The research versions of the iSolveIt puzzles were designed with a back-end database that collected information on variables such as which puzzles a student chose, the steps students took in solving, the use of embedded supports, and the elapsed time between each action. Each student had a personal log-in/account that enabled tracking of individual data. The public version of the iSolveIt puzzles does not include this data-collection component.

Future research versions of iSolveIt will include ways to analyze data of the strategies students use and how those strategies change as they use the puzzles. We will apply basic principles of learning analytics to the research version database in order to study and create preliminary categories for student pathways through the puzzles. We plan to create a format for displaying, or visualizing, each student’s historic decision-making data in the context of the puzzles that will help us see the strategic approaches being made and how they change over time.