copy the linklink copied! 2. Adults’ proficiency in key information-processing skills
This chapter describes the level and distribution of proficiency in the three information-processing skills assessed – literacy, numeracy and problem solving in technology-rich environments – among adults in the countries and economies participating in the Survey of Adult Skills. To help readers interpret the findings, it describes what the different levels of proficiency mean in concrete terms for each of these three domains. The chapter looks at the distribution in scores across countries and economies, and within participating countries, with particular focus on the six countries that participated in the third and final round of this cycle of data collection – Ecuador, Hungary, Kazakhstan, Mexico, Peru and the United States.
A note regarding Israel
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.
The Survey of Adult Skills, a product of the OECD Programme for the International Assessment of Adult Competencies (PIAAC), assesses the proficiency of adults in literacy, numeracy and problem solving in technology-rich environments. These are considered to be key information-processing skills (OECD, 2019[1]) in that they are:
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necessary for fully integrating and participating in the labour market, education and training, and in social and civic life
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highly transferable, in that they are relevant to many social contexts and work situations
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“learnable” and, therefore, subject to the influence of policy.
Literacy and numeracy skills form a foundation for developing higher-order cognitive skills such as analytic reasoning and are essential for accessing and understanding specific domains of knowledge. In addition, they are relevant across a range of life contexts, from education and work to home, social life and interaction with public authorities. The capacity to manage information and solve problems in technology-rich environments is becoming a necessity as information and communications technology (ICT) applications permeate the workplace, the classroom and lecture hall, the home, and social interactions more generally. Adults who are highly proficient in the skills measured by the Survey of Adult Skills are likely to be able to make the most of the opportunities created by the technological and structural changes modern societies are going through. Those who struggle to use new technologies are at greater risk of losing out.
The skills assessed in the Survey of Adult Skills are each defined by a framework that guided the development of the assessment and that provides a reference point for interpreting results. Each framework defines the skills assessed in terms of:
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Content – the texts, artefacts, tools, knowledge, representations and cognitive challenges that constitute the corpus to which adults must respond or use when they read, act in a numerate way or solve problems in technology-rich environments.
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Cognitive strategies – the processes that adults must bring into play to respond to or use any given content in an appropriate manner.
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Context – the situations in which adults have to read, handle numerical information, and solve problems.
For an overview of the conceptual frameworks of each of the three domains, please consult the Reader’s Companion (OECD, 2019[1]).
The main findings discussed in this chapter are:
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There is substantial variation in adults’ average proficiency in the three domains assessed in the Survey of Adult Skills across countries and economies: some 100 score points separate the highest- and lowest-scoring countries in literacy and numeracy proficiency, although many countries score within a relatively narrow band. While overall proficiency differs across countries, it varies to a large extent even within countries: the average difference between the top and bottom 25% of adults was 61 score points in literacy and 68 score points in numeracy.
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Among the countries participating in Round 3 of the study, the average proficiency of adults in Hungary and the United States in all three domains was close to the OECD average, while in Ecuador, Mexico and Peru average proficiency was substantially below it. Average proficiency in Kazakhstan was somewhere between these two groups. The variation in scores between high- and low-performing adults also differed between the countries in Round 3. Peru, Ecuador and the United States displayed the greatest variation, with the score-point difference between the best- and worst-performing 25% of adults being greater than the OECD average. The variation between the top and bottom performers was similar to the average in Hungary and Mexico and below average in Kazakhstan.
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Low-skilled adults make up a significant share of the population in all participating countries and economies. On average across the OECD countries taking part in the survey, around one in five adults perform at or below Level 1 in either literacy or numeracy. In some Round 3 countries, like Mexico, Peru and Ecuador, more than half of adults scored at or below Level 1 in literacy and numeracy, while in Hungary and the United States, the shares were comparable to the OECD average. Even in high-performing countries like Japan, almost 10% of the adult population performed at the lowest levels of either literacy or numeracy.
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While many adults in all countries may have poor literacy skills, there are very few adults in the countries participating in PIAAC who could be regarded as illiterate. In most cases, adults with low proficiency performed well on the reading components module that assesses mastery of the basic building blocks of reading comprehension – vocabulary knowledge, understanding the logic of sentences and reading fluency. In Ecuador, Mexico and Peru, which have very high proportions of adults performing at Level 1 or below for literacy, only around 8-20% of adults failed the literacy and numeracy core tests designed to identify the respondents who had the capacity to undertake the full assessment. In addition, those failing the core test in these countries correctly answered more than 77% of the items in the sentence-processing elements of the reading components assessment, more than 74% of the passage-comprehension items and 92% of the print-vocabulary items.
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Across OECD countries on average, around one in four adults have no or only limited experience with computers or lack confidence in their ability to use computers. In addition, nearly half of adults are proficient only at or below Level 1 in problem solving in technology-rich environments. This means they are able to use only familiar applications to solve problems that involve few steps and explicit criteria, such as sorting e-mails into pre-existing folders. Among the Round 3 countries, the share of adults with no or little ICT experience was similar to the OECD average of 16.3% in Hungary (14.4%) and Kazakhstan (19.7%) and below the average in the United States (7.4%). In contrast, Ecuador, Mexico and Peru stand out for the large proportions of their adult populations with no prior computer experience or very poor ICT skills: 32.9% in Ecuador, 39.3% in Mexico and 43.6% in Peru.
