responding to a set of SJT questions reflect some level of consensus on what are themost and least effective ways of handling each situation. Some low consensus response optionsmay be used as distractors or thrown out, but the whole question might be discarded if expertconsensus is limited or nonexistent. The question of what counts as consensus is also debatable. Page 26.442.10Additionally, we plan to explore use of various other scoring strategies that have been proposedin the SJT literature, comparing them for their relative strengths and weaknesses in terms ofdiagnostic accuracy, as well as strongest predictive validity.20-21,30-31 Doing so
development of the categories and questions included in the RACI. Resultsfrom a pilot test were used to assess (1) the level of improvement for question sets and conceptcategories after course instruction, (2) student confidence in answering question sets, (3)relationships between performance on the RACI and course performance measures, and (4)internal consistency reliability measures of the instrument and categories. The paper ends with adiscussion of plans for ongoing and future work.Summary of Exploratory Work The primary objective of the exploratory study was to identify and categorize studentmisconceptions that may impede student learning of engineering concepts related to water flowprocesses5. The context of the study was an urban
Theory-Based Approach to Reflective Planning and Instruction, Faculty of Education, University of Regina. Appendix A: Student SurveyTOPIC: Course Name Please rate the following questions based on the scale given below. 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 1. The course was effective in helping me learn the 1 2 3 4 5 material presented. Page 26.1533.142. The course was effective in helping me to understand 1 2 3 4 5 the material. 3. The course format
, coping strategies, and academic performance: An evaluation of theoretical models. The Journal of Experimental Education, 80, 196–218. doi:10.1080/00220973.2011.596853 4 Hackett, G., Betz, N. E., Casas, J. M., and Rocha-Singh, I. A. (1992). Gender, ethnicity, and social cognitive factors predicting the academic achievement of students in engineering. Journal of Counseling Psychology, 39(4), 527–538. 5 Jones, B. D., Paretti, M. C., Hein, S. F., & Knott, T. W. (2010). An analysis of motivation constructs with first- year engineering students: Relationships among expectancies, values, achievement, and career plans. Journal of Engineering Education, 99, 319–336. doi: 10.1002/j
revisions to be minor compared to the prior design efforts.Specifically, we will identify whether any items perform poorly and need to be removed.Additionally, we plan to conduct structural analyses (e.g., exploratory and confirmatory factoranalyses) to test the hypothesized conceptual structure represented in our domain model (i.e., the4 FKs). The Q-matrix specifies a priori predictions about the structure of the domain representedby the items. We can use the Q-matrix codings to specify the item loadings in our confirmatoryfactor analysis (i.e., items coded as ‘1’ are hypothesized to load an that factor). Moreover, wecan assess the diagnostic capacity of the TTCI by using the version of Q-matrix with itemresponse levels (see Table 2) to create
Economic Future, Washington, DC: The National Academies Press, 2005.27. National Governors Association, Building a Science, Technology, Engineering and Math Agenda, Washington, DC, 2007.28. National Science Board, A National Action Plan for Addressing the Critical Needs of the U.S. Science, Technology, Engineering, and Mathematics Education System, Arlington, VA: National Science Foundation, 2007.29. President’s Council of Advisors on Science and Technology, Engage to Excel: Producing One Million Additional College Graduates with Degrees in Science, Technology, Engineering, and Mathematics, Washington, DC, 2012.30. National Research Council, Monitoring Progress
Survey in active learningclassrooms to better gauge the different types of responses in other active learning classrooms. Inthe next phase of our study, we plan to collect data from introductory engineering courses across20 institutions in US. These 20 courses will provide a diverse set of classrooms differing inseveral aspects including but not limited to institution type, implemented active learningtechniques, and class size. Further data analysis will use factor analysis, correlations, andregression modeling to tease out what factors influence a student’s response to an in-classactivity, and this type of data analysis will combine courses together to try to accurately modelstudent responses.AcknowledgementsThis project is funded by the U.S
undergraduates of all class ranks that are enrolled in an introductoryengineering course within a first-year engineering program.Literature ReviewValue of educational technology. As previously mentioned, in prior studies, students havereported positive perceptions of educational technology as it relates to their learning,involvement and connectedness. For example, in an EDUCAUSE Center for Applied Research(ECAR) study of 10,000 U.S. students at 184 colleges/universities, over two-thirds of individualsbelieve technology “helps them achieve their academic outcomes,” “prepares them for futureeducational plans” and “prepares them for the workforce.” 2 Over half of all participants believethey are “more actively involved in courses that use technology” and
describe the relevant background and literature that informed survey itemdevelopment. Next, we provide an overview of the Spring 2017 distribution, statistical analyses,and measurement issues identified by the research team as a result of that distribution andanalysis. Finally, we present the revised version of the instrument and explicate implementedchanges as well as outline plans for the next round of survey distribution.Because we describe the development and validation of a research instrument, and the not theresults of an existing or valid instrument, the format for this particular paper differs slightly fromthat of a traditional research paper. Here, our methods are presented as the process of instrumentdevelopment, while the results are
