Premium
Estimating the degree of failed understanding: a possible role for online technology
Author(s) -
Grabe M.,
Holfeld B.
Publication year - 2014
Publication title -
journal of computer assisted learning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.583
H-Index - 93
eISSN - 1365-2729
pISSN - 0266-4909
DOI - 10.1111/jcal.12038
Subject(s) - operationalization , strengths and weaknesses , computer science , identification (biology) , calibration , data collection , psychology , artificial intelligence , machine learning , statistics , social psychology , mathematics , philosophy , botany , epistemology , biology
Accurate identification of what a learner does not know is essential for efficient self‐directed learning. The accuracy of this awareness, often described as calibration, has been operationalized in several ways. Calibration data are often collected in applied settings by having students predict a future examination score. This method is efficient but not a direct measurement of the awareness of specific strengths and weaknesses. Online technology allows a practical way to collect more specific, local data; that is, the accuracy of confidence ratings for individual assessment items. These two methods of estimating calibration, global and local, were contrasted as predictors of performance in an introductory college course. Both measures were demonstrated to be significant and unique predictors of future examination performance. Online study environments requiring certitude judgments for study questions and offering immediate opportunities for review may offer the means for improving the efficiency of self‐directed learning.