This report provides an overview of the results from the three rounds of the first cycle of the Survey of Adult Skills. Data collection in each of the rounds used the same survey instruments and was conducted under the same survey protocols. Round 1, which involved 24 countries and economies, took place in 2011-12; 9 additional countries participated in Round 2, which was conducted during 2014-15; and 6 countries participated in Round 3 (2017-18) including the United States, which had also collected data in Round 1.
The survey was designed to ensure that the cross-country comparisons of proficiency in literacy, numeracy and problem solving in technology-rich environments are as robust as possible and that the content of the assessment was equivalent in difficulty in each of the 28 language versions of the assessment. Care was taken to standardise implementation, including the sample design and field operations, in all participating countries and economies. The quality assurance and quality control procedures put in place are among the most comprehensive and stringent ever implemented for an international household survey. The details of the technical standards guiding the design and implementation of the survey can be found in the Survey of Adult Skills: Reader’s Companion, Third Edition (OECD, 2019[1]) and in the Technical Report of the Survey of Adult Skills, Third Edition (OECD, 2019[2]).
Interpreting differences in results among countries is nonetheless a challenging task, particularly as the Survey of Adult Skills covers adults born between 1946 and 1996 (for the countries included in Round 1), between 1948 and 1998 (in Round 2) and between 1951 and 2001 (in Round 3). These adults could have started their schooling at any time from the early 1950s to the early 2000s and entered the labour market from the early 1960s to the present day. The results observed for each participating country, at least at the aggregate level reported in this chapter, represent the outcomes of a period of history that extends as far back as the immediate post-war era, which has been marked by significant social, political and economic change. For this reason, the results of the Survey of Adult Skills should not be interpreted only, or even primarily, in light of current policy settings or those of the recent past, important as these may be. Adults in different countries and different age cohorts within countries will have faced different opportunities to develop, maintain and enhance the skills assessed, depending on the evolution of education and training systems and policies, the path of national economic development, and changes in social norms and expectations.
The countries and economies in the Survey of Adult Skills diverge both in terms of the timing and the rate of economic growth and educational expansion. By way of illustration, Figure 2.1 presents the evolution of gross domestic product (GDP) per capita since 1990 for the countries in Round 3 together with the average for OECD countries and some other comparator countries. The countries presented in the graph clearly started at relatively different levels of GDP per capita. All of the countries and economies included have experienced an overall increase in per capita GDP since 1990, with Ireland, Korea and Singapore seeing particularly large increases in the past three decades. In other countries, GDP has not increased nearly as rapidly. Among Round 3 countries, per capita GDP increased by almost 60% in Peru between 2005 and 2017, compared to increases of around 23% in Ecuador and Hungary and around 10% in Mexico and the United States over the same period.
Comparing the levels of educational attainment among the older and younger cohorts taking part in the Survey of Adult Skills gives an idea of the different patterns of educational expansion that occurred among participating countries over the last half century. Some countries, such as Korea, Poland and Singapore, have seen rapid expansion in participation in higher education (Figure 2.2) from a relatively low starting point, reflected in the large differences in the rates of tertiary attainment between older and younger age groups. Others, such as Canada, Estonia, Israel, New Zealand, the Russian Federation and the United States, have had high levels of participation in tertiary education throughout the post-war period. In general, increases in tertiary participation have been accompanied by a fall in the proportion of adults who have completed less than a full secondary education. However, there is significant variation across countries. In countries such as Germany, Lithuania, the Russian Federation and the United States, the proportion of adults who have less than a full upper secondary qualification has remained stable over the post-war period, while in others, such as Italy, younger adults are much less likely to lack an upper secondary education than older adults. In Mexico and Turkey there are still significant proportions of both younger and older adults without an upper secondary education. These are also among the countries with the smallest proportions of adults, both younger and older, who have attained tertiary education.
copy the linklink copied! Reporting the results
In each of the three domains assessed, proficiency is considered to be a continuum of ability involving the mastery of information-processing tasks of increasing complexity. The results are represented on a scale ranging from 0 to 500. Each of the three proficiency scales is divided into “proficiency levels”, defined by particular score-point ranges. The descriptors provide a summary of the types of tasks that can be successfully completed by adults with proficiency scores in a particular range. In other words, they suggest what adults with particular proficiency scores in a particular skills domain can do. Six proficiency levels are defined for literacy and numeracy (from below Level 1 to Level 5) and four for problem solving in technology-rich environments (from below Level 1 to Level 3). The value ranges defining the levels and their respective descriptors are presented in Table 2.1, Table 2.2 and Table 2.3 in this chapter, and in the Reader’s Companion to this report (OECD, 2019[1]).
Tasks (test items) vary in difficulty and are thus located at different points on the proficiency scales. For example, some tasks are easy and can be correctly solved by most respondents while others are difficult and can only be successfully completed by those with high proficiency. A person with a score in the middle of a certain proficiency level can successfully complete tasks located at this level around two-thirds of the time, a person with a score at the bottom of the level would successfully complete tasks at that level only about half the time, and someone with a score at the top of the level would successfully complete tasks at that level about 80% of the time.
The United States is the only country that has administered the PIAAC assessment to representative samples of its adult population more than once. This box briefly analyses the evolution of proficiency in literacy, numeracy and problem solving in technology-rich environment in the country between 2012-14 and 2017.
At first glance, very little has changed over this (short) time period. Average proficiency in literacy declined from 272 to 271 score points and in numeracy from 257 to 255, but these differences are not statistically significant, and are in any case negligible from a substantive point of view (see Tables A2.2 and A2.4 in Annex A). The share of adults who reported no prior computer experience declined from 5% to 3%, but the slight increase in the incidence of missing values and in the percentage of adults who failed the ICT core meant that the percentage of adults who were administered the problem-solving assessment did not change. Performance in the problem-solving assessment improved very marginally: the share of adults who scored at Level 2 and 3 increased from 29% to 31%, while the share scoring at or below Level 1 fell from 51% to 50% (see Table A2.7).
