Word Learning in Context -- a Computational Theory

Raluca Budiu

John R. Anderson

Abstract

This document presents two experiments related to learning new words in context. We deal with two types of new words: metaphors (words for whom a related meaning already exists) and artificial words. The new words are used anaphorically to refer to past objects in the text. For anaphoric metaphors, the experiments find support for Searle's error recovery theory of metaphor comprehension. Subjects learn the meaning of the metaphors more rapidly, but after repeated exposure to the words in appropriate contexts, both sentences containing artificial words and sentences containing metaphors are processed comparably with the sentences made only of familiar words. Results suggest that participants use context matching to understand and learn new words. We present a computational model that captures the essential trends in the data obtained from the two experiments.

ACT-R Model

Microsoft Excel Spreadsheet of the model