of our research. These data, along with a careful review ofdocuments and websites available from each community college and applicable higher educationliterature as a comparison informed the refinement of the CPPI which was developed, and testedin our previously described STEM community college study.5The Refined College Pedagogical Practice Inventory (CPPI-R): Refinement, testing, and use ofthe CPPI has been informed by measurement research of educational psychologicalresearchers.33 Specifically, the inventory was initially designed with the intent of enabling us toexplore relationships among the dependent and independent variables associated with collegepedagogical practices and to determine potentially predictive factors that relate to
community and occupational college personnel and students. For ourresearch forty-one interviews were conducted with approximately ten at each community collegesite during the first semester of our research. These data, along with a careful review ofdocuments and websites available from each community college and applicable higher educationliterature as a comparison informed the refinement of the CPPI which was developed, and testedin our previously described STEM community college study.5The Refined College Pedagogical Practice Inventory (CPPI-R): Refinement, testing, and use ofthe CPPI has been informed by measurement research of educational psychologicalresearchers.33 Specifically, the inventory was initially designed with the intent of enabling
shared understanding by organizational members regarding organizationalgoals, values, and general structures and procedures. When members are acculturated, theyusually have accepted the general goals and values of the organization, and are willing tointegrate into the culture. Familiarity with other individuals from the organization (i.e., get toknow the colleagues and establish relationships with members) can foster relationships (in bothmicro and macro-levels) bond individuals to their organizations, and become a way to increaseperceptions of self-efficacy and commitment toward the organization (Cheney et al, 2014).Recognition from others (i.e., perceiving one’s value to the organization and feeling recognized)can also link to job satisfaction
previous EFA,indicating that the Framing Agency Survey provides data that are valid for uses like instructionalrefinement and further studies into the role that framing agency plays in the professionalformation of engineers. However, such studies will require a larger dataset, as well as analysisexamining the structure of the survey that includes measures of relevant constructs, such asengineering identity, engineering self-efficacy, and persistence intentions. Our ongoing researchaims to develop full structural models that include demographic covariates to permitinvestigation of varied impacts on privileged and minoritized students.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.1751369
they were failing the course when in fact, their grades wereabove average. We also wondered, given the large number of items students miss in theseexams, whether instructors would review these items in class so that the exam could be used toinform instruction rather than just serve to measure and classify students.To find out more about LOC grading and related exam practices and their effects on students, wedesigned a survey to address the following questions: Assuming that their final grades remain the same, to what extent does the raw score of an exam affect students’ motivation, self-efficacy, learning strategies, or perception of the instructor? To what extent do students believe that exams should be criterion-based
level languages are more thoroughly understood. This paperdescribes a high school STEM education curriculum that provided sophomores hands-onopportunities to learn and understand microcontrollers through assembly language projects. Thecourse assessment evaluated the students’ computer science knowledge, course expectations,learning perspectives, creativity, and future field of study interests. Initial results indicate thatstudents have a greater breadth of knowledge, a stronger positive perception of computerscience, and a greater self-efficacy while at least maintaining student interest and creativity.Observations of the students indicate that the investigative nature of programming withmicrocontrollers is motivating the students to seek
)developed by Pintrich, Smith, García, and McKeachie in 1991 was used to measure keyconstructs associated with students' success, such as motivation, epistemic and perceptualcuriosity, and self-efficacy. Signature assignments were developed to measure student successoutcomes from adopting the pedagogy. The results of the MSLQ administered to 44 studentsimpacted by the pedagogy reveal a significant increase in the students' key constructs associatedwith success. The pedagogy reveals better knowledge gain and classroom engagement than thetraditional teaching approach.IntroductionHistorically, concepts in engineering fields have been taught using traditional methods ofinstruction [1]. In this method, the instructor is the sole provider of knowledge