A few additional insights can be gained by breaking down the analysis for adults belonging to different age groups. Figure 2.3 shows that between 2012-14 and 2017 the numeracy proficiency of 25-34 year-olds declined by 6 points. For all other age groups, the differences are much smaller and are not statistically significant.
The most valuable aspect of the repeated administration of the PIAAC assessment lies in the opportunity to better assess the effect of ageing. Although PIAAC did not retest the same individuals, it is possible to follow a representative sample of the same birth cohorts over time: adults aged 25-29 in 2012-14 were (approximately) aged 30-34 in 2017, and so on.
Figure 2.4 shows that proficiency in literacy and numeracy tends to increase among younger adults, peaking in the early 30s and then gradually declining. This is roughly the same pattern that is observed in most countries where only one round of data collection was conducted (see Figure 3.6 in Chapter 3). The average scores of the cohorts that participated in both rounds of data collection (i.e. adults aged 16-59 in 2012-14 and adults aged 20-65 in 2017) declined, over this four-years period, by 1 point in literacy and by 2 points in numeracy.
The proficiency levels have a descriptive purpose. They are intended to aid in the interpretation and understanding of the reporting scales by describing the attributes of the tasks that adults with particular proficiency scores can successfully complete. It is emphasised that they have no normative element and should not be understood as “standards” or “benchmarks” in the sense of defining levels of proficiency appropriate for particular purposes (e.g. access to post-secondary education or fully participating in a modern economy) or for particular population groups. For ease of presentation, the figures showing the distribution of population by proficiency level have made a distinction between Level 2 and below and Level 3 and above in literacy and numeracy, and Level 2 and above and Level 1 or below in problem solving in technology-rich environments.
copy the linklink copied! Proficiency in literacy
The Survey of Adult Skills defines literacy as the ability to understand, evaluate, use and engage with written texts in order to participate in society, achieve one’s goals, and develop one’s knowledge and potential. In the survey, the term “literacy” refers to reading written texts; it does not involve either comprehending or producing spoken language or producing text (writing). In addition, given the growing importance of digital devices and applications as a means of generating, accessing and storing written text, reading digital texts is an integral part of literacy measured in the Survey of Adult Skills (Box 2.3).
Digital texts are texts that are stored as digital information and accessed in the form of screen-based displays on devices such as computers and smart phones. Digital texts have a range of features that distinguish them from print-based texts: in addition to being displayed on screens, they include hypertext links to other documents, specific navigation features (e.g. scroll bars, use of menus) and interactivity. The Survey of Adult Skills is the first international assessment of adult literacy to cover this dimension of reading.
The assessment component of the Survey of Adult Skills was delivered in both a computer-based and a paper-based version. On average across OECD countries and economies 71% of respondents took the computer-based assessment and some 25% took the paper-based assessment as they had no or poor computer skills or expressed a preference to do so (Figure 2.5; see also Figure 2.15 and Table A2.11 in Annex A for further discussion).
Computer-based and paper-based assessments of literacy differ in two main ways. First, the paper-based assessment exclusively tests the reading of print texts whereas the computer-based version covers the reading of digital texts, such as simulated websites, results pages from search engines and blog posts, in addition to the reading of print texts presented on a screen. Thus, while the items that contain print text are common to both modes, a subset of items with digital text are used only in the computer-based assessment.
Second, the response modes differ. In the paper-based test, respondents provide written answers in paper test booklets. In the computer-based test, responding to the assessment tasks involves interacting with text and visual displays on a computer screen using devices, such as a keyboard and a mouse, and functions, such as highlighting and drag and drop.
In spite of these differences, most of the test items that were common to both versions were found to have equal difficulty and discrimination properties [for details, see OECD, (2019[2])]. In other words, their measurement properties are unaffected by the mode in which the test was taken and as such can be placed on the same scale. This means that the processes of understanding the meaning of a text are fundamentally the same for all types of text. Analyses of the results from the Survey of Adult Skills show that once socio-demographic factors (age, educational attainment, immigration background and gender) are taken into account, there are no systematic differences between the scores of adults who took the paper-based assessment and those who took the computer-based assessment (the differences across several variables between adults who took the paper-based assessment and those who took the computer-based assessment are shown in Table A2.13 in Annex A).
Levels of literacy proficiency across countries and economies
The literacy proficiency scale is divided into six levels: Levels 1 to 5 and below Level 1. The features of the tasks at these levels are described in detail in Table 2.1 and examples of literacy items are available in OECD (2013[4]) and the Reader’s Companion to this report (OECD, 2019[1]). Figure 2.6 presents the percentage of adults in each participating country or economy who scored at each of the six levels of proficiency on the literacy scale.
On average, across all OECD countries participating in the Survey of Adult Skills, one in ten adults (10.0%) scored at Level 4 or higher and one in three (34.6%) scored at Level 3. Overall, almost half of all adults (44.6%) scored at the three highest levels (Level 3, 4 or 5). Below these levels, around one in three adults (34.3%) performed at Level 2 and around one in five adults at Level 1 (15.0%) or below Level 1 (4.8%). Among countries participating in Round 3 of PIAAC, the proportions of adults scoring at the different levels in Hungary (42.1% at Level 3 and above; 38.7% at Level 2; 18.5% at Level 1 and below) and the United States (45.6% at Level 3 and above; 31.5% at Level 2; 17.6% at Level 1 and below) were close to the OECD average.
