Reader's Guide

Student Access to Digital Learning Resources Outside of the Classroom draws upon relevant data sources, existing research, and relevant state and local intervention efforts to examine the five research areas identified in the Every Student Succeeds Act (ESSA) and to provide a comprehensive picture of student access to digital learning resources (DLR) outside of the classroom. This report is available on the National Center for Education Statistics (NCES) website as a full PDF and in HTML. The reference tables can be found in Appendix C: Reference Tables

Data Sources, Estimates, and Literature Search

The data, presented in the form of brief indicators, were obtained from many different sources—including students, parents, and teachers; state education agencies; and local elementary and secondary schools—using surveys. Users should be cautious when comparing data from different sources. Differences in aspects such as procedures, timing, question phrasing, and interviewer training can affect the comparability of results across data sources.

Most indicators in this report summarize data from surveys conducted by NCES or by the Census Bureau with support from NCES. Brief descriptions of the major NCES surveys used in these indicators can be found in the Appendix A: Guide to Data Sources for Indicators. More detailed descriptions can be obtained on the NCES website under "Surveys and Programs."

The Guide to Data Sources for Indicators also includes information on non-NCES sources used to develop indicators, such as the Census Bureau's American Community Survey (ACS) and Current Population Survey (CPS). For further details on the ACS, see https://www.census.gov/programs-surveys/acs/. For further details on the CPS, see https://www.census.gov/programs-surveys/cps.html.

Data for indicators in this report are obtained from sample surveys, which collect data from a sample of the population of interest. For example, the National Assessment of Educational Progress (NAEP) assesses a representative sample of students rather than the entire population of students. When a sample survey is used, statistical uncertainty is introduced, because the data come from only a portion of the entire population. This statistical uncertainty must be considered when reporting estimates and making comparisons. For more information, please see the section on standard errors below.

Various types of statistics derived from sample surveys are presented in this report. Many indicators report the size of a population or a subpopulation, and often the size of a subpopulation is expressed as a percentage of the total population. In addition, the average (or mean) value of some characteristic of the population or subpopulation may be reported. The average is obtained by summing the values for all members of the population and dividing the sum by the size of the population.

The summary of existing research is limited to empirical studies published in peer-reviewed journals and government reports from 2005 to 2016, so as to best describe the current state of DLR access outside of the classroom. Relevant journal articles and reports published during this period were located by searching online databases and checking reference lists. The databases used included Education Resources Information Center (ERIC), Education Research Complete via EBSCO, and Google Scholar. Keywords for the search included terms such as "home internet access," "home computer access," and "information communication technologies (ICTs)," as well as related derivations such as "home internet," "home computer," etc. When a relevant journal article was identified, a review of other literature that had cited that article was also conducted. All articles that were located through this search process that examined the topic of interest were included in the findings described below. No further evaluation of study quality was undertaken.

In Section 5, this report focuses on efforts conducted in 2015 and 2016 (2015 being the most recent data year reported in the indicators and 2016 being the year before the report was in production). For this section, we had limited ability to address the Congressional mandate within the timeframe and scope of this report. We searched for relevant reports on technology, but did not identify any national data or evaluations addressing systematic efforts to address DLR access at home. We did identify some reports published by political organizations and advocacy groups, and provided some examples of state and local efforts from those reports. It is important to understand that these examples are not representative of all the types of efforts that are currently being made. It is likely that there are other examples of state and local initiatives that are not discussed here because reports were not produced about these efforts within the time frame that we used for our search procedures.

Top

Standard Errors

Using estimates calculated from data based on a sample of the population requires consideration of several factors before the estimates become meaningful. When using data from a sample, some margin of error will always be present in estimations of characteristics of the total population or subpopulation because the data are available from only a portion of the total population. Consequently, data from samples can provide only an approximation of the true or actual value. The margin of error of an estimate, or the range of potential true or actual values, depends on several factors such as the amount of variation in the responses, the size and representativeness of the sample, and the size of the subgroup for which the estimate is computed. The magnitude of this margin of error is measured by what statisticians call the "standard error" of an estimate. Larger standard errors typically mean that the estimate is less accurate, while smaller standard errors typically indicate that the estimate is more accurate.

