Understanding student pathways in context-rich problems |
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| Authors: | Pavlo D Antonenko Craig A Ogilvie Dale S Niederhauser John Jackman Piyamart Kumsaikaew Rahul R Marathe and Sarah M Ryan |
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| Institution: | (1) Oklahoma State University, Stillwater, OK 74078, USA;(2) Iowa State University, Ames, IA 50011, USA;(3) Bangkok Bank, PCL, Bangkok, 10500, Thailand;(4) Indian Institute of Technology Madras, Chennai, 600 036, India |
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| Abstract: | This paper describes the ways that students’ problem-solving behaviors evolve when solving multi-faceted, context-rich problems
within a web-based learning environment. During the semester, groups of two or three students worked on five physics problems
that required drawing on more than one concept and, hence, could not be readily solved with simple “plug-and-chug” strategies.
The problems were presented to students in a data-rich, online problem-based learning environment that tracked which information
items were selected by students as they attempted to solve the problem. The students also completed a variety of tasks, like
entering an initial qualitative analysis of the problem into an online form. Students were not constrained to complete these
tasks in any specific order. As they gained more experience in solving context-rich physics problems, student groups showed
some progression towards expert-like behavior as they completed qualitative analysis earlier and were more selective in their
perusal of informational resources. However, there was room for more improvement as approximately half of the groups still
completed the qualitative analysis task towards the end of the problem-solving process rather than at the beginning of the
task when it would have been most useful to their work. |
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