Deriving Empirically-Based Design Guidelines for Advanced Learning Technologies that Foster Disciplinary Comprehension
Abstract
Planning, conducting, and reporting leading-edge research requires professionals who are capable of highly skilled reading. This study reports the development of an empirically informed computer-based learning environment designed to foster the acquisition of reading comprehension strategies that mediate expertise in the social sciences. Empirical data were gathered in a mixed-methods explanatory sequential design that examined the reading comprehension strategies used by an expert social scientist while reading a professional-level text. Process data were collected through a concurrent think-aloud protocol and coded according to reading comprehension processes. We combined both quantitative and qualitative analyses to identify, describe, and explain patterns in the expert’s use of reading strategies. Our findings indicate that highly-skilled reading is characterized by critiquing text information, relating information to prior knowledge, and evaluating one’s own understanding of text information. Findings are used to inform the design of worked-examples and a pedagogical agent embedded within the Highly-Skilled Reading Tutor.
Canadian Journal of Learning and Technology
