Academic journal article Reading & Writing

Automaticity in Reading isiZulu

Academic journal article Reading & Writing

Automaticity in Reading isiZulu

Article excerpt

Introduction

Recent years have seen a surge of policy supporting the use of indigenous languages in Africa (Trudell 2010), but literature about reading in African languages is sparse. The article reports on indications of automaticity in a study of competent readers of isiZulu, the most widely spoken indigenous South African language.

Automaticity in reading

'Reading is arguably the most complex cognitive activity in which humans routinely engage' (Reichle, Warren & McConnell 2009), and yet it is taken for granted by millions of experienced readers who barely notice the fine combination of elements of perception and cognitive activity that cohere during reading. In brief, these are that as we read, we shift our focus along lines of text, processing symbols and their locations to generate visual representations of letters and words and select some of these to convert to concepts. As we glean information from each point of focus, we use unclear images in the parafoveal view that suggest word boundaries to plan the next focus shift. Simultaneously, we integrate lexical information gained with semantic and syntactic information from text already read to construct meaning of the text.

This complex combination of skills can become automatically integrated into a relaxed, swift exercise. When this happens, we have developed automaticity and can use brief visual perceptions of symbol clusters to automatically access associated pieces of language and meanings without additional active cognitive decoding (Penner-Wilger 2008). We can then engage imaginatively with meaning, making inferences, links with remembered information and judgements on what the writer has communicated. Without automaticity, it is extremely difficult for readers to construct a growing interpretation of texts as they read, to use context to aid comprehension (Marinelli, Martelli & Zoccolotti 2010), to gain new information from the text (Verhoeven, Reitsma & Siegel 2011), or to perform any higher order skills associated with reading (Abadzi 2012).

Attaining automaticity

Automaticity is regarded as crucial for reading by Helen Abadzi whose work in neuroscience has brought new insight to understanding reading processes. Abadzi describes automaticity as a 'vaccine' and an 'on-off switch' for literacy (2011); without it, competent reading is not possible. Confirming psycholinguistic evidence, neuroscience indicates that to read effectively, readers must move through text fluently and swiftly because human working memory has a capacity of about 12 seconds (Abadzi 2012). To understand messages in text, we must construct them as wholes, and so must read rapidly enough to get from the beginning to the end of each message within 12 seconds. In English, a minimum reading rate of 45-60 words per minute (wpm) appears necessary for reading at a basic level (Abadzi 2012). Complex tasks, like searching for information, require speeds of about 250 wpm (Abadzi 2010). This reading rate can be achieved only through automatic, instantaneous recognition of a significant proportion of words, and to establish automaticity clusters of letters must be perceived as whole words or units rather than groups of characters. This develops only through extensive exposure to text and repeated association of particular clusters with words or units they represent.

Children who are included in literacy-related practices early and have explicit instruction in developing reading skills and plenty of supported reading practice usually achieve automaticity easily. In contrast, children who have little exposure to literacy practices, mediocre instruction and infrequent reading practice may never achieve it (Abadzi 2012). People who learn to read after adolescence rarely achieve automaticity, and adults learning to read a new script report that although they see all the letters, they must consciously work out what words they represent (Abadzi 1996). In a new script, a word needs to be decoded approximately 3000 times before it is automatically recognised (Abadzi 2012). …

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