); ethical in its conductand implications (Walther, Pawley, & Sochacka, 2015); as well as a carefully-planned researchdesign that responds to the research questions, whereby the generation of data enables theresearchers to make supported claims. Although rigor is bound up in all aspects of a study—fromits level of cultural responsiveness to communication with internal and external stakeholdersthroughout the research process—our definition of rigor is narrower than our definition ofquality. Specifically, we understand rigor to mean that a study’s claims and implications havebeen carefully supported with data, and that alternative explanations have been considered andaddressed throughout the research design.Validity and reliability have
team member contribution or guidance from a facilitator. Overt activities include: connect or link, reflect and self-monitor, planning, predicting outcomes, and generating hypotheses [20]. Collaborative Students’ dialogue substantively on the same self-constructed idea vocalized to the team. They engagement can accept the ideas presented to the team, little conflict is caused, and dialogue serves to continue the current course of discussion. Or, ideas are questioned or misunderstood, disequilibrium leads to students trying to bring the course of discussion to their understanding. Overt activities include: building on a team member’s contribution, argue, defend
keep the focus of the changes on students’backgrounds and desires. The new program structure consists of a base of six courses for allstudents in the program, followed by primary and secondary concentrations (seven courses andthree courses respectively) from a variety of technical specialties in ECE. Students will also havethe option defining their own secondary concentrations rather than choosing one of the definedsecondary concentrations. At the time of this writing (January 2018), the new program structurehas been approved by the faculty, the paperwork for university approval of the structure is beingprepared, and planning is underway for implementing the changes in the fall semester of 2018.More information about this project is available
yourself make you like an engineer? and, (4) What characteristics ofyourself make you unlike an engineer? These questions were developed to explore students’feelings of belongingness within the field of engineering and how they conceptualized theiralignment with the role of an engineer in their communities of practice. Due to the semi-structured nature of the interviews, the order of presentation varied and each of these fourbelongingness questions were not asked in every interview. For this analysis, only the directresponses to these four belongingness questions were investigated. Table 1—Participant Information Institution Pseudonym Gender Race/Ethnicity Planned major at time
. Tinkering SE 4 0.87 0.89 Design SE 4 0.90 0.94† Abbreviations: SE = self-efficacy; OE = outcome expectationsChoice Self-Efficacy and Student Major ChangesStudents’ self-reported majors at admission (Figure 1, left column), six weeks into the Fallsemester (Figure 1, center column), and the major they are most likely to pursue (Figure 1, rightcolumn) were analyzed to visualize trends in student majors. Over 71% of all students indicatedtheir major was and would be the same at each of the three time points (n = 219), but there arestill many students who indicate a change in major or a planned change in major (n = 89
activity. In future work, we plan ondeploying our survey to institutions with a broad range of student population, departments withvarying engineering and design cultures, and professors with different approaches to the designof reflection activities. ConclusionThrough this survey development process, we have been able to identify four complications thatarise when trying to understand student reactions to reflection. Through understanding studentexperiences, we can find ways to improve reflection activities and at the same time empathizewith students as we learn how properties of reflection can cause diversity of reactions fromstudents. Understanding student reactions to reflection is a promising route
. Educ. Res., vol. 97, no. 6, pp. 287–298, 2004.[7] S.-M. R. Ting and R. Man, "Predicting academic success of first-year engineering students from standardized test scores and psychosocial variables," Int. J. Eng. Educ., vol. 17, no. 1, pp. 75–80, 2001.[8] J. C. F. De Winter and D. Dodou, "Predicting academic performance in engineering using high school exam scores," Int. J. Eng. Educ., vol. 27, no. 6, p. 1343, 2011.[9] B. D. Jones, M. C. Paretti, S. F. Hein, and T. W. Knott, "An analysis of motivation constructs with first‐year engineering students: Relationships among expectancies, values, achievement, and career plans," J. Eng. Educ., vol. 99, no. 4, pp. 319–336, 2010.[10] R. Steinmayr, A. F. Weidinger, M
Baccalaureate,” Soc. Sci. Q., vol. 92, no. 5, pp. 1169–1190, 2011.[17] S. L. Morgan, D. Gelbgiser, and K. A. Weeden, “Feeding the pipeline: Gender, occupational plans, and college major selection,” Soc. Sci. Res., vol. 42, no. 4, pp. 989– 1005, 2013.[18] J. Price, “The effect of instructor race and gender on student persistence in STEM fields,” Econ. Educ. Rev., vol. 29, no. 6, pp. 901–910, 2010.[19] J. D. Speer, “The gender gap in college major: Revisiting the role of pre-college factors,” Labour Econ., vol. 44, no. December 2016, pp. 69–88, 2017.[20] L. Russell, “Can learning communities boost success of women and minorities in STEM? Evidence from the Massachusetts Institute of Technology,” Econ. Educ. Rev
start with learning objectivesas narrowly defined behaviors but with “program educational outcomes (broad goals)”6 (p. 7). Inorder to address the resulting lack of specificity more detailed “program outcomes (knowledge,skills, and attitudes)” (p.7) are subsequently defined.Felder6 further develops Tyler’s17 targeted instruction into an iterative process of instructionaldesign in three areas: “planning (identifying course content and defining measurable learningobjectives), instructing (selecting and implementing the methods that will facilitate studentachievement of the objectives), assessment and evaluation (implementing methods that […]determine whether objectives have been reached)” (p. 8).This concept has significantly advanced engineering
