According to the results of a survey held in the United States, the share of Americans who had read more than ** books in the last three months stood at **** percent in February 2024. However, **** percent had not any read any books in the three months running up to the survey.

The Progress in International Reading Literacy Study, 2001 (PIRLS 2001), is a study that in the Progress in International Reading Literacy Study (PIRLS) program. PIRLS 2001 (https://nces.ed.gov/surveys/pirls/) is a cross-sectional study that provides international comparative information of the reading literacy of fourth-grade students and examines factors that may be associated with the acquisition of reading literacy in young students. The study was conducted using questionnaires and direct assessments of fourth-grade students. In the United States a total of 174 schools were sampled and 3,763 fourth-grade students were tested. The final weighted student response rate was 96 percent and the final weighted school response rate was 86 percent. The overall weighted response rate was 83 percent. Key statistics produced from PIRLS 2001 are how well fourth-grade students read, how students in one country compare with students in another country, how much fourth-grade students value and enjoy reading, and internationally, how the reading habits and attitudes of students vary.

During a survey held in early 2021, it was found that 83 percent of adults aged between 18 and 29 years old had read a book in any format in the previous year, up by two percent from the share who said the same in 2019. The survey results showed that adults within this age category were more likely than older respondents to have read a book within the last twelve months.

Book readers in the U.S.

While it is mostly believed that book reading is a vanishing pastime, particularly among Millennials, surveys among consumers in the U.S. have shown the opposite. The share of book readers in the U.S. has varied from 72 percent to 79 percent between 2011 and 2016.

In regards to age of book readers in the country, a 2016 survey shows about 80 percent of respondents between the ages of 18 to 29 had read at least one book in the previous 12 months, the highest share amongst all age groups. About 73 percent of the respondents aged between 30 to 49 years old said they read at least one book in the last 12 months. The share among respondents between 50 and 64 years old stood at 70 percent, whereas 67 percent of respondents aged 65 plus stated reading book during the time measured. In terms of education level, book readers in the U.S. are more likely to have a college degree, or at least some college education – 86 percent and 81 percent respectively. Women in the U.S. read slightly more than men; 68 percent of male respondents started reading at least one book in the previous 12 months, against 77 percent of female respondents that said the same.

Despite the rise of digital platforms and the rising popularity of e-reading devices such as Kindle, Kobo and others, printed books still remain the most popular book format in the U.S., as 65 percent of Americans stated preference for printed books in 2016. E-books were consumed by 28 percent of respondents in 2016, whereas audio books were listened by 14 percent of the respondents. Millennials accounted for the largest share of printed book readers in the U.S. – 72 percent as of 2016.

Recent data revealed that ** percent of Boomers who responded to a survey held in the United States in March 2020 were more likely to read books as a result of the coronavirus outbreak, compared to ** percent of Gen X respondents.Millennials were the most likely to read more books to keep themselves entertained whilst self-isolating, with ** percent saying that they were more inclined to read books, ***** percent higher than all adults in total.

The country reported to have read books most regularly in 2017 was China, where a survey among internet users across ** countries revealed that ** percent of respondents read a book every day or most days, and ** percent read at least once a week. Conversely, just ** percent of South Korean respondents were reading books on a daily basis. Other countries with a low share of those aged 15 years or above reading daily included Belgium, Japan, the Netherlands and Mexico.

Age and reading habits

It is surprising how much age can affect reading habits, even on a global level. In Germany, more 12 to 13-year-olds read daily or several times per week than their slightly older peers. Meanwhile, in the United Kingdom, a survey showed that more teenagers and Millennials said that they would be happy without books than adults aged 34 or older. More than double the percentage of adults in Colombia aged 65 or above read a book every day than those aged between 12 and 25 years.

The number of books read over the past year in the United States was overall higher among adults aged 18 to 34 than older generations, and in Canada the share of children reading books for fun halved with the approach of teenage years. Whilst ** percent of children aged between six and eight years old were reading for pleasure multiple times per week, among ** to 17-year-olds this figure amounted to just ** percent. Meanwhile, the opposite was true of going online for fun, which increased sharply with age and replaced the activity of reading.

A survey examining book readership in the United States as of February 2021 showed that ** percent of 18-to-29-year-olds had read a print book in the last year. The share was slightly lower among older adults, though more than ** percent of respondents in each age group reported having read at least one printed book in the 12 months leading to the survey.

