the Massachusetts Institute of Technology, and four degrees from Columbia University: an M.S in Anthropology, an M.S. in Computer Science, a B.A. in Mathematics, and a B.S. in Applied Mathematics. Hammond mentored 17 UG theses (and many more non-thesis UG through 351 undergraduate research semesters taught), 29 MS theses, and 9 Ph.D. dissertations. Hammond is the 2020 recipient of the TEES Faculty Fellows Award and the 2011-2012 recipient of the Charles H. Barclay, Jr. ’45 Faculty Fellow Award. Hammond has been featured on the Discovery Channel and other news sources. Hammond is dedicated to diversity and equity, reflected in her publications, research, teaching, service, and mentoring. More at http://srl.tamu.edu
, findings, and conclusions, and recommendations expressed in thisreport are those of the authors and do not necessarily reflect the views of the NSF.References[1] R. Sowell, Doctoral Initiative on Minority Attrition and Completion., Washington, DC: Council of Graduate Schools, 2015.[2] M. Ong, C. Wright, L. L. Espinosa, and G. Orfield, “Inside the double bind: A Synthesis of empirical research on undergraduate and graduate women of color in science, technology, engineering, and mathematics,” Harv. Educ. Rev., vol. 81, no. 2, pp. 172–208, Jun. 2011, doi: 10.17763/haer.81.2.t022245n7x4752v2.[3] M. Cabay, B. L. Bernstein, M. Rivers, and N. Fabert, “Chilly climates, balancing acts, and shifting pathways: What happens to
some engineering disciplines at the larger schools also study rigid body dynamicsat the second-year level. Two instructors (Region 1) were funded by BCcampus, and workedclosely together. The third instructor (Region 2) was funded by the Association of ProfessionalEngineers and Geoscientists of Saskatchewan (APEGS), the provincial professional engineeringregulator. We also focused on different strategies and priorities for problem creation: a largebank of fundamental questions (Site 2) versus fewer, more complex questions (Sites 1A and 1B).This is reflected in our estimates for problem cost: excluding learning objective development andother start-up time, Site 2 estimated $16 CAD/problem in student and faculty time, while Sites1A and 1B
an explanation can be found in the published dissertation. Asis traditionally followed in IRT, item fit statistics were obtained. Cut-off criteria for a reasonablefit were SRMR and RMSEA < 0.08, CFI and TLI > 0.90 or 0.95 [43]. Items with |Yen’s Q3| >0.20 (Q3 fit statistic represents the correlation between the residuals for a pair of items) has localdependence and significant item fit values (p < 0.05) revealed misfit items [44]. Finally, itemand test information functions graphically reflected the reliability (1 - [1 / peak information]) ofthe items and the test as a whole in estimating the construct over the entire scale range [45].FIGURE 3. Hypothesized 2-D measurement model for the APT-STEM instrument [12]ResultsThe results
thinking, data modeling, communication, reproducibility and ethics [11]. In a similar study [13], researchers monitored trends across Europe in order to assess thedemands for particular Data Science skills and expertise. They [13] used automated tools for theextraction of Data Science job posts as well as interviews with Data Science practitioners. Thegoal of the study [13] was to find the best practices for designing Data Science curriculum whichinclude; industry aligned, use of industry standard tools, use of real data, transferable skill set,and concise learning goals. The best practices for delivery of Data Science Curriculum includemultimodality, multi-platform, reusable, cutting-edge quality, reflective and quantified, andhands-on. In
science (statistician,computer scientist, industrial engineering, operations researchers, etc.) are in-demand and requirehighly skilled professionals with knowledge of data science, which has resulted in a highlycompetitive labor market. While the median annual salary for data scientists is quite high, about$122,000, according to the BLS, this reflects the higher educational, experience, and skill levelrequirements needed for such positions, as well as geographical differences related to keyemployer locations.Employers have recognized that data science professionals will be a critical resource to theiroperational excellence, as well as for the future of their innovation ecosystems. This need fordata science professionals has naturally driven an
learn the material and could complete the experiment without instructor intervention.Henke et al [4] used a hybrid approach where students are able to design control algorithms tocontrol electro-mechanical models in the online lab. In this format, the experiment actually takesplace, and the data reflects interactions between physical devices, not virtual entities. However,these remote web-accessible laboratories are in some respect similar to simulations in that thestudent does not have to be co-located with a particular piece of laboratory apparatus. Nedic et al.[5] developed remotely controlled labs called NetLab that allows multiple students to run anexperiment remotely in real time. Amiguid et al. [6] evaluated 100 web-based remote labs
varyconsiderably and we found no evidence of programs sharing the same assessment instruments orprotocols. A few examples are below. They describe evaluation from different viewpoints and we presentthem here to show examples of the diversity of methods employed, and some research outcomes andreflections. • One paper described the use of specific assessment methods including competency rubrics, individual development plans, and ePortfolios for evaluation (Chang, Semma, Fowler, & Arroyave, 2021). The rubrics encompassed professional and technical skills including: 1) interdisciplinary knowledge generation, 2) collaboration, 3) conflict resolution, 4) oral communication, 5) written communication, 6) self-reflection, 7
