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. 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. The purpose was to document their different vocabulary trajectories during Grade 3. 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. Another 284 learners from the same eight Grade 3 classes participated in a receptive vocabulary test at the end of the year. This test assessed their knowledge of the 60 most frequent words that occur in South Africa Grade 4 English textbooks. 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%. 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. No significant gender differences were found. Learners in both language groups who were above their grade age had significantly lower scores than their younger peers. This confirms findings that children who start school with weak language skills tend to stay weak. Finally, initial active vocabulary knowledge was found to be a strong predictor of vocabulary development during the school year.
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. 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 PIRLS, the Low International Benchmark of 400 reflects basic, literal understanding of explicitly stated information in a text. Not being able to achieve this basic level of reading puts learners at risk of not being able to read. Only 13% of Grade 4 learners in South Africa reached this benchmark; in other words, 87% of Grade 4 learners in South Africa were at serious risk of not being able to read. Reading performance in the African languages was particularly low. When South Africa participated in the next round of PIRLS in 2011, the results were not much better. This time, Grade 4 learners participated in pre-PIRLS, an easier reading assessment with shorter texts (Howie & Van Staden
Given that PIRLS assesses reading comprehension, poor performance in PIRLS obviously points to comprehension challenges that need to be addressed in South African classrooms. But what other lessons, besides the obvious comprehension ones, can be drawn from PIRLS? Reading research has consistently shown that poor reading comprehension is also strongly associated with two other factors: poor decoding skills and inadequate vocabulary. Decoding enables comprehension. If learners cannot yet decode written language fluently, their comprehension is severely compromised (Hoover & Gough
From this, it can be argued that South Africa’s poor performance in PIRLS also points to vocabulary challenges that need to be addressed in the classrooms. Spaull (
Research has shown that vocabulary correlates strongly with all aspects of language proficiency, such as oral comprehension (Alderson
Vocabulary also shows strong associations with socio-economic status, and there are large disparities in word knowledge amongst children when they start formal schooling (Corson
Despite the importance of vocabulary in language and reading achievement, there is surprisingly little formal vocabulary research being undertaken in Home Language (HL) or First Additional Language (FAL)
In this article, we report on a small-scale study that examined the active and receptive English vocabulary of two different groups of Grade 3 learners in schools that serve poor communities. The first Grade 3 group comprised English HL learners in township schools in the Cape Flats in the Western Cape, while the other group were Xhosa HL and English FAL learners in township schools in Port Elizabeth. While the learners differed in terms of whether they were HL or FAL users of English, what they had in common was that they attended schools in disadvantaged areas. Given the large differences in vocabulary knowledge that naturally exist between HL and FAL learners, the purpose was not to compare the two groups, but rather to document their different vocabulary trajectories during Grade 3 in non-affluent schooling conditions. Before we turn to the study itself, we first provide a brief review of vocabulary development in the early school years and the effects that poverty can have on vocabulary.
Children learn their first words from social interaction with people in their lives. This interaction is grounded in the concrete, here-and-now of daily events and actions of the young child’s life, and provides a potentially rich oral communicative context within which words are acquired.
Although many words are explicitly ‘taught’ to young children during social interaction, it is generally agreed that there is a large amount of vocabulary that, for all practical purposes, could not have been explicitly taught and must therefore have been incidentally acquired. In other words, it is generally held that children infer the meanings of a large number of unfamiliar words from oral contexts before they start school (Nagy & Herman
Estimates about vocabulary size and rate of development vary, depending on how the concept of ‘word’ is defined, how word counts in a particular language are undertaken, how word knowledge is defined and assessed, and whether one is referring to HL or FAL vocabulary development. Some scholars define a word as a graphically distinct type (e.g. White, Graves & Slater
Furthermore, vocabulary development does not only involve the quantitative accumulation of new words to the lexicon; qualitative development is also an integral part of vocabulary acquisition. Many words in a language’s lexicon are polysemous, conveying different meanings in different contexts (e.g. light comes from the sun; a light wind; light blue). Vocabulary development should therefore also take into account the degree of knowledge, which progresses from receptive knowledge (recognising words when heard or seen) to active or productive knowledge (using words in speech or writing). We always know more words than we use. There are a large number of words that never progress to free active use but remain part of a learner’s receptive vocabulary repertoire.
