Graph and download economic data for Literacy Rate, Adult Total for Argentina (SEADTLITRZSARG) from 1980 to 2020 about literacy, adult, Argentina, and rate.

Argentina AR: Literacy Rate: Adult: % of People Aged 15 and Above data was reported at 97.193 % in 2001. This records an increase from the previous number of 96.041 % for 1991. Argentina AR: Literacy Rate: Adult: % of People Aged 15 and Above data is updated yearly, averaging 96.041 % from Dec 1980 (Median) to 2001, with 3 observations. The data reached an all-time high of 97.193 % in 2001 and a record low of 93.913 % in 1980. Argentina AR: Literacy Rate: Adult: % of People Aged 15 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Argentina – Table AR.World Bank.WDI: Social: Education Statistics. Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed September 19, 2023. https://apiportal.uis.unesco.org/bdds.;Weighted average;

Actual value and historical data chart for Argentina Literacy Rate Youth Male Percent Of Males Ages 15 24

Argentina AR: Literacy Rate: Youth Male: % of Males Aged 15-24 data was reported at 99.000 % in 2001. This records an increase from the previous number of 98.000 % for 1991. Argentina AR: Literacy Rate: Youth Male: % of Males Aged 15-24 data is updated yearly, averaging 98.000 % from Dec 1980 (Median) to 2001, with 3 observations. The data reached an all-time high of 99.000 % in 2001 and a record low of 96.000 % in 1980. Argentina AR: Literacy Rate: Youth Male: % of Males Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Argentina – Table AR.World Bank.WDI: Social: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

View yearly updates and historical trends for Argentina Adult Literacy Rate. Source: World Bank. Track economic data with YCharts analytics.

Actual value and historical data chart for Argentina Literacy Rate Adult Total Percent Of People Ages 15 And Above

Historical dataset showing Argentina literacy rate by year from 1980 to 2001.

Argentina: Female literacy rate, ages 15-24: The latest value from 2001 is 99 percent, unchanged from 99 percent in 1991. In comparison, the world average is 87.41 percent, based on data from 36 countries. Historically, the average for Argentina from 1980 to 2001 is 98.33 percent. The minimum value, 97 percent, was reached in 1980 while the maximum of 99 percent was recorded in 1991.

Argentina: Male literacy rate, ages 15-24: The latest value from 2001 is 99 percent, an increase from 98 percent in 1991. In comparison, the world average is 90.61 percent, based on data from 36 countries. Historically, the average for Argentina from 1980 to 2001 is 97.67 percent. The minimum value, 96 percent, was reached in 1980 while the maximum of 99 percent was recorded in 2001.

Argentina: Youth literacy rate, ages 15-24: The latest value from 2001 is 99 percent, an increase from 98 percent in 1991. In comparison, the world average is 88.97 percent, based on data from 36 countries. Historically, the average for Argentina from 1980 to 2001 is 98 percent. The minimum value, 97 percent, was reached in 1980 while the maximum of 99 percent was recorded in 2001.

Actual value and historical data chart for Argentina Elderly Literacy Rate Population 65 Years Male Percent

99.0 (%) in 2018. Adult (15+) literacy rate (%). Total is the percentage of the population age 15 and above who can, with understanding, read and write a short, simple statement on their everyday life. Generally, ‘literacy’ also encompasses ‘numeracy’, the ability to make simple arithmetic calculations. This indicator is calculated by dividing the number of literates aged 15 years and over by the corresponding age group population and multiplying the result by 100.

Actual value and historical data chart for Argentina Literacy Rate Youth Female Percent Of Females Ages 15 24

Actual value and historical data chart for Argentina Elderly Literacy Rate Population 65 Years Both Sexes Percent

Argentine: Female literacy rate, ages 15-24: Pour cet indicateur, UNESCO fournit des données pour la Argentine de 1980 à 2001. La valeur moyenne pour Argentine pendant cette période était de 98.33 pour cent avec un minimum de 97 pour cent en 1980 et un maximum de 99 pour cent en 1991.

