Cross Disciplinary Perceptions of the Computational Thinking among Freshmen Engineering Students

In this paper, we analyzed the perception of Computational Thinking among engineering students from three engineering disciplines (Electrical, Mechanical, and Civil) and correlated their performance with their discipline. The goal of this analysis is to determine whether structuring discipline-specific Computational Thinking courses can improve the retention or having a diverse group of students in this course is more beneficial by allowing multidisciplinary interaction. This analysis was quantitatively verified by assessing the students\u27 performance in over 40 different sections of Computing for Engineers course taught from Fall 2012 to Spring 2014. Our sample consisted of 861 students (142 Civil, 484 Mechanical, and 235 Electrical). Students’ performance was assessed using quizzes, assignments, lab projects, and exams. We statistically analyzed students\u27 performance in this multi-section course to draw our conclusions which can help structuring Computational Thinking courses for engineering students from different engineering disciplines

Symbolic Manipulators Affect Mathematical Mindsets

Symbolic calculators like Mathematica are becoming more commonplace among upper level physics students. The presence of such a powerful calculator can couple strongly to the type of mathematical reasoning students employ. It does not merely offer a convenient way to perform the computations students would have otherwise wanted to do by hand. This paper presents examples from the work of upper level physics majors where Mathematica plays an active role in focusing and sustaining their thought around calculation. These students still engage in powerful mathematical reasoning while they calculate but struggle because of the narrowed breadth of their thinking. Their reasoning is drawn into local attractors where they look to calculation schemes to resolve questions instead of, for example, mapping the mathematics to the physical system at hand. We model the influence of Mathematica as an integral part of the constant feedback that occurs in how students frame, and hence focus, their work

Computing Foundations for the Scientist

There is a need for a new style of supporting a computer course. Although it is widely recognized that computer technology provides essential tools for all current scientific work, few university curricula adequately ground science majors in the fundamentals that underlie this technology. Introducing science students to computational thinking in the areas of algorithms and data structures, data representation and accuracy, abstraction, performance issues, and database concepts can enable future scientists to become intelligent, creative and effective users of this technology. The intent of this course is not to turn scientists into computer scientists, but rather to enhance their ability to exploit computing tools to greatest scientific advantage

Trialing project-based learning in a new EAP ESP course: A collaborative reflective practice of three college English teachers

Currently in many Chinese universities, the traditional College English course is facing the risk of being ‘marginalized’, replaced or even removed, and many hours previously allocated to the course are now being taken by EAP or ESP. At X University in northern China, a curriculum reform as such is taking place, as a result of which a new course has been created called ‘xue ke’ English. Despite the fact that ‘xue ke’ means subject literally, the course designer has made it clear that subject content is not the target, nor is the course the same as EAP or ESP. This curriculum initiative, while possibly having been justified with a rationale of some kind (e.g. to meet with changing social and/or academic needs of students and/or institutions), this is posing a great challenge for, as well as considerable pressure on, a number of College English teachers who have taught this single course for almost their entire teaching career. In such a context, three teachers formed a peer support group in Semester One this year, to work collaboratively co-tackling the challenge, and they chose Project-Based Learning (PBL) for the new course. This presentation will report on the implementation of this project, including the overall designing, operational procedure, and the teachers’ reflections. Based on discussion, pre-agreement was reached on the purpose and manner of collaboration as offering peer support for more effective teaching and learning and fulfilling and pleasant professional development. A WeChat group was set up as the chief platform for messaging, idea-sharing, and resource-exchanging. Physical meetings were supplementary, with sound agenda but flexible time, and venues. Mosoteach cloud class (lan mo yun ban ke) was established as a tool for virtual learning, employed both in and after class. Discussions were held at the beginning of the semester which determined only brief outlines for PBL implementation and allowed space for everyone to autonomously explore in their own way. Constant further discussions followed, which generated a great deal of opportunities for peer learning and lesson plan modifications. A reflective journal, in a greater or lesser detailed manner, was also kept by each teacher to record the journey of the collaboration. At the end of the semester, it was commonly recognized that, although challenges existed, the collaboration was overall a success and they were all willing to continue with it and endeavor to refine it to be a more professional and productive approach

