Assessing conceptual representations of Ill-defined problems
Göğüş, Aytaç and Koszalka, Tiffany A. and Spector, J. Michael (2009) Assessing conceptual representations of Ill-defined problems. Technology, Instruction, Cognition and Learning (TICL), 7 (1). pp. 1-20. ISSN 1540-0182 (print) 1540-0174 (on-line)
Official URL: http://www.oldcitypublishing.com/TICL/TICL.html
This paper presents research findings related to the “Enhanced Evaluation of Learning in Complex Domains (DEEP)” (Spector & Koszalka, 2004) methodology for assessing how participants conceptualize ill-structured problems in biology using annotated concept maps. The methodology engages highly experienced (expert) and less experienced (novice) participants in creating annotated problem representations. The study addresses the lack of assessment methods to assess learning progress and relative level of expertise in complex domains. This paper addresses (1) differences between experts and novices, (2) learning in complex domains, and (3) rational for using annotated concept maps to assess learning in complex domains. Findings suggest that there are similarities in how experts think about ill-structured problems and these similarities are different than novices. These findings thus suggest that this methodology is useful in distinguishing relative levels of expertise in conceptualization of ill-structured problems in a biology context.
Repository Staff Only: item control page