engineering disciplines, for a number of reasons.It has been shown as a useful recruiting tool, allowing undergraduates, who may not havethought of pursuing a graduate degree (Mraz-craig et al., 2018; Noguez & Neri, 2019). CUREprojects have also been shown to increase students’ self-efficacy, as well as other improvementsin motivation, when measured using the LCAS (Laboratory Course Assessment Survey) (Harriset al., 2021). Though these CURE projects do have improved outcomes, there are concerns that,as the projects have a limited time frame and can have limited objectives. As most undergraduatestudents are enrolled in more courses than graduate students, and as these projects are limited toa single academic term, students are not able to complete
(S-STEM) grant to increase engineering degree completion of low-income, high achievingundergraduate students. The project aims to increase engineering degree completion byimproving student engagement, boosting retention and academic performance, and enhancingstudent self-efficacy by providing useful programming, resources, and financial support (i.e.,scholarships). This work is part of a larger grant aimed at uncovering effective strategies tosupport low-income STEM students’ success at HBCUs. The next section will discuss thebackground of this work.Keywords: Historically black colleges/universities (HBCUs), learning environment,undergraduate, underrepresentationBackgroundA public historically black land-grant university in the southeastern
certificate and degree programs, four-year engineering transfer programs, workforce development programs, and industry.2.2 Theoretical FrameworksTo better understand the career orientations of ET students, two leading career developmenttheories have been used to guide this study, Social Cognitive Career Theory (SCCT) andSchein’s Career Anchors Theory.2.2.2 Social Cognitive Career Theory (SCCT)Social Cognitive Career Theory (SCCT) is a theory which links students’ attitudes, interests,experiences, self-efficacy beliefs, outcome expectations, and personal goals to educational andcareer decisions and outcomes [9]. SCCT aims to “understand the processes through whichpeople form interests, make choices, and achieve varying levels of success in educational
aspects involving both student outcomes and teacher outcomes.For students, we assessed student growth, such as interest, self-efficacy and confidence incomputing. For teachers, we assessed teachers’ learning and adoption of inquiry-based practices,basic App Inventor computing skills, and observed how and to what extent they incorporatedApp Inventor programming and project app development into their courses. We also assessed theoverall impact of their project participation.MethodsThe project underwent both formative and summative evaluation throughout, all conducted by anexternal evaluation team (second and third authors) and reported regularly to the project leads(first and fourth author). Data collection included several components: • Annual
Paper ID #18317Cluster Analysis in Engineering EducationMr. Andrew Jackson, Purdue Polytechnic Institute Andrew Jackson is currently pursuing a PhD in Technology through Purdue’s Polytechnic Institute, with an emphasis on Engineering and Technology Teacher Education. His research interests are engineering self-efficacy, motivation, and decision making. Andrew is the recipient of a 2015 Ross Fellowship from Purdue University and has been recognized as a 21st Century Fellow by the International Technology and Engineering Educators Association. He completed his Master of Science in Technology Leadership and Innovation at
information available in the environment in combination withwhat they already know, (b) learners can control and regulate aspects of their thinking, motivation,and behavior and in some instances their environment, (c) learners compares their progress toward agoal against some criterion and this comparison informs the learner of the status of progress towardthe goal, and (d) self-regulatory mechanisms mediate between the person, the context, andachievement (pp 387-388). Zimmerman emphasized that in addition to metacognitive skill,students need a sense of self-efficacy and personal agency for success in self-directedenvironments. 16 From these descriptions, it is clear that self-regulation involves many forms ofautonomy.Based on this description of
, studies of students’ self-efficacy in engineering contexts providevaluable insights into how students’ perceived abilities to accomplish particular tasks mayinfluence important student outcomes; however, these studies do not fully account for other aspectsof students experiences and identities including attitudes toward subject material, motivation,background experiences, social identities like race and gender, and other salient and interwovenstudent attitudes, beliefs, and mindsets. Accounting for multiple and overlapping measures canprovide additional explanatory power to understand student outcomes, but this approach alsobrings methodological challenges in analyzing complex data with multiple correlated dimensions.One newer statistical
provision on elementary Taiwanese students’ question-generation in a science class,” 2013.[12] S. Lerner, S. Sheppard, and S. D. Sheppard, “What Makes an Inquisitive Engineer? An Exploration of Question-Asking, Self-Efficacy, and Outcome Expectations among Engineering Students,” in American Society for Engineering Education Annual Meeting, 2017.[13] K. A. Harper, E. Etkina, and Y. Lin, “Encouraging and analyzing student questions in a large physics course: Meaningful patterns for instructors,” J. Res. Sci. Teach., vol. 40, no. 8, pp. 776–791, 2003.
