Abstract
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.
| Original language | English (US) |
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| Title of host publication | CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society |
| Subtitle of host publication | Computational Foundations of Cognition |
| Publisher | The Cognitive Science Society |
| Pages | 1884-1889 |
| Number of pages | 6 |
| ISBN (Electronic) | 9780991196760 |
| State | Published - 2017 |
| Externally published | Yes |
| Event | 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 - London, United Kingdom Duration: Jul 26 2017 → Jul 29 2017 |
Publication series
| Name | CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition |
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Conference
| Conference | 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 |
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| Country/Territory | United Kingdom |
| City | London |
| Period | 7/26/17 → 7/29/17 |
Bibliographical note
Funding Information:The work presented in this paper was partially funded by the University Politehnica of Bucharest through the “Excellence Research Grants” Program, UPB – GEX Contract number 12/26.09.2016, by the EC H2020 project RAGE (Realising and Applied Gaming Eco-System) http://www.rageproject .eu/ Grant agreement No 644187, as well as funding to Arizona State University (IES 305A130124, IES R305A120707, NSF 1417997, NSF 1418378, ONR 12249156, ONR N00014140343). Any opinions or conclusions expressed are those of the authors and do not represent views of the IES, NSF, or ONR.
Funding Information:
The work presented in this paper was partially funded by the University Politehnica of Bucharest through the “Excellence Research Grants” Program, UPB - GEX Contract number 12/26.09.2016, by the EC H2020 project RAGE (Realising and Applied Gaming Eco-System) http://www.rageproject.eu/Grant agreement No 644187, as well as funding to Arizona State University (IES 305A130124, IES R305A120707, NSF 1417997, NSF 1418378, ONR 12249156, ONR N00014140343). Any opinions or conclusions expressed are those of the authors and do not represent views of the IES, NSF, or ONR.
Publisher Copyright:
© CogSci 2017.
Keywords
- comprehension
- dialogism
- discourse analysis
- polyphonic model
- self-explanation
- think-aloud