Grade 4 South African learners wrote the test in the language which had been the language of learning and teaching (LoLT) during the Foundation Phase. In 2006, South Africa was one of the 45 countries that participated in the Progress in International Reading Literacy Study (PIRLS), which assesses reading comprehension. Finally, initial active vocabulary knowledge was found to be a strong predictor of vocabulary development during the school year. This confirms findings that children who start school with weak language skills tend to stay weak. Learners in both language groups who were above their grade age had significantly lower scores than their younger peers.
No significant gender differences were found. Regarding their receptive vocabulary, the English FAL learners on average only knew 27% of the most frequent words at the end of their Grade 3. Results showed that although the HL learners knew almost double the number of words their English FAL peers did, both groups of learners increased their active word knowledge through the year by about 9%. This test assessed their knowledge of the 60 most frequent words that occur in South Africa Grade 4 English textbooks. Another 284 learners from the same eight Grade 3 classes participated in a receptive vocabulary test at the end of the year. The Woodcock-Muñoz Language Survey was used to measure the active vocabulary levels of 118 learners at the beginning and the end of the school year. The purpose was to document their different vocabulary trajectories during Grade 3. The groups consisted of English Home Language (HL) learners in the Western Cape and Xhosa HL and English First Additional Language (FAL) learners in the Eastern Cape. In this article, we report on a study that examined the active and receptive English vocabulary of two different groups of Grade 3 learners in South African township schools. IICentre for Language Studies, Radboud University Nijmegen, Netherlands IDepartment of Linguistics and Modern Languages, University of South Africa, South Africa The effects of noise (i.e., the introduction of acoustic analyzer errors) and lexicon size will also be discussed.How is their word knowledge growing? Exploring Grade 3 vocabulary in South African township schoolsĮlizabeth J. If, on the other hand, we hypothesize that the acoustic analyzer can make a six‐way distinction, then roughly 1 3 of the lexicon has unique patterns. For example, if we hypothesize that the acoustic analyzer can only make a distinction between consonants and vowels, then the specification of the CV pattern of a given word can, on the average, prune the 20 000 word lexicon down to less than 1%. We focused on the question: Can properties of the lexicon be exploited in the design of the acoustic analyzer? Our results indicate that the search space can be substantially reduced without having to specify the detailed phonetic characteristics of the lexical entries. As part of our goal to design large‐vocabulary, speaker‐independent IWR systems, we investigated the properties of large lexicons ranging from 1250 words to 20 000 words. Even if cost is not an issue, the performance of these IWR systems for a very large vocabulary is questionable. When the size of the lexicon is very large (over 10 000 words), the computation and storage requirements associated with current IWR systems will become prohibitively expensive. A limitation of pattern‐recognition‐based, isolated‐word recognition (IWR) systems is that computation and storage grows (essentially) linearly with the size of the vocabulary.
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