Paper ID #37589Active Project: Supporting Young Children’s Computational ThinkingSkills Using a Mixed-Reality EnvironmentDr. Jaejin Hwang, Northern Illinois University Dr. Jaejin Hwang, is an Associate Professor of Industrial and Systems Engineering at NIU. His expertise lies in physical ergonomics and occupational biomechanics and exposure assessment. His representative works include the design of VR/AR user interfaces to minimize the physical and cognitive demands of users. He specializes in the measurements of bodily movement as well as muscle activity and intensity to assess the responses to physical and environmental
theirrelationship with academic performance. Second, longitudinal studies to identify the relationshipand impact of employed study strategies on the students' academic performance over the courseof their engineering degree should be conducted. Finally, the researchers may includemotivational factors to discuss the relationship between the students' study strategies and theiracademic performance.AcknowledgmentThe authors would like to thank Dr. Heidi Diefes-Dux and Dr. Morgan Hynes for access tostudent data.References[1] M. C. W. Yip, “Learning strategies and self-efficacy as predictors of academic performance: a preliminary study,” Qual. High. Educ., vol. 18, no. 1, pp. 23–34, 2012, doi: 10.1080/13538322.2012.667263.[2] N. Rosenberg and R. R. Nelson
are cognitive engagement and self-efficacy. Thus,the learning environment was based on authenticity, inquiry and collaboration. Flight simulationsoftware was used to engage students in a real word scenario. Flight data was collected by thestudents, processed, analyzed and interpreted by the students. Teams of two students while flyingtheir own missions were provided the opportunity to discuss their data analysis. Next, studentswere engaged in a discussion about the data analysis and interpretation. The math concepts studiedduring the camp were the Pythagorean theorem and similar triangles, while the science conceptinvestigated was the standard atmosphere. The mission associated with the math concepts was alanding approach in a Cessna 172
leadership role Extent to which leadership role contributed to skills in speaking, critical thinking, problem- solving, interacting with diverse groups, and becoming a leaderThe HERI dataset is being used to address Research Question 2, and analysis on this dataset iscurrently at a preliminary stage. Using leadership self-efficacy and social self-concept as proxiesfor leadership identity, the longitudinal dataset will be analyzed using multi-level regressiontechniques to isolate the specific effect of engineering identity, and activities intended to enhanceengineering identity, on leadership identity. Engineering identity will be derived from exploratoryand confirmatory factor analyses on three specific items measured on both TFS and
strongly related to learner-centered practices (r=.45), withmathematics achievement running a close second (r=.34). Grades as an outcome show a muchlower relationship (r=.25). Affective/motivational variables showed higher association, typically,than cognitive outcomes. Student participation, for example, is strongly related to learner-centeredness (r=.55), closely followed by satisfaction (r=.44), drop-out prevention (r=.35), self-efficacy (r=.35), positive motivation (r=.32), and social connection/skills (r=.32). Given these affective/motivational variables are causally and reciprocally related tostudent achievement in mathematics and science4, we propose that faculty learner centeredattitudes and practices put in place a positive
confounding factor of altered behavior.To extend Clausen’s research, Traugott and Katosh also investigated the ‘stimulushypothesis’ as compared to two alternative hypotheses about the cause of the intervieweffect proposed in 1973: a ‘self-concept hypothesis’ and a ‘alienation reductionhypothesis.’10 Both involved changes in the individual’s psychological attitudes due tothe personal contact of the interview. To test this effect, political self-efficacy andpolitical alienation were measured on each survey; taking additional surveys did notchange either measure, so these hypotheses were rejected. Traugott and Katoshconcluded that there was an interview effect and it was caused by Clausen’s stimulushypothesis, as supported by the cumulative effect of
shown: 1) stereotypeswere formed through media exposure11; 2) stereotypes are less present at the kindergarten andfirst grade ages10; 3) interventions were successful at changing student views of scientists12 and4) interventions positively affected self-efficacy and interest in science9.Knight and Cunningham1 modified the DAST when developing the DAET and included fourquestions for students to answer in writing and one that prompted them to draw a picture of anengineer working. The results of the written and drawn parts of the test were similar to the DASTstudies as they depicted common misperceptions of engineers, who were primarily depicted asbuilding houses and bridges or fixing cars. In the study limitations, the researchers noted that
