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.

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.

The Progress in International Reading Literacy Study, 2006 (PIRLS 2006), is a study that is part of the Progress in International Reading Literacy Study (PIRLS) program. PIRLS 2006 (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 183 schools were sampled and 5,190 fourth-grade students were tested. The final weighted student response rate was 95 percent and the final weighted school response rate was 99 percent. The overall weighted response rate was 82 percent. Key statistics produced from PIRLS 2006 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.

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.

In 2022 there were more than 5.4 million book readers in Italy between the ages of six and 24 years who read at least one book in the last 12 months. By comparison, the corresponding figure for those aged 45 to 64 years stood at more than 6.7 million, with this age group also being the most likely to read several books per year.

This dataset is about books. It has 1 row and is filtered where the book is How to read statistics. It features 7 columns including author, publication date, language, and book publisher.

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.

In 2021, ** percent of respondents with a high school degree or less reported not having read a book in the last year, compared to ** percent who had some college education. Survey respondents who were college graduates or had pursued further education beyond college were the least likely to say that they had not read a single print book, e-book, or audiobook in the past 12 months.

Number of programs held, by branch, during annual “Summer Read & Learn” (June through August). Numbers represent programs held for target audiences (i.e., babies, toddlers, preschoolers, kindergartners, elementary school-aged, teenagers).

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.

Vocabulary knowledge is crucial for accessing the school curriculum and for performance on school assessments. It is also strongly influenced by a child’s exposure to language in the home and disadvantages in knowledge are apparent at school-entry. Vocabulary knowledge has a lasting influence on academic achievement that persists into secondary school and disadvantages are only partially ameliorated by teacher-directed instruction. Reading ability is also crucial for academic achievement, but contrasts with vocabulary as a skill in which initial disadvantages tend to fade over time. We followed primary-aged pupils from the Aston Literacy Project (a large longitudinal study of reading from school-entry to late-primary) during the critical but under-researched transition to secondary school. This data set includes information on children’s vocabulary, word reading and reading comprehension at the and of primary school and the beginning of secondary school. The data were used to examine reading and vocabulary development across the primary-secondary school transition.

README

Authors

César E. Corona-González, Claudia Rebeca De Stefano-Ramos, Juan Pablo Rosado-Aíza, Fabiola R Gómez-Velázquez, David I. Ibarra-Zarate, Luz María Alonso-Valerdi

Contact person

César E. Corona-González

https://orcid.org/0000-0002-7680-2953

a00833959@tec.mx

Project name

Psychophysiological data from Mexican children with learning difficulties who strengthen reading and math skills by assistive technology

Year that the project ran

2023

Brief overview of the tasks in the experiment

The current dataset consists of psychometric and electrophysiological data from children with reading or math learning difficulties. These data were collected to evaluate improvements in reading or math skills resulting from using an online learning method called Smartick.

The psychometric evaluations from children with reading difficulties encompassed: spelling tests, where 1) orthographic and 2) phonological errors were considered, 3) reading speed, expressed in words read per minute, and 4) reading comprehension, where multiple-choice questions were given to the children. The last 2 parameters were determined according to the standards from the Ministry of Public Education (Secretaría de Educación Pública in Spanish) in Mexico. On the other hand, group 2 assessments embraced: 1) an assessment of general mathematical knowledge, as well as 2) the hits percentage, and 3) reaction time from an arithmetical task. Additionally, selective attention and intelligence quotient (IQ) were also evaluated.

Then, individuals underwent an EEG experimental paradigm where two conditions were recorded: 1) a 3-minute eyes-open resting state and 2) performing either reading or mathematical activities. EEG recordings from the reading experiment consisted of reading a text aloud and then answering questions about the text. Alternatively, EEG recordings from the math experiment involved the solution of two blocks with 20 arithmetic operations (addition and subtraction). Subsequently, each child was randomly subcategorized as 1) the experimental group, who were asked to engage with Smartick for three months, and 2) the control group, who were not involved with the intervention. Once the 3-month period was over, every child was reassessed as described before.

Description of the contents of the dataset

The dataset contains a total of 76 subjects (sub-), where two study groups were assessed: 1) reading difficulties (R) and 2) math difficulties (M). Then, each individual was subcategorized as experimental subgroup (e), where children were compromised to engage with Smartick, or control subgroup (c), where they did not get involved with any intervention.

Every subject was followed up on for three months. During this period, each subject underwent two EEG sessions, representing the PRE-intervention (ses-1) and the POST-intervention (ses-2).