As the discussion so far indicates, vocabulary development is quantitatively and qualitatively cumulative, and for HL English learners, fairly rapid too, with about 1000 word families (equivalent to about 3000 words) added each year. Increasing age typically reflects increasing word knowledge, unless children have language or learning difficulties, in which case their vocabulary is often below that of their age peers. Proposing a developmental sequence for HL vocabulary, Nation (
Research indicates that variables such as home and school background as well as individual ability affect vocabulary development considerably. As already indicated, socioeconomic status has been found to have an early and persistent effect on children’s vocabulary. In their groundbreaking research, Hart and Risley (
Further evidence of vocabulary differences between socioeconomic groups comes from Corson’s British research (
What about FAL vocabulary development, and what are the estimates with regard to the size of English FAL learners’ vocabularies? The notion of incidental word learning in context is obviously less problematic when applied to the HL because, by the time children start school, they have already acquired basic competence in the language, which provides a scaffold for inferring word meaning from context. Furthermore, they are extensively exposed to the language in print or oral form on a daily basis. The underlying linguistic competence of FAL students is not commensurate with that of HL students, and they typically have less exposure to the language. Thus, not only do they have fewer bootstrapping mechanisms to infer word meaning but they also have fewer opportunities in which to apply word inferencing processes. Laufer (
Turning to South Africa, in the Threshold report, Macdonald (
Although there is a strong association between vocabulary and reading, the nature of the relationship changes at different stages of schooling, with vocabulary becoming an increasingly stronger determinant of reading ability as children move up the schooling ladder. The following trends have been observed:
Some studies have shown vocabulary size to be a weak predictor of Grade 1 reading ability (e.g. Scarborough
Vocabulary is a strong predictor of reading achievement in Grade 4 (Scarborough
Vocabulary size at the end of Grade 1 is a significant predictor of reading comprehension 10 years later (Cunningham & Stanovich
Children with restricted vocabularies at the end of Grade 3 show declining reading comprehension scores in later primary school (Chall et al.
Given the multilingual nature of South African schooling, what guidelines does the curriculum provide regarding vocabulary development? The Foundation Phase
Mindful of two factors – the expected differences in vocabulary knowledge in HL and FAL, and the barriers that low SE status can impose on learning and vocabulary knowledge across languages – the main aim of this study was to investigate the vocabulary levels of Grade 3 learners in schools that serve disadvantaged communities. This is a small-scale exploratory study of Grade 3 learners in four schools in the Western and Eastern Cape provinces. We captured the aim in the following research questions:
How does active word knowledge of Grade 3 learners in English HL and English FAL schools develop during the course of the Grade 3 year?
What is the receptive word knowledge of high-frequency words of Grade 3 learners at the end of the Foundation Phase?
Are there age and gender differences in active and receptive word knowledge of Grade 3 learners?
Is there a relationship between the learners’ active and receptive word knowledge?
What is the role of initial active vocabulary knowledge on vocabulary development during the year?
A pre-test post-test design using intact classroom groups was used in which Grade 3 learners’ active vocabulary knowledge in English was measured at the beginning and at the end of the school year. The learners’ receptive knowledge of high-frequency words was also measured at the end of the school year. Because no vocabulary assessment instruments and development norms have yet been established in the African languages, and because very little attention has been given to vocabulary research in the South African context, it was decided to make do with two existing instruments: the Woodcock-Muñoz picture vocabulary test and Sibanda’s high-frequency word tests (Sibanda
Two different low-SE urban primary schools in the Eastern Cape and two in the Western Cape participated in the study. The two schools in the Western Cape were English HL primary schools, situated in the Cape Flats and serving mainly low-income mixed race communities. The schools had Afrikaans as their First Additional Language in Foundation Phase. These will be referred to as schools WC1 and WC2.
The two schools in the Eastern Cape had Xhosa Home Language as their LoLT and English as their FAL in Foundation Phase. These are Quintile 3 schools situated in township areas of Port Elizabeth. These will be referred to as schools EC1 and EC2. From each school, two classes participated in the vocabulary research, amounting to a total of eight classes, four from each province.