Investigating an Instructional Model for Integrated STEM in Teacher Education

Active learning experiences that incorporate technology, design, and making combine to form an important and necessary pedagogical approach that supports the 21st century skills of collaboration, communication, creativity, digital literacies, and computational thinking as a problem-solving framework. Active learning experiences in teacher preparation serve as a model for future educators to follow, while building the educators\u27 efficacy to conduct future implementations with their own students. In this study, a multidisciplinary Pop-Up Makerspaces activity was conducted as an active hands-on approach to interdisciplinary STEM education. The intersectionality of English language arts with integrated STEM through design and making included: (a) enriching language and integrated STEM literacy, (b) scaffolding and supporting pre- and inservice educators through well-designed active learning as these opportunities help to develop self-efficacy, and (c) exploring new models and frameworks for transdisciplinarity

Engaging Minority Students in Sustainable Bioenergy and Water Quality through an Education and Research Network

Growing energy demand is connected to water availability and climate change and it places additional stress on the environment. Thereby, It is critical to prepare the next generation of engineers and professionals to face the challenges in bioenergy, expand sustainable alternatives to fossil fuels1 and enable climate-smart agriculture2,3. To address this challenge, a career-oriented multidisciplinary educational model is being implemented at three minority-serving institutions. This paper discusses the foundation of this educational program, which provides a robust response to the current sustainability issues by conducting multidisciplinary coordinated education, mentoring, research and extension activities among multiple universities and laboratories. This educational program aims to accomplish the ultimate goal of increasing minority participation in pursuing advanced degrees in STEM and attaining a diverse highly trained and skillful workforce with a strong pragmatic, experimental, analytical and computational background as well as scientific literacy in sustainable energy and the energywater nexus. In this model, students are expected to gain knowledge and understanding of the operational complexity of sustainable energy systems from source-to-use. Students will be able to conduct research and discovery from the feedstock properties passing through the conversion technologies to the mathematical modeling and optimization of the whole bioenergy value chain. In addition, students will be able to translate their findings in the laboratory regarding water quality and treatment into operational parameters to be included in comprehensive water systems models

I Decide, Therefore I Am (Relevant!): A Project-Based Learning Experience in Linear Algebra