When data from sample surveys are reported, the standard error is calculated for each estimate. The standard errors for all estimated totals, means, medians, or percentages are reported in the reference tables.

In order to caution the reader when interpreting findings in the indicators, estimates from sample surveys are flagged with a "!" when the standard error is between 30 and 50 percent of the estimate, and suppressed with a "‡" when the standard error is 50 percent of the estimate or greater.

Top

Data Analysis and Interpretation

When estimates are from a sample, caution is warranted when drawing conclusions about whether one estimate is different in comparison to another; about whether a time series of estimates is increasing, decreasing, or staying the same; or about whether two variables are associated. Although one estimate may appear to be larger than another, a statistical test may find that the apparent difference between them is not measurable due to the uncertainty around the estimates. In this case, the estimates will be described as having no measurable difference, meaning that the difference between them is not statistically significant.

Whether differences in means or percentages are statistically significant can be determined using the standard errors of the estimates. In the indicators in this report and other reports produced by NCES, when differences are statistically significant, the probability that the difference occurred by chance is less than 5 percent, according to NCES standards.

For all indicators that report estimates based on samples, differences between estimates (including increases and decreases) are stated only when they are statistically significant. To determine whether differences reported are statistically significant, two-tailed t tests at the .05 level are typically used. The t test formula for determining statistical significance is adjusted when the samples being compared are dependent. The t test formula is not adjusted for multiple comparisons, with the exception of statistical tests conducted using the NAEP Data Explorer. When the variables to be tested are postulated to form a trend over time, the relationship may be tested using linear regression or ANOVA trend analyses instead of a series of t tests. Indicators that use other methods of statistical comparison include a separate technical notes section. For more information on data analysis, please see the NCES Statistical Standards, Standard 5-1, available at http://nces.ed.gov/statprog/2012/pdf/Chapter5.pdf.

Data presented in the indicators do not investigate complex hypotheses or support causal inferences. This report uses descriptive statistics to explore differences in students' access to and use of DLR at home by individual, family, and neighborhood characteristics, as well as associations between DLR access/use and academic outcomes. One of the limitations of bivariate statistics is that they describe subpopulation differences without taking into account the influence of other individual, family, school, or environmental factors. Many of the variables examined in this report may be related to other factors outside of students' access to and use of computers and the Internet in their homes. Future research using more complex methods, such as multivariate analyses, can further explore variations in student access to and use of DLR; it can also examine relationships between access and academic outcomes after taking into account other characteristics of students, families, and schools that are interrelated. We encourage readers who are interested in more complex questions and in-depth analysis to explore other NCES resources, including publications, online data tools, and public- and restricted-use datasets at http://nces.ed.gov.

A number of considerations influence the ultimate selection of the data years to feature in the indicators. To make analyses as timely as possible, the latest year of available data is shown. The choice of comparison years is often also based on the need to show the earliest available survey year. In the figures and tables of the indicators, intervening years are selected in increments in order to show the general trend. The narrative for the indicators typically compares the most current year's data with those from the initial year. Where applicable, the narrative may also note years in which the data begin to diverge from previous trends.

Top

Rounding and Other Considerations

All calculations within the indicators in this report are based on unrounded estimates. Therefore, the reader may find that a calculation, such as a difference or a percentage change, cited in the text or figure may not be identical to the calculation obtained by using the rounded values shown in the accompanying tables. Although values reported in the reference tables are generally rounded to one decimal place (e.g., 76.5 percent), values reported in each indicator are generally rounded to whole numbers (with any value of 0.50 or above rounded to the next highest whole number). Due to rounding, cumulative percentages may sometimes equal 99 or 101 percent rather than 100 percent. While the data labels on the figures have been rounded to whole numbers, the graphical presentation of these data is based on the unrounded estimates.

