Prediction of Chinese Reading Fluency by Verbal and Non-verbal Visual Attention Span Measures

Abstract

This study explored (1) the relationship between verbal and non-verbal visual attention span measures and (2) the relationship between visual attention span and reading fluency in traditional Chinese, among 101 university students in Hong Kong. The participants' visual attention span was assessed using verbal measures (i.e., a global report task and a partial report task) and non-verbal measures (i.e., visual 1-back task with Chinese characters and visual 1-back task with symbols). The results of the confirmatory factor analysis indicated that the single latent factor model, composed of the global report task, the partial report task, the visual 1-back task with Chinese characters, and the visual 1-back task with symbols, was a good fit for the data. The results of the regression analysis showed that the global report task significantly predicted traditional Chinese reading fluency. Structural equation modeling revealed a significant predictive relationship between the single latent factor composed of verbal and non-verbal visual attention span measures and traditional Chinese reading fluency. Overall, the results indicate that visual attention span contributes to reading fluency in traditional Chinese.

The visual‐attention span deficit in developmental dyslexia: Review of evidence for a visual‐attention‐based deficit

“…Group studies reported small to no correlations between performance on verbal STM and oral VAS tasks in dyslexic individuals (C. Chen, Schneps, Masyn, & Thomson, 2016; Cheng et al, 2021). Second, the deficit when observed in the whole report condition was also found in partial report (Bosse et al, 2007; Valdois et al, 2021; Zoubrinetzky et al, 2014) and scores on the two tasks were highly correlated (correlation coefficients varying from .44 to .71; Bosse et al, 2007; Bosse & Valdois, 2009; Chan & Yeung, 2020; C. Chen et al, 2016; Holmes & Dawson, 2014; Valdois et al, 2021; Zoubrinetzky et al, 2014). Although no study provided a direct comparison of performance in the whole and partial report tasks, similar levels were typically reported, or slightly higher performance in partial report (Bosse et al, 2007; Bosse & Valdois, 2009; Saksida et al, 2016; Zoubrinetzky et al, 2014, 2016).…”

“…Group studies reported small to no correlations between performance on verbal STM and oral VAS tasks in dyslexic individuals (C. Chen, Schneps, Masyn, & Thomson, 2016;Cheng et al, 2021). Second, the deficit when observed in the whole report condition was also found in partial report (Bosse et al, 2007;Valdois et al, 2021;Zoubrinetzky et al, 2014) and scores on the two tasks were highly correlated (correlation coefficients varying from .44 to .71; Bosse et al, 2007;Bosse & Valdois, 2009;Chan & Yeung, 2020;C. Chen et al, 2016;Holmes & Dawson, 2014;Valdois et al, 2021;Zoubrinetzky et al, 2014).…”

“…This holds even for the partial oral report paradigm since the location of the target is unpredictable and the location cue is only displayed at the offset of the multielement string. Several paradigms were subsequently designed to assess VAS (for details see Supplementary Material), including tasks of non‐oral partial report (Collis et al, 2013; Hawelka, Huber, & Wimmer, 2006; Hawelka & Wimmer, 2005; Holmes & Dawson, 2014), visual‐1 back (Banfi et al, 2018; Chan & Yeung, 2020; Cheng et al, 2021; Huang, Lorusso, Luo, & Zhao, 2019; Lallier, Acha, & Carreiras, 2016; Lallier et al, 2018; Zhao et al, 2018a; Zhao, Kwok, Liu, Liu, & Huang, 2017; Zhao, Liu, Liu, & Chen, 2018b), two‐alternative forced choice (Jones, Branigan, & Kelly, 2008; Pammer, Lavis, Cooper, Hansen, & Cornelissen, 2005; Pammer, Lavis, Hansen, & Cornelissen, 2004; Yeari et al, 2017; Ziegler et al, 2010) and categorization (Lobier, Peyrin, Le Bas, & Valdois, 2012; Lobier, Peyrin, Pichat, Le Bas, & Valdois, 2014; Lobier, Zoubrinetzky, & Valdois, 2012; Peyrin et al, 2012; Peyrin, Démonet, Baciu, Le Bas, & Valdois, 2011). If the constraints of brief visual display and multielement processing were met in most studies, differences in the implementation of these paradigms may have had a non‐trivial impact on performance and explain some discrepancy between the reported findings, as will be discussed below.…”

Orthographic learning of novel words in adults: effects of exposure and visual attention on eye movements

“…Typically, VA span is estimated through tasks of multi-letter or multi-digit oral report but the VA span is not specific to verbal tasks and alphanumeric material. It can be very similarly estimated using nonverbal tasks and non-verbal stimuli, like symbols or pseudo-letters (Chan & Yeung, 2020;Lobier et al, 2012). Performance on VA span tasks reflects the amount of visual attention capacity available for processing (Dubois et al, 2010;Lobier et al, 2013), which relates to the dorsal attention network (Lobier et al, 2014(Lobier et al, , 2012Reilhac et al, 2013;Valdois et al, 2019aValdois et al, , 2014.…”

Probabilistic modeling of orthographic learning based on visuo-attentional dynamics

“…This seems to be the case. Indeed, there is growing evidence that visual attention is a concurrent and longitudinal predictor of word reading fluency (Bosse & Valdois, 2009;Chan & Yeung, 2020;Valdois et al, 2019;van den Boer & de Jong, 2018) and word spelling acquisition (Niolaki et al, 2020;Valdois et al, submitted;van den Boer et al, 2015) and that individuals with reduced visual attention capacity are slow readers and poor spellers (Bosse et al, 2007;Chen et al, 2019;Valdois et al, 2011;Valdois et al, 2021;Zoubrinetzky et al, 2014). Evidence that BRAID-Learn can account for the evolution of eye movement patterns when repeatedly confronted to the same input strings is further evidence in support of its theoretical assumptions.…”