perspective, we assume the following principles: problematize status quo,look at the use of language as clues to how ways of thinking and behaviour are structured, lookfor existing mechanisms of inequality, and look for creative alternatives for a more just/equitableoutcome.First, in order to describe what mechanisms of exclusion exist and become significant in studentexperiences, we looked for student accounts of their direct experiences (e.g. of barriers to fullparticipation in engineering education). Students also reflected on their observations on thecontrast between exclusion and inclusion. This resulted in the identification of: the location ofrepresentation gap that became influential; socially-mediated mechanisms that actually lead
STEM Education (IUSE) program under Award Numbers DUE-1562773 and DUE-1525112. Any opinions, findings, and conclusions expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation. The authorswould like to thank the reviewers for their thoughtful and encouraging feedback on improving thepaper.References [1] C. Ebert and S. Counsell, “Toward software technology 2050,” IEEE Software, vol. 34, no. 4, pp. 82–88, 2017. [2] H. Krasner, “The cost of poor quality software in the us: A 2018 report,” Consortium for IT Software Quality (CISQ), September 2018, https://cra.org/data/Generation-CS/ (retrieved August, 2020). [3] R. Florea and V. Stray, “A global view on the hard skills
included teachers explaining how to usestudents’ computational models to test their designs or guiding students to reflect on their priorknowledge to consider how certain materials may or may not be accessible to students withphysical disabilities.Table 4. Epistemic, practical, or not practice-based teacher talk by class. Epistemic Practical Not Practice-Based Lesson Orange Blue Orange Blue Orange Blue All Lessons 7% 17%+ 66% 67% 27%+ 16% Design 6% 15%+ 66% 75%+ 28%+ 10% Test 0% 11%+ 82% 79% 18%+ 11% Communicate 12
iGens or not. The observations of the authors thus farsuggest that many STEM university students reflect the iGen trends and are no different.Helping iGen Prepare for the Workplace and LifeAs students enter the university, there is an implied requirement to help students mature fromwhere they are to where they need to be upon graduation. Van Treuren and Jordan addressed therole of the university in the formation of student maturity [18]. The university is a communitywhere personal development occurs. A function of the university is embodied in the phrase “inloco parentis.” Legally, it means “in place of a parent” and refers to the obligation of a person ororganization to take on some of the functions and responsibilities of a parent. At any
exploring constructionist learning for a new generation of young people. In after-school and out-of-school settings, educational robotics became uniquely supportive for applyingconstructionism to engineering design education [22]. Similar to the early promotion of Logo,the hands-on engineering design affordances of educational robotics is purported to advance stu-dents’ knowledge and skills by flattening the hierarchy between concrete and formal thinking[23], [24], [25], [15]. As children engage in robotics activities they are given the opportunity to learn-by-doing,a foundation to constructionist design that reflects real world enterprises and encourages the ma-terial exploration of “big ideas” [26], [12], [2], [27]. Robotics kits for out
undergraduate mentors to reflect on theirassumptions. They re-conceptualized learning as a collaborative action as opposed to thetransmission of knowledge from a teacher to students [23] and overcame their frustrations andstruggles with the program. Accordingly, they began to play the role of a collaborator and partnerwith children and developed productive and meaningful learning experiences for themselves andthe children.In our work, for several years, we have been implementing workshops for teachers and theirstudents, to allow them to jointly learn the fundamental concepts, engineering design, andengineering practices through hands-on learning with robotics. Using the characteristics ofinformal learning [16], we identify our workshops as a semi
differences in the mean between the two samples. In thisstudy, statistical significance is assumed to be referring to a significance level of 5%. It isclarified that, although a more accurate statistical analysis that would account for properprobability distributions and sample sizes is possible, the analysis presented here is consideredsufficient to identify trends within the context of this study.According to these tables, the proposed assessment model clearly improves the quality of courseinstruction and learning environment during the semester and results in higher studentsatisfaction, particularly as this latter is reflected in the overall rating of the course and instructor(Q7/Q8 and Q16 in Tables 1 through 6, and several questions in Tables 7
: “Compared to other PD I participated (not a part of the SfT PD series),the amount I learned in this PD was:” 66.4% answer Much more, 23,7% Somewhat more and8.6% About the same. This affirmative answer is also reflected in the responses of the open-ended questions.When asked the question: “Overall, the course was:” 71.1% answer Excellent and 25.7%answerVery good.4.2.1.3 – Open-ended questionsAfter reviewing the response of the open-ended questions, it is possible to see some patterns.These common constructs are presented below:To the question: "What elements of the PD most contributed to your learning?", the vastmajority expressed that the use of hands-on activities to develop the concepts. Also, to constructthe artifacts involved in each module was
