The current study uncovers secondary school students' actual use of text-learning strategies during an individual learning task by means of a concurrent self-reported thinking aloud procedure. Think-aloud data of 51 participants with different learning strategy profiles, distinguished based on a retrospective self-report questionnaire (i.e., 15…

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

In this paper, we examine how students discuss and interpret data and whether these actions vary depending on the type of data they analyse. More specifically, we are interested in whether students perform differently when analysing first-hand data, which they collect themselves, compared with second-hand data provided to them. Our data analysis…

Finding ways to improve the design of large-scale tests is a timely issue. Recent changes in Federal legislation (including the No Child Left Behind Act of 2001) have placed greater emphasis on accountability via large-scale tests. Students who have previously been exempted from large-scale assessments, including students with disabilities and…