@incollection{williamson_shaffer_epistemic_2017,
	address = {Alberta, Canada},
	edition = {1},
	title = {Epistemic {Network} {Analysis}: {A} {Worked} {Example} of {Theory}-{Based} {Learning} {Analytics}},
	isbn = {978-0-9952408-0-3},
	url = {http://solaresearch.org/hla-17/hla17-chapter1},
	abstract = {In this article, we provide a worked example of a theory-based approach to learning ana- lytics in the context of an educational game. We do this not to provide an ideal solution for others to emulate, but rather to explore the affordances of a theory-based - rather than data-driven - approach. We do so by presenting 1) epistemic frame theory as an approach to the conceptualization of learning; 2) data from an epistemic game, an approach to edu- cational game design based on epistemic frame theory; and 3) epistemic network analysis (ENA), a technique for analyzing discourse and other data for evidence of complex thinking based on the same theory. We describe ENA through a speci c analytic result, but our aim is to explore how this result exempli es what we consider a key "best practice" in the  eld of learning analytics.},
	booktitle = {The {Handbook} of {Learning} {Analytics}},
	publisher = {Society for Learning Analytics Research (SoLAR)},
	author = {Williamson Shaffer, David and Ruis, Andrew},
	editor = {Lang, Charles and Siemens, George and Wise, Alyssa Friend and Gaševic, Dragan},
	year = {2017},
	pages = {175--187}
}