A Model-based Approach for Assessment and Motivation

J. Michael Spector1 and ChanMin Kim2

  1. University of North Texas
    mike.spector@unt.edu
  2. University of Georgia
    chanmin@uga.edu

Abstract

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.

Key words

assessment; complex problem solving; critcal reasoning; mental model; model-facilitated learning; motivation; problem conceptualization; problem representation

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS111226016S

Publication information

Volume 9, Issue 2 (June 2012)
Year of Publication: 2012
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Spector, J. M., Kim, C.: A Model-based Approach for Assessment and Motivation. Computer Science and Information Systems, Vol. 9, No. 2, 893-915. (2012)