Bibliographic record
Abstract
Summary Reading and writing are based on complex adaptive processes of perception, attention, and memory. A failure in learning to read can be due to a dysfunction of a single process, a number of serial processes, or to the interaction of parallel processes. This article focuses on the role of working memory functions for reading and writing. Evidence for a deficit of working memory in dyslexic children is reviewed. Furthermore, evidence is presented which shows that a training of special working memory functions leads to a critical improvement in reading and writing performance in dyslexic children. Key words: working memory, reading, writing, dyslexia, training methods The importance of working memory for reading and writing In order to perform reading and writing, perceptual information has to be maintained in working memory for a certain period to be available for active processing. At the same time, semantic, syntactic, orthographic and episodic information from long-term memory is activated to be merged with the perceptual input (see Figure 1). Baddeley and Hitch (1974) assume three components of working memory. They postulate two capacity-limited and modality-specific subsystems, that are, the phonological loop and the visual-spatial sketch pad. These subsystems are controlled by a third component, the so-called Central Executive. According to Cowan (1995) the functions of the Central Executive can be differentiated by their proportion of automatic and controlled executive processes. Automatic executive processes are to a great extent unconscious and can be performed with a low degree of mental effort. Such automatic executive processes occur, for instance, in automatic word recognition. Controlled executive processes, on the other hand, require the conscious analysis and synthesis of information. This is the case, for instance, in reading on the basis of grapheme-phoneme-correspondences (see Figure 1). Consequently, the question arises whether certain deficits in the efficiency of working memory may account for the problems in learning to read and to write. Deficits of working memory in dyslexic individuals Deficits of working memory in dyslexics have been studied using different paradigms and types of material both with auditory and visual stimuli. There are different results concerning visual-spatial deficits. So and Siegel (1997) have found deficits in Canadian and Chinese dyslexics in the free recall of word lists. Ellis (1981) reported four visual matching experiments. He did not find any group differences when the stimuli to be compared were shapes. However, when the stimuli were phonologically similar letters, significant group differences were found. Ellis interpreted these results as naming deficits. Vellutino's findings (1987) disagree with a general deficit of the visual working memory as well. His dyslexic children were able to reproduce unknown Hebrew words and letters just as well as children of the control group. If the word list was in English, however, the dyslexic children performed significantly poorer than the control group. Vellutino interpreted these findings as a deficit in serial recall of linguistic items in dyslexics. Barnea, Lamm, Epstein and Pratt (1994) found differences in Hebrew speaking dyslexics when they had to deal with visual lexical stimuli when presented as a series as well. In visual same-different tasks Willows, Corcos and Kershner (1993) used Hebrew letters, which were unknown to the dyslexic and the control children at the age level of 6, 7 and 8 years. The authors found differences in speed and accuracy which tend to be stronger in younger children of 6 years in comparison to 8 years. In a study by Witruk and Rosendahl (1999), the compensation of the deficits of visual working memory was proved. The authors used visual and phonological matching tasks as well as visual and phonological serial recall. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".