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Erschienen in: Technology, Knowledge and Learning 3/2017

22.07.2017 | Original research

nStudy: A System for Researching Information Problem Solving

verfasst von: Philip H. Winne, John C. Nesbit, Fred Popowich

Erschienen in: Technology, Knowledge and Learning | Ausgabe 3/2017

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Abstract

A bottleneck in gathering big data about learning is instrumentation designed to record data about processes students use to learn and information on which those processes operate. The software system nStudy fills this gap. nStudy is an extension to the Chrome web browser plus a server side database for logged trace data plus peripheral modules that analyze trace data and assemble web pages as learning analytics. Students can use nStudy anywhere they connect to the internet. Every event related to creating, modifying, reviewing, linking and organizing information artifacts is logged in fine grain with a time stamp. These data fully trace information students operate on and how they operate on it. Ambient big data about studying gathered au naturel can be tailored by configuring several of nStudy’s features. Thus the system can be used to gather data across a wide range lab studies and field trials designed to test a range of models and theories.

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Metadaten
Titel
nStudy: A System for Researching Information Problem Solving
verfasst von
Philip H. Winne
John C. Nesbit
Fred Popowich
Publikationsdatum
22.07.2017
Verlag
Springer Netherlands
Erschienen in
Technology, Knowledge and Learning / Ausgabe 3/2017
Print ISSN: 2211-1662
Elektronische ISSN: 2211-1670
DOI
https://doi.org/10.1007/s10758-017-9327-y

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