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Scanning and deep processing of information in hypertext: an eye tracking and cued retrospective think‐aloud study
Author(s) -
Salmerón L.,
Naumann J.,
García V.,
Fajardo I.
Publication year - 2017
Publication title -
journal of computer assisted learning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.583
H-Index - 93
eISSN - 1365-2729
pISSN - 0266-4909
DOI - 10.1111/jcal.12152
Subject(s) - hypertext , comprehension , computer science , reading comprehension , the internet , eye tracking , reading (process) , information processing , think aloud protocol , cued speech , information retrieval , artificial intelligence , multimedia , psychology , world wide web , usability , human–computer interaction , cognitive psychology , linguistics , programming language , philosophy
When students solve problems on the Internet, they have to find a balance between quickly scanning large sections of information in web pages and deeply processing those that are relevant for the task. We studied how high school students articulate scanning and deeper processing of information while answering questions using a Wikipedia document, and how their reading comprehension skills and the question type interact with these processes. By analyzing retrospective think‐aloud protocols and eye‐tracking measures, we found that scanning of information led to poor hypertext comprehension, while deep processing of information produced better performance, especially in location questions. This relationship between scanning, deep processing, and performance was qualified by reading comprehension skills in an unexpected way: Scanning led to lower performance especially for good comprehenders, while the positive effect of deep processing was independent of reading comprehension skills. We discussed the results in light of our current knowledge of Internet problem solving.