We propose that machine-learned computational models (MLCMs), in which the model parameters and perhaps even structure are learned from data, can complement extant approaches to the study of text and discourse. Such models are particularly useful when theoretical understanding is insufficient, when the data are rife with nonlinearities and…

Taken together, the Coherence Principle of Multimedia Learning Theory and the Integrated Systems Hypothesis propose that co-occurring and semantically congruent verbal and visual information should be integrated into one mental representation that enhances memory. The purpose of this paper was to examine how learning pseudowords with matching…