All the schools were part of a larger three year project, the Zenex Literacy Project (2015-2017), that worked with Foundation Phase teachers in Quintile 1–3 schools
In total, 118 Grade 3 learners from eight different classes from the four selected schools participated in an active vocabulary test. Their active vocabulary was assessed twice: at the start of the year (January 2016) and at the end of the year (November 2016). Their average age at the start of the year was 8.4 years and towards the end of the year it was 9.1 years. The genders were fairly evenly distributed across the classes, except for school EC1 where there were more girls than boys in the class (for details, see data collection procedures). The dominant HL spoken by the learners’ parents was Xhosa in the Eastern Cape and English in the Western Cape (see
Home languages spoken by Grade 3 learners’ parents (percentages) (
Language | Western Cape |
Eastern Cape |
||
---|---|---|---|---|
HL Mother | HL Father | HL Mother | HL Father | |
English | 79.3 | 74.1 | 0.0 | 1.7 |
Xhosa | 13.8 | 12.1 | 98.3 | 95.0 |
Afrikaans | 5.2 | 10.3 | 0.0 | 3.3 |
Shona | 1.7 | 1.7 | 0.0 | 0.0 |
Zulu | 0.0 | 0.0 | 1.7 | 0.0 |
Unknown | 0.0 | 1.7 | 0.0 | 0.0 |
HL, Home Language.
No standardised or normed vocabulary tests have yet been developed in South Africa. The Woodcock-Muñoz Language Survey was used to measure the active vocabulary levels of 15 Grade 3 learners from each of the eight classes in our sample. It was developed in the USA to assess the language development of bilingual children (mainly Hispanic). Because it was developed specifically for bilingual children, it was decided to use this test in the South African context. The Woodcock-Muñoz Language Survey (English) is a standardised set of four subtests that measure proficiency in oral language, reading and writing in speakers of English as a second language, with a minimum starting age of at least 2 years. The vocabulary subtest tests active vocabulary where testees must name 59 picture objects. The picture items start with familiar everyday items (e.g.
The test is administered one-on-one, and provides scores for individual vocabulary knowledge which can be used to classify a learner’s English vocabulary level according to age and grade level. To ensure the test items were appropriate for the sample, an analysis of the items was performed to assess suitability for primary school children in the South African context. As a result, 15 test items that were considered to be potentially unfamiliar to South African primary school students were replaced by items from a similar instrument (the Renfrew Vocabulary Test
Two high-frequency word tests were also used based on the work of Sibanda (
A definition matching test (Sibanda’s Test 4): here a list of definitions is given on the left side of the page, and the testee is asked to match them up with a list of relevant words given in an oval on the right of the page (e.g.
A modified cloze (gap-filling) test (Sibanda’s Test 6): a list of sentences is provided on the left side of the page with one word missing from the sentence, and the testee fills in the gap with words chosen from an oval containing words on the right of the page. This test assesses receptive knowledge, as prompts to the gaps are provided. Several of the words in this subtest were function words (e.g. prepositions, auxiliaries, etc.)
A total of 36 items were included in the tests. The Cronbach’s alpha reliability coefficient for the combined tests was high (0.95), which means that this is a robustly reliable test. Details of the tests used in the current research are presented in
Vocabulary tests used.
Instruments | Dimension of word knowledge tested | Type of words tested |
---|---|---|
1. Woodcock-Muñoz test | Active vocabulary knowledge | 59 words (concrete nouns) |
2. Definition matching test | Receptive vocabulary Knowledge | 13 words from Sibanda’s HFW list |
3. Cloze (gap-filling) test | Receptive vocabulary Knowledge | 23 words from Sibanda’s HFW list |
HFW, high frequency word.
The tests were administered by two external researchers during school hours. Because of time and budgetary constraints, for the one-on-one active vocabulary assessment, a purposive stratified sample of 15 learners from each of the eight Grade 3 classes was used. The classroom teachers were asked to select participants based on their class performance: five top learners, five average learners and five weak learners, respectively. Demographic characteristics of the test participants are presented in
Active word knowledge test: Participants per school, gender distribution and average age (January 2016).
School | Female (%) | Male (%) | Average age | |
---|---|---|---|---|
EC School 1 | 30 | 63.3 | 36.7 | 8.7 |
EC School 2 | 30 | 50.0 | 50.0 | 8.8 |
WC School 1 | 28 | 53.6 | 46.4 | 8.2 |
WC School 2 | 30 | 43.3 | 56.7 | 8.0 |
Overall | 118 | 52.5 | 47.5 | 8.4 |
Sibanda’s receptive word knowledge test of high-frequency words was administered in November to all 284 learners from the same eight Grade 3 classes. The pen-and-paper test was administered to the whole class, in the classroom, by two external researchers during regular class hours. Demographic characteristics of the test participants are presented in
Receptive word knowledge test of high-frequency words: Participants per school, gender distribution and average age (in November 2016).