, racism, and social marginalization (First edition.). Stylus Publishing, LLC.[9] Mondisa, J. L. & McComb, S. A. (2015) Social community: A mechanism to explain the success of STEM minority mentoring programs. Mentoring & Tutoring: Partnership in Learning. 23(2), 149-163. doi:10.1080/13611267.2015.1049018[10] Maton, K. I., Beason, T. S., Godsay, S., Sto. Domingo, M. R., Bailey, T. C., Sun, S., & Hrabowski, F. A., III. (2016) Outcomes and processes in the Meyerhoff Scholars Program: STEM PhD completion, sense of community, perceived program benefit, science identity, and research self-efficacy. CBE - Life Sciences Education, 15(3), ar48. doi: 10.1187/cbe.16-01-0062[11] Atkins, K., Dougan, B. M
–257.10 Locke, E. A., Frederick, E., Lee, C., & Bobko, P. (1984). “Effects of self-efficacy, goals and task strategies on task performance.” Journal of Applied Psychology, 69, 241–251.11 Meyer, J. P., & Gellatly, I. R. (1988). “Perceived performance norm as a mediator in the effect of assigned goal on personal goal and task performance.” Journal of Applied Psychology, 73, 410–420.12 Reidel, J. A., Nebeker, D. M., & Cooper, B. L. (1988). “The influence of monetary incentive on goal choice, goal commitment, and task performance.” Organizational Behavior and Human Decision Processes, 42, 155–180.13 House, R. J. (1971). “A path goal theory of leader effectiveness.” Administrative Science Quarterly, 16, 321– 328.14
Page 22.191.4the curriculum necessitates that students experience such problem solving settings. However,insufficient attention has been given to these issues in the literature, despite their potentialimportance for building self-efficacy as well as increased student learning and performance.In experimental settings, due to their potential impact on student performance (i.e., designedartifact, or design solutions) perceived ambiguity level of a design task and the tolerance forambiguity level of experiment participants (subjects) should be taken into account during theanalysis of results.A relevant construct to ambiguity might be the gender orientation of a design task as certaintasks can be more oriented towards one gender, and perhaps less
, orSES. In the third and final pass, we focused on reading for details related to themes identified inthe initial analysis, including discussion of the conceptual framework and patterns in types of out-of-class involvement.Findings and DiscussionProfessional Development Outcomes Associated with Student Organization Involvement.Researchers have defined and examined student outcomes impacted by out-of-class experiencesin a variety of ways. In the realm of professional development, these outcomes range fromintellectual and competency development to value constructs (e.g., ethics, professionalresponsibility, sustainability affect) and constructs of self-efficacy and professional identity(including sense of belonging, work self-efficacy, and
, 2015.[36] S. Cheryan, S. A. Ziegler, A. K. Montoya, and L. Jiang, “Why are Some STEM fields more gender balanced than others?” Psychological Bulletin, vol. 143, no. 1, pp. 1-35, 2017.[37] E. Yost, D. M. Handley, S. R. Cotten, and V. Winstead, “Understanding the links between mentoring and self-efficacy in the new generation of women STEM scholars,” In Women in engineering, science and technology: Education and career challenges. IGI Global, 2010.[38] J. Owens, C. Kottwitz, J. Tiedt, and J. Ramirez, “Strategies to attain faculty work-life balance,” Building Healthy Academic Communities Journal, vol. 2, no. 2, pp. 58-73, 2018.[39] E. M. Lee, “ ‘Where people like me don’t belong’: Faculty members from low
.” AMCIS 2004 Proceedings. 397.[4] Milligan, S. K., and Griffin, P., 2016, “Understanding Learning and Learning Design in MOOCs: A Measurement-Based Interpretation,” Journal of Learning Analytics, 3(2), pp. 88–115.[5] Jonassen, D. H., 1995, “Operationalizing Mental Models: Strategies for Assessing Mental Models to Support Meaningful Learning and Design¬ Supportive Learning Environments.” CSCL ’95 Proceedings. 182-186[6] Bucciarelli, M., 2007, “How the Construction of Mental Models Improves Learning,” Mind and Society, pp. 67–89.[7] Ramalingam, V., Labelle, D., and Wiedenbeck, S., 2004, Self-Efficacy and Mental Models in Learning to Program. SIGCSE Bull. 36, 3 (September 2004), 171–175.[8] Hwang, G. J., Shi, Y. R., and Chu
paper evaluates the effectiveness of strategies geared toward encouragingcreativity and innovation in conjunction with the engineering design process during a one-weekcivil engineering summer course. The evaluation methodology used three assessment tools toevaluate creativity and innovation: class surveys, student artifacts, and instructor feedback. First,pre-and post-course surveys were administered to measure the effectiveness of the pedagogy onstudents’ understanding of creativity and innovation in relation to engineering design.Additionally, an analytic scoring rubric was used to assess creativity, innovation, andengineering design process application in student artifacts. Instructor feedback was also analyzedto illustrate the student’s
Sonnet Lite software.Insights from 2020 Summer ProgramThe SageFox Consulting Group is responsible for all SCR2 program assessments. The insightsdocumented in this section are derived from their assessment report. The assessment instrumentsused include: A pre-survey for students and teachers; A post-survey for students and teachers; afollow-up survey for students and teachers; and a post-program survey for mentors. These surveyswere created in consultation with Audrey Rorrer, author of the CISE REU Evaluation Toolkitsurvey instruments[22,23], which contains construct subscales measuring research skills,leadership skills, self-efficacy, scientist identity formation, intention to attend graduate school,grit, mentoring relationships, and attitudes
