Pickle, J.M., Basu, S., Flannery, K. & Bridges, R. (2005). An artificial intelligence algorithm for customizing texts to match the prior knowledge of individual readers. In C. Crawford et al. (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2005 (pp. 2969-2972). Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/19571.
Society for Information Technology & Teacher Education International Conference (SITE) 2005
Phoenix, AZ, USA
Caroline Crawford, Roger Carlsen, Ian Gibson, Karen McFerrin, Jerry Price, Roberta Weber & Dee Anna Willis
More Information on SITE
The construction of meaning from expository text is a recurrent theme in reading research, and factors affecting the comprehension of a text have been investigated. Varying instructional algorithms and using different kinds of texts during instruction have been studied. Difficulties with investigations of the interaction of prior knowledge and text structure include the static nature of printed texts and individual differences in the content of prior knowledge. If a text were customized computationally to address alternative conceptions in a reader's prior knowledge, the comprehension of that text would be increased. We are developing an application, an artificial intelligence algorithm based on a connectionist architecture, that adapts the structures within a text to address incompatible concepts in a reader's content knowledge. Input from a reader is used to adjust the rhetorical and syntactic structure of the text. In this paper, we describe the use of the application.