Effects of transcription ability and transcription mode on translation:: Evidence from written compositions, language bursts and pauses when students in grades 4 to 9, with and without persisting dyslexia or dysgraphia, compose by pen or by keyboard

In a split second: Handwriting pauses in typical and struggling writers

Introduction

A two-second threshold has been typically used when analyzing the writing processes. However, there is only a weak empirical basis to claim that specific average numbers and durations of pauses may be associated with specific writing processes. We focused on handwriting execution pauses, because immature writers are known to struggle with transcription skills. We aimed to provide an evidence-based account of the average number and duration of handwriting pauses in the mid-Primary grades and to identify process-level markers of writing difficulties.

Methods

Eighty 3rd and 5th graders, with and without writing difficulties, participated in the study. We examined pauses in a handwriting-only task, to be able to isolate those which could only be attributed to handwriting processes. Letter features were considered, as well as children's handwriting fluency level.

Results

The average duration of handwriting pauses was around 400ms, in line with assumptions that transcription pauses would fall under the 2,000ms threshold. We found that 3rd graders made more and longer pauses than 5th graders. Struggling writers made a similar number of pauses across grades than typically-developing children, although they were significantly longer, even after controlling for the effect of handwriting fluency.

Discussion

Our findings provide an evidence-based account of the duration of handwriting pauses. They also suggest that children need fewer and shorter handwriting pauses as they progress in automatizing transcription. However, some young writers struggle with letter formation even after 3 to 5 years of instruction.

Co-Occurrence of Reading and Writing Difficulties: The Application of the Interactive Dynamic Literacy Model

This article presents the application of the interactive dynamic literacy (IDL) model (Kim, 2020b) toward understanding difficulties in learning to read and write. According to the IDL model, reading and writing are part of communicative acts that draw on largely shared processes and skills as well as unique processes and skills. As such, reading and writing are dissociable but interdependent systems that have hierarchical, interactive, and dynamic relations. These key tenets of the IDL model are applied to the disruption of reading and writing development to explain co-occurrence of reading-writing difficulties using a single framework. The following hypotheses are presented: (a) co-occurrence between word reading and spelling and handwriting difficulties; (b) co-occurrence of dyslexia with written composition difficulties; (c) co-occurrence between reading comprehension and written composition difficulties; (d) co-occurrence of language difficulties with reading difficulties and writing difficulties; (e) co-occurrence of reading, writing, and language difficulties with weak domain-general skills or executive functions such as working memory and attentional control (including attention-deficit/ hyperactivity disorder [ADHD]); and (f) multiple pathways for reading and writing difficulties. Implications are discussed.

Mode effect: An issue of perspective? Writing mode differences in a spelling assessment in German children with and without developmental dyslexia

Digital technology has an increasing influence on writing processes. In this context, the question arises whether changes in writing mode (i.e., handwriting vs. computer-keyboard typing) also require changes in writing assessments. However, data directly comparing writing mode influences in children with and without developmental writing deficits are scarce. This study investigated the influence of writing mode in German-speaking, typically developing children and children with developmental dyslexia (DD) from two different levels. Results showed on a general level that writing mode influenced overall spelling accuracy, writing time, and self-corrections comparably in children with and without DD. On a rule-specific level, outcomes for writing time and self-corrections substantiated these findings. However, as regards spelling accuracy, a mode effect was only apparent for capitalization, whereas other spelling rules were resistant to writing mode influences. Present findings suggest that a mode effect is present only for typing specific aspects (e.g., capitalization) rather than reflecting a general influence on orthographic principles (e.g., grapheme-phoneme assignment, morphologic principles). These mode-specific aspects seem to comparably affect the writing performance of typically developing children and children with DD. We recommend writing assessments to consider that different writing modes may influence individual spelling rules differently.

Dysgraphia detection through machine learning

Dysgraphia, a disorder affecting the written expression of symbols and words, negatively impacts the academic results of pupils as well as their overall well-being. The use of automated procedures can make dysgraphia testing available to larger populations, thereby facilitating early intervention for those who need it. In this paper, we employed a machine learning approach to identify handwriting deteriorated by dysgraphia. To achieve this goal, we collected a new handwriting dataset consisting of several handwriting tasks and extracted a broad range of features to capture different aspects of handwriting. These were fed to a machine learning algorithm to predict whether handwriting is affected by dysgraphia. We compared several machine learning algorithms and discovered that the best results were achieved by the adaptive boosting (AdaBoost) algorithm. The results show that machine learning can be used to detect dysgraphia with almost 80% accuracy, even when dealing with a heterogeneous set of subjects differing in age, sex and handedness.

Online Writing Processes in Translating Cognition into Language and Transcribing Written Language by Stylus and Keyboard in Upper Elementary and Middle School Students With Persisting Dysgraphia or Dyslexia

Participants in this study completed an on-line experiment in which they wrote essays by stylus or keyboard. Three translation measures (length of language burst, length of pauses, and rate of pausing) and four transcription measures (total words, total time, words/minute, and percent spelling errors) for composition were analyzed for two research aims. Research Aim 1 addressed whether upper elementary and middle school students with carefully diagnosed transcription disabilities (dysgraphia with impaired handwriting, n=18, or dyslexia with impaired spelling, n=20) showed significant differences from pretest to posttest, across modes of transcription (stylus or keyboard), and between diagnostic groups. Results showed significant (a) change after intervention (18 computerized lessons with learning activities in letter formation/selection, spelling, and composing) in length of pauses, total time, and words per minute; (b) mode effects (fewer words and less time by stylus; fewer pauses per minute by keyboard); and (c) interactions with diagnostic group in response to intervention on some measures. Research Aim 2 addressed whether following intervention each of the diagnostic groups performed comparably to a typical control group (n=15) in the same on-line experiment. Results showed (a) comparable performance of the dysgraphia and control groups on all keyboarding tasks but differences on two stylus measures; and (b) lack of comparable performance of the dyslexia and control groups on two stylus measures (total words and percent spelling errors) and the four keyboarding tasks related to transcription. Implications for assistive technology and writing instruction for dysgraphia and dyslexia are discussed.