School | No. of students | Female (%) | Male (%) | Average age |
---|---|---|---|---|
EC School 1 | 71 | 60.6 | 39.4 | 9.3 |
EC School 2 | 70 | 50.0 | 50.0 | 9.4 |
WC School 1 | 72 | 51.4 | 48.6 | 9.0 |
WC School 2 | 71 | 46.5 | 53.5 | 8.8 |
Overall | 284 | 52.1 | 47.9 | 9.1 |
For both samples, the demographic items on gender, age and HL were averaged per school. The average score on the vocabulary test was calculated for all participants. The Kolmogorov–Smirnov test was used to determine normal distributions within the two separate groups (Western Cape [WC)]and Eastern Cape [EC]). Scores were normally distributed within each sample: the EC,
All the schools were part of a larger three year project that worked with Foundation Phase teachers, the aim of which was to improve learner literacy levels through improved classroom literacy practices. Permission to work in these schools was obtained at national and provincial levels. The focus of this larger intervention was on improving teacher reading instruction and increasing reading opportunities, primarily in the HL and also in the FAL.
All the schools were informed about the vocabulary study at the beginning of the year and two schools from each province were asked to volunteer to participate. Permission to use the Sibanda’s high-frequency word tests was obtained in March 2016.
The first research question is related to how active vocabulary knowledge of Grade 3 learners in English HL and English FAL schools developed during the course of the Grade 3 year, using the Woodcock-Muñoz vocabulary test.
Results at province level are presented in
Woodcock-Muñoz vocabulary test scores per province (%).
Province | Pre-test | Post-test | Gains | ||
---|---|---|---|---|---|
Western Cape English HL ( |
Mean | 60.3 | 68.8 | 8.5 | |
SD | 13.4 | 12.6 | 5.4 | ||
SE | 1.8 | 1.7 | 0.7 | ||
Minimum | 36.2 | 46.6 | 10.4 | ||
Maximum | 86.2 | 94.8 | 8.6 | ||
Percentiles | 25 | 51.7 | 58.6 | 4.7 | |
50 | 58.6 | 67.2 | 9.5 | ||
75 | 69.8 | 77.6 | 12.1 | ||
Eastern Cape English FAL ( |
Mean | 31.4 | 41.2 | 9.7 | |
SD | 9.2 | 8.6 | 5.7 | ||
SE | 1.2 | 1.1 | 0.7 | ||
Minimum | 10.3 | 20.7 | 10.4 | ||
Maximum | 60.3 | 70.7 | 10.4 | ||
Percentiles | 25 | 24.1 | 36.2 | 5.2 | |
50 | 31.0 | 41.4 | 8.6 | ||
75 | 37.9 | 46.6 | 13.8 |
HL, home language; FAL, first additional language; SD, standard deviation.
By the end of the year, this gap remained more or less the same, with the mean score of English FAL learners in the Eastern Cape at 41.2%, whereas the mean score of the English HL learners in the Western Cape was 68.8%. What is also interesting to note is that across all the schools, the vocabulary growth of children at the 25th percentile (i.e. those with lower scores) was lower, at around 5%, than the better performing learners at the 75th percentile, who showed a vocabulary growth of 12% – 13%.
The second research question focuses on the receptive vocabulary knowledge of high-frequency words of Grade 3 learners at the end of the Foundation Phase, using two of Sibanda’s receptive knowledge tests.
Results of the high-frequency word test are presented in
Receptive knowledge of high-frequency words per province (%).
Province | Word meaning test | Cloze test | Receptive vocabulary knowledge average | ||
---|---|---|---|---|---|
Western Cape English HL ( |
Mean | 46.7 | 69.9 | 60.6 | |
SD | 33.2 | 31.9 | 29.4 | ||
SE | 2.8 | 2.7 | 2.5 | ||
Minimum | 0.0 | 0.0 | 3.0 | ||
Maximum | 100.0 | 100.0 | 100.0 | ||
Percentiles | 25 | 16.7 | 50.0 | 36.7 | |
50 | 41.7 | 83.3 | 66.7 | ||
75 | 75.0 | 100.0 | 86.7 | ||
Eastern Cape English FAL ( |
Mean | 18.9 | 33.0 | 27.4 | |
SD | 18.8 | 26.2 | 21.1 | ||
SE | 1.6 | 2.2 | 1.8 | ||
Minimum | 0.0 | 0.0 | 0.0 | ||
Maximum | 100.0 | 100.0 | 100.0 | ||
Percentiles | 25 | 8.3 | 11.1 | 10.0 | |
50 | 16.7 | 22.2 | 20.0 | ||
75 | 25.0 | 52.8 | 40.0 |
SD, standard deviation.
