Understanding the epistemology-learning connection when exploring an ill-structured task using the Internet
Tianyi Zhang, Michigan State University, United States
Michigan State University . Awarded
Within the context of exploring an ill-structured task using the Google search engine, this study examines (1) the connections between personal epistemology and the complexity of knowledge exploration (i.e., learning complexity), and (2) the role of activating learners’ task-oriented epistemic beliefs in affecting their knowledge exploration processes. When covariates (i.e., prior content knowledge, verbal comprehension, effort investment, and learning time) were controlled, hierarchical regression analyses were conducted to investigate (1) whether or not the complexity of participants’ knowledge exploration was associated with their epistemic beliefs (including general and task-specific epistemic beliefs) and epistemic activation; and (2) whether or not epistemic activation could affect the relationship between epistemic beliefs and the complexity of knowledge exploration. The results show that epistemic beliefs were connected to the complexity of learners’ knowledge exploration. Complex learners were more likely to benefit from the epistemic activation to (1) view the task as complex and subjective (and thus perceive their learning to be insufficient), (2) adopt more complex strategies to evaluate web information veracity, and (3) perceive the value of studying specific cases (e.g., empirical studies, first-hand experiences, etc). This research contributes to (1) theoretical understandings of personal epistemology in connection to learning complexity when learning resources are not pre-selected and learning tasks are open-ended and unstructured, and (2) the investigation of the pedagogical value of a teaching strategy (i.e., to activate learners’ epistemic beliefs prior to learning) to promote deep learning in Internet-based learning environments.
Zhang, T. Understanding the epistemology-learning connection when exploring an ill-structured task using the Internet. Ph.D. thesis, Michigan State University.
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