Modeling Comprehension Processes via Automated Analyses of Dialogism / Mihai Dascalu, Laura K. Allen and Danielle S. McNamara.

Dialogism provides the grounds for building a comprehensive model of discourse and it is focused on the multiplicity of perspectives (i.e., voices). Dialogism can be present in any type of text, while voices become themes or recurrent topics emerging from the discourse. In this study, we examine the...

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Online Access: Full Text (via ERIC)
Main Authors: Dascalu, Mihai, Allen, Laura K. (Author), McNamara, Danielle S. (Author), Trausan-Matu, Stefan (Author), Crossley, Scott A. (Author)
Format: eBook
Language:English
Published: [Place of publication not identified] : Distributed by ERIC Clearinghouse, 2017.
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Summary:Dialogism provides the grounds for building a comprehensive model of discourse and it is focused on the multiplicity of perspectives (i.e., voices). Dialogism can be present in any type of text, while voices become themes or recurrent topics emerging from the discourse. In this study, we examine the extent that differences between self-explanations and think-alouds can be detected using computational textual indices derived from dialogism. Students (n = 68) read a text about natural selection and were instructed to generate self-explanations or think-alouds. The linguistic features of these text responses were analyzed using "ReaderBench," an automated text analysis tool. A discriminant function analysis using these features correctly classified 80.9% of the students' assigned experimental conditions (self-explanation vs. think aloud). Our results indicate that self-explanation promotes text processing that focuses on connected ideas, rather than separate voices or points of view covering multiple topics. [This paper was published in: G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), "Proceedings of the 39th Annual Meeting of the Cognitive Science Society" (CogSci 2017). London, UK: Cognitive Science Society.]
Item Description:Sponsoring Agency: Institute of Education Sciences (ED).
Sponsoring Agency: National Science Foundation (NSF).
Sponsoring Agency: Office of Naval Research (ONR).
Contract Number: R305A130124.
Contract Number: R305A120707.
Contract Number: NSF1417997.
Contract Number: NSF1418378.
Contract Number: ONR12249156.
Contract Number: ONRN00014140343.
Abstractor: As Provided.
Educational level discussed: Higher Education.
Educational level discussed: Postsecondary Education.
Physical Description:1 online resource (7 pages)