The results illustrate two important things. Firstly, there are large differences in terms of distribution of scores between the HL and FAL learners. Secondly, the score differences within the language groups are equally large, suggesting that the vocabulary levels of the learners are highly unequal.
We turn now to age and gender differences in active and receptive word knowledge of Grade 3 learners. Age distribution at the province level is presented in
Age distribution of Grade 3 learners per province.
Results of the receptive vocabulary knowledge average (word meaning and cloze tests) across the age groups are shown in
Receptive knowledge of high-frequency words per province and age group (%).
Province | 8 years | 9 years | 10 years | 11 years | 12 years | |
---|---|---|---|---|---|---|
Eastern Cape | Mean | 23.6 | 32.5 | 21.9 | 20.0 | 6.7 |
SE | 5.8 | 2.6 | 2.8 | 6.3 | - | |
SD | 22.3 | 21.9 | 18.2 | 19.0 | - | |
Western Cape | Mean | 66.5 | 62.7 | 41.1 | 62.7 | - |
SE | 4.6 | 3.3 | 4.5 | 3.3 | - | |
SD | 28.6 | 30.1 | 19.3 | 30.1 | - |
There were significant differences between the age groups in the Western Cape (
There is typically an increase in vocabulary knowledge of high-frequency words with age during the school years; exceptions do of course occur, and children with learning problems often present with lower vocabulary knowledge. The majority of Grade 3 children in this cohort were 9 years old. The older learners are likely to be learners who repeated a grade in Foundation Phase. The results seem to confirm this: the 10-, 11- and 12-year olds in particular seemed to display much lower vocabulary knowledge, suggesting that they were weak learners.
Active and receptive vocabulary knowledge (mean % and SE) as measured in November.
Province | Active vocabulary knowledge |
Receptive vocabulary knowledge |
||
---|---|---|---|---|
Male | Female | Male | Female | |
Eastern Cape | 40.4 (10.3) | 41.8 (7.1) | 25.8 (21.1) | 28.6 (21.2) |
Western Cape | 68.9 (12.8) | 68.7 (12.5) | 57.4 (30.5) | 64.0 (28.0) |
Although female FAL learners in the Eastern Cape scored slightly higher on active vocabulary (
Girls in the Eastern Cape scored slightly higher in receptive word knowledge (
The fourth research question investigated the relationship between the learners’ active and receptive word knowledge. Pearson’s correlation coefficient was calculated for active and receptive vocabulary knowledge, and the results are presented in
Pearson’s correlation coefficients of active and receptive word knowledge.
Active word knowledge (Jan) | Active word knowledge (Nov) | Receptive word knowledge (Nov) |
---|---|---|
1.00 | 0.95 |
ns |
1.00 | ns | |
1.00 |
ns, not significant
Correlation is significant at the 0.01 level (two tailed).
The fact that no correlation was found between learners’ active and receptive vocabulary knowledge might be explained by the different levels of vocabulary that are measured by both tests. In the Sibanda tests, 97.1% of the words are from the 1000 word family list (i.e. the most common words in English). In contrast, the Woodcock-Muñoz test only has 39.5% words at the 1000 word family level and includes far more difficult vocabulary (up to the 14 000 word family list). Details of the word family levels per test are presented in
Word family representations in the active and receptive vocabulary tests.
BNC/COCA word family list | Woodcock-Muñoz test (token %) | Sibanda word list (token %) |
---|---|---|
K-1 | 39.5 | 97.1 |
K-2 | 18.4 | 2.9 |
K-3–5 | 18.4 | |
K 6–10 | 11.9 | |
K 11–14 | 9.2 | |
Proper nouns | 2.6 |
BNC/COCA, British National Corpus/Corpus of Contemporary American English.
