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Adult literacy and numeracy in New Zealand - Key factors

Publication Details

This report explores a range of factors associated with English literacy and numeracy among people aged 25-65, using data from the Adult Literacy and Life Skills (ALL) Survey 2006. It finds that three key factors can account for a large part of the variation between people in their literacy and numeracy skills: completed education, language background and computer use. Computer use was strongly associated with higher literacy and numeracy, especially the combination of work and home computer use. Computer use was associated with intensive and extensive reading, writing and numeracy practices. Work computer use or non-use divided jobs broadly into those that required higher literacy and numeracy and those that did not. There was a large overlap between the groups of people with low literacy and low numeracy, and the group of people who did not use a computer at work.

Author(s): Chris Lane, Tertiary Sector Performance Analysis and Reporting, Ministry of Education.

Date Published: July 2010


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Please consider the environment before printing the contents of this report.

Conclusion

This report has analysed a number of variables with a view to accounting for variation (e.g. regional differences) in literacy and numeracy, and explored their relationships with English prose literacy and numeracy among people aged 25-65. These variables include:

  • Level of education completed, and recent upskilling
  • Labour force status
  • Computer use at work and at home
  • Occupation, industry and income
  • First language, main language spoken at home, place of birth and ethnic identification
  • Age and gender 


Over 40 per cent of the variation in prose literacy and numeracy scores can be accounted for in regression models which include completed education, labour force status, work and home computer use, and first language and main home language. Occupational, age, gender and ethnicity variables have significant but relatively small additional effects.

Higher prose literacy and numeracy scores were strongly associated with having upper secondary or tertiary education, being employed, using a computer at work, using a computer at home for five or more hours per month, and having English as both first and main home language. The computer use variables are found to be strongly related to white collar employment, to involvement in upskilling and to the intensity of involvement in literacy and numeracy activities at work and in personal reading. Computer use at work distinguishes within occupation and within industry between jobs requiring or not requiring high involvement in literacy and numeracy activities.

Higher prose literacy and numeracy were also associated with working in a managerial, professional or technical occupation. After controlling for education, computer use, language and occupation, the additional characteristics of being male or the combination of having English as a first language and being Māori or Pasifika favoured low prose literacy (though the effects were relatively small); while being older, being female or the combination of having English as a first language and being Māori or Pasifika favoured low numeracy (although the age and gender effects were relatively small).

The various factors are now considered in a little more detail.

Education

There was a strong association between level of education completed and the percentage of people with higher prose literacy or numeracy. People whose highest completed level was lower secondary (Year 11 or less) were much less likely to have higher prose literacy or numeracy (i.e. more likely to have low prose literacy or numeracy) compared with people who had completed upper secondary or tertiary education. People who had completed bachelors or postgraduate degrees were much more likely than those who had not, to have higher prose literacy and especially higher numeracy.

At every level of completed education, people who had completed formal or non-formal courses in the past year were more likely to have higher prose literacy and higher numeracy than people who had not taken courses.

Labour force status, computer use and employment related factors

Among people aged 25-65, those who were employed and students were most likely to have higher prose literacy and higher numeracy, although there were very few people in this age range whose main labour force status was student.

People who had been employed in the past year were significantly more likely to have higher prose literacy and numeracy than people who had not, although the advantage of being employed was confined mainly to people who had used a computer at work.

People aged 25-65 who had been employed and used a computer at work in the past year were significantly more likely to have higher literacy and numeracy compared with people who had not been employed or who had been employed and not used a computer at work.

Use of a computer at work was strongly associated with being employed in managerial, professional, technical or clerical occupations, although a significant proportion of workers in other occupational groups also used computers. People who had used a computer at work in the past year were likely to be involved in a much wider range of regular work activities related to literacy and numeracy than those who had not, and those who were involved in a greater number of types of regular literacy or numeracy activities were more likely to have higher literacy or numeracy. Computer use at work appears to pinpoint, more effectively than occupational categories, those jobs which require or encourage regular literacy and numeracy activities, and this probably reflects the importance of the computer as a tool for literacy and numeracy activities. The difference in mean prose literacy and numeracy between work computer users and non-users within occupations was comparable with the difference between occupations, and was considerably greater than the differences between industries.

Similarly, people who used a computer at home were more likely to engage in a wide range of regular personal reading activities. There was a straightforward relationship between increase in the number of types of regular personal reading and higher literacy and numeracy scores.

Computer use at work and computer use at home were only moderately correlated with each other, and have separate and cumulative effects in the statistical models. Taken together they form a four-step scale, such that people who used a computer at work and also used a computer at home were more likely to have higher prose literacy or numeracy than those who used a computer only at work, who were more likely to have higher prose literacy and numeracy than those who used a computer only at home, who in turn were much more likely to have higher prose literacy or numeracy than those who did not use a computer in either location.

Those who used a computer both at work and at home, or who had used a computer at work, were significantly more likely to have taken formal or non-formal courses in the past year than those who used a computer at home but not at work, and these people were significantly more likely to have taken courses than people who did not use a computer at home or at work. The association between computer use and upskilling held across all levels of completed education.

