Project Information

Name:	Mixed-Initiative Writing
Abstract	Writing is a core skill students are expected to develop early in their schooling. However, tracking and understanding the development of learners’ expertise in writing poses considerable challenges, given the complexity of the writing process and the volume of data. This research explores a technologically-enhanced pedagogical method that hold the potential to enhance writing competence. It tracks learners’ writing activities as they complete a writing exercise using a special mixed-initiative editor called MI-Writer. The tracked activities are mapped onto a causal model to answer questions related to specific writing competencies of the learner. As a mixed-initiative system, learners can receive context-specific support from the system, just in time, as they write. The overall goals are to measure individual competencies of writing, identify writing competency-gaps, and promote means to address these gaps.
Start Date	2011-01-01
End Date	2012-08-31

Research Areas
artificial intelligence and education	bayesian belief networks	causal modelling
co-regulated learning	cognitive modelling	knowledge tracing
mixed initiatives	model tracing	ontologies
realtime feedback	self-regulated learning	user modelling

Source Name	Amount
NSERC	15,000

Faculty Researcher(s)

Kinshuk

Dunwei Wen

Vivek Kumar

Research Assistant(s)

Clayton Clemens