This dataset supports learning how to code and analyze think-aloud data in cognitive and educational psychology studies that examine reading. Think-aloud methods can be utilized across a variety of fields, including education, psychology, marketing, policy studies, and more. The data are provided by Dr. Catherine Bohn-Gettler and Olivia Olson. The data represent samples drawn from a study published by Bohn-Gettler and Kendeou (2014), in which they examined interactions between text structure, reading goals, and working memory as participants thought aloud during reading. The examples of think-aloud data focus on how to reliably code for various cognitive processes that commonly occur during comprehension, which include paraphrasing, connecting and reinstatement inferences, elaborative inferences, predictions, opinions, statements of uncertainty, and associations. The data samples provide an example of a coded think-aloud transcript, as well as several uncoded think-aloud transcripts. The dataset files are accompanied by a Teaching Guide and a Student Guide.
Please log in from an authenticated institution or log into your member profile to access the email feature.
You are viewing a preview of the dataset file. To download the full dataset file close this window and select one of the download options presented.