Hello,
I am with the School of Computing and Information Systems at Athabasca University, living in Edmonton. My research interest, since 1990, have been in Artificial Intelligence in Education, particularly in Model Tracing and Competency Modelling. This fits perfectly with my take on Learning Analytics (LA) as an area of research primarily associated with the analysis and proactive reaction to observed relations between human learning and contextual factors that influence it.
LA also deals with the longitidinal evolution of competence as a product of human learning. I am particularly interested in 'discovering' relations from observed online learning activities and tracing the evolution of these relations over a timeframe.
In general, I see LA as a common subset of a number of established research areas such as Artificial Intelligence in Education, User Modelling and User-Adapted Instruction, Educational Technology, Education, Cognition, Instructional Design, Data Mining, Semantic Web, Social Networks, and Knowledge Management.
Statistical methods that enable such discoveries are particularly useful in educational research since they typically use observational data from authentic learning scenarios with minimal bias. Also, the observational data can be longitudinally collected and trace the evolution of competency models. The models can be causal in nature and the underlying relations can be causally inferred and interpreted. My current work involves causal discovery of LA relations corresponding to Self-Regulated Learning (SRL) in the domains of reading, discussions, writing, and programming. Under this, we develop online learning technologies to capture both causal and non-causal data, populate this data in a causal model, and discover new causal and non-causal relations or update strengths of relations, pertaining to learners' efficiency of learning and their individual and group evolution of domain competency and meta knowledge competency. Further we interpret these relations with respect to the contextual factors to compute future competency estimates and optimal learning pathways.
We are still very much in the preliminary stages of data collection and would love to discuss this notion or parner up to share the technology.
Cheers,
Vive
Associate Professor - SCIS, Athabasca University, Edmonton.
Adjunct Professor - SIAT, Simon Fraser University, Surrey.
http://vivek.athabascau.ca