interpersonalcommunication and conflict resolution strategies that encourage peripheral participation acrosssectors and help formulate the T-shaped individual [8,9]. Teams may be self-selected and self-managed, enhancing motivation and instilling a sense ownership over the project, whichultimately contributes to self- efficacy as an outcome [10,11,12].However, professionalization in today’s global market has taken on new meaning in an industrymore focused on dynamic change, innovation and entrepreneurship. The National Academy ofEngineering predicted the joint roles of globalization and technological diversity in shaping theengineer of 2020, themes that are also reflected in the 2018-2019 ABET student outcomes[13,14]. There is greater emphasis placed on creative
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’ pathways to their success. c American Society for Engineering Education, 2016 Enculturation of Diverse Students to the
self- efficacy, change in attitude towards teaching Participant Teaching Practices Evidence of improvement in participants’ teaching strategies, such as implementing learner centered pedagogy, creating assessment better aligned with learning objectives, course design Student outcomes Evidence of change in student learning achievements, attitude towards learning, retention Student level feedback Feedback from students about teaching in form of comments or end of course evaluations Participant level feedback
makerspacescan be found in the news as the source of the next manufacturing revolution [6].Makerspaces as a locus for design learning is a topic that has received extensive attention. Thetheory of maker education relates to many educational frameworks, including Piaget’sconstructivism theory [7], the Situated Learning Model [8], and Community of Practice [9], allof which have been applied to understand learning in a makerspace [10]. The style of learningand appropriate frameworks depend highly on the type, location, and use of a makerspace.Experience working in a makerspace improves creativity [11], collaboration in diverse teams[12], design self-efficacy [13], and technical skills used in industry [12]. Agency is an importantcomponent of a makerspace
education [2, 13].Previous studies have found that hands-on, design-oriented activities can increase students'engagement and interest in engineering [13, 23]. Several studies have examined the effectivenessof hands-on engineering technology summer camps in increasing the representation ofunderrepresented students in STEM majors. A recent study found that participation in a hands-onengineering technology summer camp was associated with increased interest in pursuing anengineering degree among underrepresented high school students [24]. Another study by DeanHughes [25] found that underrepresented high school students who participated in a hands-onengineering technology summer camp had higher levels of self-efficacy in engineering and weremore likely
provided a strong foundation of findings, one limitation was that the studypredominantly focused on science students and not engineering undergraduate researchers.Our own prior work 7 on undergraduate research experiences previously focused on socialcognitive aspects of an NSF funded Research Experiences for Undergraduates (REU) program,finding that the experience positively impacted participants’ academic and career plans,especially for doctoral level work. We utilized a mixed-methods approach to gain in-depthinformation about the impact of the undergraduate research experience, and particularly the roleof graduate student mentors, on participants’ self efficacy
+/- one standard deviation of each other and of the National averages.Interestingly, unlike the Science scores, which showed a mixture of student affinity relative tostudent confidence levels, Figure 3 shows that at every school – as well as the national averagedata – students responded more positively to questions regarding their confidence in mathematicsthan to questions concerning how much they like the subject.Given that quantitative survey response methods fall short of adequately assessing our program’simpact on student attitudes or feelings of self-efficacy, other than to show that our students’attitudes are in line with the National averages, we’ve used post-program questionnaireresponses and reflective essays to provide additional
,” showeda drop of 1.75 (P value < 0.00001 using an unranked T-test), from an initial 6.36 to a final 4.61.Interestingly, the place of these scores almost exactly reverses Q2, going from the highest initialscore to the lowest final score. We have not seen previous studies on this drop in self-efficacy ata time of increasing knowledge in the literatures of writing or communication. We understandthis shift as a clear indicator of a transition stage between novice and expert, and as a step inprofessionalization.We also saw a small increase (+ 0.35, P value 0.0193 using an unranked T-test) in Q8, “Iunderstand how to reflect on the communication choices I make in light of context, purpose, andaudience.” These terms were used consistently in workshops