There was a small but significant additional effect (incorporated in the extended statistical models) of occupation, with managers, professionals and technicians having higher prose literacy and numeracy than clerks and service workers and farmers, fishers and tradespeople, who in turn had higher prose literacy and numeracy than machine operators and elementary workers.

People in the industry category ‘finance, business and community services’ were more likely to have higher prose literacy and numeracy than people in other industries. Prose literacy and numeracy also correlated with income: people with higher personal incomes were more likely to have higher prose literacy or numeracy than people with lower incomes.

However, industry and personal income are redundant in the statistical models for prose literacy and numeracy once other factors (including labour force status, computer use and occupation) are taken account of, because of the correlations that industry and income have with those other variables; and the computer use variables have stronger predictive value in the statistical models.

On the basis of previous research it could be expected that there would be a relationship between the variables of work and home computer use and the measures of prose literacy and numeracy. How it would compare with employment-related factors such as occupation and industry was not clear.

It is therefore remarkable to find that the computer use variables are such strong predictors of prose literacy and numeracy, and that they are somewhat stronger than occupation and industry as predictors (when education is controlled for). Computer use at work in fact accounts for some of the variation between different occupations, but has a bigger effect within occupations and industries.

Language and ethnic identification

Of all people aged 25-65, 84 per cent had English as a first language, and 99 per cent of these had English as their main home language. Five per cent did not have English as a first language but had English as their main home language, while 10 per cent did not have English either as a first language or as their main home language.

There was a strong association between these language categories and higher prose literacy and numeracy. A majority of people with English as a first language had higher prose literacy and higher numeracy, while only a minority of people whose first language was not English had higher prose literacy or numeracy. Among those people whose first language was not English, those whose main home language was English were more likely to have higher prose literacy than those whose main home language was not English.

People whose first language was not English were much more likely to have a degree than native English speakers, but were significantly less likely to be employed, and if employed, to have used a computer at work.

There was a close relationship (though not an exact match) between language variables and ethnic identification. A minority of people aged 25-65 who identified as Asian (15 per cent) and Pasifika (33 per cent) had English as a first language, while a majority of people who identified as New Zealand European (97 per cent), Māori (94 per cent) and Other (65 per cent) were native English speakers.

In the statistical models, the language variables account for a large part of the relative advantage in prose literacy and numeracy of Europeans, and a large part of the relative disadvantage of Pasifika and Asian people.

However, the language variables do not account for the relative disadvantage of Māori and Pasifika who were native English speakers. This is dealt with in the extended statistical models by the inclusion of independent variables combining having English as a first language with having Māori or Pasifika ethnic identification, which have significant but small effects in improving the model of prose literacy, but much larger and also significant effects on the model of numeracy.

Age and gender

People aged 55-65 were significantly less likely to have higher prose literacy than people aged 45-54 or 35-44, but not significantly less likely than people aged 25-34. People aged 55-65 were significantly less likely to have higher numeracy than people aged 45-54, 35-44 or 25-34.

The percentage of men and women aged 25-65 with higher prose literacy was not significantly different, but there was a significantly greater percentage of men (57 per cent) with higher numeracy than women (46 per cent).

Age and gender were also considered together, with age divided into two bands (25-44 and 45-65) for statistical robustness.

There were no significant differences among the age/gender categories in the percentage with higher prose literacy, but there were significant differences in numeracy. Within each age band, men were significantly more likely to have higher numeracy than women, but younger women were on a par with older men. The percentage of younger and older men with higher numeracy was not significantly different, but younger women were significantly more likely to have higher numeracy than older women. In fact, the percentage of older women with higher numeracy was significantly less than that for each of the other three age/gender groups.

Women, especially older women, were disadvantaged in terms of education, employment and computer use. Once these gender differences were controlled for, women emerged as having a significant advantage in prose literacy.

These complexities are dealt with in the extended statistical models by including age and gender variables, with being older a negative predictor of higher numeracy, and being male a negative predictor of higher prose literacy but a positive predictor of higher numeracy.

Regional comparisons

A large number of variables have been considered in this report, and all of them show some relationship with prose literacy or numeracy. This analysis was originally developed for the purpose of comparing geographical regions within New Zealand.  Trying to account for regional differences in prose literacy and numeracy in terms of all these variables could be a recipe for confusion. However, this report has identified a set of key factors which account for a large part of the variation in prose literacy and numeracy, and which provide a basis for a focused approach to comparing regions. These key factors are: level of completed education, work and home computer use, and first language and main home language.

Combined effect of education, computer use and language

The combined effect of the three key factors identified can be represented by a variable (the key factor scale) based on three characteristics which favour higher literacy and numeracy, namely having upper secondary or tertiary education (as opposed to lower secondary or less), using a computer at work (as opposed to not being employed, or being employed but not using a work computer), and having English as a first language (as opposed to not having English as a first language). The key factor scale is the number of these characteristics held by an individual, so that a scale value of zero represents anyone with lower secondary education or less who did not use a computer at work and who did not have English as a first language. A scale value of 1 or 2 represents anyone with any one or any two of the characteristics favouring higher prose literacy and numeracy. And a scale value of 3 represents anyone with upper secondary or tertiary education who used a computer at work and had English as a first language.

