Regulative support during inquiry learning with simulations and modeling

Abstract : Many factors impact learning; the environment and resources available, the domain, how much prior-knowledge a student has, and how well they make use of their metacognitive skills, all of these factors impact new knowledge creation. The series of studies described in this dissertation focuses on the latter; i.e. the metacognitive skillfulness of students. Known collectively as self-regulation, planning, monitoring, and evaluation, when applied appropriately will enhance learning. Students who make plans, check their progress and understanding, and take a step back at key moments to evaluate both their learning products and processes are generally thought to have an advantage over students who less successfully implement these skills. During classroom settings teachers and the presence of a peer often take a regulative function to promote enactment of these skills. Teachers, students, and peers, will make goals for learning, ask comprehension checking questions, and evaluate final products and their work processes. As such they provide “natural” scaffolding for regulative skill enactment. Within technology-enhanced settings scaffolding these processes is less clearly defined. The four studies within this dissertation address issues in design of support by looking at student enactment of regulation within a technology-enhanced scientific inquiry learning environment which incorporates simulations and student-construction of scientific systems dynamic models. Successively each study builds a picture of regulative support, how it's used, and where it's useful, with the aim of providing insight. Insight into the problems students have with regulation, aspects of the learning setting which impact use of regulative supports, and aspects of regulative support which have the potential to promote learning.
Keywords : self-regulation
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Submitted on : Friday, November 23, 2007 - 8:33:22 AM
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Sarah Manlove. Regulative support during inquiry learning with simulations and modeling. 2007. ⟨hal-00190075⟩

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