Desirable Difficulty in Learning: A Computational Investigation

Abstract

Certain difficulties of a word learning situation can promote long-term learning, and thus are referred to as "desirable difficulties". We use a computational modelling approach to examine the possible explanatory factors of the observed patterns in a cross-situational word learning experiment. Our results suggest that the within-trial ambiguity and the presentation duration of each trial in addition to other distributional characteristics of the input (experimental stimuli) may explain these results. Our findings also emphasize the role of computational modelling in understanding empirical results.


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