The EEG recordings from the reading difficulties group consisted of a resting state condition (run-1) and while performing active reading and reading comprehension activities (run-2). On the other hand, EEG data from the math difficulties group was collected from a resting state condition (run-1) and when solving two blocks of 20 arithmetic operations (run-2 and run-3). All EEG files were stored in .set format. The nomenclature and description from filenames are shown below:

Example: the file sub-Rc11_ses-1_task-SmartickDataset_run-2_eeg.set is related to: - The 11th subject from the reading difficulties group, control subgroup (sub-Rc11). - EEG recording from the PRE-intervention (ses-1) while performing the reading activity (run-2)

Independent variables

• Study groups:
  • Reading difficulties
    • Control: children did not follow any intervention
    • Experimental: Children used the reading program of Smartick for 3 months
  • Math difficulties
    • Control: children did not follow any intervention
    • Experimental: Children used the math program of Smartick for 3 months
• Condition:
  • PRE-intervention: first psychological and electroencephalographic evaluation
  • POST-intervention: second psychological and electroencephalographic evaluation

Dependent variables

• Psychometric data from the reading difficulties group:

  • Orthographic_ERR: number of orthographic errors.
  • Phonological_ERR: number of phonological errors.
  • Selective_Attention: score from the selective attention test.
  • Reading_Speed: reading speed in words per minute.
  • Comprehension: score on a reading comprehension task.
  • GROUP: C for the control group, E for the experimental group.
  • GENDER: M for male, F for Female.
  • AGE: age at the beginning of the study.
  • IQ: intelligence quotient.

• Psychometric data from the math difficulties group:

  • WRAT4: score from the WRAT-4 test.
  • hits: hits during the EEG acquisition [%].
  • RT: reaction time during the EEG acquisition [s].
  • Selective_Attention: score from the selective attention test.
  • GROUP: C for the control Group, E for the experimental group.
  • GENDER: M for male, F for female.
  • AGE: age at the beginning of the study.
  • IQ: intelligence quotient.

Psychometric data can be found in the 01_Psychometric_Data.xlsx file

• Engagement percentage within Smartick (only for experimental group)
  • These values represent the engagement percentage through Smartick.
  • Students were asked to get involved with the online method for learning for 3 months, 5 days a week.
  • Greater values than 100% denote participants who regularly logged in more than 5 days weekly.

Engagement percentage be found in the 05_SessionEngagement.xlsx file

Methods

Subjects

Seventy-six Mexican children between 7 and 13 years old were enrolled in this study.

Information about the recruitment procedure

The sample was recruited through non-profit foundations that support learning and foster care programs.

Apparatus

g.USBamp RESEARCH amplifier

Initial setup

1. Explain the task to the participant.
2. Sign informed consent.
3. Set up electrodes.

Task details

The stimuli nested folder contains all stimuli employed in the EEG experiments.

Level 1 - Math: Images used in the math experiment.​​​​​​​ - Reading: Images used in the reading experiment.

Level 2 - Math * POST_Operations: arithmetic operations from the POST-intervention.
* PRE_Operations: arithmetic operations from the PRE-intervention. - Reading * POST_Reading1: text 1 and text-related comprehension questions from the POST-intervention. * POST_Reading2: text 2 and text-related comprehension questions from the POST-intervention. * POST_Reading3: text 3 and text-related comprehension questions from the POST-intervention. * PRE_Reading1: text 1 and text-related comprehension questions from the PRE-intervention. * PRE_Reading2: text 2 and text-related comprehension questions from the PRE-intervention. * PRE_Reading3: text 3 and text-related comprehension questions from the PRE-intervention.

Level 3 - Math * Operation01.jpg to Operation20.jpg: arithmetical operations solved during the first block of the math

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 # 70-74 years (46) | Female # 55-59 years (54). 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

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.

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).

Descriptive and inferential statistics are taught to students in many disciplines. More classroom time is often spent on the theory behind different statistical methods that investigate relationships between variables rather than on how to interpret the results obtained to answer the research question that started the process. While statistical software (such as R, Stata, and SPSS) has made it easier to undertake regression with any dataset, the output produced remains challenging to understand and explain to intended audiences. To address this issue, the author created a 90-minute workshop that teaches students how to read tables of descriptive statistics and linear regression results produced by statistical software. The workshop has been taught each semester at the author’s institution since its creation in the Fall 2022 term, attracting a predominantly graduate student audience. Feedback has been positive thus far, with student requests for additional workshops on reading the results of different statistical models, such as logistic and count regression. Through an explanation of the process and the resources used, this presentation will provide a practical overview of how librarians can teach others how to read descriptive statistics and regression results using a research question and their own experiences working with data to guide them. It will include steps to prepare for designing a statistical literacy workshop. The aim of this presentation is to provide ideas that will help librarians move towards teaching a statistical literacy workshop at their own institutions or help them expand their teaching activities in this area.

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

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.

Jordan: PISA reading scores: The latest value from 2022 is 342.166 index points, a decline from 419.064 index points in 2018. In comparison, the world average is 437.426 index points, based on data from 78 countries. Historically, the average for Jordan from 2006 to 2022 is 395.66 index points. The minimum value, 342.166 index points, was reached in 2022 while the maximum of 419.064 index points was recorded in 2018.

A survey held in 2021 found that 74 percent of non-Hispanic Black respondents had read at least one book in the previous 12 months, up from 65 percent who said the same during the 2019 study. Non-Hispanic White adults were the most likely group to have read a print or digital book in the last year.