In contrast, less than one in eight adults performed at Level 3 or higher in Peru (6.1%), Mexico (11.7%) and Ecuador (5.2%). These proportions compare with those observed in other middle-income countries (see Box 1.2 in Chapter 1) such as Turkey (12.1%), one of the lowest performers from Round 2. These Round 3 Latin American countries were also among the countries and economies with the largest proportions of adults who scored at Level 1 or below. With more than half of their population scoring at these levels, Peru (70.2%), Ecuador (71.2%), Mexico (50.6%) are comparable to the other countries in the region which participated in the survey such as Chile which also had a significant proportion of low-performing adults (53.4%).
Kazakhstan, despite being a middle-income country itself, falls somewhere between these two groups of Round 3 countries. The proportion of adults scoring at Level 3 and above in Kazakhstan (25%) is smaller than in Hungary and the United States but higher than in Ecuador, Mexico and Peru. Close to half of the adult population in Kazakhstan performs at Level 2 (48.5%) and the proportion of the population scoring at Level 1 and below (26.3%) is only marginally higher than the corresponding OECD average (19.7%).
Literacy-related non-response
In all of the participating countries and economies, some adults were unable to complete the background questionnaire, as they were unable to understand or read the language of the assessment, had difficulty reading or writing, or had learning or mental disabilities. In the case of the background questionnaire, there was no one present (either the interviewer or another person) to translate into the language of the respondent or answer on behalf of the respondent.
In the case of these respondents, only their age, sex and, in some cases, educational attainment is known. In most countries, non-respondents represented less than 5% of the total population. This category is identified separately in Figure 2.6 as a patterned bar in each country (categorised as “missing”). While the proficiency of this group is likely to vary among countries, in most cases these individuals are likely to have low levels of proficiency (Level 1 or below) in the test language(s) of the country concerned.
Distribution of proficiency scores across and within countries and economies
Figure 2.7 shows the average score for each country or economy alongside a list of the other countries with average scores that are not statistically different from its own (see Box 2.4).
The statistics in this report are estimates of national performance based on samples of adults from each country. Consequently, each estimate referring to the target population has an associated degree of uncertainty, which is expressed through a standard error. The use of confidence intervals provides a way to make inferences about the population means and proportions in a manner that reflects the uncertainty associated with the sample estimates. From an observed sample statistic, and assuming a normal distribution, it can be inferred that the result for the corresponding population would lie within the confidence interval in 95 out of 100 replications of the measurement on different samples drawn from the same population.
In many cases, readers are primarily interested in whether a given value in a particular country is different from a second value in the same or another country, e.g. whether women in a country perform better than men in the same country or whether adults in one country have higher average scores than adults in another country. In the tables and figures used in this report, differences are labelled as statistically significant when there is less than a 5% chance that an observed difference between two representative samples reflects random sample variation, rather than actual differences between these populations.
In addition to errors associated with sampling, there are a range of other possible sources of errors in sample surveys such as the Survey of Adult Skills, including errors associated with survey non-response (see Chapter 3 of the Reader’s Companion to this report (OECD, 2019[1]) for a discussion of response rates and non-response bias). While the likely level of bias associated with non-response is assessed as minimal to low for most of the countries and economies participating in the study, the possibility of biases associated with non-response cannot be ruled out. Readers should therefore exercise caution in drawing conclusions from small score-point differences between countries or population groups, even if the differences concerned are statistically significant.
The average literacy score across the OECD countries and economies that participated in the assessment is 266 points, towards the top of Level 2 on the literacy scale. Among the Round 3 countries, the average proficiency of adults in Hungary (264 points) and the United States (271 points) was similar to the OECD average, that in Mexico (222 points), Peru (196 points) and Ecuador (196 points) was substantially below it and in Kazakhstan, the average proficiency of adults was between these two groups (249 points).
In addition to examining differences in average literacy proficiency between countries, it is also useful to explore differences in the distribution of scores within each country or economy. This can be done by identifying the score below which 5%, 25%, 75% and 95% of adults perform. Comparing score-point differences among adults at different points in the distribution of proficiency measures the extent of variation in that distribution in each participating country or economy. Figure 2.8 presents the distribution of scores within countries and economies in addition to the mean score. A longer bar indicates greater variations in literacy proficiency within a country; a shorter bar indicates smaller variations.
On average among OECD countries, 61 score points separate the 25% of adults who attained the highest and lowest scores in literacy (a measure known as the interquartile range). Of the countries participating in Round 3, Peru has the widest variation in literacy scores with a gap of 74 score points between the top- and bottom-performing 25%. This is virtually identical to the gap observed in its Latin American counterpart from Round 2, Chile (73 score points) and slightly less than Singapore, the country with the widest gap (77 score points).
Among the other countries participating in Round 3, the gap in literacy scores between the top- and bottom-performing 25% of adults in Ecuador (68 points) and the United States (69 points) is wider than the OECD average. In Mexico (61 points) and Hungary (58 points), the variation in scores is close to the OECD average, while in Kazakhstan, it is lower than the OECD average (52 points).
copy the linklink copied! Proficiency in numeracy
The Survey of Adult Skills defines numeracy as the ability to access, use, interpret and communicate mathematical information and ideas in order to engage in and manage the mathematical demands of a range of situations in adult life. A numerate adult is one who responds appropriately to mathematical content, information and ideas represented in various ways in order to manage situations and solve problems in a real-life context. While performance on numeracy tasks is, in part, dependent on the ability to read and understand text, numeracy involves more than applying arithmetical skills to information embedded in text.
