Using Markov Models and Random Walks to Examine Strategy Use of More or Less Successful Comprehenders

Prompting students to generate constructed responses as they read provides a window into the processes and strategies that they use to make sense of complex text. In this study, Markov models examined the extent to which (1) patterns of strategies and (2) strategy combinations could be used to inform computational models of students’ text comprehension. Random Walk models further revealed how consistency in strategy use over time was related to comprehension performance. High school (n = 257) and college students (n = 153) produced constructed responses at predetermined points while reading a scientific text. Each constructed response was scored for the presence of three common comprehension strategies (i.e., paraphrasing, bridging, elaborating), such that each constructed response could then be categorized as one of eight combination types. Markov chains revealed that more and less successful comprehenders leveraged different comprehension strategies, such that skilled comprehenders were more likely to use combinations of strategies while reading the text, particularly paraphrasing and making connections between ideas within the text (i.e., bridging). Random Walk analysis further demonstrated that successful comprehenders employed strategies more consistently. The results demonstrate the utility of Markov and Random Walk models in profiling learners' strategy use based on their constructed responses.