TY  - CHAP
TI  - Learning Analytics for Self-Regulated Learning
AU  - Winne, Philip
T2  - The Handbook of Learning Analytics
A2  - Lang, Charles
A2  - Siemens, George
A2  - Wise, Alyssa Friend
A2  - Gaševic, Dragan
AB  - The Winne-Hadwin (1998) model of self-regulated learning (SRL), elaborated by Winne’s (2011, in press) model of cognitive operations, provides a framework for conceptualizing key issues concerning kinds of data and analyses of data for generating learning analyt- ics about SRL. Trace data are recommended as observable indicators that support valid inferences about a learner’s metacognitive monitoring and metacognitive control that constitute SRL. Characteristics of instrumentation for gathering ambient trace data via software learners can use to carry out everyday studying are described. Critical issues are discussed regarding what to trace about SRL, attributes of instrumentation for gathering ambient trace data, computational issues arising when analyzing trace and complementary data, the scheduling and delivery of learning analytics, and kinds of information to convey in learning analytics that support productive SRL.
CY  - Alberta, Canada
DA  - 2017///
PY  - 2017
ET  - 1
SP  - 241
EP  - 249
PB  - Society for Learning Analytics Research (SoLAR)
SN  - 978-0-9952408-0-3
UR  - http://solaresearch.org/hla-17/hla17-chapter1
ER  -