Automated Evaluation of Text and Discourse with Coh-Metrix by McNamara D.S., Graesser A.C., McCarthy P.M., Cai Z. PDF

By McNamara D.S., Graesser A.C., McCarthy P.M., Cai Z.

ISBN-10: 0521192927

ISBN-13: 9780521192927

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They found that low-knowledge readers benefited from the added cohesion according to all of the comprehension and text recall measures. The size of the difference in comprehension scores can be measured using Cohen’s d (see Chapter 11 for a discussion of effect sizes and their interpretation). 2013 7:32PM Automated Evaluation of Text and Discourse with Coh-Metrix Accordingly, the average difference between reading a low-cohesion version and a high-cohesion version for a low-knowledge reader was almost a full standard deviation.

Britton and Gulgoz manipulated an Original passage about the war in Vietnam, Air War in the North, from three different theoretical perspectives. They created Heuristic, Readability Formula, and Principled versions of the passage. In the Heuristic revision, the authors used their own intuitive notions of better writing practice to improve the passage. Some information was reordered or clarified, unimportant ideas were omitted, and important ideas were elaborated. , approximately grades 13–14). Most relevant here is the Principled version.

For example, consider the following examples: Smoking was forbidden. The store had inflammables. 6) Smoking was forbidden because the store had inflammables. 3 is not a compulsory rule of language; nonetheless, its addition facilitates the understanding of why smoking was forbidden. When discourse lacks cohesion, the reader must make inferences to connect the dots. These inferences can be generated by accessing prior text, everyday world knowledge, or subject matter knowledge associated with a particular area of specialization (called domain knowledge).

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Automated Evaluation of Text and Discourse with Coh-Metrix by McNamara D.S., Graesser A.C., McCarthy P.M., Cai Z.


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