| Autor: |
Amna Zuberi, Vivek Venkatesh, Arun Lakhana, Kathryn Urbaniak, Timothy Gallant, Kamran Shaikh |
| Rok vydání: |
2013 |
| Předmět: |
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| Zdroj: |
International Handbook of Metacognition and Learning Technologies ISBN: 9781441955456 |
| DOI: |
10.1007/978-1-4419-5546-3_19 |
| Popis: |
The empirical research reported in this chapter explores learner metacognition and self-regulation in information retrieval environments equipped with a powerful indexing technology called Topic Maps. The theoretical foundation for our work lies in the nexus of theories of self-regulation and those of cognitive information retrieval. Through a series of mixed-method studies conducted at the Topic Maps laboratory at Concordia University, we describe academic self-regulatory processes associated with graduate learners’ understandings of ill-structured academic writing tasks and attempt to relate them to learners’ metacognitive ability to judge their own performance on iterations of these writing tasks. The thirty-eight participants in the studies described in this chapter used the Topic Maps technology throughout a semester to navigate a repository of instructor-annotated essays. The repository was designed not only to help learners complete their own writing assignments, but also to improve their task understanding and better calibrate their performance from one instantiation of the writing assignment to the next. Results are discussed in light of the novel intra-sample statistical analyses used to uncover relationships between academic performance, metacognition and task understanding. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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