The final research question looked at the role of initial vocabulary knowledge on vocabulary development during the year. To what extent did the learners’ active vocabulary knowledge at the beginning of the year predict their vocabulary growth during the year, as reflected in their final active vocabulary knowledge scores and their scores on the high-frequency words?
In both English HL and English FAL, learners who knew more words at the beginning of the year seemed to acquire more words by the end of the year. In order to investigate the role of initial active vocabulary in vocabulary development during the year, a simple linear regression was calculated to predict post-test active vocabulary knowledge based on pre-test active vocabulary knowledge. A significant regression equation was found in the Western Cape:
Another simple linear regression was calculated to predict receptive vocabulary knowledge at the end of the year based on active vocabulary knowledge at the beginning of the year. No significant regression equation was found either in the Western Cape (
The paucity of local research into vocabulary development in the early primary school years by English HL and English FAL learners prompted this study, the aim of which was to explore the receptive and active vocabulary knowledge of Grade 3 learners who attend schools that serve low-SE communities. Although the four schools in this vocabulary study were involved in an intervention aimed at improving reading levels in the schools, the purpose of this study was simply to record the learners’ vocabulary knowledge within this context, and not to evaluate the impact of the intervention on the learners’ vocabulary development. In this study the different classroom contexts were not compared, nor were there measures to determine how much reading was happening in HL or FAL across the classrooms and how this might affect vocabulary acquisition. The main findings are summarised and discussed below.
Firstly, as to be expected, the HL learners knew almost double the number of words their English FAL peers did, and this difference remained fairly constant throughout the year. Although both groups of learners increased their active word knowledge through the year, their growth was similar, at about 9%. An important finding was that the learning effect in practical terms was substantial for both groups of learners. A limitation of the current study is that it does not have a control group; therefore, whether this reflects a ‘normal’ growth pattern or whether the learners’ vocabulary was benefitting from the larger reading intervention are issues that require further research. Home language learners have far greater exposure to their language at home and at school than FAL learners, whom for many, school is the only place where they get exposed to the FAL. According to CAPS, learners should have 7–8 HL instructional hours a week, and FAL learners 3–4 instructional hours. Despite these differences in exposure to language, it is surprising that the HL learners’ rate of acquisition in terms of percentage increase in scores from pre- to posttest time was the same as that of the English FAL learners. A further area of interest would be to compare this growth pattern with that of learners in high performing Quintile 5 schools, and to see how SES impacts vocabulary growth patterns in our schools, and whether vocabulary growth can be accelerated in low income schools, for both HL and FAL learners.
Research on vocabulary development in the English-speaking world suggests that children acquire about 3000 words on average every year, with children from lower SE backgrounds learning fewer words than their middle-class peers because of differences in exposure to opportunities for vocabulary acquisition. Given that approximately 70% of schools in South Africa serve low-SE communities (Fleisch
Vocabulary development is a complex phenomenon that can be assessed in terms of size and breadth as well as receptive or active knowledge. Receptive knowledge is usually in advance of active knowledge; we know more words than we actively use in speaking and writing. Assessing vocabulary is always a challenging task, and it is made more so when there is a lack of culture-appropriate tests that have been normed and standardised on a large group of children across SE and regional differences within the same country. The receptive vocabulary test used in this study assessed knowledge of the 60 most frequent words that occur in South African Grade 4 English textbooks (Sibanda
Given that the receptive vocabulary test in this study assessed knowledge of the 60 most frequent words that occur in South African Grade 4 English textbooks, it is disconcerting to note that the English FAL learners knew on average only 27% of these most common words at the end of their Grade 3 year. This means that these learners were entering the Intermediate Phase with barely a third of the basic vocabulary knowledge needed to cope with the demands of the Intermediate Phase and the need to ‘read to learn’ from content subject textbooks. Even the strongest English FAL learners (at the 75th percentile) knew only 40% of these words, while the weakest learners (at the 25th percentile) knew merely 10% of the most common English words. However, the fact that both the HL and FAL learners were unfamiliar with these kinds of vocabulary tasks speaks to instructional practices in the classrooms. Writing and various forms of written assessment tend to be neglected in South African classrooms and children on the whole lack familiarity with more literate tasks and activities (Hoadley
Surprisingly, no significant gender differences were found in this cohort of Grade 3 learners, although in early primary school girls typically perform better than boys on literacy measures (Howie & Van Staden
Finally, there was considerable variation in the learners’ vocabulary knowledge, both within and across English HL and English FAL learners. This is in line with Sibanda’s (
This was an exploratory study that adapted a standardised active picture word test to be more in line with South African English vocabulary conventions. Although the reliability of the adapted test was acceptable, further refinements of such a test are still needed. It was also a small-scale study; therefore, generalisations to the larger population are necessarily curtailed. Vocabulary acquisition is largely a function of exposure to rich oral and print-based input in homes and schools. International vocabulary research has shown that children from lower SE backgrounds tend to come to school with smaller vocabularies than their more affluent peers. Vocabulary is also central to additional language learning, and adequate vocabularies are especially important for children for whom the FAL is also their LoLT. As prior local studies have suggested, young South African English FAL learners are struggling with vocabulary (Macdonald
There is an urgent need to develop linguistically appropriate and culturally sensitive standardised vocabulary tests suitable for the South African multilingual educational context.
