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A Model-based Approach for Assessment and Motivation
Computer Science and Information Systems, Tome 9 (2012) no. 2 Cet article a éte moissonné depuis la source Computer Science and Information Systems website

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Representations support learning and instruction in many ways. Two key aspects of representations are discussed in this paper. First we briefly review the research literature about cognition and processing internal mental models. The emphasis is on the role that mental models play in critical reasoning and problem solving. We then present a theoretically-grounded rationale for taking internal mental representations into account when designing and implementing support for learning. The emphasis is on interaction with meaningful problems. Lastly, we present research that has led to a conceptual framework for integrating models into learning environments that includes technologies for formative assessment and motivation.
Keywords: assessment; complex problem solving; critcal reasoning; mental model; model-facilitated learning; motivation; problem conceptualization; problem representation 
@article{CSIS_2012_9_2_a18,
     author = {J. Michael Spector and ChanMin Kim},
     title = {A {Model-based} {Approach} for {Assessment} and {Motivation}},
     journal = {Computer Science and Information Systems},
     year = {2012},
     volume = {9},
     number = {2},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2012_9_2_a18/}
}
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J. Michael Spector; ChanMin Kim. A Model-based Approach for Assessment and Motivation. Computer Science and Information Systems, Tome 9 (2012) no. 2. http://geodesic.mathdoc.fr/item/CSIS_2012_9_2_a18/