How do task demands and aging affect lexical prediction during online reading of natural texts?

Autor: Aaron Veldre, Sally Andrews, Erik Reichle, Lili Yu, Roslyn Wong
Rok vydání: 2023
Předmět:
Zdroj: Journal of Experimental Psychology: Learning, Memory, and Cognition
ISSN: 1939-1285
0278-7393
DOI: 10.1037/xlm0001200
Popis: Facilitated identification of predictable words during online reading has been attributed to the generation of predictions about upcoming words. But highly predictable words are relatively infrequent in natural texts, raising questions about the utility and ubiquity of anticipatory prediction strategies. This study investigated the contribution of task demands and aging to predictability effects for short natural texts from the Provo corpus. The eye movements of 49 undergraduate students (mean age 21.2) and 46 healthy older adults (mean age 70.8) were recorded while they read these passages in two conditions: (i) ‘reading for meaning’ to answer occasional comprehension questions; (ii) ‘proofreading’ to detect ‘transposed letter’ lexical errors (e.g., clam instead of calm) in intermixed filler passages. The results suggested that the young adults, but not the older adults, engaged anticipatory prediction strategies to detect semantic errors in the proofreading condition, but neither age group showed any evidence of costs of prediction failures. Rather, both groups showed facilitated reading times for unexpected words that appeared in a high constraint within-sentence position. These findings suggest that predictability effects for natural texts reflect partial, probabilistic expectancies rather than anticipatory prediction of specific words.
Databáze: OpenAIRE