Argentine: Youth literacy rate, ages 15-24: Pour cet indicateur, UNESCO fournit des données pour la Argentine de 1980 à 2001. La valeur moyenne pour Argentine pendant cette période était de 98 pour cent avec un minimum de 97 pour cent en 1980 et un maximum de 99 pour cent en 2001.

Context

With almost 40 million inhabitants and a diverse geography that encompasses the Andes mountains, glacial lakes, and the Pampas grasslands, Argentina is the second largest country (by area) and has one of the largest economies in South America. It is politically organized as a federation of 23 provinces and an autonomous city, Buenos Aires.

Content

We will analyze ten economic and social indicators collected for each province. Because these indicators are highly correlated, we will use principal component analysis (PCA) to reduce redundancies and highlight patterns that are not apparent in the raw data. After visualizing the patterns, we will use k-means clustering to partition the provinces into groups with similar development levels.

These results can be used to plan public policy by helping allocate resources to develop infrastructure, education, and welfare programs.

Acknowledgements

DataCamp

（停止更新）非文盲率：成年男性：15岁及以上男性百分比在12-01-2001达97.000%，相较于12-01-1991的96.000%有所增长。（停止更新）非文盲率：成年男性：15岁及以上男性百分比数据按年更新，12-01-1980至12-01-2001期间平均值为96.000%，共3份观测结果。该数据的历史最高值出现于12-01-2001，达97.000%，而历史最低值则出现于12-01-1980，为94.000%。CEIC提供的（停止更新）非文盲率：成年男性：15岁及以上男性百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的阿根廷 – Table AR.World Bank.WDI: Social: Education Statistics。

Abstract

The PIRLS 2001 aimed to generate a database of student achievement data in addition to information on student, parent, teacher, and school background data for the 35 countries that participated in PIRLS 2001.

Geographic coverage

Nationally Coverage

Analysis unit

Units of analysis in the study are schools, students, parents and teachers.

Universe

The PIRLS 2001 target populations are all children in "the upper of the two grades with the most 9-year-olds at the time of testing" (PIRLS, 1999) in each participating country. This corresponds to the fourth grade in most countries. This population was chosen because it represents an important transition point in children's development as readers. In most countries, by the end of fourth grade, children are expected to have learned how to read, and are now reading to learn.

The teachers in the PIRLS 2001 international database do not constitute representative samples of teachers in the participating countries. Rather, they are the teachers of nationally representative samples of students. Therefore, analyses with teacher data should be made with students as the units of analysis and reported in terms of students who are taught by teachers with a particular attribute. Teacher data are analyzed by linking the students to their teachers. The student-teacher linkage data files are used for this purpose. The same caveat applies to analyses of schools and parents.

Kind of data

Sample survey data [ssd]

Sampling procedure

To be acceptable for PIRLS 2001, national sample designs had to result in probability samples that gave accurate weighted estimates of population parameters such as means and percentages, and for which estimates of sampling variance could be computed. The PIRLS 2001 sample design is derived from the design of IEA's TIMSS (see Foy & Joncas, 2000), with minor refinements. Since sampling for PIRLS was to be implemented by the National Research Coordinator (NRC) in each participating country - often with limited resources - it was essential that the design be simple and easy to implement while yielding accurate and efficient samples of both schools and students.

The international project team provided manuals and expert advice to help NRCs adapt the PIRLS sample design to their national system, and to guide them through the phases of sampling. The School Sampling Manual (PIRLS, 1999) describes how to implement the international sample design to select the school sample; and offers advice on initial planning, adapting the design to national situations, establishing appropriate sample selection procedures, and conducting fieldwork. The Survey Operations Manual and School Coordinator Manual (PIRLS, 2001b, 2001a) provide information on sampling within schools, assigning assessment booklets and questionnaires to sampled students, and tracking respondents and non-respondents. To automate the rather complex within-school sampling procedures, NRCs were provided with sampling software jointly developed by the IEA Data Processing Center and Statistics Canada (IEA, 2001).

