دانلود مقاله ISI انگلیسی شماره 59728
ترجمه فارسی عنوان مقاله

تفاوت های فردی در خواندن با صدای بلند: متا بررسی، اثر مورد و برخی از مدل ها

عنوان انگلیسی
Individual differences in reading aloud: A mega-study, item effects, and some models
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
59728 2014 48 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Cognitive Psychology, Volume 68, February 2014, Pages 113–160

ترجمه کلمات کلیدی
بازشناسی کلمات بصری؛ نامگذاری کلمه؛ تفاوتهای فردی؛ مدل سازی محاسباتی؛ بلند خواندن
کلمات کلیدی انگلیسی
Visual word recognition; Word naming; Individual differences; Computational modelling; Reading aloud
پیش نمایش مقاله
پیش نمایش مقاله  تفاوت های فردی در خواندن با صدای بلند: متا بررسی، اثر مورد و برخی از مدل ها

چکیده انگلیسی

Normal individual differences are rarely considered in the modelling of visual word recognition – with item response time effects and neuropsychological disorders being given more emphasis – but such individual differences can inform and test accounts of the processes of reading. We thus had 100 participants read aloud words selected to assess theoretically important item response time effects on an individual basis. Using two major models of reading aloud – DRC and CDP+ – we estimated numerical parameters to best model each individual’s response times to see if this would allow the models to capture the effects, individual differences in them and the correlations among these individual differences. It did not. We therefore created an alternative model, the DRC-FC, which successfully captured more of the correlations among individual differences, by modifying the locus of the frequency effect. Overall, our analyses indicate that (i) even after accounting for individual differences in general speed, several other individual difference in reading remain significant; and (ii) these individual differences provide critical tests of models of reading aloud. The database thus offers a set of important constraints for future modelling of visual word recognition, and is a step towards integrating such models with other knowledge about individual differences in reading.