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Using Eye-Tracking Measures to Predict Reading Comprehension

Mézière Diane C; Yu Lili; Reichle Erik D; von der Malsburg Titus; McArthur Genevieve

Using Eye-Tracking Measures to Predict Reading Comprehension

Mézière Diane C
Yu Lili
Reichle Erik D
von der Malsburg Titus
McArthur Genevieve
Katso/Avaa
Reading Research Quarterly - 2023 - M zi re - Using Eye‐Tracking Measures to Predict Reading Comprehension.pdf (627.8Kb)
Lataukset: 

Wiley
doi:10.1002/rrq.498
URI
https://ila.onlinelibrary.wiley.com/doi/10.1002/rrq.498
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2023051344305
Tiivistelmä

This study examined the potential of eye-tracking as a tool for assessing reading comprehension. We administered three widely used reading comprehension tests with varying task demands to 79 typical adult readers while monitoring their eye movements. In the York Assessment of Reading for Comprehension (YARC), participants were given passages of text to read silently, followed by comprehension questions. In the Gray Oral Reading Test (GORT-5), participants were given passages of text to read aloud, followed by comprehension questions. In the sentence comprehension subtest of the Wide Range Achievement Test (WRAT-4), participants were asked to provide a missing word in sentences that they read silently (i.e., a cloze task). Linear models predicting comprehension scores from eye-tracking measures yielded different results for the three tests. Eye-tracking measures explained significantly more variance than reading-speed data for the YARC (four times better), GORT (three times better), and the WRAT (1.3 time better). Importantly, there was no common strong predictor for all three tests. These results support growing recognition that reading comprehension tests do not measure the same cognitive processes, and that participants adapt their reading strategies to the tests' varying task demands. This study also suggests that eye-tracking may provide a useful alternative for measuring reading comprehension.

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