Reliable tests that tap into both receptive and active vocabulary knowledge at different frequency levels are needed.
It is important to establish a broad framework of normative vocabulary acquisition at different grade levels in South African schools, both in the HL and FAL, especially if the FAL also becomes the LoLT from Grade 4 onwards. This should derive from local empirical research and not be extrapolated from research contexts that are different from our own. How much vocabulary growth (or stasis) learners display when left to their own devices (i.e. when schools do not pay particular attention to improving vocabulary in classrooms) and how vocabulary growth can be accelerated are issues that need attention.
Learners at risk of learning and reading difficulty should be identified as early as possible. Well-developed vocabulary tests that have been standardised and normed on South African children can help in this regard. To what extent can initial vocabulary gaps be narrowed as learners move up the education ladder?
Rich verbal input is a prerequisite for good vocabulary growth. Interventions that increase exposure to incidental word learning through print-rich classrooms and extended teacher talk are needed. Research has also consistently documented the effects that regular storybook reading in and outside the classroom have on children’s vocabulary development, both in the HL and FAL (Agustín-Llach & Alonso
At the same time, explicit vocabulary instruction that occurs within the prescribed instructional hours should target high-frequency words, especially in English FAL, so that the 200 words that make up 90% of the running words of English texts in Grade 3 can be acquired as quickly as possible.
The importance of vocabulary for reading achievement and for school success cannot be overstated. As this small-scale study shows, there is still much that we do not know about vocabulary development amongst South African learners. The sooner we embark on a systematic and comprehensive research programme to address gaps in the understanding of this phenomenon, the sooner our learners can benefit from instruction that closes gaps in their vocabulary acquisition.
The authors would like to extend sincere thanks to the schools, Grade 3 teachers and learners for their generous participation in the vocabulary study. Sincere thanks are also due to the Zenex Foundation for accommodating this small study within the larger reading project, the Zenex Literacy Project (2015–2017), that was aimed at Foundation Phase teachers.
The authors declare that they have no financial or personal relationships which may have inappropriately influenced them in writing this article.
E.J.P. was the project leader of the vocabulary study and responsible for the testing of the learners, while L.S. was responsible for the testing of the learners, data analysis and reporting. Both authors contributed jointly to the writing of the article.
Overview of Woodcock-Muñoz test items that were replaced.
Original item | Alternative item | Original item | Alternative item |
---|---|---|---|
21 Piggy bank | Elbow | 53 Mortarboard | Parachute |
34 Zeppelin | Helicopter | 54 Radar dome | Binoculars |
39 Platypus | Penguin | 55 Chevron | Saddle |
41 Thermostat | Thermometer | 56 Transom | Spanner |
42 Churn | Igloo | 57 Baluster | Chimney |
48 Tuning fork | Violin | 58 Amphora | Racket |
50 T-square | Calendar | 59 Mortise | Compass |
51 Cornucopia | Oval |
Woodcock-Muñoz test items.