Top

Race and Ethnicity

The Office of Management and Budget (OMB) is responsible for the standards that govern the categories used to collect and present federal data on race and ethnicity. The OMB revised the guidelines on racial/ethnic categories used by the federal government in October 1997, with a January 2003 deadline for implementation. The revised standards require a minimum of these five categories for data on race: American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White. The standards also require the collection of data on ethnicity categories, at a minimum, Hispanic or Latino and Not Hispanic or Latino. It is important to note that Hispanic origin is an ethnicity rather than a race, and therefore persons of Hispanic origin may be of any race. Origin can be viewed as the heritage, nationality group, lineage, or country of birth of the person or the person's parents or ancestors before their arrival in the United States. The race categories White, Black, Asian, Native Hawaiian or Other Pacific Islander, and American Indian or Alaska Native, as presented in these indicators, exclude persons of Hispanic origin unless noted otherwise.

The categories are defined as follows:

• American Indian or Alaska Native: A person having origins in any of the original peoples of North and South America (including Central America) and maintaining tribal affiliation or community attachment.
• Asian: A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.
• Black or African American: A person having origins in any of the black racial groups of Africa.
• Native Hawaiian or Other Pacific Islander: A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.
• White: A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.
• Hispanic or Latino: A person of Mexican, Puerto Rican, Cuban, South or Central American, or other Spanish culture or origin, regardless of race.

Within these indicators, some of the category labels have been shortened in the text, tables, and figures for ease of reference. American Indian or Alaska Native is denoted as American Indian/Alaska Native (except when separate estimates are available for American Indians alone or Alaska Natives alone); Black or African American is shortened to Black; and Hispanic or Latino is shortened to Hispanic. Native Hawaiian or Other Pacific Islander is shortened to Pacific Islander.

The indicators in this report draw from a number of different data sources. Many are federal surveys that collect data using the OMB standards for racial/ethnic classification described above; however, some sources have not fully adopted the standards, and some indicators include data collected prior to the adoption of the OMB standards. This report focuses on the six categories that are the most common among the various data sources used: White, Black, Hispanic, Asian, Pacific Islander, and American Indian/Alaska Native. Asians and Pacific Islanders are combined into one category in indicators for which the data were not collected separately for the two groups.

Some of the surveys from which data are presented in these indicators give respondents the option of selecting either an "other" race category, a "Two or more races" or "multiracial" category, or both. Where possible, indicators present data on the "Two or more races" category; however, in some cases this category may not be separately shown because the information was not collected or due to other data issues. In general, the "other" category is not separately shown. Any comparisons made between persons of one racial/ethnic group to "all other racial/ethnic groups" include only the racial/ethnic groups shown in the indicator. In some surveys, respondents are not given the option to select more than one race. In these surveys, respondents of Two or more races must select a single race category. Any comparisons between data from surveys that give the option to select more than one race and surveys that do not offer such an option should take into account the fact that there is a potential for bias if members of one racial group are more likely than members of the others to identify themselves as "Two or more races."³

For more information on race/ethnicity, see Appendix B: Definitions.

Top

Locale

Federal departments and agencies use various classification systems to define community types.

Indicators in Student Access to Digital Learning Resources Outside of the Classroom use the National Center for Education Statistics (NCES) system of locale codes. These locale codes are based on an address's proximity to an urbanized area.

• City, Large: Territory inside an urbanized area and inside a principal city with population of 250,000 or more.
• City, Midsize: Territory inside an urbanized area and inside a principal city with population less than 250,000 and greater than or equal to 100,000.
• City, Small: Territory inside an urbanized area and inside a principal city with population less than 100,000.
• Suburb, Large: Territory outside a principal city and inside an urbanized area with population of 250,000 or more.
• Suburb, Midsize: Territory outside a principal city and inside an urbanized area with population less than 250,000 and greater than or equal to 100,000.
• Suburb, Small: Territory outside a principal city and inside an urbanized area with population less than 100,000.
• Town, Fringe: Territory inside an urban cluster that is less than or equal to 10 miles from an urbanized area.
• Town, Distant: Territory inside an urban cluster that is more than 10 miles and less than or equal to 35 miles from an urbanized area.
• Town, Remote: Territory inside an urban cluster that is more than 35 miles from an urbanized area.
• Rural, Fringe: Census-defined rural territory that is less than or equal to 5 miles from an urbanized area, as well as rural territory that is less than or equal to 2.5 miles from an urban cluster.
• Rural, Distant: Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an urbanized area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an urban cluster.
• Rural, Remote: Census-defined rural territory that is more than 25 miles from an urbanized area and is also more than 10 miles from an urban cluster.

