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Titlebook: Big Data in Education: Pedagogy and Research; Theodosia Prodromou Book 2021 Springer Nature Switzerland AG 2021 learning analytics (LA).ed

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发表于 2025-3-21 20:00:52 | 显示全部楼层 |阅读模式
期刊全称Big Data in Education: Pedagogy and Research
影响因子2023Theodosia Prodromou
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发行地址Fills a gap in the research to the implications of the Big data revolution for statistics education and research.Gives direction to future research.Describes novel ways of visualising data and open da
学科分类Policy Implications of Research in Education
图书封面Titlebook: Big Data in Education: Pedagogy and Research;  Theodosia Prodromou Book 2021 Springer Nature Switzerland AG 2021 learning analytics (LA).ed
影响因子.This book discusses how Big Data could be implemented in educational settings and research, using empirical data and suggesting both best practices and areas in which to invest future research and development. It also explores: 1) the use of learning analytics to improve learning and teaching; 2) the opportunities and challenges of learning analytics in education...As Big Data becomes a common part of the fabric of our world, education and research are challenged to use this data to improve educational and research systems, and also are tasked with teaching coming generations to deal with Big Data both effectively and ethically..The Big Data era is changing the data landscape for statistical analysis, the ways in which data is captured and presented, and the necessary level of statistical literacy to analyse and interpret data for future decision making. The advent of Big Data accentuates the need to enable citizens to develop statistical skills, thinking and reasoning needed for representing, integrating and exploring complex information..This book offers guidance to researchers who are seeking suitable topics to explore. It presents research into the skills needed by data practi
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Mixed extensions of bimatrix games,obviating old ethical concerns. Nonetheless, Big Data offer many opportunities, allowing researchers to study previously inaccessible problems, with previously inconceivable sources of data. Although Big Data overcome some of the challenges of small data studies, Big Data studies will not supplant s
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https://doi.org/10.1007/978-93-86279-17-0 relatively straight forward yet appealing interactive activities, and support resources, to develop rudimentary but essential concepts and processes for each of the 4–7 years and 8–18 years age groups. A combination of activities and freely available software to support data exploration such as iNZ
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The imputation set and the core,istory of the unit, topics of study, learning outcomes, assessment tasks, and how students were included in decision making for their projects is described before presenting two case studies from students’ projects.
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https://doi.org/10.1007/978-1-4612-4316-8ocess. In some fields, such as software engineering, professional and open source projects gather this sort of data, and those same tools allow collection of student data, allowing us to explore whether students are adopting strategies that experts find to be successful. We see this as the goal of d
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