Towards a Textual Cohesion Model that Predicts Self-Explanations Inference Generation as a Function of Text Structure and Readers' Knowledge Levels
Cédrick Bellissens, Patrick P. J. M. H. Jeuniaux, Nicholas D. Duran, Danielle S. McNamara · eScholarship (California Digital Library) · 2007
The Interactive Strategy Trainer for Active Reading and Thinking (iSTART) is an intelligent tutoring system that provides students with automated training on reading strategies.In particular, iSTART trains students to selfexplain target sentences so as to integrate encoded information into a coherent mental representation.The goal of this study was to investigate the relation between text structures and the generation of bridging and elaborative inferences during self-explanation.We developed a computational model in which textual cohesion was interpreted as matrices of textbase cohesion values, such as argument overlap or semantic similarity, but also as matrices of situation model cohesion values such as causality.The model successfully predicted the different types of selfexplanations as a function of the textual cohesion.We also found that students' prior knowledge interacts with the textual cohesion effect when cohesion was based on situation model indices.