Read Philippines or Basa Pilipinas was a four-year early grade reading project that operated from January 2013 to December 2016 and supported the Philippine Department of Education’s national reading program. Basa assisted the implementation of transformative literacy practices in selected divisions of Regions 1 and 7 by providing teacher and student materials, training teachers and school heads, and providing post-training support for Grade 1, 2 and 3 teachers, as well as providing Early Language, Literacy and Numeracy training to kindergarten teachers. The Basa Pilipinas activity used a quasi-experimental cross-sectional design to evaluate the impact of the treatment in improving reading and comprehension skills. Sampling was conducted at three levels: school, classrooms, and student. The school sample was drawn randomly from the activity’s five provinces. Within each school, one grade 2 classroom was selected randomly for baseline and midline with an additional grade 3 classroom selected during the endline. Within each classroom, students were randomly selected to be administered the assessment. A total of 469 students were sample from 40 schools in two provinces at the baseline (comparison), 1,216 students were sampled from 80 schools in five provinces at the midline (intervention 1), and 1,658 students were sampled from 5 provinces at the endline (intervention 2). The disparity in the number of provinces sampled is due to the expansion of the intervention from two provinces to five provinces starting at the midline to provide a more complete picture of the Basa outcomes. To enable the computation of estimates of literacy skills among students in all schools affected by the Basa intervention, design weights were applied to the analyses of EGRA data. Design weights were applied to compensate for differences in provincial sampling and to ensure an appropriate representation of learners in all provinces in the sample.

ABSTRACT Purpose: the study aims to obtain preliminary normative data for early reading and writing skills of 5-year-old children in a sample from the Northeast of Brazil. It also aims to investigate the effects of the type of school (public vs. private) and the time of assessment (beginning vs. end of the school year), and whether there were significant differences in performance, as compared to those of children from the Southeast of Brazil. Methods: 389 5-year-old children from 17 private and 12 public schools were assessed in the beginning and at the end of the school year, by using the Reading and Writing Test. Each student was individually assessed in the two times of the year. Appropriate statistical tests were applied, adopting a significance level lower than 0.05. Results: the progress in the performance of private school children was stronger than that of their peers from public schools, accentuating the existing learning gap. The comparison with normative data from the Southeast revealed that the public schools in the Northeast outperformed those in all topics of comparison. Private schools in the Southeast had a better performance at the beginning of the year, but were outperformed by those of the Northeast at the end of the year. Conclusion: the differences in performance identified in the samples suggest the need for specific norms by geographical regions of Brazil, and by type of school (public or private). The data presented in this study are preliminary and can be enlarged in future studies.

This dataset contains the school-level data related to the study "Methodological Decisions and their impacts on the perceived relations between school funding and educational achievement". The data contained within was pulled from data from the Florida Progress Monitoring and Reporting Network (PMRN; https://www.fldoe.org/core/fileparse.php/7544/urlt/PMRNv51PSLUG.pdf) as well as school-level per pupil expenditure data from the Florida Department of Education (https://web08.fldoe.org/TransparencyReports/CostReportSelectionPage.aspx). Data for this project included all public students and schools in the state of Florida during the 2009-2010 school year for whom reading comprehension/fluency data was available at both Fall (Wave 1) and Spring (Wave 3) assessment periods. Funding/expenditure data is further broken down by spending category and level (school vs. district).

This data is school-level, and as such represents data aggregated from student-level data over the same time period and using the same measures. The second tab contains a codebook describing all of the variables used in the dataset.

Estimated average scores of 15-year-old students, reading, mathematics and science, Programme for International Student Assessment (PISA), Canada, provinces and participating countries, Council of Ministers of Education Canada (CMEC). This table is included in Section C: Elementary-secondary education: Student achievement of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

Dataset Overview: This dataset contains survey responses collected from students in a college located in Satara, Maharashtra, India. The survey was conducted to gather information about students' library usage, reading habits, learning preferences, and other related factors.

Columns: The dataset consists of 29 columns representing different survey questions and responses. The columns include information such as gender, faculty, location, preferred study materials, library visit frequency, average time spent in college, preferred learning language, reading preferences, COVID-19 pandemic impact, book purchasing behavior, parents' occupation and education, and more.

Data Collection: The survey was shared with students in the college library, and their responses were collected using a Google Form. Approximately 10-15k students studying in various courses, ranging from 11th grade to master's degree, participated in the survey.

Data Format: The dataset is provided in CSV format, with each row representing a student's survey response and each column representing a specific survey question.

Data Usage: This dataset can be used to gain insights into students' library usage patterns, reading habits, and learning preferences. It can be used for exploratory data analysis, statistical analysis, and building predictive models related to student behavior, library services, or educational interventions.

Data Quality: The dataset has been cleaned and preprocessed to remove any identifiable personal information and ensure data privacy. However, it is always advisable to handle the data responsibly and in accordance with applicable data protection regulations.

