| There is ample evidence demonstrating that the degree of interest for an informational environment (e.g., a textual passage, a perceptual stimulus, a problem-solving task, educational software) predicts the quantity and quality of learning from that environment, with higher levels of interest leading to better learning. What is less understood are the causal factors that produce interest for such an environment. This dissertation proposes and tests a theory, called the knowledge-schema theory of cognitive interest (KST), which identifies the cognitive mechanisms that determine whether information will be considered interesting. The KST, which integrates a number of previously proposed hypotheses regarding the causes of interest, states that interest for information occurs as a function of schema enhancement and schema modification; the theory predicts that information that induces learning through either of these processes will be considered more interesting than information that does not. Chapter 1 presents the foundations, assumptions, and predictions of the KST. Chapters 2, 3, and 4 describe a series of experiments that test the efficacy of the theory in predicting interest for information as a function of schema enhancement and modification. The general findings of these experiments support the predictions of the KST: information that induced either schema enhancement or schema modification is rated as more interesting than information that induces neither. In addition, across all 4 experiments, measures of learning positively covary with measures of interest, and covariance matrix modeling techniques support the hypothesis that learning is a predictor of interest. Future research directions and the pedagogical implications of the knowledge-schema theory are discussed in Chapter 5. |