Top

Metropolitan Status

Metropolitan areas refer to metropolitan statistical areas which contain at least one urbanized area with a population of 50,000 or more. Nonmetropolitan areas refer to areas that are outside of metropolitan statistical areas.

Top

Poverty and Income

In indicators using U.S. Census Bureau data, such as the ACS and CPS, poverty and family income are discussed. In determining poverty, the U.S. Census Bureau uses a set of money income thresholds that vary by family size and composition. A family, along with each individual in it, is considered poor if the family's total income is less than that family's threshold. The poverty thresholds do not vary geographically and are adjusted annually for inflation using the Consumer Price Index. The official poverty definition counts money income before taxes and does not include capital gains and noncash benefits (such as public housing, Medicaid, and food stamps).

Family income includes all monetary income from all sources (including jobs, businesses, interest, rent, and Social Security payments) over a 12-month period. The income of nonrelatives living in the household is excluded, but the income of all family members age 15 or older (age 14 or older in years prior to 1989), including those temporarily living outside of the household, is included.

Top

Limitations of the Data

The relatively small sizes of the American Indian/Alaska Native and Pacific Islander populations pose many measurement difficulties when conducting statistical analyses. Even in larger surveys, the numbers of American Indians/Alaska Natives and Pacific Islanders included in a sample are often small. Researchers studying data on these two populations often face small sample sizes that reduce the reliability of results. Survey data for American Indians/Alaska Natives often have somewhat higher standard errors than data for other racial/ethnic groups. Due to large standard errors, differences that seem substantial are often not statistically significant and, therefore, not cited in the text.

Data on American Indians/Alaska Natives are often subject to inaccuracies that can result from respondents self-identifying their race/ethnicity. According to research on the collection of race/ethnicity data conducted by the Bureau of Labor Statistics in 1995, the categorization of American Indian and Alaska Native is the least stable self-identification. The racial/ethnic categories presented to a respondent, and the way in which the question is asked, can influence the response, especially for individuals who consider themselves as being of mixed race or ethnicity. These data limitations should be kept in mind when reading this report.

As mentioned above, Asians and Pacific Islanders are combined into one category in indicators for which the data were not collected separately for the two groups. The combined category can sometimes mask significant differences between subgroups. For example, prior to 2011, the National Assessment of Educational Progress (NAEP) collected data that did not allow for separate reporting of estimates for Asians and Pacific Islanders. Information from Digest of Education Statistics, 2015 (table 101.20), based on the Census Bureau Current Population Reports, indicates that 96 percent of all Asian/Pacific Islander 5- to 24-year-olds are Asian. This combined category for Asians/Pacific Islanders is more representative of Asians than Pacific Islanders.

Top

Symbols

In accordance with the NCES Statistical Standards, many tables in this volume use a series of symbols to alert the reader to special statistical notes. These symbols, and their meanings, are as follows:

— Not available.

† Not applicable.

# Rounds to zero.

! Interpret data with caution. The coefficient of variation (CV) for this estimate is between 30 and 50 percent.

‡ Reporting standards not met. Either there are too few cases for a reliable estimate or the coefficient of variation (CV) for this estimate is 50 percent or greater.

* p < .05 Significance level.

---

³ Such bias was found by a National Center for Health Statistics study that examined race/ethnicity responses to the 2000 Census. This study found, for example, that as the percentage of multiple-race respondents in a county increased, the likelihood of respondents stating Black as their primary race increased among Black/White respondents but decreased among American Indian or Alaska Native/Black respondents.