Workshop of Assessment of Group and Individual Learning Through Intelligent Visualization (AGILEeViz). CSCL 2007

We explore AI-based methods for analyzing and visualizing data collected from on-line assessments of young students' numeracy and literacy skills. Traditionally, educational assessment data is reported in the form of test scores, often two numbers that each represent a student's achievement or ability in mathematics and language. However, state-of-the-art, adaptive on-line environments are gaining favor for student assessment and these types of systems obtain a wealth of data. Distilling these robust data sets down to two numbers results in great loss of information; and we have been exploring richer ways of presenting and analyzing these data to allow deeper understanding of student performance by teachers, parents and education researchers.