instructors adopted digital technologies “as a replacement forthe missing physical learning environments, with the learning process remaining the same. Thisresulted in ineffective learning when compared to traditional face-to-face learning environments”(p. 294). 82 students in the Qatar study participated in written reflections about their experiencesand eight students were interviewed. The students felt that the emergency remote learningenvironment needed to “be supported by teaching activities that involve more participationthrough interactive activities and teamwork” [15, p. 13]. Overall, the surveys and interviewsshowed that the quality of instruction suffered after the move to remote teaching in Spring 2020.MethodologyThe results in this paper
training of mathematics teachers that is at the core of this problem. Since enrollment at UIC, Janet had dedicated her studies and research efforts on Mathematics Socialization and identity amongst pre-service elementary teachers, an effort at understanding the reasons for lack of interest in the subject with a view to proffer solution and engender/motivate interest amongst this group that will eventually reflect in their classroom practices. She is currently a Graduate Assistant with UIC Engage, a commu- nity focused project that provides help for less-privileged students from K-8 in mathematics, reading and writing. She continues to work as a substitute teacher occasionally to keep abreast with current practices
capstone supporters hasdelivered a set of ideas, options, and solutions, and further built community.Many of the recommendations in the numbered list above can be adopted going forwardregardless of the course delivery mode, major, setting, or product form. In the abrupt transitionto virtual capstone conditions, capstone leaders and stakeholders made the pivot, demonstratedagile thinking, reflected on lessons learned, and have adeptly identified best practice for futurecapstone offerings. This work could not be accomplished without these dedicated and responsivepractitioners.REFERENCES[1] T. Vander Ark, “Remote Learning Could Be A Good Time For A Capstone Project,” Apr. 2020. https://www.forbes.com/sites/tomvanderark/2020/04/02/remote-learning
, Microsoft, and others. Hammond holds a Ph.D. in Computer Science and FTO (Finance Technology Option) from 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 and Physics. Hammond advised 17 UG theses, 29 MS theses, and 10 Ph.D. dissertations. Hammond is the 2020 recipient of the TEES Faculty Fellows Award and the 2011 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, which is reflected in her publications, research, teaching, service, and
thecodebook, we finalized a codebook, based on the data collected, describing communication onvirtual teams experienced by a majority of participants (Table 2). The development andrefinement of the codebook is illustrated in Figure 2 from [15]. Figure 2: Illustration of the development and refinement of the codebook adapted from [15]Prior to analysis, the two members of the research team who lead the coding process (Researcher1 and Researcher 2) wrote positionality statements reflecting on their experiences working onteam projects. These statements were reviewed throughout the analysis process to encourage usto think about how our experiences might impact data analysis.Researcher 1My name is Nathaniel Blalock I am pursuing a degree in chemical and
. There is aseparable outcome one is trying to obtain or avoid, such as a reward or punishment. Commonexternal factors are grades or evaluations, which are metrics that have been constructed to“measure” a student’s success and serve as motivation for improvement. Another type ofexternal factor can be derived from another person, such as the opinion of a mentor, friend, orpeer. Intrinsic motivation comes from internal drives and is defined as doing an activity for itsinherent satisfaction [12]. These actions reflect ideas like core values, personal interests, andone's sense of morality. Intrinsic and extrinsic motivation are considered to be part of the "locusof causality," meaning they are the perceived sources of motivation.The study of rural
visualization embedded in the textbook. These visualizationswere integrated in the e-textbook and offered students the chance to see aspects of iterationdemonstrated immediately after the relevent paragraph.The design of the visualization reflected the appearance of the block-based language the studentswere using on their first encounter with iteration. The horizontal green segmented rectangle is thelist which moves from right to left on each iteration so that a single list item becomes the value ofthe iteration variable (”price” in this example). Figure 1: Example of a Textbook VisualizationTo interact with these visualizations, students clicked on the four arrow icons seen at the top ofthe figure. Clicking the ‘¿’ button
multidisciplinary use. We hope that the analysis and reflections on our initial offeringshas improved our understanding of these challenges, and how we may address them whendesigning future data science teaching modules. These are the first steps in a design-basedapproach to developing data science modules that may be offered across multiple courses.1. Introduction As technology advances, familiarity and expertise in data-driven analysis is becoming anecessity for jobs across many disciplines. Data science is an emerging field that encompasses alarge array of topics including data collection, data preprocessing, data quality, data visualization,and data analysis using statistical and machine learning methods. A recent National Academy ofSciences
college consistently ranked at the bottom of student concerns across everyyear and engineering major. We also needed a better understanding of how the studentsexperienced the program structure of our women in engineering program and if it could beimproved to better reflect the needs of this new student cohort. Finally, we wanted to know howprevalent these declining engagement trends were on campus and what, if any, steps could betaken to improve them. This paper focuses on focus groups held with undergraduate women inengineering students, and contextual interviews held with other campus programs, clubs andorganizations. First, we present a summary of what we learned about this new cohort of studentsas well as the key survey findings that informed