Levels of numeracy proficiency across countries and economies
As with the literacy scale, the numeracy proficiency scale is divided into six proficiency levels: Levels 1 to 5 and below Level 1. The features of the tasks located at these levels are described in detail in Table 2.2 and examples of numeracy items are available in OECD (2013[4]).
Figure 2.9 presents the percentage of adults who scored at each of the six proficiency levels on the numeracy scale in each participating country. On average across participating OECD countries/economies, two in five adults scored at Level 3 and above (42.2%) in numeracy (see Table A2.3 in Annex A). Of the countries participating in Round 3, Hungary had the highest proportion of adults performing at this level (49.4%), slightly above the OECD average and close to the proportion observed in countries such as Austria, Germany, the Czech Republic and Estonia. In the United States, 35.4% of adults were proficient at Level 3 and above (well below the OECD average). Very small shares of the population performed at this level in Mexico (8.9%), Peru (5.6%) and Ecuador (3.6%). In this, these countries were similar to Chile (11.9%) and Turkey (14.5%) in Round 2. The proportion of adults performing at these levels in Kazakhstan was higher than that of other Round 3 middle-income countries but lower than that of Hungary and the United States. With 21.4% of adults performing at the three highest levels of numeracy proficiency, Kazakhstan is similar to countries like Italy and Spain.
On average, across all OECD countries participating in the Survey of Adult Skills, around one in three adults scored at Level 2 (33.0%) and around one in four adults (23.5%) scored at the two lowest levels of numeracy proficiency (16.4% at Level 1 and 7.1% below Level 1). Of the countries taking part in Round 3, the share of adults in the United States at Level 2 and below was similar to the OECD average, while Hungary again performed better than the average with 17.7% of its adults at the lowest proficiency levels (Level 1 and below). In Kazakhstan, as in the case of literacy, around half the adult population performed at Level 2 and the share of adults at the lowest proficiency levels was 26.8%, close to the OECD average. Around three-quarters of the adult population in Ecuador (76.8%) and Peru (74.8%) were only proficient at Level 1 or below in numeracy. In Mexico, this was true of 60.1% of adults. Prior to Round 3, the countries with the largest proportions of adults scoring at Level 1 and below in numeracy were Chile (61.9%) and Turkey (50.2%).
Literacy-related non-response
As noted above, in all countries and economies there were some adults who could not complete the background questionnaire as they were unable to understand or read the language of the assessment, have difficulty reading or writing, or have a learning or mental disability. This category is identified separately in Figure 2.9 as a patterned bar in each country (categorised as “missing”). In most cases, these persons will have low proficiency (Level 1 or below) in numeracy when assessed in the test language(s) of the country concerned.
Distribution of proficiency scores across and within countries and economies
Figure 2.10 shows the average score for each country and economy alongside a list of the other countries with average scores that are not statistically different from its own. For example, the mean score among adults in Hungary (272 points) is not statistically different from that of adults in Estonia (273 points), Germany (272 points), New Zealand (271 points) and the Russian Federation (270 points), but is significantly different from those of adults in other countries or economies at the 95% confidence level (see Box 2.4).
The average numeracy score across the OECD countries and economies that participated in the assessment is 262 points. Among countries participating in Round 3, the average numeracy proficiency of adults in Hungary (272 points) was significantly higher than the OECD average, while the average in the United States and Kazakhstan was significantly lower (255 and 247 points respectively). Latin American countries, three of which participated in Round 3, recorded the lowest average scores across all participating countries/economies – Ecuador (185 points), Peru (179 points), Chile (206 points) and Mexico (210 points).
As the literacy and numeracy scales measure different constructs, scores on the two scales cannot be compared directly. However, it is interesting to examine the extent to which countries perform differently in literacy and numeracy relative to other countries and the OECD average. With some exceptions, the relative performance of countries is similar for literacy and numeracy. Among the Round 3 countries, Hungary and the United States stand out as going against the general pattern. Adults in Hungary scored close the OECD average in literacy, but significantly above average in numeracy. In contrast, adults in the United States performed above the OECD average in literacy, but well below the average in numeracy (see Figure 2.16 below).
Figure 2.11 shows the variation in numeracy proficiency observed within countries, giving the distribution of scores in addition to the mean score. A longer bar indicates greater variations in numeracy proficiency within a country or economy; a shorter bar indicates smaller variations.
On average across OECD countries, the gap between the highest and lowest 25% of performers in numeracy is 68 score points. Among the countries participating in Round 3, Peru, Ecuador and the United States all have a larger gap in scores between these groups than the OECD average (91 points for Peru, 74 points for Ecuador and 76 points for the United States), while in Hungary and Mexico, the gap is similar to the average, at 67 points for both. The score gap is much lower than the OECD average in Kazakhstan and at 48 points is relatively similar to the gap found in the Russian Federation, a country that is comparable to the former in terms of its middle-income status and socio-demographic characteristics. Peru has the widest distribution of numeracy proficiency among all the countries and economies participating in the first cycle of PIAAC.
copy the linklink copied! Adults with low proficiency and the reading components assessment
In almost all countries and economies that took part in the Survey of Adult Skills, a sizable proportion of adults have low proficiency in either literacy or numeracy. In most countries, between 15% and 38% of 16-65 year-olds are proficient at Level 1 or below in either literacy or numeracy (see Figure 2.12). As described above, at Level 1, individuals can usually successfully complete simple reading and numeracy tasks, such as locating information in a short text or performing simple one-step arithmetic operations but they have trouble extracting information from longer and more complex texts or performing numerical tasks involving several steps and mathematical information represented in different ways. Individuals who perform below Level 1 are not only unable to locate information in complex texts but they experience difficulty doing so even with simple texts. Similarly, they struggle to complete simple numerical tasks.
