Exploring patterns in undergraduate students’ information problem solving: A cross-case comparison study

Kun Huang, Victor Law, Xun Ge, Ling Hu, Yan Chen, | |

Abstract


Students today routinely conduct research in the digital world to solve problems in daily life and in learning tasks. Although research to date has proposed different models to describe the processes of information problem solving (IPS), little is known about the cognitive patterns demonstrated in the processes, particularly the iterative nature of IPS and the driving factors behind iterations. The current study employed the lens of a self-regulated problem-solving model to develop an in-depth understanding of learners’ IPS processes. Analysis and cross comparisons of three students’ on-screen research activities, think-aloud articulations, artifacts, and interviews revealed three representative patterns for performing an IPS task: reasoning-driven, prior knowledge/task-driven, and information-driven. These different patterns manifest qualitative differences in the three students’ research behaviors and iterations of problem-solving stages. The findings afford an in-depth understanding of the cognitive dimension of IPS, and yield important implications for scaffolding learners in effective IPS.

https://doi.org/10.34105/j.kmel.2019.11.023


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Laboratory for Knowledge Management & E-Learning, The University of Hong Kong