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Computing education, as a research discipline, is the study of how people come to understand computational processes and devices, and how to improve that understanding. As computation becomes ubiquitous in our world, understanding of computing in order to design, structure, maintain, and utilize these technologies becomes increasingly important – both for the technology professional, but also for the technologically literate citizen. The research study of how the understanding of computation develops, and how to improve that understanding, is critically important for the technology-dependent societies in which we live. Learning: Computing education is naturally concerned with how students make sense of computational processes and devices in formal education, including primary, secondary, and post-secondary institutions. Computing education also goes beyond formal education. What do adults understand about computation, and how do they come to that understanding? What do children understand about computation given their limited conceptions of time, process, and agency, and how does that affect their later formal learning about computation? Instruction: Learning may be enhanced or impeded by instruction. Educators bring instructional methods, formal or informal theories, and values to specific learning environments and situations. As researchers we explore the educators’ role in the learning process?whether that educator is a teacher, near-peer, remote resource or the computer itself. Computing Education Research employs methodologies from many fields, amongst them psychology, education, anthropology and statistics. As a consequence, research is frequently characterised by a diversity of methodological approaches; these may be applied directly, or may be combined and modified to suit the particular cross-disciplinary questions that we ask.

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Research areas of particular interest include:

  • discipline based education research (DBER) in computer science (CS), information sciences (IS), and related disciplines

  • learnability/usability of programming languages and the psychology of programming

  • pedagogical environments fostering computational thinking

  • design-based research, learner-centered design, and evaluation of educational technology supporting computing knowledge development

  • learning sciences work in the computing content domain

  • learning analytics and educational data mining in CS/IS content areas

  • informal learning experiences related to programming and software development (all ages), ranging from after-school programs for children, to end-user development communities, to workplace training of computing professionals

  • measurement instrument development and validation (e.g., concept inventories, attitudes scales, etc) for use in computing disciplines

  • research on CS/computing teacher thinking and professional development models at all levels

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重要日期
  • 会议日期

    09月09日

    2016

    09月11日

    2016

  • 09月11日 2016

    注册截止日期

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