Five countries stand out as having very large shares of adults who are only proficient at Level 1 or below in literacy or numeracy, including three of the Round 3 countries: Turkey (56.9%), Mexico (64.7%), Chile (67.1%), Peru (80.1%) and Ecuador (82.2%).
In order to provide more information about the skills of adults with poor reading proficiency, the Survey of Adult Skills includes an assessment of reading components. The reading components assessment was designed to assess three skills considered to be an essential precondition for understanding the meaning of written texts: knowledge of print vocabulary (word recognition), the ability to evaluate the logic of sentences (sentence processing) and fluency in reading passages of text (passage comprehension).1 Skilled readers are able to undertake these types of operations automatically. Chapter 1 of the Reader’s Companion to this report (OECD, 2019[1]) presents samples of the reading components tasks. The reading components assessment was implemented in all countries except Finland, France, Japan and the Russian Federation.
The assessment of reading components was taken by respondents who failed the literacy and numeracy core assessment in the computer-based version of the assessment, and by all respondents taking the paper version of the assessment (Box 2.3).
Figure 2.13 presents information about two dimensions of performance in the reading components assessment: the proportion of items that were correctly answered by respondents and the time taken to complete the assessment. The first panel shows the relationship between literacy proficiency and the percentage of items answered correctly (accuracy); the second panel shows the relationship between literacy proficiency and the time taken (in seconds) to complete an item (speed). Both accuracy and speed increase with greater proficiency in all three components, with the gains in both accuracy and speed tapering off markedly among adults who are proficient at Level 2 or higher.
There is little difference across countries and economies in the average proportion of correct answers in the print-vocabulary component, with the proportion varying between 93.1% in Singapore and 99.6% in the Czech Republic among those scoring at Levels 1 and below. Greater variation is observed in the case of passage comprehension among low-performing adults. The largest variation occurs in the sentence-processing component, where the proportion of correct answers varies between 76.2% in Singapore and 92.7% in the Czech Republic.
The results suggest that while there are many adults in most of the countries participating in the Survey of Adult Skills who have poor reading skills, there are very few who are illiterate in the sense of not being able to read at all. This is as true of countries such as Chile, Ecuador, Mexico, Peru and Turkey, in which the majority of adults are proficient at Level 1 and below on the literacy scale, as it is of countries with far smaller proportions of adults at this level (see Figure 2.14). In Ecuador, Mexico and Peru, which have very high proportions of adults performing at Level 1 or below for literacy, only around 8-20% of adults failed the literacy and numeracy core tests designed to identify the respondents who had the capacity to undertake the full assessment. Those failing the core test in these countries also correctly answered more than 77% of the items in the sentence-processing elements of the reading components assessment, more than 74% of the passage-comprehension items and 92% of the print-vocabulary items. A more detailed analysis of reading components results is presented in Grotlüschen et al. (2016[5]).
copy the linklink copied! Proficiency in problem solving in technology-rich environments
The Survey of Adult Skills defines problem solving in technology-rich environments as “using digital technology, communication tools and networks to acquire and evaluate information, communicate with others and perform practical tasks” (PIAAC Expert Group in Problem Solving in Technology-Rich Environments, 2009[6]). It focuses on “the abilities to solve problems for personal, work and civic purposes by setting up appropriate goals and plans, and accessing and making use of information through computers and computer networks” (OECD, 2012[7]).
Problem solving in technology-rich environments does not measure the cognitive skills required to solve problems in isolation. It measures both problem-solving and basic computer literacy skills (i.e. the capacity to use ICT tools and applications). This is done by assessing how well adults can use ICT tools and applications to assess, process, evaluate and analyse information in a goal-oriented way. For more details about the characteristics and some examples of problem solving tasks, see OECD (2013[4]).
A prerequisite for displaying proficiency in problem solving in technology-rich environments is having some rudimentary skills in the use of computer tools and applications. Given the very different levels of familiarity with computer applications in the countries and economies participating in the Survey of Adult Skills, the share of the population to which the estimates of proficiency in this domain refer thus vary widely. In other words, the populations for which proficiency scores for problem solving in technology-rich environments are reported are not identical across countries. Proficiency scores relate only to the share of the target population who were able to undertake the computer-based version of the assessment, and thus meet the preconditions for displaying competency in this domain. For this reason, the presentation of the results focuses on defining the proportions of the population at each proficiency level, rather than on comparing mean proficiency scores.2
The survey provides two different, albeit related, pieces of information about the capacity of adults to manage information in technology-rich environments. The first is the proportion of adults who are familiar enough with computers to use them to perform information-processing tasks. The second is the proficiency levels among adults with at least some ICT skills in solving the types of problems commonly encountered in their roles as workers, citizens and consumers in a technology-rich world.