Professor in the Center for the Advancement of Engineering Education at Colorado School of Mines. She is also the Associate Director for CSM's Center for Engineering Education. Dr. Loshbaugh taught in CSM's EPICS program, for which she developed extensive course and faculty-support materials, and designed and implemented a leadership course and overseas summer field session. She has recently been appointed to develop Page 12.1295.1 a diversity plan for CSM, and has experience in international education, corporate training and coaching, and academic editing.Marcus Jones, Howard University
presented an opportunity for lively peer discussion that then led students tothe correct answer. In this study, most of the questions were in the lower levels(definition, basic application). This was partly because the course itself was anintroductory level programming course and that the questions had to fit with otherlearning activities in a 50-minute lecture. Furthermore, the instructor has had limitedexperience with using multiple-choice questions and this study was the first time that theinstructor had used a PRS. As PRS become more widely used, textbook publishers arebeginning to offer polling questions along with their books. The instructor plans tocontinue the use of PRS and will build up a question bank, focusing on creating morehigh level
Queensland into the nature ofengineering competence indicate, however, that some competencies of recent graduates arenot the result of the systematic instruction envisaged in the concept of outcomes-basededucation. Based on these findings this paper introduces the concept of AccidentalCompetencies. These are the competencies that graduates achieve through the co-action ofseveral curricular elements and additional aspects surrounding the formal process ofeducation. Accidental Competencies are therefore not a planned outcome resulting fromcurriculum design.Critical Review of the Competency MovementIn order to understand this concept it is necessary to review the definition and underlyingassumptions behind the idea of competencies, the foundation of
actual circuit deviceanatomical drawing living human bodyhouse or building plan existing (or proposed) house or buildingneural net model “real” human learningpicture or painting of a flower vase the actual flower vasescript the performed playscore the performed music Page 11.1081.13 Table Two Summary of the survey results of chemical (ChE) or mechanical (ME) engineering senior capstone design courseResponding programs
important to be able to work in teams. … Usually problems are bigger [than] just one person [can] solve.” [Paige, SPri, Sophomore]By sophomore year, Paige had already learned that the scope of problems in engineeringrequired teamwork in order to adequately address them.The precipitous drop in the importance of teamwork among graduates was surprising. Paige, oneof the three participants that report teamwork as “not important” in her work, told theinterviewer: “One of the skills you need for this job is program management, just knowing how to plan out, how to get a team going” [Paige, SPri, EPS]This seems to contradict her survey response. Similarly, Nate said teamwork was not importantbut reported working with various teams on a
response of a student in Engineering Dynamics about the definition of lifelonglearning and the research experience:“To me, lifelong learning is a skill, an acquired ability for one to continue their education in non-academic environments. ……. I knew that there were online journals available to the CCSUstudents from the FYE program, but since it wasn't a requirement for any assignment, I neverutilized it. I’m happy now that I did because some of the information is of high quality andexactly what I was looking for. For example, trying to Google-search about bungee cordsproduced ……... All in all, now that I know how to and where to find new information, I plan touse it for the future, starting with a Matlab vision project, and even for fun when I
the implementation of K-12 engineering education research. Furthermore, from this it can also be inferred that K-12 engineeringcurriculum might include lesson plans with pertinent information from these top fields. The social network analysis results reveal that there is a high trend of collaboration betweenauthors in the K-12 EngER community. Krause, S. was found to be the most collaborative author— whoalso had a significant position as a bridge for communication for other authors in this field in addition toRoberts, C. The fact that the two most collaborative authors are connected is a good sign; however, morecollaboration could greatly improve the field as a whole. Overall, more work needs to be done in thisfield in order to make
learnengineering content and skills.“No gender difference in the importance of engineering skills for children”Regarding the importance of engineering education, there was no different between boys andgirls. To be precise, one of the items in attitude scale that had the highest score (M = 4.42) was:“I think it is equally important for both girls and boys to learn engineering.” This is reinforcedthrough the ratings for two additional items: “I think it is more important for boys to learnengineering than it is for girls to learn engineering (M = 2.0)” and “I think it is more importantfor girls to learn engineering than it is for girls to learn engineering (M = 2.0)”The work presented in the paper has many implications. While we plan to collect additional
prescribed in a planned sequence to allow students to scaffold critical newknowledge on top of core concepts learned in earlier classes. Students that have difficulty andwithdraw from the core gateway classes risk disrupting the course-taking progression,complicate their ability to register for courses in subsequent semesters, and may requireadditional time to complete their degree. Identifying these students at an earlier point providesmore time to offer supportive interventions and encourage them to consider alternative academic Page 24.586.5strategies besides withdrawing. The study is envisioned as part of a broader analysis to identifystudents