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In recent years, the “search as learning” community has argued that search systems should be designed to support learning. We report on a lab study in which we manipulated the learning objectives associated with search tasks assigned to participants. We manipulated learning objectives by leveraging Anderson and Krathwohl’s taxonomy of learning (A&K’s taxonomy) [2], which situates learning objectives at the intersection of two orthogonal dimensions: the cognitive process and the knowledge type dimension. Participants in our study completed tasks with learning objectives that varied across three cognitive processes (apply, evaluate, and create) and three knowledge types (factual, conceptual, and procedural knowledge). We focus on the effects of the task’s cognitive process and knowledge type on participants’ pre-/post-task perceptions and search behaviors. Our results found that the three knowledge types considered in our study had a greater effect than the three cognitive processes. Specifically, conceptual knowledge tasks were perceived to be more difficult and required more search activity. We discuss implications for designing search systems that support learning.
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Anderson and Krathwohl's Two-Dimensional Taxonomy Applied to Task Creation and Learning Assessment
Search tasks play an important role in the study and development of interactive information retrieval (IIR) systems. Prior work has examined how search tasks vary along dimensions such as the task’s main activity, end goal, structure, and complexity. Recently, researchers have been exploring task complexity from the perspective of cognitive complexity—related to the types (and variety) of mental activities required by the task. Anderson & Krathwohl’s two-dimensional taxonomy of learning has been a commonly used framework for investigating tasks from the perspective of cognitive complexity [1]. A&K’s 2D taxonomy involves a cognitive process dimension and an orthogonal knowledge dimension. Prior IIR research has successfully leveraged the cognitive process dimension of this 2D taxonomy to develop search tasks and investigate their effects on searchers’ needs, perceptions, and behaviors. However, the knowledge dimension of the taxonomy has been largely ignored. In this conceptual paper, we argue that future IIR research should consider both dimensions of A&K’s taxonomy. Specifically, we discuss related work, present details on both dimensions of A&K’s taxonomy, and explain how to use the taxonomy to develop search tasks and learning assessment materials. Additionally, we discuss how considering both dimensions of A&K’s taxonomy has important implications for future IIR research.
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- Award ID(s):
- 1718295
- PAR ID:
- 10112034
- Date Published:
- Journal Name:
- Proceedings of the 5th ACM SIGIR International Conference on the Theory of Information Retrieval
- Page Range / eLocation ID:
- 117 - 124
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3341981.3344226