Levels of proficiency in problem solving in technology-rich environments across countries and economies
The scale of problem solving in technology-rich environments is divided into four levels of proficiency (Levels 1 to 3 plus below Level 1). The features of the tasks at these levels are described in detail in Table 2.3 [some examples of problem-solving items are available in OECD (2019[1]) and OECD (2013[4])]. Figure 2.15 presents the proportion of adults across all participating countries and economies in each of the four proficiency levels for this domain. On average, across the OECD countries participating in the Survey of Adult Skills, around one-third of adults (29.7%) are proficient at the two highest levels (Level 2 or 3). Only one in ten adults or less in Ecuador (5.2%), Peru (6.6%), and Mexico (10.2%) achieved these levels, comparable to other middle-income economies like Turkey (where 7.8% of adults scored at Level 2 and 3). Just as in the case of literacy and numeracy, the proportions of adults performing at Level 2 or 3 in Hungary (28.5%) and the United States (31.2%) are close to the OECD average, while the share in Kazakhstan (16.2%) is below the OECD average but larger than the proportion in the Latin American Round 3 participants.
Across all participating OECD countries and economies, 43% of adults scored at Level 1 and below on this measure. Among the Round 3 countries, 42.6% of adults in Hungary and 49.8% in the United States only reached the lowest proficiency levels, both similar to the OECD average. These shares were higher than similar proportions observed in Mexico (32.1%) and Peru (37.8%) which are among the countries that have recorded the lowest performance in other domains across all survey participants. However, these anomalies could be explained by the large shares of adults in these Latin American countries who either failed the ICT core test or had no computer experience (see section below). In other words, smaller shares of adults might be scoring at Level 1 and below in countries like Peru and Mexico because these countries had large proportions of adults who were unable to display enough proficiency in problem solving to have scored at even the lowest levels.
The proportion of adults without basic information and communications technology skills
Each participating country and economy had a substantial proportion of adults who were unable to display any proficiency in problem solving in technology-rich environments since they took the assessment in the paper-based format. Three separate groups of adults fall in this category: those with no computer experience, those who failed the ICT core test and thus did not have basic computer skills needed for the computer-based assessment, and those who opted to take the paper-based version of the assessment even though they reported having ICT experience.
Overall, around one in ten adults (11.7%) reported having no prior computer experience and a further 4.7% of adults did not have the basic ICT skills that were assessed by the ICT core test, such as the capacity to use a mouse or scroll through a web page. Together with Turkey (38%), the Round 3 countries Ecuador (32.9%), Mexico (39.2%) and Peru (43.6%) stand out for the very large proportion of their adult populations who have no prior computer experience or very poor ICT skills. These results should be understood in context, however. The share of adults without basic ICT skills or computer experience reflect these countries’ level of economic development and ICT penetration. In 2017, only about one-third of households in Ecuador (38.1%) and Mexico (36.9%) had a fixed line phone subscription, while the share was significantly lower in Peru (21.9%). Internet and computer access in these countries are also limited: only around 40% of households had access to a computer and functional Internet in Ecuador and Mexico in 2017 and the share of such households in Peru stood even lower at around 30% (ITU, 2019[8]). This is in stark contrast to many of the high-income OECD countries where more than two-thirds of the households have access to a computer, Internet and a telephone line.
Table 2.3 Description of the problem solving in technology-rich environments proficiency levels
Not all Round 3 countries have large proportions of adults with no or poor computer skills, however. In contrast to Ecuador, Mexico and Peru, the proportion of adults without basic ICT skills or computer experience in Kazakhstan (19.7%), Hungary (14.4%) and the United States (7.4%) was much lower.
Some adults preferred not to use a computer in the assessment, despite reporting some prior experience with computers. On average, one in ten adults (10.0%) opted to take the paper-based version of the assessment without first taking the ICT core test (Box 2.3). Among the Round 3 countries, large proportions of adults in Ecuador (18.1%) and Mexico (17.8%) opted out of the computer-based assessment. While these proportions were similar to those observed in other countries with a similar performance in the survey such as Turkey (17.7%), they were also comparable to proportions in relatively better-performing countries like Poland (23.8%) and Ireland (17.4%). Other Round 3 participants had smaller shares of adults opting out: in Hungary (13.7%) and Peru (11.1%) the shares were similar to the OECD average, and the share was significantly lower in the United States (6.3%) and Kazakhstan (7.5%).
No information was collected on why people chose to take the paper-based assessment. However, information regarding the characteristics of these people and their patterns of ICT use is available and can be used to make inferences about their likely level of ICT skills and/or comfort with using a computer in a test situation (see Chapter 3).
copy the linklink copied! Summarising performance across countries and economies
Figure 2.16 summarises the proficiency of adults in participating countries and economies in each of the three domains assessed. It provides an overview of the average proficiency in each participating country and economy relative to the average in each domain. It also indicates whether the mean scores are statistically significantly greater than, equal to or less than the average across participating OECD countries and economies. In the case of problem solving in technology-rich environments, the average proficiency is not presented because of variations in the proportions of respondents who did not take the computer-based version and were not assessed in the problem-solving domain. Instead, the figure shows the proportion of the total population performing at Level 2 or 3 on this scale.
Among the Round 3 countries, Peru and Ecuador had scores that were statistically significantly below average in numeracy and literacy along with the smallest proportion of adults at Level 2 or 3 in problem solving in technology-rich environments. Although it performed slightly better, Mexico also reported extremely low levels of proficiency in all three domains. In this respect, these countries were similar to Chile, Greece, Israel, Slovenia and Turkey.