We present a project-based learning experience in the context of linear algebra developed for the recently launched double major in business administration and management/engineering of technology and telecommunication services at the universitat politecnica de valencia 2014-15. Decision-making is used to motivate students towards applying, understanding, and appreciating linear algebra in a diversity of projects. this experience introduces students to the analytic hierarchy process (AHP), a multi-attribute, decision-making technique that is rooted in linear algebra. Through a simulation scenario, each team of students develops a project about any real-world problem consisting of a decision-making process in the presence of multiple intangibles. At the same time, the algebraic fundamentals that make the process valid and consistent are clarified. The students showed great interest in the experience; and the results obtained confirmed that the activities helped them understand several complex concepts related to linear algebra, and fostered a significant interest in a subject traditionally considered frighteningly abstract. Finally, the students appreciated the stimulating insights provided by linear algebra that are crucial in decision-making. This multi-disciplinary experience enables the evaluation of several cross skills and competencies such as critical thinking and ethical leadership. (C) 2016 Wiley Periodicals, Inc.Izquierdo Sebastián, J.; Benítez López, J.; Berenguer, A.; Lago-Alonso, C. (2016). I Decide, Therefore I Am (Relevant!): A Project-Based Learning Experience in Linear Algebra. Computer Applications in Engineering Education. 24(3):481-492. doi:10.1002/cae.21725S481492243Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). 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V., & Tai, R. H. (2011). Pipeline persistence: Examining the association of educational experiences with earned degrees in STEM among U.S. students. Science Education, 95(5), 877-907. doi:10.1002/sce.20441L. C. Wilcox M. S. WilcoxHOTALING, N., FASSE, B. B., BOST, L. F., HERMANN, C. D., & FOREST, C. R. (2012). A Quantitative Analysis of the Effects of a Multidisciplinary Engineering Capstone Design Course. Journal of Engineering Education, 101(4), 630-656. doi:10.1002/j.2168-9830.2012.tb01122.xSaaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234-281. doi:10.1016/0022-2496(77)90033-52015 http://bie.org/about/why_pblBenítez, J., Delgado-Galván, X., Izquierdo, J., & Pérez-García, R. (2011). Achieving matrix consistency in AHP through linearization. Applied Mathematical Modelling, 35(9), 4449-4457. doi:10.1016/j.apm.2011.03.013Benítez, J., Delgado-Galván, X., Gutiérrez, J. A., & Izquierdo, J. (2011). Balancing consistency and expert judgment in AHP. Mathematical and Computer Modelling, 54(7-8), 1785-1790. doi:10.1016/j.mcm.2010.12.023Benítez, J., Izquierdo, J., Pérez-García, R., & Ramos-Martínez, E. (2014). A simple formula to find the closest consistent matrix to a reciprocal matrix. Applied Mathematical Modelling, 38(15-16), 3968-3974. doi:10.1016/j.apm.2014.01.007Elmer, F., Seifert, I., Kreibich, H., & Thieken, A. H. (2010). A Delphi Method Expert Survey to Derive Standards for Flood Damage Data Collection. Risk Analysis, 30(1), 107-124. doi:10.1111/j.1539-6924.2009.01325.xIsasi, P., Quintana, D., Saez, Y., & Mochon, A. (2007). APPLIED COMPUTATIONAL INTELLIGENCE FOR FINANCE AND ECONOMICS. Computational Intelligence, 23(2), 111-116. doi:10.1111/j.1467-8640.2007.00297.xBenítez, J., Delgado-Galván, X., Izquierdo, J., & Pérez-García, R. (2012). An approach to AHP decision in a dynamic context. 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Computational Thinking in Education: Where does it fit? A systematic literary review

Computational Thinking (CT) has been described as an essential skill which everyone should learn and can therefore include in their skill set. Seymour Papert is credited as concretising Computational Thinking in 1980 but since Wing popularised the term in 2006 and brought it to the international community's attention, more and more research has been conducted on CT in education. The aim of this systematic literary review is to give educators and education researchers an overview of what work has been carried out in the domain, as well as potential gaps and opportunities that still exist. Overall it was found in this review that, although there is a lot of work currently being done around the world in many different educational contexts, the work relating to CT is still in its infancy. Along with the need to create an agreed-upon definition of CT lots of countries are still in the process of, or have not yet started, introducing CT into curriculums in all levels of education. It was also found that Computer Science/Computing, which could be the most obvious place to teach CT, has yet to become a mainstream subject in some countries, although this is improving. Of encouragement to educators is the wealth of tools and resources being developed to help teach CT as well as more and more work relating to curriculum development. For those teachers looking to incorporate CT into their schools or classes then there are bountiful options which include programming, hands-on exercises and more. The need for more detailed lesson plans and curriculum structure however, is something that could be of benefit to teachers

The Case for Improving U.S. Computer Science Education

Despite the growing use of computers and software in every facet of our economy, not until recently has computer science education begun to gain traction in American school systems. The current focus on improving science, technology, engineering, and mathematics (STEM) education in the U.S. school system has disregarded differences within STEM fields. Indeed, the most important STEM field for a modern economy is not only one that is not represented by its own initial in "STEM" but also the field with the fewest number of high school students taking its classes and by far has the most room for improvement—computer science