Machine-Learned Computational Models Can Enhance the Study of Text and Discourse: A Case Study Using Eye Tracking to Model Reading Comprehension.

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...

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Publicado en:	Discourse Processes Vol. 57; no. 5/6; pp. 420 - 441
Autores principales:	D'Mello, Sidney K., Southwell, Rosy, Gregg, Julie
Formato:	Artículo
Publicado:	Taylor & Francis Ltd Jun/Jul2020
Materias:	Reading comprehension Eye tracking Receiver operating characteristic curves R-curves Eye movements Listening comprehension
Acceso en línea:	Ver este registro en EBSCOhost