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Education Research International
Volume 2011, Article ID 735643, 11 pages
Research Article

Uncovering Relationships between Task Understanding and Monitoring Proficiencies in Postsecondary Learners: Comparing Work Task and Learner as Statistical Units of Analyses

Department of Education, Centre for the Study of Learning and Performance & Learning for Life Centre, Concordia University, 1455 de Maisonneuve West, Montreal, Quebec, Canada H3G 1M8

Received 26 August 2010; Accepted 20 December 2010

Academic Editor: Susan O'Neill

Copyright © 2011 Vivek Venkatesh and Kamran Shaikh. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Educational psychologists have researched the generality and specificity of metacognitive monitoring in the context of college-level multiple-choice tests, but fairly little is known as to how learners monitor their performance on more complex academic tasks. Even lesser is known about how monitoring proficiencies such as discrimination and bias might be related to key self-regulatory processes associated with task understanding. This quantitative study explores the relationship between monitoring proficiencies and task understanding in 39 adult learners tackling ill-structured writing tasks for a graduate “theories of e-learning” course. Using learner as unit of analysis, the generality of monitoring is confirmed through intra-measure correlation analyses while facets of its specificity stand out due to the absence of inter-measure correlations. Unsurprisingly, learner-based correlational and repeated measures analyses did not reveal how monitoring proficiencies and task understanding might be related. However, using essay as unit of analysis, ordinal and multinomial regressions reveal how monitoring influences different levels of task understanding. Results are interpreted not only in light of novel procedures undertaken in calculating performance prediction capability but also in the application of essay-based, intra-sample statistical analysis that reveal heretofore unseen relationships between academic self-regulatory constructs.