Development of a function to adaptively provide a series of tasks for progressive knowledge acquisition in virtual experimental environments

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We have developed a task-generation function in virtual experimental environments which enable learners make scientific experiments on computers. It generates a series of tasks adaptive to each learner's progress. 'Microworld graph (GMW)' is used for organizing tasks with their learning purposes and target models. GMW cooperates with the function which models a learner's understanding to generate appropriate tasks automatically. Preliminary tests validated its usefulness.