Here's a column-wise description of the dataset:

gender: Gender of the student. faculty: Faculty or department of the student. Enter Your Location: Location of the student. kind of books preferred for study: Preferred type of books for studying. How Frequently do you visit library: Frequency of visiting the library. For what Purposes do you visit library: Purposes for visiting the library. Average Time spent in college: Average time spent in college. What is general Purposes: General purposes of the student. Which one is your Preferred location: Preferred location. What is your preferred time?: Preferred time for activities. Preferred language for Learning: Preferred language for learning. Preferred type for reading: Preferred type of reading material. Do you enjoy the Reading: Enjoyment of reading. Which mode of learning: Preferred mode of learning. Dose Covid Pandemic Ch: Impact of the Covid pandemic on learning. How do you study before collage: Study habits before college. How do you study after Collage: Study habits after college. Do you aware about Nati: Awareness about National Digital Library. Do you Using National di: Usage of National Digital Library. Dose Covid 19 Pandemic Affected Your Reading Habits: Impact of the Covid-19 pandemic on reading habits. Do you purchase Books from store: Book purchasing behavior from physical stores. Average Expenditure on books: Average expenditure on books. Occupation Of Father: Occupation of the student's father. Parents Education: Education level of the student's parents. Select your Faculty: Select faculty or department. Enter your Location: Enter location. Preferred Language for Learning: Preferred language for learning. Do you Using National dig: Usage of National Digital Library. Occupation of Father: Occupation of the student's father.

According to the results of an early 2024 survey, ** percent of all book readers had read between one and five books in 2024. Consumers aged 65 and above were the most frequent readers, with ** percent having read ** books or more in the last year.

Graph and download economic data for Expenditures: Reading by Age: from Age 25 to 34 (CXUREADINGLB0403M) from 1984 to 2023 about book, age, 25 years +, expenditures, and USA.

This table contains 336 series, with data for years 1997 - 2009 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...); Household spending, reading materials (6 items: Total reading materials and other printed matter; Newspapers; Magazines and periodicals; Books and pamphlets (excluding school books); ...); Statistics (4 items: Average expenditure; Percent of households reporting; Estimated number of households reporting; Median expenditure per household reporting).

ABSTRACT Purpose: to compare, with Adult Reading History Questionnaire results, the reading habits of adults with and without dyslexia of different cultures and languages. Methods: the research comprised 119 university students (60 Czechs and 59 Brazilians, half of them with dyslexia) assessed by responding to the self-report reading history questionnaire and taking a reading level test. ARHQ scores were compared between the groups and countries with the analysis of variance (ANOVA), and their correlation was assessed with the Spearman’s test, both with the significance level set at p < 0.05. Results: adults with dyslexia had lower reading habit scores and reading level scores than typical readers in both languages. Reading habits were positively correlated with reading levels in both languages. Regardless of the group, Brazilians had lower reading habit scores than Czechs. Conclusion: the results suggest that self-assessing reading habits is an effective way to screen for reading disorders. However, cultural and school factors must be considered.

Vietnam VN: Literacy Rate: Youth: % of People Age 15-24 data was reported at 97.092 % in 2009. This records an increase from the previous number of 94.837 % for 2000. Vietnam VN: Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 94.837 % from Dec 1979 (Median) to 2009, with 5 observations. The data reached an all-time high of 97.092 % in 2009 and a record low of 93.734 % in 1989. Vietnam VN: Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: 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; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

The Basque Youth Observatory is an instrument of the Basque Government that allows to have a global and permanent vision of the situation and evolution of the youth world that allows to evaluate the impact of the actions carried out in the CAPV by the different administrations in the field of youth.The Basque Youth Observatory regularly publishes more than 100 statistical indicators that can be consulted in euskadi.eus, along with other research and reports. Statistics are provided in various formats (csv, excel).

In September 2017, USAID commissioned RTI and Pratham Education Foundation’s (Pratham) Annual Status of Education Report (ASER) Centre to conduct the Analysis of Early Grade Reading Assessment (EGRA) in India activity. Together, RTI and Pratham developed a research plan and modified standard ASER and EGRA instruments to serve the research objective. The five largest education projects from the Mission’s portfolio were selected for inclusion into the assessment. Projects use different approaches and strategies to achieve similar goals – some work through government systems while others are working directly with schools to improve learning outcomes.

About this dataset

Context

The dataset tabulates the population of Reading town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Reading town. The dataset can be utilized to understand the population distribution of Reading town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Reading town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Reading town.

Key observations

Largest age group (population): Male # 60-64 years (98) | Female # 60-64 years (120). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Reading town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Reading town is shown in the following column.
• Population (Female): The female population in the Reading town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Reading town for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Reading town Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Reading by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Reading. The dataset can be utilized to understand the population distribution of Reading by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Reading. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Reading.

Key observations

Largest age group (population): Male # 0-4 years (89) | Female # 5-9 years (86). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Reading population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Reading is shown in the following column.
• Population (Female): The female population in the Reading is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Reading for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Reading Population by Gender. You can refer the same here