider careers in advanced manufacturing; 6. Deliver workforce development specific professional development targeted to increase teachers’ knowledge of regional career opportunities in advanced manufacturing to inspire
. Page 11.632.9Variable 4: Amount of Computer Use The connection between computer use and positive attitudes and interest has been amplysupported by previous research15, 38. While experience with computers games has been shown tobe an important predictor of men’s interest in computer related fields40, this is not the case forour women respondents. Other research has shown, however, that experience with computerprogramming may be an important predictor of self-efficacy and success in a computer field forwomen. Learning a programming language is significantly associated for women with anincreased sense of computer competence28, 42. High school programming experience has alsobeen shown to be a significant predictor of women’s success in
motivation to usethe tools they learned, and specific behaviors learners adopted after attending a Carpentriesworkshop.We compiled existing instruments measuring computer self-efficacy [14], Java programmingself-efficacy [15], Python and computational ability [16], self-efficacy towards FLOSS projects[17], and student-instructor relationships [18]. Assessment specialists on staff and from ourinstructor community used a rubric to vote on whether to omit questions, keep them as-is, oradapt them for the purposes of our data collection. Rather than focusing on learners’ skills withrespect to particular tools, we wanted to focus on assessing learner confidence, motivation, andadoption of good research practices [19], as these elements represent the
could choose “I don’t know” option. That is, a “0” was given for a wrong answer, a “1” was given for selecting “I don’t know” and finally a “2” was given for a correct answer. The adjusted assessment score was computed as the percentage of the sum of answers to seven assessment questions to maximum possible score (14 in this case). Page 15.1114.7 Exit self-efficacy, self-reported motivation, perceived usefulness, and perceived difficulty of laboratory activity measured with the previously mentioned tool and ranged from 1 to 5 for self
report using the search term “STEM outreach”[2].Despite efforts to recruit more underrepresented students to engineering, overly difficultengineering tasks and courses can serve as a barrier to recruiting students to the engineeringworkforce. Research shows that negative STEM experiences such as “weed out” courses, orcourses that are purposefully difficult, cause low STEM persistence in first-generation collegestudents [3]. A separate study on outreach events geared towards female elementary schoolstudents stated that decreases in STEM self-efficacy occur around young elementary age [4]. Tomitigate negative experiences, there is a need to focus on creating positive STEM experienceswhich can increase student engagement and increase the likelihood
/15428052.2012.677610.[21] A. R. Carberry, H.-S. Lee, and M. W. Ohland, “Measuring Engineering Design Self- Efficacy,” Journal of Engineering Education, vol. 99, no. 1, pp. 71–79, Jan. 2010, doi: 10.1002/j.2168-9830.2010.tb01043.x.[22] E. Cevik et al., “Assessing the Effects of Authentic Experiential Learning Activities on Teacher Confidence with Engineering Concepts,” in 2018 ASEE Annual Conference & Exposition Proceedings, Salt Lake City, Utah, Jun. 2018, p. 29827. doi: 10.18260/1-2-- 29827.
exception is that Huang (2017) conducted quantitative surveyon students who participated in “Creation Youth” National University StudentEntrepreneurship Competition, and found that entrepreneurship practice education includingentrepreneurship competitions had significant positive impacts on mediating variable ofentrepreneurial self-efficacy and therefore can improve college students’ entrepreneurialintention [23]. Although the prior study has proven the promoting effect of entrepreneurialcompetition on entrepreneurial intention, it remains to explore which specific learningexperiences in entrepreneurship competitions function. This current study shall continue toexplore the specific impact of engaging in TIECs on engineering students
for Engineering Education, 2017 The Influence of Gender Grouping on Female Students’ AcademicEngagement and Achievement in Engineering and Biology: A Case of Small Group Work in Design-Based Learning (Work in Progress) IntroductionDuring the past 30 years, much attention has been drawn to the lack of women in STEMfields and the need to attract and retain them in these fields. In the relevant literature, theinfluence of gender grouping on variables such as female students’ interest, self-efficacy,participation/engagement and achievement in STEM subjects has been a salient line ofresearch. However, researchers have arrived at mixed findings. Also, while researchers haveinvestigated the influence of