not only metacognition knowledge and strategies, but also metacognition controlexperience over specific cognitive tasks through efforts driven by intrinsic motivation. Thecreativity and self-regulated learning are essentially interacted attributes and can result in optimalperformance and self-efficacy (or confidence), and in return help forming positive attitudes andenhancing intrinsic motivation, which lead to persistent efforts for pursuing further self-directedlearning and creativity. There is a synergic cycles among these attributes. Based on cognitivetheoretical frameworks, a new Pedagogical Model is proposed to integrate new CognitiveInstruction Model and Problem/Project-Based learning into co-curricular design projects, inwhich
needed new ways to measure impact onstudents. First, we knew we knew we wanted to identify the strengths and assets salient forengineering that our diverse students develop from their everyday and cultural experiences. Weconjectured that because many of them had to “make it work” and “make do” that they haddeveloped everyday ingenuity that could serve as a strong foundation as engineers. For instance,when asked, “How have you used a table knife?” our students respond: • a screwdriver • a putty knife • changing the volume on my stereo after the knob broke off • getting into my car after the handle brokeWe developed a survey using published questions about knowledge of design problem framing,engineering self-efficacy, their
• Agreeableness • NeuroticismOpenness refers to introspection, intellectual curiosity, willingness to entertain novel ideas, andimagination. Conscientiousness refers to being purposeful, being strong-willed, determination,accomplishment, self-efficacy, and reliability. Extraversion refers to being social, a preferencefor large groups, being talkative, being active, and assertion. Agreeableness refers to beingaltruistic, being empathetic towards others, a willingness to assist others, and an assumption thatothers will be helpful in turn. Neuroticism refers to a tendency to experience negative affectssuch as embarrassment, guilt, and anxiety. Each of the five traits in the FFM is represented as ascaled dimension such that a person could have any level
of the assessment. While self-reflections are important components of experiential learning [4-6], positive self-reflections are significant components of the self-efficacy theory [19]. Here are some student comments: “That was such a good course offered. It was amazing,” “I loved getting hands on experience programming VR applications and doing the project as an individual, not in a group,” and “I liked the integration of VR and mechatronics and how we can combine the two to create applications that can help in that regard.” Question 8 was assessing the challenges students had in the course. Students did not have any problems with the VR concepts, only the implementation. Most comments addressing challenges were dealing with the EON
existence and influence of motivation have been studied in numerousenvironments including, notably, academic settings. Strong correlations have been foundbetween a person’s motivational state and short, medium, and long-term outcomes suchas performance, satisfaction, and persistence - three goals central to pedagogicalrefinement and revision. Specifically, research conducted over the past three decadesstrongly suggests that motivations are tightly linked to outcomes such as self-efficacy,critical thinking, creativity, self-regulation, and pro-social behavior2-8 - goals that areidentified as critical to the professional success, and in particular, to the success of STEMgraduates.9-13One useful framework for characterizing the dynamics of motivation
understanding of the DSP topics covered in lectures, which might not be a good direct measure of student’s understanding of topics. However, it shows a relatively high level of students’ self-efficacy which can improve learning performance9, 10. Students also supported the use of this platform for future DSP offerings except for one student who pointed out that the selected K65 board might be too powerful for most senior design projects. As noted in Section III, we are currently investigating a similar but smaller size MCU board (i.e., the FRDM-K66F development board) as the alternative platform for the DSP laboratory coursework. This board could be a better option for some senior design projects compared
takingmultiple non-CPMSE computing courses. Also, although students’ perceptions regarding utilityand intention of use did not show significant increase from the pretest to the posttest, they did notdecrease either. And both of them showed a reasonable positive score during the pretest (Utility= 3.43, Intention of Use = 2.78).The results of this study can be explained through the lens of the literature in self-efficacy.Previous research about student self-efficacy has identified that students’ confidence in theirabilities to complete a variety of tasks, specifically mathematical-related tasks in courses at thecollege level, predicted their future interests in mathematics courses 39. We believe that this mayalso be the case with exposure to
