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Call for Papers: Science teaching, learning, and assessment with 21st century, cutting‐edge digital ecologies
Author(s) -
Neumann Knut,
Waight Noemi
Publication year - 2019
Publication title -
journal of research in science teaching
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.067
H-Index - 131
eISSN - 1098-2736
pISSN - 0022-4308
DOI - 10.1002/tea.21529
Subject(s) - computer science , big data , software deployment , multimedia , educational technology , science education , data science , world wide web , software engineering , mathematics education , mathematics , operating system
The science education community has embraced the deployment of contemporaneous technological tools and platforms in the service of improving science teaching, learning, and assessment. Technology use in science education has ranged—among many other things—from computer-assisted instruction in the 1970s, to using microcomputer-based laboratories and first-generation simulations and micro-worlds in the 1980s and throughout the 1990s. The 1990s also witnessed the deployment of interactive videodiscs, multimedia, hypermedia, and other digital resources as cognitive tools in science classrooms (Songer, 2007), which was followed by efforts to harness the power of the Internet to, for instance, share data in support of multisite student-driven inquiry projects, among many other applications (Abd-El-Khalick, 2001). The last two decades featured the expanded and integrated use of learning-specific software applications, interactive visualizations, modeling tools, and immersive e-learning environments in science teaching and learning (Krajcik & Mun, 2014). The last decade or so has witnessed rapid and groundbreaking advancements in technologies and digital platforms, as well as their application to teaching and learning. These include advances that made high-powered computing and powerful applications in serious gaming, and virtual and augmented reality more accessible to mainstream users. Similar advances have been evident in big data curation, data mining and data analytics, natural language processing, as well as next-generation machine learning and the application of artificial intelligence (AI) to the real-time and adaptive assessment of learning. The coordination through powerful computing and AI of tangible, immersive, intelligent, and multiuser technologies and digital media systems (coordinating, for instance, learner interactions with interactive wall displays, intelligent interfaces, multitouch tables, motion sensors, etc.) now allow the creation of digital ecologies that provide learners with highly engaging and authentic interactive science learning experiences. Simultaneously, these technologies and interfaces enable the collection of massive data about the choices, behaviors, and cognition of an individual learner or groups of learners (keyboard strokes, mouse clicks, eye tracking, body movement, etc.) that allow for real-time feedback both to learners and their teachers, as well as the delivery of adaptive and personalized learning experiences (ILSDI, 2014). These digital technologies and ecologies have the potential to transform science teaching and learning, as well as deliver on the promise of more personalized science education experiences in service of promoting scientific literacy for all (NGSS Lead States, 2013) including, but not limited to, historically underrepresented populations in science, culturally, ethnically, and linguistically diverse students, as well as learners in underprivileged and underserved communities in the United States and around the globe. The aims of this Special Issue of JRST is to provide a platform for reporting on empirical research that examines the use and impact of 21st century cutting-edge technologies, technological platforms, technological activity, and digital ecologies on science teaching, learning, and assessment. We also Received: 20 December 2018 Accepted: 20 December 2018

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