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Register a new userQuantitative Assessment of Solution Innovation in Engineering Education
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Added by
Vladimir Ivanov
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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The article discusses the quantitative assessment approach to the innovation of engineering system components. The validity of the approach is based on the expert appraisal of the universitys electronic information educational environment components and the measurement of engineering solution innovation in engineering education. The implementation of batch processing of object innovation assessments is justified and described.
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The article presents the possibilities of using game simulator Sotware Inc in the training of future software engineer in higher education. Attention is drawn to some specific settings that need to be taken into account when training in the course of training future software engineers. More and more educational institutions are introducing new teaching methods, which result in the use of engineering students, in particular, future software engineers, to deal with real professional situations in the learning process. The use of modern ICT, including game simulators, in the educational process, allows to improve the quality of educational material and to enhance the educational effects from the use of innovative pedagogical programs and methods, as it gives teachers additional opportunities for constructing individual educational trajectories of students. The use of ICT allows for a differentiated approach to students with different levels of readiness to study. A feature of any software engineer is the need to understand the related subject area for which the software is being developed. An important condition for the preparation of a highly qualified specialist is the independent fulfillment by the student of scientific research, the generation, and implementation of his idea into a finished commercial product. In the process of research, students gain knowledge, skills of the future IT specialist and competences of the legal protection of the results of intellectual activity, technological audit, marketing, product realization in the market of innovations. Note that when the real-world practice is impossible for students, game simulators that simulate real software development processes are an alternative.
Educational technologies, and the systems of schooling in which they are deployed, enact particular ideologies about what is important to know and how learners should learn. As artificial intelligence technologies -- in education and beyond -- have led to inequitable outcomes for marginalized communities, various approaches have been developed to evaluate and mitigate AI systems disparate impact. However, we argue in this paper that the dominant paradigm of evaluating fairness on the basis of performance disparities in AI models is inadequate for confronting the structural inequities that educational AI systems (re)produce. We draw on a lens of structural injustice informed by critical theory and Black feminist scholarship to critically interrogate several widely-studied and widely-adopted categories of educational AI systems and demonstrate how educational AI technologies are bound up in and reproduce historical legacies of structural injustice and inequity, regardless of the parity of their models performance. We close with alternative visions for a more equitable future for educational AI research.
In the past few years, we have observed a huge supply-demand gap for autonomous driving engineers. The core problem is that autonomous driving is not one single technology but rather a complex system integrating many technologies, and no one single academic department can provide comprehensive education in this field. We advocate to create a cross-disciplinary program to expose students with technical background in computer science, computer engineering, electrical engineering, as well as mechanical engineering. On top of the cross-disciplinary technical foundation, a capstone project that provides students with hands-on experiences of working with a real autonomous vehicle is required to consolidate the technical foundation.
The goal of TFPIE is to gather researchers, professors, teachers, and all professionals interested in functional programming in education. This includes the teaching of functional programming, but also the application of functional programming as a tool for teaching other topics. The post-workshop review process received 13 submissions, which were vetted by the program committee, assuming scientific journal standards of publication. The six articles in this volume were selected for publication as the result of this process.
Digital Engineering, the digital transformation of engineering to leverage digital technologies, is coming globally. This paper explores digital systems engineering, which aims at developing theory, methods, models, and tools to support the emerging digital engineering. A critical task is to digitalize engineering artifacts, thus enabling information sharing across platform, across life cycle, and across domains. We identify significant challenges and enabling digital technologies; analyze the transition from traditional engineering to digital engineering; define core concepts, including digitalization, unique identification, digitalized artifacts, digital augmentation, and others; present a big picture of digital systems engineering in four levels: vision, strategy, action, and foundation; briefly discuss each of main areas of research issues. Digitalization enables fast infusing and leveraging novel digital technologies; unique identification enables information traceability and accountability in engineering lifecycle; provenance enables tracing dependency relations among engineering artifacts; supporting model reproducibility and replicability; helping with trustworthiness evaluation of digital engineering artifacts.
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