engineering 9/16 16/17 Learn about engineering research 10/16 17/17 Engage in engineering research 12/16 16/17 Enhance my knowledge of technology 11/16 17/17 Design an engineering-based lesson for my classroom 11/16 17/17 Form partnerships with other schools 8/16 8/17___________________________________________________________________________________________Teachers also responded to questions about their confidence level or motivation (self-efficacy)for various aspects of their teaching (See Table 3). Paired
program trained participants togain technical skills to design and conduct experiments, simulate, and analyze the results as well as softskills to work in teams and communicate technical statements. Acquiring such skills has been proven todevelop confidence, self-efficacy and a sense of proficiency and mastery in disciplinary research in STEM[24-26]. The SPW activities were meant to equip/expose participants with/to hard and soft skills andproficiencies. They ranged from writing technical statements and interaction with recruiters to anintroduction to carrying out experiments in a research laboratory under the mentorship of a faculty member,analyzing data, simulation, coding, and writing final research reports.Industry Partnership and
• I am confident with Precalculus • I am confident with Calculus • I enjoy math • I can apply my math skills to computing and engineering projectsThe post-bootcamp survey included these same ratings so we could investigate potential changesin their attitudes. Fourteen (n=14) of the seventeen bootcamp participants (82%) completed bothsurveys and consented to include their data in our formative assessment. We performed aWilcoxon-Mann-Whitney test to compare pre- and post-bootcamp ratings to test the hypothesisthat the bootcamp would improve students’ self-efficacy. Table 1 shows the mean (M) andstandard deviation (sd) for each item’s rating, as well as the p-value of the hypothesis test.Overall, the average
was designed to assess improvements in studentlearning and self-efficacy for those participating in the redesigned Introduction to Statics course.Of the 90 students enrolled in the course, 61% (n=55) participated in with complete pre- andpost-course survey responses. Of participating students, 60% are underrepresented minoritystudents (with one or more of the following identities: women, non-binary gender, Black,Latinx). The remaining 40% are white men. At the time of taking the course, 78% ofparticipating students were in their second year of college, 14% were in their third year, and 8%were in their fourth year.Data were collected using a retrospective survey. The Student Assessment of their LearningGains (SALG) was administered at the end
obtained, allincluded commercialization metrics such as founding a company, number of employees,and revenue.Education and learning metrics: Out of the four post-course surveys obtained, allincluded questions about participants’ satisfaction with the course, as well as their intentto become an entrepreneur. Three included measures of self-rated improvement inknowledge or learning, and three included measures of confidence or self-efficacy. Ofthe seven Nodes that used post-course surveys, five also collected pre-course data. Outof the three programs for which both pre- and post- surveys were obtained, all includeda subset of questions that were consistent on the pre- and post-surveys to allow for theassessment of change over time. Out of the 3
Teaching, vol. 38, no. 10, pp. 1065–1088, Nov. 2001. doi:10.1002/tea.10001[9] K. Moser, Redefining transfer student success: Transfer capital and the Laanan-Transfer Students’ questionnaire (L-TSQ) revisited, 2012. doi:10.31274/etd-180810-498[10] Sachitra, V., & Bandara, U. (2017). Measuring the academic self-efficacy of undergraduates: The role of gender and academic year experience. International Journal of Educational and Pedagogical Sciences, 11(11), 2608-2613.[11] McNally, Sandra (2020): Gender differences in tertiary education: What explains STEM participation?, IZA Policy Paper, No. 165, Institute of Labor Economics (IZA), Bonn. Retrieved from: https://www.econstor.eu/bitstream/10419/243451/1/pp165.pdfTable 1
,understanding engineering, self-efficacy, and hands-on activities/structure and virtual format. Toincrease validity in the coding, multiple researcher triangulation was conducted. The statementsset forth in Table 1 below are representative responses of students to each of the emergingthemes. Representation "I enjoyed hearing about different engineers and black and women excellence.” “It was an amazing experience to meet so many women from all different backgrounds who are so successful.” “I really liked when the women from [manufacturing company] came and spoke to us about what they did. And, when the women came and spoke her computer science journey.” “My favorite part was hearing from the speakers and their wisdom. It opened job opportunities that I
how they impact their career development.Cadenas, Cantú, Poder Evaluate program Underrepresented Social Cognitive Quantitative A program designed with aLynn, Spence & effectiveness in community college Career Theory*, curriculum that is culturallyRuth (2020) entrepreneurial students Critical responsive does promote career self- efficacy Consciousness*, development and entrepreneurial
