TY - JOUR
T1 - The relationship of (perceived) epistemic cognition to interaction with resources on the internet
AU - Knight, Simon
AU - Rienties, Bart
AU - Littleton, Karen
AU - Mitsui, Matthew
AU - Tempelaar, Dirk
AU - Shah, Chirag
N1 - Publisher Copyright:
© 2017 Elsevier Ltd
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/8/1
Y1 - 2017/8/1
N2 - Information seeking and processing are key literacy practices. However, they are activities that students, across a range of ages, struggle with. These information seeking processes can be viewed through the lens of epistemic cognition: beliefs regarding the source, justification, complexity, and certainty of knowledge. In the research reported in this article we build on established research in this area, which has typically used self-report psychometric and behavior data, and information seeking tasks involving closed-document sets. We take a novel approach in applying established self-report measures to a large-scale, naturalistic, study environment, pointing to the potential of analysis of dialogue, web-navigation – including sites visited – and other trace data, to support more traditional self-report mechanisms. Our analysis suggests that prior work demonstrating relationships between self-report indicators is not paralleled in investigation of the hypothesized relationships between self-report and trace-indicators. However, there are clear epistemic features of this trace data. The article thus demonstrates the potential of behavioral learning analytic data in understanding how epistemic cognition is brought to bear in rich information seeking and processing tasks.
AB - Information seeking and processing are key literacy practices. However, they are activities that students, across a range of ages, struggle with. These information seeking processes can be viewed through the lens of epistemic cognition: beliefs regarding the source, justification, complexity, and certainty of knowledge. In the research reported in this article we build on established research in this area, which has typically used self-report psychometric and behavior data, and information seeking tasks involving closed-document sets. We take a novel approach in applying established self-report measures to a large-scale, naturalistic, study environment, pointing to the potential of analysis of dialogue, web-navigation – including sites visited – and other trace data, to support more traditional self-report mechanisms. Our analysis suggests that prior work demonstrating relationships between self-report indicators is not paralleled in investigation of the hypothesized relationships between self-report and trace-indicators. However, there are clear epistemic features of this trace data. The article thus demonstrates the potential of behavioral learning analytic data in understanding how epistemic cognition is brought to bear in rich information seeking and processing tasks.
KW - Collaborative information seeking
KW - Epistemic cognition
KW - Information processing
KW - Information seeking
KW - Learning analytics
KW - Trace data
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U2 - 10.1016/j.chb.2017.04.014
DO - 10.1016/j.chb.2017.04.014
M3 - Article
AN - SCOPUS:85017369380
VL - 73
SP - 507
EP - 518
JO - Computers in Human Behavior
JF - Computers in Human Behavior
SN - 0747-5632
ER -