Reading with the eyes and under the skin : Comprehending conflicting digital texts

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2020
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Mason, Lucia
Zaccoletti, Sonia
Scrimin, Sara
Tornatora, Maria Caterina
Florit, Elena
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Journal of Computer Assisted Learning. Wiley. 2020, 36(1), pp. 89-101. ISSN 0266-4909. eISSN 1365-2729. Available under: doi: 10.1111/jcal.12399
Zusammenfassung

This study investigated the contribution of both physiological and behavioural process data to the comprehension of conflicting digital texts. We measured skin conductance level (SCL) as an index of arousal and the first‐pass and look‐back fixation times as indices of visual behaviour while reading. Forty‐eight seventh graders read four webpages on genetically modified food, and their comprehension of the texts was measured using a short essay. Results showed that the type of webpage did not differentiate the process data. Statistical procedures for the comparison of a series of regression models revealed that SCL and first‐pass fixation time negatively predicted multiple‐text comprehension while also considering the control variables. The more the students were aroused while reading and the longer the processing time during the first encounter with the reading material, the poorer their comprehension of the conflicting texts. However, the interaction of prior knowledge and arousal positively predicted multiple‐text comprehension. A slope analysis revealed that when participants had high prior knowledge and high arousal during reading, their postreading comprehension performance increased.

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ISO 690MASON, Lucia, Sonia ZACCOLETTI, Sara SCRIMIN, Maria Caterina TORNATORA, Elena FLORIT, Thomas GÖTZ, 2020. Reading with the eyes and under the skin : Comprehending conflicting digital texts. In: Journal of Computer Assisted Learning. Wiley. 2020, 36(1), pp. 89-101. ISSN 0266-4909. eISSN 1365-2729. Available under: doi: 10.1111/jcal.12399
BibTex
@article{Mason2020-02Readi-49096,
  year={2020},
  doi={10.1111/jcal.12399},
  title={Reading with the eyes and under the skin : Comprehending conflicting digital texts},
  number={1},
  volume={36},
  issn={0266-4909},
  journal={Journal of Computer Assisted Learning},
  pages={89--101},
  author={Mason, Lucia and Zaccoletti, Sonia and Scrimin, Sara and Tornatora, Maria Caterina and Florit, Elena and Götz, Thomas}
}
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