Of the estimated 2,122,000 people aged 25-65, 893,000 (42 per cent) had low prose literacy and 1,040,000 (49 per cent) had low numeracy. 1,230,000 (58 per cent) had higher prose literacy and 1,083,000 (51 per cent) had higher numeracy.

Among the 56,000 people with a key factor scale value of zero (i.e. low education, no work computer use, first language not English), 97 per cent had low prose literacy (Levels 1-2) and 97 per cent also had low numeracy (Levels 1-2). This group accounted for an estimated 54,000 (6 per cent) of those with low prose literacy and also 54,000 (5 per cent) of those with low numeracy. The numbers in this group with higher prose literacy or higher numeracy were too small to be reliably estimated.

Among the 399,000 people with a key factor scale value of 1 (i.e. only one of the characteristics favouring higher literacy and numeracy), 77 per cent had low prose literacy (and so 23 per cent had higher prose literacy) and 83 per cent had low numeracy (hence 17 per cent had higher numeracy). This group accounted for 307,000 (34 per cent) of those with low prose literacy and 333,000 (32 per cent) of those with low numeracy. This group also included 93,000 (8 per cent) of those with higher prose literacy and 66,000 (6 per cent) of those with higher numeracy.

Of the 702,000 people with a scale value of 2, 49 per cent had low prose literacy (and so 51 per cent had higher prose literacy) and 56 per cent had low numeracy (thus 44 per cent had higher numeracy). This group accounted for 343,000 (39 per cent) of those with low prose literacy and 394,000 (38 per cent) of those with low numeracy. This group also included 359,000 (29 per cent) of those with higher prose literacy and 308,000 (29 per cent) of those with higher numeracy.

Finally, of the 965,000 people with a scale value of 3 (i.e. those with upper secondary or tertiary education, who used a computer at work and had English as a first language), 20 per cent had low prose literacy (and so 80 per cent had higher prose literacy) and 27 per cent had low numeracy (hence 73 per cent had higher numeracy). This group accounted for 189,000 (21 per cent) of those with low prose literacy and 259,000 (25 per cent) of those with low numeracy. This group also included 776,000 (63 per cent) of those with higher prose literacy and 706,000 (65 per cent) of those with higher numeracy.

Some implications and cautions

Educational qualifications have often been used as approximate indicators of literacy and numeracy. Previous analyses of the ALL survey data (Earle, 2009b; Earle, 2009c; Smyth and Lane, 2009) have highlighted a number of situations in which educational qualifications do not give a good guide to literacy or numeracy skills.

This study provides a basis for similar caution more broadly. After controlling for other factors, the difference between having English as a first language, and not having English as either a first language or as the main home language, was of the same order as the difference between having a degree and having a lower secondary education or less, in terms of the likelihood of having higher literacy or numeracy. The difference between being employed and using a computer at work, and not being employed or not using a computer at work, was of the same order as the difference between having a degree and having an upper secondary education but no tertiary education.

Although computer use at work was a good guide to higher prose literacy and numeracy (at least in 2006 when the survey was done), it does not follow that increasing the use of computers would in itself improve the literacy or numeracy rate. Computer use at work appears to be a clue to the kind of work undertaken, that is, the computer is a tool for literacy and numeracy and that is why it is an indicator of jobs which regularly involve a wide range of literacy and numeracy activities. One would need a certain level of literacy and/or numeracy to begin such a job, and working in such a position would provide continuing practice and probably enhancement of literacy and/or numeracy.

There would be much more involved in increasing the proportion of jobs which have this character than changing the technology to be used (although this would be a part of it). The fact that education and language were key factors in the variation in literacy and numeracy indicates that provision of education in general, and specifically English for speakers of other languages, has a significant role to play.

One way to appreciate the implications of this analysis is to examine the characteristics of people with higher prose literacy or numeracy, and of those with low prose literacy or numeracy.

Of people with higher prose literacy or numeracy, the majority had all three of the key characteristics favouring higher literacy and numeracy, namely upper secondary or tertiary education, English as a first language, and use of a computer at work.

People who lacked just one of these key characteristics were approximately as likely to have low literacy or numeracy as they were to have higher literacy or numeracy. The majority of people with none or only one of the key characteristics had low literacy or numeracy.

Of people aged 25-65 with low prose literacy or numeracy (Levels 1-2), those with lower secondary education or less, and those whose first language was not English, were considerably over-represented. A majority of people with low prose literacy or numeracy had not used a computer at work in the past year, just as a majority of those who had not used a computer at work had low prose literacy and numeracy.

This high degree of overlap between the groups of people with low prose literacy and low numeracy, and the group who had little or no use of computers is of considerable importance. It indicates that programmes seeking to use information and communication technologies in improving people’s literacy and numeracy need to take into account their likely lack of proficiency in using computers. Programmes aimed at introducing non-computer users to ICT need to allow for the likely low literacy and numeracy of learners. It also indicates that there may be scope for combining upskilling in ICT and literacy and numeracy in integrated programmes.


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