Supplemental Material for From Individual Word Recognition to Word List and Text Reading Fluency

2018 ◽  
Author(s):  
Angeliki Altani ◽  
Athanassios Protopapas ◽  
Katerina Katopodi ◽  
George K. Georgiou

This study aimed to examine (a) the developing interrelations between the efficiency of reading individually presented words (i.e., isolated word recognition speed) and the efficiency of reading multiword sequences (i.e., word list and text reading fluency), (b) whether serial digit naming, indexing the ability to process multi-item sequences, accounts for variance in word list and text reading fluency beyond isolated word recognition speed, and (c) if these patterns of relations/effects differ between two alphabetic languages varying in orthographic consistency (English and Greek). In total, 710 Greek- and English-speaking children from Grades 1, 3, and 5 completed a serial digit naming task and a set of reading tasks, including unconnected words presented individually, unconnected words presented in lists, and sentences forming a meaningful passage. Our results showed that the relation between isolated word recognition speed and both word list and text reading fluency gradually decreased across grades, irrespective of contextual processing requirements. Moreover, serial digit naming uniquely predicted both word-list and text reading fluency in Grades 3 and 5, beyond isolated word recognition speed. The same pattern of results was observed across languages. These findings challenge the notion that individual word recognition and reading fluency differ only in text-level processing requirements. Instead, an additional component of processing multi-item sequences appears to emerge by Grade 3, after a basic level of both accuracy and speed in word recognition has been achieved, offering a potential mechanism underlying the transition from dealing with words one at a time to efficient processing of word sequences.


2020 ◽  
Vol 112 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Angeliki Altani ◽  
Athanassios Protopapas ◽  
Katerina Katopodi ◽  
George K. Georgiou

2017 ◽  
Vol 5 (3) ◽  
pp. 448
Author(s):  
Xiangying Jiang

<em>Cross-linguistic studies on second language (L2) reading reveal that component skills of reading such as word recognition, phonemic decoding, spelling, and oral text reading are prone to the influence of first language (L1) orthography but few empirical studies have examined the possible influence of L1 orthography on these skills. This study investigates how adult ESL learners of two different L1 backgrounds (Spanish and Chinese) compare in their performances on word recognition efficiency, phonemic decoding efficiency, spelling, and oral text reading fluency and how these skills are related to their overall ability in reading comprehension. The differences in the learners’ performances on the component skills and the variations in the role of these skills in ESL reading comprehension indicated possible influence of the orthographic features of learners’ first language.</em>


2021 ◽  
Vol 126 (3) ◽  
pp. 230-248
Author(s):  
Mallory A. Stevens ◽  
Matthew K. Burns

Abstract The purpose of the current study was to determine the extent to which practicing keywords increased word recognition, reading fluency and comprehension for students with intellectual disability (ID). The dependent measures included word recognition (i.e., the percentage of previously unknown keywords read correctly in the given text), reading fluency (i.e., words read correctly in 1 minute), and reading comprehension (i.e., number of questions answered correctly out of five). The participants were three fourth-grade students who were identified as having ID in early childhood with IQ scores of 45, 62, and 78. Words from reading passages were practiced with Incremental Rehearsal (IR) using a multielement, single-case design. Practicing keywords led to higher subsequent in-text recognition and generalization for a high percentage of the taught words. Additionally, there was clear experimental control for increases in reading fluency. There was not a strong effect on reading comprehension. Implications for research and practice are discussed.


2022 ◽  
Vol 12 ◽  
Author(s):  
Sietske van Viersen ◽  
Athanassios Protopapas ◽  
Peter F. de Jong

In this study, we investigated how word- and text-level processes contribute to different types of reading fluency measures. We aimed to increase our understanding of the underlying processes necessary for fluent reading. The sample included 73 Dutch Grade 3 children, who were assessed on serial word reading rate (familiar words), word-list reading fluency (increasingly difficult words), and sentence reading fluency. Word-level processes were individual word recognition speed (discrete word reading) and sequential processing efficiency (serial digit naming). Text-level processes were receptive vocabulary and syntactic skills. The results showed that word- and text-level processes combined accounted for a comparable amount of variance in all fluency outcomes. Both word-level processes were moderate predictors of all fluency outcomes. However, vocabulary only moderately predicted sentence reading fluency, and syntactic skills merely contributed to sentence reading fluency indirectly through vocabulary. The findings indicate that sequential processing efficiency has a crucial role in reading fluency across various measures besides individual word recognition speed. Additionally, text-level processes come into play when complexity and context availability of fluency measures increases, but the exact timing requires further study. Findings are discussed in terms of future directions and their possible value for diagnostic assessment and intervention of reading difficulties.


2019 ◽  
Vol 8 (4) ◽  
pp. 460
Author(s):  
Mahmoud I. Abdalla ◽  
Mohsen A. Rashwan ◽  
Mohamed A. Elserafy

During the previous year's holistic approach showing satisfactory results to solve ‎the ‎problem of Arabic handwriting word  recognition instead of word letters ‎‎segmentation.‎ ‎In this paper, we present an efficient system for ‎ generation realistic Arabic handwriting dataset from ASCII input ‎text. We carefully selected simple word list that contains most Arabic ‎letters normal and ligature connection cases. To improve the ‎performance of new letters reproduction we developed our ‎normalization method that adapt its clustering action according to ‎created Arabic letters families. We enhanced  Gaussian Mixture ‎Model process to learn letters template by detecting the ‎number and position of Gaussian component by implementing ‎Ramer-Douglas-Peucker‎ algorithm which improve the new letters ‎shapes reproduced by using and Gaussian Mixture Regression. ‎‎We learn the translation distance between word-part to achieve ‎real handwriting word generation shape.‎ Using combination of LSTM and CTC layer as a recognizer to validate the ‎efficiency of our approach in generating new realistic Arabic handwriting words inherit user handwriting style as shown by the experimental results.‎ 


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