In IEA studies, the target population for all countries is known as the international desired target population. This is the grade or age level that each country should address in its sampling activities. The international desired target population for PIRLS 2001 was the following: "All students enrolled in the upper of the two adjacent grades that contain the largest proportion of 9-year-olds at the time of testing."

PIRLS expected all participating countries to define their national desired population to correspond as closely as possible to its definition of the international desired population. Using its national desired population as a basis, each participating country had to define its population in operational terms for sampling purposes. This definition, known in IEA terminology as the national defined population, is essentially the sampling frame from which the first stage of sampling takes place. Ideally, the national defined population should coincide with the national desired population, although in reality there may be some school types or regions that cannot be included; consequently, the national defined population is usually a very large subset of the national desired population. All schools and students in the desired population not included in the defined population are referred to as the excluded population.

The international sample design for PIRLS is generally referred to as a two-stage stratified cluster sample design. The first stage consists of a sample of schools, which may be stratified; the second stage consists of a sample of one or more classrooms from the target grade in sampled schools.

For more information on the approach to sampling adopted please consult section 5 of the PIRLS 2001 user guide.

Sampling deviation

Although countries were expected to do everything possible to maximize coverage of the population by the sampling plan, schools could be excluded, where necessary, from the sampling frame for the following reasons:

• They were in geographically remote regions.

• They were extremely small in size.

• They offered a curriculum or a school structure that was different from the mainstream educational system(s).

• They provided instruction only to students in the categories defined as “within-school exclusions.”

Within-school exclusions were limited to students who, because of some disability, were unable to take the PIRLS tests. NRCs were asked to define anticipated within school exclusions. Because these definitions can vary internationally, they were also asked to follow certain rules adapted to their jurisdictions. In addition, they were to estimate the size of the included population so that their compliance with the 95 percent rule could be projected. The general PIRLS rules for defining within-school exclusions included the following three groups:

• Educable mentally-disabled students. These are students who were considered, in the professional opinion of the school principal or other qualified staff members, to be educable mentally disabled – or who had been so diagnosed in psychological tests. This category included students who were emotionally or mentally unable to follow even the general instructions of the PIRLS test. It did not include students who merely exhibited poor academic performance or discipline problems.

• Functionally-disabled students. These are students who were permanently physically disabled in such a way that they could not perform in the PIRLS tests. Functionally-disabled students who could perform were included in the testing.

• Non-native-language speakers. These are students who could not read or speak the language of the test, and so could not overcome the language barrier of testing. Typically, a student who had received less than one year of instruction in the language of the test was excluded, but this definition was adapted in different countries. A major objective of PIRLS was that the effective target population, the population actually sampled by PIRLS, be as close as possible to the international desired population. Each country had to account for any exclusion of eligible students from the international desired population. This applied to school-level exclusions as well as within-school exclusions. See Appendix B of the PIRLS 2001 Technical Report (attached as Related Material) for a detailed account of sample implementation in each country

Mode of data collection

Face-to-face [f2f]

Research instrument

• PIRLS Background Questionnaires By gathering information about children’s experiences together with reading achievement on the PIRLS test, it is possible to identify the factors or combinations of factors that relate to high reading literacy. An important part of the PIRLS design is a set of questionnaires targeting factors related to reading literacy. PIRLS administered four questionnaires: to the tested students, to their parents, to their reading teachers, and to their school principals.

• Student Questionnaire Each student taking the PIRLS reading assessment completes the student questionnaire. The questionnaire asks about aspects of students’ home and school experiences – including instructional experiences and reading for homework, self perceptions and attitudes towards reading, out-of-school reading habits, computer use, home literacy resources, and basic demographic information.

• Learning to Read (Home) Survey The learning to read survey is completed by the parents or primary caregivers of each student taking the PIRLS reading assessment. It addresses child-parent literacy interactions, home literacy resources, parents’ reading habits and attitudes, homeschool connections, and basic demographic and socioeconomic indicators.