level contributes to this vision. Despite some gains in recent decades, women faculty inengineering are still underrepresented. Between 2006 and 2016, the proportion of women facultyin engineering grew from 16% to 23% at the assistant level, from 11.9% to 18.3% at theassociate level, and from 3.8% to 10.6% at the full professor level [2], [3]. While the proportionof women faculty at the lower ranks has increased significantly, the limited representation ofwomen at higher faculty ranks limits their potential for reaching leadership roles andcontribution with significant decision-making to influence engineering education [4]. Althoughthe presented gains are of value, and may already reflect the effect of multiple initiativesimplemented to support
change their institution’s policies and practices, they are also seeking out mentors [10],[12], and [23]-[27], and networks of mentors [11], [12], [19] to provide strategies and support asthey move through their academic lives. This paper provides four examples of conferencesdeveloped by universities as an avenue to build communities for women of color who are currentor prospective faculty members. Goals, strategies, outcomes, and lessons learned from each ofthe conferences are described. The strategies reflect the varying cultures of the institutions andindividuals involved in developing them. The paper concludes with a summary of actions theseuniversities are taking forward to continue to build communities and networks for current
and flagged to generate a listing of internally consistent, discretecategories (open coding), followed by fractured and reassembled (axial coding) of categories bymaking connections between categories and subcategories to reflect emerging themes andpatterns. Categories were integrated to form grounded theory (selective coding), to clarifyconcepts and to allow for interview interpretations, conclusions and taxonomy development.Frequency distribution of the coded and categorized data were obtained using a computerizedqualitative analytical tool, Hyperrresearch® version 3.5.2. The intent of this intensive qualitativeanalysis was to identify patterns, make comparisons, and contrast one transcript of data withanother during our taxonomy and CPPI
correctly. Also, those who did not know the rules regardingfriction force could not predict correctly or changed their ideas to correct ones after engagingwith the PMT. These findings are aligned with prior studies that claimed that the PMT is not asufficient tool itself to improve physics content knowledge (Triona & Klahr, 2003; Zacharia, andOlympiou, 2011). Identifying false affordances that leads to misconceptions and perceptible affordances of PMT,can help to inform the design of visuo-haptics simulations that considers the learner as the centerof the design process. For instance, a perceptible affordance of the PMT we identified was thatthe sense of touch helps participants to explain and reflect about their reasoning of each scenario.We
curriculum.AcknowledgementsThis project is supported by the National Science Foundation through the ImprovingUndergraduate STEM Education (IUSE) program, Award No. DUE ########. Any opinions,findings, and recommendations expressed in this paper are those of the authors and do notnecessarily reflect the views of the National Science Foundation.REFERENCES President’s Council of Advisors on Science and Technology (PCAST) (2012). Engage to excel: Producing one million additional college graduates with degrees in science, technology, engineering, and mathematics. Retrieved from http://www.whitehouse.gov/sites/default/files/microsites/ostp/pcast-engage-to-excel-final_2-25- 12.pdf National Research Council and National Academy of Engineering (2012). Community
programdifferentiates it from clubs and extracurricular activities. Participation in VIP earns studentscredits toward their degree requirements, engaging students who might not otherwise have timefor extracurricular activities. The grading aspect holds students accountable for theirperformance, with letter grades maintaining a higher level of engagement than do pass/failgrades. In support of the grading and evaluation, VIP programs require students to maintainrigorous documentation of their efforts, typically in the form of VIP notebooks or institution-approved electronic portfolios. VIP programs also involve peer evaluations, reflecting the team-based nature of the course. Georgia Tech has developed a web-based peer evaluation tailored toVIP, which will soon
questions. First andforemost, the responses emphasize the importance of investing time and resources in educatingyour own undergraduates about the options available to them at their home academic institution.As reflected in the data, a number of students will opt to stay an additional fifth year to obtain amaster’s degree especially when they are not considering continuing on to a Ph.D. Furthermore,keeping faculty informed of your programs will pay dividends during the recruiting season. Evenin this advanced technological age, quality students continue to reach out to faculty members foradvice on where to attend graduate school. The combined response totals for interactions withfriends or program alumni as a significant factor in their decision to