Hungary’s numeracy scores were above average while its literacy scores were below average, albeit only slightly. The opposite was true for the United States. For both these countries, the share of adults at Level 2 or 3 in problem solving in technology-rich environments were not significantly different from the average across OECD countries, while the remaining countries had mixed results. Kazakhstan, despite also being a middle-income country, recorded higher performances than its Round 3 middle-income counterparts, Ecuador, Mexico and Peru, but performed below Hungary and the United States.
copy the linklink copied! Summary
The results from the third (and final) round of data collection in Cycle 1 of PIAAC further expand the coverage of the study and knowledge about the proficiency of adults in key information processing skills globally. In total, 39 countries and economies participated in the study, most of which are high-income countries. However, with the addition of Ecuador, Kazakhstan, Mexico and Peru in Round 3, some seven middle-income countries have now been included. In addition, the Round 3 data collection in the United States means that PIAAC now has two measures of the proficiency of adults in literacy, numeracy and problem solving in technology-rich environments in the United States.
In summary, Hungary is notable for the fact that it performed well above average in numeracy but slightly below average in literacy. The results for the United States have changed little during the five years separating the first and third rounds of the study. This is in line with expectations, as changes in the overall proficiency of the adult population primarily results from the replacement of older cohorts by younger ones. As only around 10% of the target population will have been replaced over five years, there has been limited scope for major changes in this period.
The middle-income Latin American countries that participated in Round 3, Ecuador, Mexico and Peru, stand out as having low overall proficiency in all three of the domains assessed in PIAAC. Ecuador and Peru had the lowest mean scores of the countries participating in the first cycle of the study and the largest proportions of working-age adults performing at the lowest proficiency levels. Their performance reflects a range of factors such as the quality of the schooling system, their level of economic development and historical levels of educational participation. These results are also in line with studies of school-age children in the Programme for International Student Assessment (PISA) which found that among economies with a per capita GDP below USD 20 000 (such as Chile, Mexico, Peru and Turkey), the greater the country’s wealth, the higher its mean score on the PISA reading test until that threshold is reached (OECD, 2018[9]; OECD, 2012[10]). In Kazakhstan, the fourth and last middle-income country participating in Round 3, the proportion of adults scoring at the highest levels in literacy, numeracy and problem solving is smaller than in Hungary and the United States but larger than in Ecuador, Mexico and Peru. Close to half of the adult population in Kazakhstan performs at Level 2 in both the literacy and numeracy domains and the proportion of the population scoring at Level 1 and below is close to the OECD average.
The low levels of proficiency in information-processing skills among working-age adults represent challenges for governments in these countries. Some commentators claim that middle-income countries might lack the absorptive capacity for digital technologies compared to high-income countries, making the demand and supply of ICT skills in the former group different from the latter. Moreover, to some extent, take up of new technologies, particularly digital technologies, depends on the educational levels of the population, including their information-processing skills, as does the roll out of digitally based services. At the same time, PIAAC provides examples of very high-income countries with large proportions of adults with low proficiency in literacy and numeracy (e.g. Singapore and the United States) as well as examples of countries (Korea and Singapore) that have, over the last half century, successfully increased the proficiency of successive generations from a similar starting point to where Ecuador and Peru currently find themselves.
References
[5] Grotlüschen, A. et al. (2016), “Adults with low proficiency in literacy or numeracy”, OECD Education Working Papers, No. 131, OECD Publishing, Paris, https://doi.org/10.1787/5jm0v44bnmnx-en.
[8] ITU (2019), ICT Statistics, International Telecommunications Union, https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx.
[2] OECD (2019), Technical Report of the Survey of Adult Skills, Third Edition, OECD, http://www.oecd.org/skills/piaac/publications/PIAAC_Technical_Report_2019.pdf.
[1] OECD (2019), The Survey of Adult Skills: Reader’s Companion, Third Edition, OECD Skills Studies, OECD Publishing, Paris, https://doi.org/10.1787/f70238c7-en.
[9] OECD (2018), Skills in Ibero-America: Insights from PISA 2015, http://www.oecd.org/pisa/sitedocument/Skills-in-Ibero-America-Insights-from-PISA-2015.pdf.
[4] OECD (2013), OECD Skills Outlook 2013: First Results from the Survey of Adult Skills, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264204256-en.
[10] OECD (2012), “Does money buy strong performance in PISA?”, PISA in Focus, No. 13, OECD Publishing, Paris, https://doi.org/10.1787/5k9fhmfzc4xx-en.
[7] OECD (2012), Literacy, Numeracy and Problem Solving in Technology-Rich Environments: Framework for the OECD Survey of Adult Skills, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264128859-en.
[6] PIAAC Expert Group in Problem Solving in Technology-Rich Environments (2009), “PIAAC Problem Solving in Technology-Rich Environments: A conceptual framework”, OECD Education Working Papers, No. 36, OECD Publishing, Paris, https://doi.org/10.1787/220262483674.
[3] World Bank (2019), GDP per capita (constant 2010 US$), World Bank Data, https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.
Notes
← 1. The print-vocabulary tasks required test takers to select the word corresponding to a picture of an object from a selection of four alternative words. The sentence-processing tasks required test takers to identify whether a sentence made logical sense, given the properties of the real world. The passage-comprehension tasks entailed reading a prose text. At certain points in the text, test takers were given a choice of two words and required to select the word that made the most sense in the context of the passage.
← 2. This can be better understood by means of a hypothetical example: a country where around 50% of the population opts to sit the problem-solving assessment or knows how to use computers or passes the ICT core test might have a higher score in problem solving than a country where these three groups account for 80% of the population. These differences among countries in the proportions of the population for which problem-solving skills are measured at all makes it difficult to compare countries based on average scores in the domain of problem solving in technology-rich environments.
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