Item # | Eastern Cape mean score | Western Cape mean score | Item # | Eastern Cape mean score | Western Cape mean score |
---|---|---|---|---|---|
1 (Ball) | 0.97 | 1.00 | 18 (Truck) | 0.08 | 0.95 |
8 (Apple) | 0.95 | 1.00 | 0.07 | 0.82 | |
4 (Balloons) | 0.90 | 1.00 | 31 (Jellyfish) | 0.07 | 0.50 |
12 (Ice cream) | 0.90 | 1.00 | 25 (Eagle) | 0.03 | 0.55 |
5 (Cat) | 0.89 | 1.00 | 0.03 | 0.38 | |
11 (Sailboat) | 0.89 | 0.98 | 0.03 | 0.53 | |
7 (House) | 0.87 | 1.00 | 0.03 | 0.22 | |
16 (Flashlight) | 0.85 | 0.82 | 28 (Astronaut) | 0.02 | 0.63 |
14 (Toothbrush) | 0.77 | 1.00 | 29 (Notebook) | 0.02 | 0.20 |
2 (Mouth) | 0.75 | 0.93 | 37 (Eyedropper) | 0.02 | 0.02 |
24 (Stapler) | 0.75 | 0.93 | 0.02 | 0.35 | |
9 (Sock) | 0.70 | 1.00 | 44 (India) | 0.02 | 0.00 |
10 (Glasses) | 0.70 | 1.00 | 46 (Waterwheel) | 0.02 | 0.12 |
13 (Cow) | 0.70 | 1.00 | 52 (Trap) | 0.02 | 0.00 |
0.70 | 0.77 | 27 (Lawn mower) | 0.00 | 0.27 | |
6 (Chair) | 0.67 | 0.98 | 32 (Weights) | 0.00 | 0.15 |
20 (Hanger) | 0.64 | 0.90 | 33 (Crutches) | 0.00 | 0.45 |
3 (Window) | 0.57 | 1.00 | 35 (Knots) | 0.00 | 0.45 |
23 (Microphone) | 0.49 | 0.90 | 36 (File cabinet) | 0.00 | 0.12 |
47 (Biplane) | 0.43 | 0.87 | 38 (Pocket watch) | 0.00 | 0.08 |
0.41 | 0.92 | 40 (Trombone) | 0.00 | 0.05 | |
22 (Toaster) | 0.36 | 0.92 | 0.00 | 0.05 | |
17 (Rocking chair) | 0.33 | 0.98 | 43 (Beaker) | 0.00 | 0.12 |
0.33 | 0.87 | 49 (Weathervane) | 0.00 | 0.00 | |
15 (Drum) | 0.31 | 0.93 | 0.00 | 0.22 | |
45 (Mallet) | 0.31 | 0.83 | 0.00 | 0.05 | |
30 (High chair) | 0.25 | 0.70 | 0.00 | 0.45 | |
26 (Bookcase) | 0.20 | 0.27 | 0.00 | 0.20 | |
19 (Spider web) | 0.13 | 0.92 | 0.00 | 0.15 | |
0.10 | 0.28 |
NB: The mean scores for some of the replaced items are rather high, especially for the higher item numbers (more difficult vocabulary) that were replaced. Examples include 50 (Calendar), 34 (Helicopter), 39 (Penguin), 53 (Parachute) and 21 (Elbow). If a more difficult vocabulary would have been selected to replace the items, the scores for the Western Cape group might have been much lower.
Scores from the pre-test; Eastern Cape mean scores determine the chronological order of the items, from high scores to low scores. Replaced items are shown in bold.
Sibanda’s 60 high-frequency words.
Words 1–22 | Words 23–55 | Words 56–98 | Words 99–151 | Words 152–212 |
---|---|---|---|---|
and | only | |||
own | between | stop | ||
use | but | |||
can | explain | because | ||
do | why | |||
what | some | until | ||
are | each | time | ||
again | ||||
it | before | |||
or | easy | |||
more | ||||
that | look | family |
Words in bold were used in Test 2: definition matching test (12 words, the word ‘teacher’ is not in the list).
Words
The words ‘need’ and ‘also’ were repeated in both tests.
Terms such as first language (L1) or mother tongue and second langugae (L2 or ESL) or additional language (AL) are also used in the literature. In this article, we adopt the terms ‘Home Language’ (HL) and ‘First Additional Language’ (FAL) as used in the South African curriculum documents.
In South Africa, the Foundation Phase includes Grade R plus Grades 1–3.
State aid to public schools in South Africa is determined by SE factors. Schools serving poor communities receive the most funding. Schools are categorised from Quintile 1 to 5, with Quintile 1–3 being the poorer schools.
The Renfrew vocabulary test is also a picture vocabuary test developed in the UK. It has been standardised on socio-economically diverse groups of children in Britain, Australia and South Africa.