Cultural Intelligence: Definition, Distinctiveness, and Nomological Network. In L. Van Dyne and S. Ang (Eds.), Handbook of Cultural Intelligence: Theory, Measurement, and Applications (3-15). M.E. Sharpe, Inc., Armonk, NY. 2008.23 Earley, P., and Ang, S. Cultural Intelligence: Individual Interactions Across Cultures. Stanford University Press, Palo Alto, CA. 2003.24 Lawrence, N. The Effects of Cultural Intelligence, Self Efficacy and Cross Cultural Communication on Cross Cultural Adaptation of International Students in Taiwan. Masters Thesis. National Taiwan Normal University. 2011. Available at http://ir.lib.ntnu.edu.tw/retrieve/49356/metadata_07_12_s_05_0014.pdf25 Ang, S., Van Dyne, L., and Koh, C. Personality
, self-efficacy in problem solving, academic performance, and knowledge retention as indicators oflearning effectiveness.Some students also used achieved outcomes to gauge their learning effectiveness. The outcomesidentified by focus group participants included enhanced conceptual understanding (ST11),increased confidence in problem solving (ST9), better grades (ST11, ST12) and betterknowledge retention (ST10), particularly after some time (ST12). The three student responsesalso illustrated the importance they placed on understanding the course structure (ST9) and theconnections among topics (ST9, ST10). It was also a math-based course, but the whole course was structured around problems. We started the class every day with a problem
presence of the words, rather than the same % as the standarddictionary. This still gives a measure of relative usage when comparing across papers.Refer to Table 8 for our custom dimension findings related to the following discussion. Allpapers used generic study jargon (e.g., data, research, etc.). While all papers used somedemographic jargon, they primarily communicated age, race, and sex dimensions ofdemographics rather than meaningfully discussing location or socioeconomic status. EnEdJargon was unsurprisingly the highest category for most papers [17]–[19], [22]. Besides thegeneric eID Jargon, these papers tended to focus on the identity dimensions of attitude,intersectionality, and mentors rather than self-efficacy or competence. Besides the
pursue undergraduate degrees in STEM fields, and have slightlyhigher undergraduate grade point averages6, while evaluations of FIRST Robotics programs haveshown similar outcomes7,8. One of the few studies exploring the effects of a wide range of pre-college engineering activities measured significantly higher engineering self-efficacy amongstudents who had participated in pre-college engineering classes or had engineering-relatedhobbies9. Overall, relatively little work has been done to broadly understand the effects of pre-college engineering participation on the experiences and success of university engineeringstudents, resulting in limited theory to guide the understanding of this experience.To address these limitations, we developed a
them, expectancy, self-concordance, and commitment canbe adopted since WOC faculty in engineering with sustained motivation may be predicted toshow greater goal persistence and attainment .10,11 Buse and Billimoria12 use a mixed methodsapproach in studying the factors related to the retention of women in the engineering profession.They first used a qualitative method to collect narratives of women through interviews. From thenarratives, they argue that one’s personal vision was a contributing factor to persistence. Basedupon this finding, they developed a scale to measure one’s personal vision conceptualized as the“ideal self,” which is comprised of self-efficacy, hope, optimism, and core-identity. They arguethat this ideal self directly
provide a general overview of student perceptions, the questions on theevaluation fail to address some interesting aspects of student motivation and choice. To addressthis shortcoming, a survey instrument was created and implemented in paper form at the end ofthe Winter 2011 semester in 9 of 11 sections of the course offered that semester, with usableresponses from 420 students (of 499 students enrolled in these sections). Responses wereanonymous and participation was encouraged, but voluntary. The collected data was analyzed inaggregate to determine how students were selecting their section of Engineering 100 and toassess their perceptions of the impact of the specific course they had just completed on theirsense of self-efficacy as an engineer
class or physics class. While all of the students participated inthe InSPIRESS project not all of them were planning to pursue a STEM career in college if theyplanned to attend college at all.Implementation: The researchers in this study collected multiple measures and utilized a quasi-experimental design to assess the impact of the project’s authentic learning activities on thestudents’ attitudes, motivation and self-efficacy toward engineering.At the beginning of the school year, the students were provided with consent forms explainingthe research study. After receipt of the signed consent forms, the Pre-surveys were administeredby the researchers to students who, along with their parents, agreed to participate in the project.The rest of the