approaches related to airport challenges. The design competitionrequires student teams to interact with airport operators and industry experts to get input on theirdesign ideas and solution [2]. This paper explores the number and value of these interactions byevaluating the winning design proposals.Statistics are used to analyze trends in the winning design proposals which may reflect theimportance of number of the experts contacted by student teams and their demographics. Thewinning design proposals contain written sections that discuss the team’s reported benefits oftheir interactions with industry experts. Thematic analysis is used to identify themes for designproposals from first, second, and third place teams. The paper presents a study of
departments.AcknowledgmentsThis material is based upon work supported by the National Science Foundation (NSF) No.EEC-1653140 and 2123016 given to the second author. Any opinions, findings, and conclusionsor recommendations expressed in this material do not necessarily reflect those of the NSF. Wewant to give a special thanks to the institutional liaisons, Dr. Hector Cruzado, Dr. Sindia Rivera-Jimenez, Dr. Heather Shipley, Dr. Kimberly Cook-Chennault, and Dr. Paul Barr who assisted uswith collecting participant data in the first stage of sampling. We also want to thank theparticipants for sharing their experiences with us and the readers of this work.References[1] National Center for Science and Engineering Statistics, “Women, Minorities, and Persons with
for women in science expanded but gendersegregation still existed. In the nineteenth century, women participated in aspects of science butmainly engaged in data-gathering rather than idea-creation [26] and were largely invisible andconcentrated in nurturing career tracks [39]. Prior to the 20th century and beyond, womensupported science but not pioneers in the field; reflective of the patriarchal society they lived in.Commonly known as biological determinism, the physical, psychological, and intellectual natureof women prohibited them from producing great science [38]. The Nineteenth and earlyTwentieth centuries posited if women were incorporated into scientific employment, they weresegregated in it with stereotypes of appropriate sex roles
futureprojects after receiving their feedback from CP 1.The decrease in scores for CP 3 can be attributed to the type of project it is compared to the other projectsin the course. It is the truss analysis program that introduces some linear algebra concepts that studentshave not had much exposure to, and the code theory does not follow the same method as handcalculations for trusses. Also, the route for verification and exploration is more open-ended than the otherprojects (at least that is how students view it) and this is reflected in their overall scores. The value of thisproject, however, can be built upon in future courses for more complex system analysis and often studentsreflect on this project as they get into those upper-division classes.There
rooted at the intersection of my identity as ablack woman. I have had to defend myself at times against tenured professors and illuminatemaltreatment and disrespect. The most frequent abuses I have experienced were at the handsStaff Researchers that direct and maintain campus user facilities (like a cleanroom, or an opticalanalysis laboratory). A Staff Researcher or technician (white males in my instances) either threwaway equipment while I was using it (disposing of my gloves while I was using the scanningelectron microscope) or antagonizing and questioning my “right” to be in the space, in aninstance where I was using an x-ray diffraction tool in a characterization laboratory.Summary: Panelists describe both internal reflection and external
all perspectives.Heuristic for an Accomplice’s Ethic of Care and AccountabilityIn order to establish coalitional accomplice relationships that appreciate and celebrate difference,the authors suggest three heuristic activities that can establish trust and build a sharedunderstanding. This heuristic reflects a Black Feminist epistemology, not only because it is builtin pursuit of an ethic of care but also because it invests in knowledge-making in action. ForBlack Feminist theorists, this means that the experiential knowing that occurs in situ establishesthe basis for relationships. Importantly, we use a heuristic because there is no one-size-fits allapproach to activist work or to establishing ally, advocate or accomplice relationships. Yet
Model [4], [5] andcompleting his learning style inventory survey. The results of the survey provide each studentwith rating on a scale of 1 to 11 regarding their preference for sensory versus intuitive, visualversus verbal, active versus reflective, and sequential versus global learning situations. Usingslides from the ASCE ExCEEd Teaching Workshop [6], the instructor explains what the learningstyle dimensions mean and provides insights as to how students can use this information to assistin their own learning. The survey sheets are collected, the data are assembled and the compositeresults for the entire course are shown at a later date. COVID format: This was one of two activities in the course that were conducted entirelyvirtually
and fears that impactedtheir mental health and reduced learning and performance.3. Adaptation Strategies: Adaptation strategies improved STEM learning(a) Relaxation Strategies: Seventy-seven percent (77%) of RPs tried to reduced stressesthrough relaxation strategies such as working out, taking breaks, meditation, reflection sheets,movies, family support, self-leniency, mental wellness visits, and other mental health strategies.One RP noted that, “Yeah, so, you know, I kind of, I forced myself to, uh, to at least get somephysical activity. Even If I didn't want to or not, I just knew I'd feel a little better, I was able tofocus a little better if I did."(b) Peer Collaboration: Seventy percent (70%) of RPs connected with their peers
last decades of the past half century suggest that while manyfactors are contributing to the actualization of “thinking machines”, paradigms about AI are acritical in translating AI research into effective, reliable and trustworthy real-world applicationsfor learning, health, automation and other domains.References1 Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journalof Artificial Intelligence in Education, 26(2), p.582-599.2 Schön, D. A. (c1983.). The reflective practitioner: How professionals think in action /. Basic Books,.3 Osoba, O. A., & Welser IV, W. (2017). An intelligence in our image: The risks of bias and errors in artificialintelligence. Rand Corporation
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