Abstract
We propose a novel method for identifying questioning patterns, which are assumed to be one of the essential factors indicating the quality of knowledge-building discourse. The underlying principle of the proposed method is to extract syntactic and sematic information before segmenting the raw data and annotating them according to a multilayer framework called ACODEA. As a bottom layer of the framework, the "pre-coding" phase makes it possible to translate the raw data into machine-readable and contextindependent language, and to make Natural Language Processing tools aware of users' preferences and underpinning mechanisms of identifying the desired pattern. Explorative but promising evidence is reported toward a more comprehensive perspective by combining qualitative and quantitative methods to analyze the discourse data. Given those findings, we argue in favor of mixed methods of content analysis and they further generated directions for future methodological development and empirical applications.
Original language | English |
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Title of host publication | Proceedings of International Conference of the Learning Sciences, ICLS. Volume 1 |
Pages | 333-340 |
Number of pages | 8 |
Publication status | Published - 1 Jan 2014 |
Externally published | Yes |
Event | 11th International Conference of the Learning Sciences, ICLS 2014 - Boulder, United States Duration: 23 Jun 2014 → 27 Jun 2014 Conference number: 11 |
Conference
Conference | 11th International Conference of the Learning Sciences, ICLS 2014 |
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Abbreviated title | ICLS |
Country/Territory | United States |
City | Boulder |
Period | 23/06/14 → 27/06/14 |