• Teacher Questionnaire The reading teacher of each fourth-grade class sampled for PIRLS completes a questionnaire designed to gather information about classroom contexts for developing reading literacy. This questionnaire asks teachers about characteristics of the class tested (such as size, reading levels of the students, and the language abilities of the students). It also asks about instructional time, materials and activities for teaching reading and promoting the development of their students’ reading literacy, and the grouping of students for reading instruction. Questions about classroom resources, assessment practices, and home-school connections also are included. The questionnaire also asks teachers for their views on opportunities for professional development and collaboration with other teachers, and for information about

Abstract

PIRLS provides internationally comparative data on how well children read by assessing students’ reading achievement at the end of grade four. PIRLS 2016 is the fourth cycle of the study and collects considerable background information on how education systems provide educational opportunities to their students, as well as the factors that influence how students use this opportunity. In 2016 PIRLS was extended to include ePIRLS – an innovative assessment of online reading.

The results of PIRLS 2016 demonstrate a number of positive developments in reading literacy worldwide. For the first time in the history of the study, as many as 96 percent of fourth graders from over 60 education systems achieved above the PIRLS low international benchmark.

Geographic coverage

Nationally representative samples of approximately 4,000 students from 150 to 200 schools participated in PIRLS 2016. About 319,000 students, 310,000 parents, 16,000 teachers, and 12,000 schools participated in total.

Analysis unit

The unit of analysis describes:

• Schools

• Students

• Parents

• Teachers

Universe

All students enrolled in the grade that represents four years of schooling counting from the first year of ISCED Level 1, providing the mean age at the time of testing is at least 9.5 years.

All students enrolled in the target grade, regardless of their age, belong to the international target population and should be eligible to participate in PIRLS. Because students are sampled in two stages, first by randomly selecting a school and then randomly selecting a class from within the school, it is necessary to identify all schools in which eligible students are enrolled. Essentially, eligible schools for PIRLS are those that have any students enrolled in the target grade, regardless of type of school.

Kind of data

Sample survey data [ssd]

Sampling procedure

PIRLS is designed to provide valid and reliable measurement of trends in student achievement in countries around the world, while keeping to a minimum the burden on schools, teachers, and students. The PIRLS program employs rigorous school and classroom sampling techniques so that achievement in the student population as a whole may be estimated accurately by assessing just a sample of students from a sample of schools. PIRLS assesses reading achievement at fourth grade. The PIRLS 2016 cycle also included PIRLS Literacy-a new, less difficult reading literacy assessment, and ePIRLS-an extension of PIRLS with a focus on online informational reading.

PIRLS employs a two-stage random sample design, with a sample of schools drawn as a first stage and one or more intact classes of students selected from each of the sampled schools as a second stage. Intact classes of students are sampled rather than individuals from across the grade level or of a certain age because PIRLS pays particular attention to students’ curricular and instructional experiences, and these typically are organized on a classroom basis. Sampling intact classes also has the operational advantage of less disruption to the school’s day-to-day business than individual student sampling.

SAMPLE SIZE

For most countries, the PIRLS precision requirements are met with a school sample of 150 schools and a student sample of 4,000 students for each target grade. Depending on the average class size in the country, one class from each sampled school may be sufficient to achieve the desired student sample size. For example, if the average class size in a country were 27 students, a single class from each of 150 schools would provide a sample of 4,050 students (assuming full participation by schools and students). Some countries choose to sample more than one class per school, either to increase the size of the student sample or to provide a better estimate of school level effects.

For countries choosing to participate in both PIRLS and PIRLS Literacy, the required student sample size is doubled-i.e., around 8,000 sampled students. Countries could choose to select more schools or more classes within sampled schools to achieve the required sample size. Because ePIRLS is designed to be administered to students also taking PIRLS, the PIRLS sample size requirement remains the same for countries choosing also to participate in ePIRLS.