/978-94-6091-821-6.Magnusson, S., Krajcik, J. & Borko, H. (1999). Nature, sources, and development of pedagogical content knowledge for science teaching: Examing pedagogical content knowledge, Eds.: Gess-Newsome, J., Lederman, N. G., Kluwer Academic Publishers, Doordrecht, Hollanda, 95-132.Maine Department of Education [MDE] (2019). Standards & instruction–science & engineering. https://www.maine.gov/doe/learning/content/scienceandtech.Marquis, S. D. (2015). Investigating the influence of professional development on teacher perceptions of engineering self-efficacy. Ph.D. Thesis, The University of Southern Maine, Portland, USA.Massachusetts Department of Elementary and Secondary Education [MDESE] (2016). 2016
learn. Performance and Instruction, 26(8), 1-7. Retrieved December 28, 2004, from ERIC database.[11] Keller, J. M. (1987). The systematic process of motivational design. Performance and Instruction, 26(9- 10), 1-8. Retrieved December 28, 2004, from ERIC database.[12] Jackson, J.W. (2002). Enhancing self-efficacy and learning performance. The Journal of Experimental Education, 70(3), 243-254. Retrieved December 28, 2004, from ERIC database.[13] Gabrielle, D.M. (2003). The Effects of Technology-Mediated Instructional Strategies on Motivation, Performance, and Self-Directed Learning. Unpublished doctoral dissertation, Florida State University.[14] Visser, J., & Keller, J. (1990
work.Comparing the effectiveness of virtual learning events with personal workshops would provideinsights into the advantages and challenges associated with each format as well as their overallimpact.References[1] Stewart, A. J., Malley, J. E., & LaVaque-Manty, D. (Eds.). (2007). Transforming scienceand engineering: Advancing academic women. University of Michigan Press. [2] Ford, A. Y., Dannels, S., Morahan, P., & Magrane, D. (2021). Leadership programs foracademic women: building self-efficacy and organizational leadership capacity. Journal ofWomen’s Health, 30(5), 672-680. [3] Eagly, A. H., & Carli, L. L. (2007). Through the labyrinth: The truth about how womenbecome leaders. Harvard Business Review Press [4] Eagly, A. H., & Carli, L
ofeffective engineering education. Hensel and Sigler (2007) discussed strategies for supportingstudents through structured programs, emphasizing the need for mentorship and academicresources [2]. Similarly, Myers, Byrd, and Hensel (2005) focused on designing first-yearprograms aimed at boosting retention and academic performance, including event-based learningcontexts like EngineerFEST [3]. Exploring students’ perceptions and self-efficacy in engineeringis crucial for understanding the broader impacts of such initiatives. Morris, Dygert, and Hensel(2020) linked students’ views of engineering as a career to their self-efficacy and grit, suggestingthat well-designed events can reinforce positive perceptions and career aspirations [4].Engineering
, professionaland honor societies, scientific research [3], or identity-based organizations [8].In engineering education literature, experiential education has also been studied for its potentialto support professional formation via engineering identity development [9]. Engineering identity,a concept that describes how students understand themselves as engineers, has been argued to bea significant indicator of educational and professional persistence [10], [11]. Literature hasconnected a stronger engineering identity with higher retention rates, improved climateperceptions, and better experiences for underrepresented groups in engineering [12]. Scholarshave studied how engineering identity connects with self-efficacy, or individuals’ beliefs abouttheir own
. Details of the GradTrack structure arediscussed in the next section.GradTrack Program StructureFormatGradTrack is an academic-year-long program with monthly online meetings, four meetings eachin fall and spring semesters. Structuring the program to be fully online and incorporating virtualmentoring is a unique and strategic aspect of the GradTrack Program. While the practice ofonline mentoring – or e-mentoring – has existed for over 20 years [8], [9], [10], the COVID-19pandemic has led to the transition of on-campus student success and URM-focused programsinto a virtual setting [5]. Virtual mentoring has also been shown to increase STEM achievement,self-efficacy, and drive to persist in mentors and mentees in a recent study performed at
interventions for undergraduate level coursework with the goal ofincreasing student exposure in microelectronics. Fig. 1. Social Cognitive Career Theory Interest Model Flow Chart. Adapted from [3]Students having an idea about what they as individuals can contribute to a field (self-efficacy),and developing outcome expectations for their schooling and career can trigger the followingstages in the flowchart. The program that is being developed aims to be a source of activityselection and practice, eventually certifying performance outcomes for the students. SCCT wasused in the planning and development of this program, and Figure 1 outlines many of the aims ofthe program. Although the project as a whole aims to target all aspects of the SCCT model