Textese and use of texting by children with typical language development and Specific Language Impairment

Blom, Elma; Dijk, Chantal van; Vasić, Nada; Witteloostuijn, Merel van; Avrutin, Sergey

doi:10.1016/j.chb.2016.09.010

Cited by 8 publications

(14 citation statements)

References 38 publications

(53 reference statements)

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“…Since textisms are very different from conventional English words or phrases in terms of morphology, orthography and spelling, there are concerns that long-term use of textisms may adversely affect children's standard literacy. Many studies have explored the relationship between children's use of textisms and their standard literacy, but most of the findings have shown that children who text more and use more textese obtain higher scores on assessments of literacy skills (Waldron et al, 2015;Blom et al, 2017). These literacy skills include word reading (Plester et al, 2009;Coe and Oakhill, 2011), phonological awareness (Plester et al, 2009;Wood et al, 2011), and spelling (Plester et al, 2008;Bushnell et al, 2011;Wood et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Does Net-Speak Experience Interfere With the Processing of Standard Words? Evidence From Net-Speak Word Recognition and Semantic Decisions

2020

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The relationship between Chinese net-speak use and traditional literacy has rarely been discussed in the literature. In this study, we conducted two experiments to explore the effects of net-speak experience on word recognition and semantic decisions. A sample of senior middle school students was divided into a high-experience group and a low-experience group according to the students' net-speak experience, and the Go/No-Go task (Experiment 1) was adopted to investigate the differences between the two groups in the recognition of pure net-speak words and standard words. The results showed that the response time (RT) of participants was longer for pure net-speak word recognition than for standard word recognition. In addition, for both types of words, the recognition RT of participants in the high-experience group was shorter than that of participants in the low-experience group, but the accuracy (ACC) of pure net-speak word recognition was higher. Taking dual semantic net-speak words with both net-speak meaning and traditional meaning as priming stimuli and standard words related to the two meanings as targets, a semantic decision task (Experiment 2) was used to explore the differences between the two groups in judgments of the semantic relationship between the target words and priming words. The results showed that the decision ACC of participants in the high-experience group for both kinds of meaning-related words was significantly higher than that of participants in the low-experience group. The decision RT of participants in the high-experience group was slightly shorter for netspeak meaning-related words than traditional meaning-related words. The decision RT and ACC of participants in the low-experience group for both kinds of meaning-related words were equivalent. This shows that for Chinese teenagers, net-speak use may not disturb the processing of standard words; on the contrary, it may enhance processing.

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Section: Introductionmentioning

confidence: 99%

Does Net-Speak Experience Interfere With the Processing of Standard Words? Evidence From Net-Speak Word Recognition and Semantic Decisions

2020

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“…The authors found no difference in the text message length of children with typically developing skills and children with SLI; however, they did report that the children with SLI used fewer textisms (alternative word spellings) than the children with typically developing language skills (Blom et al, 2017). They also reported that the children with typically developing language skills omitted more words when texting than in speech whereas, the children with SLI produced a similar number of omissions in text and speech (Blom et al, 2017). The authors noted that this result may be reflective of failure on the part of the children with SLI to distinguish between texting and speech registers.…”

Section: Specific Considerations Relating To Texting Activity Studiementioning

confidence: 86%

“…Nevertheless, when Blom and colleagues (2017) examined the use of texting and textese in 55 children (ages 10 to 13) with typically developing language skills and 15 children with specific language impairment (SLI), both potential benefit and challenge in the use of texting was reported for the children with SLI. The authors found no difference in the text message length of children with typically developing skills and children with SLI; however, they did report that the children with SLI used fewer textisms (alternative word spellings) than the children with typically developing language skills (Blom et al, 2017). They also reported that the children with typically developing language skills omitted more words when texting than in speech whereas, the children with SLI produced a similar number of omissions in text and speech (Blom et al, 2017).…”

Section: Specific Considerations Relating To Texting Activity Studiementioning

confidence: 90%

“…has examined the effects of texting on language and literacy skills as well as texting abilities in both typically developing children and children with language or learning differences (e.g., Blom, van Dijk, Vasic, van Witteloostuijn, & Avrutin, 2017;Wood, Jackson, Hart, Plester & Wilde, 2011). Although some have questioned potential negative impacts of text language on traditional language skill development, this negative impact has not been supported by recent research (e.g., .…”

Section: Specific Considerations Relating To Texting Activity Studiementioning

confidence: 99%

“…The authors noted that this result may be reflective of failure on the part of the children with SLI to distinguish between texting and speech registers. Nevertheless, the authors observed that texting appeared to enable the children with SLI to meet socio-emotional needs, such as, expressing ideas/feelings that they may not have been able to express otherwise (Blom et al, 2017).…”

Section: Specific Considerations Relating To Texting Activity Studiementioning

confidence: 99%

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Language, Literacy, and Multiliteracies: Preparing Graduate Students to Provide Language Intervention in the 21st Century

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RALF: an adaptive reinforcement learning framework for teaching dyslexic students

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Dyslexia is a learning disorder in which individuals have significant reading difficulties. Previous studies found that using machine learning techniques in content supplements is vital in adapting the course concepts to the learners' educational level. However, to the best of our knowledge, no research objectively applied machine learning methods to adaptive content generation. This study introduces an adaptive reinforcement learning framework known as RALF through Cellular Learning Automata (CLA) to generate content automatically for students with dyslexia. At first, RALF generates online alphabet models as a simplified font. CLA structure learns each rule of character generation through the reinforcement learning cycle asynchronously. Second, Persian words are generated algorithmically. This process also considers each character's state to decide the alphabet cursiveness and the cells' response to the environment. Finally, RALF can generate long texts and sentences using the embedded word-formation algorithm. The spaces between words are proceeds through the CLA neighboring states. Besides, RALF provides word pronunciation and several exams and games to improve the learning performance of people with dyslexia. The proposed reinforcement learning tool enhances students' learning rate with dyslexia by almost 27% compared to the face-to-face approach. The findings of this research show the applicability of this approach in dyslexia treatment during Lockdown of COVID-19.

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Textese and use of texting by children with typical language development and Specific Language Impairment

Cited by 8 publications

References 38 publications

Does Net-Speak Experience Interfere With the Processing of Standard Words? Evidence From Net-Speak Word Recognition and Semantic Decisions

Does Net-Speak Experience Interfere With the Processing of Standard Words? Evidence From Net-Speak Word Recognition and Semantic Decisions

Language, Literacy, and Multiliteracies: Preparing Graduate Students to Provide Language Intervention in the 21st Century

RALF: an adaptive reinforcement learning framework for teaching dyslexic students

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