PIRLS STRATIFIED TWO-STAGE CLUSTER SAMPLE DESIGN

The basic international sample design for PIRLS is a stratified two-stage cluster sample design, as follows:

• First Sampling Stage. For the first sampling stage, schools are sampled with probabilities proportional to their size (PPS) from the list of all schools in the population that contain eligible students. The schools in this list (or sampling frame) may be stratified (sorted) according to important demographic variables. Schools for the field test and data collection are sampled simultaneously using a systematic random sampling approach. Two replacement schools are also pre-assigned to each sampled school during the sample selection process, and these replacement schools are held in reserve in case the originally sampled school refuses to participate. Replacement schools are used solely to compensate for sample size losses in the event that the originally sampled school does not participate. School sampling is conducted for each country by Statistics Canada with assistance from IEA Hamburg, using the sampling frame provided by the country’s National Research Coordinator.

• Second Sampling Stage. The second sampling stage consists of the selection of one (or more) intact class from the target grade of each participating school. Class sampling in each country is conducted by the National Research Coordinator using the Within-School Sampling Software (WinW3S) developed by IEA Hamburg and Statistics Canada. Having secured a sampled school’s agreement to participate in the assessment, the National Research Coordinator requests information about the number of classes and teachers in the school and enters it in the WinW3S database.

Classes smaller than a specified minimum size are grouped into pseudo-classes prior to sampling. The software selects classes with equal probabilities within schools. All students in each sampled class participate in the assessment. Sampled classes that refuse to participate may not be replaced.

For countries participating in both PIRLS and PIRLS Literacy, students within a sampled class are randomly assigned either a PIRLS or PIRLS Literacy booklet through a booklet rotation system. This is done to ensure that PIRLS and PIRLS Literacy are administered to probabilistically equivalent samples. In countries taking part in ePIRLS, all students assessed in PIRLS are expected to participate in ePIRLS.

STRATIFICATION

Stratification consists of arranging the schools in the target population into groups, or strata, that share common characteristics such as geographic region or school type. Examples of stratification variables used in PIRLS include region of the country (e.g., states or provinces); school type or source of funding (e.g., public or private); language of instruction; level of urbanization (e.g., urban or rural area); socioeconomic indicators; and school performance on national examinations.

In PIRLS, stratification is used to:

• Improve the efficiency of the sample design, thereby making survey estimates more reliable

• Apply different sample designs, such as disproportionate sample allocations, to specific groups of schools (e.g., those in certain states or provinces)

• Ensure proportional representation of specific groups of schools in the sample School stratification can take two forms: explicit and implicit. In explicit stratification, a separate school list or sampling frame is constructed for each stratum and a sample of schools is drawn from that stratum. In PIRLS, the major reason for considering explicit stratification is disproportionate allocation of the school sample across strata. For example, in order to produce equally reliable estimates for each geographic region in a country, explicit stratification by region may be used to ensure the same number of schools in the sample for each region, regardless of the relative population size of the regions.

Implicit stratification consists of sorting the schools by one or more stratification variables within each explicit stratum, or within the entire sampling frame if explicit stratification is not used. The combined use of implicit strata and systematic sampling is a very simple and effective way of ensuring a proportional sample allocation of students across all implicit strata. Implicit stratification also can lead to improved reliability of achievement estimates when the implicit stratification variables are correlated with student achievement.

National Research Coordinators consult with Statistics Canada and IEA Hamburg to identify the stratification variables to be included in their sampling plans. The school sampling frame is sorted by the stratification variables prior to sampling schools so that adjacent schools are as similar as possible. Regardless of any other explicit or implicit variables that may be used, the school size is always included as an implicit stratification variable.

SCHOOL SAMPLING FRAME

One of the National Research Coordinator’s most important sampling tasks is the construction of a school sampling frame for the target population. The sampling frame is a list of all schools in the country that have students enrolled in the target grade and is the list from which the school sample is drawn. A well-constructed sampling frame provides complete coverage of the national target population without being contaminated by incorrect or duplicate entries or entries that refer to elements that are not