Digital divide in computer access and use between poor and non-poor youth.The main objectives of this study were to examine the "digital divide" in home computer ownership and to evaluate differences in academic and non-academic computer use between poor and non-poor youth. Data from a national sample of 1,029, 10- through 14-year-old young adolescents were analyzed an·a·lyze tr.v. an·a·lyzed, an·a·lyz·ing, an·a·lyz·es 1. To examine methodically by separating into parts and studying their interrelations. 2. Chemistry To make a chemical analysis of. 3. . Results show that poor youth were .36 times as likely to own a home computer, but equally as likely to use their home computer for academic purposes as were non-poor youth. Poor youth did not differ from non-poor youth in how often they used any computer for academic purposes, but were less likely to use any computer for non-academic purposes. Government initiatives to close the digital divide and foster computer use among poor youth are suggested. Key words: digital divide; poverty; computer use; information technology ********** The phrase "digital divide'--the disparity dis·par·i·ty n. pl. dis·par·i·ties 1. The condition or fact of being unequal, as in age, rank, or degree; difference: "narrow the economic disparities among regions and industries" between individuals who have and do not have access to information technology (IT)--became part of our country's vocabulary in the mid- mid- pref. Middle: midbrain. 1990s (Wilhelm Wilhelm. For German rulers thus named, use William. , Carmen Carmen throws over lover for another. [Fr. Lit.: Carmen; Fr. Opera: Bizet, Carmen, Westerman, 189–190] See : Faithlessness Carmen the cards repeatedly spell her death. [Fr. , & Reynolds, 2002). Well-documented inequalities This page lists Wikipedia articles about named mathematical inequalities. Pure mathematics
Publicly accessible computer network connecting many smaller networks from around the world. It grew out of a U.S. Defense Department program called ARPANET (Advanced Research Projects Agency Network), established in 1969 with connections between computers at the reflect existing patterns of social stratification Noun 1. social stratification - the condition of being arranged in social strata or classes within a group stratification condition - a mode of being or form of existence of a person or thing; "the human condition" in the United States United States, officially United States of America, republic (2005 est. pop. 295,734,000), 3,539,227 sq mi (9,166,598 sq km), North America. The United States is the world's third largest country in population and the fourth largest country in area. (Steyaert, 2002). For example, high-income, Caucasian Caucasian or Caucasoid: see race. , married, and well-educated individuals have more access to IT compared to low-income, African American African American Multiculture A person having origins in any of the black racial groups of Africa. See Race. and Latino, unmarried, and less-educated individuals (National Telecommunications and Information Administration The National Telecommunications and Information Administration (NTIA) is an agency of the United States Department of Commerce that serves as the President's principal adviser on telecommunications policies pertaining to the United States' economic and technological [NTIA NTIA National Telecommunications & Information Administration NTIA National Telecommunications & Information Association NTIA National Telecommunications Interagency NTIA National Telecommunications and Information Administration ], 2000, 2002). Although recent increases in access to IT in public schools have narrowed the IT gap between high- and low-income and white and minority students (NTIA, 2002), inequalities in IT access and use among children and adolescents continue, paralleling those of adults (Attewell & Battle, 1999). A recent survey (NTIA, 2002) indicates that less than 3% of adolescents living in the highest income families do not use computers, compared to approximately 15% of youth in the lowest income category. Although home computer use is almost universal among the wealthiest youth, only one-third of the lowest-income youth use a home computer. The survey found similar differences in Internet access See how to access the Internet. and use between low- and high-income youth and in computer and Internet access and use between Latinos and African Americans and whites. For more than a decade, numerous private and government initiatives have assisted poor communities and low-resource schools (where poor and minority students are more likely to reside and to attend) to gain access to computers, educational software, and the Internet (Wilhelm et al., 2002). Despite the well-documented IT gap between high- and low-income youth, and the billions of dollars that have been spent to close this gap (Roberts, 2000), few studies have examined IT access and type of IT use between poor and non-poor youth using multivariate The use of multiple variables in a forecasting model. methods. The multivariate methods used in this study enable the assessment of the independent influences of poverty on home computer ownership and on type of IT use, while controlling for other socio-demographic factors. Implications of the Digital Divide Diverse groups of individuals from government, education, social work, private foundations, industry, the popular press, as well as parents and youths themselves, have expressed several reasons why the nation should be concerned about the gap between the IT "haves" and "have-nots" (Brown, 2000; Hick & McNutt, 2002; NTIA, 2000; Turow & Nir, 2000). These concerns fall into four main themes: educational advantages, future employment and earnings, opportunities for social and civic involvement, and equity and civil rights issues. Many educators, researchers, policy advocates, and government officials maintain that computers, educational software, and the Internet offer a number of educational advantages (Center for Media Education, 1996; Lepper & Gurtner, 1989; Ross Ross , Sir Ronald 1857-1932. British physician. He won a 1902 Nobel Prize for proving that malaria is transmitted to humans by the bite of the mosquito. , Smith, & Morrison, 1991). IT can provide students and teachers with a large body of easily accessible information; create opportunities to reinforce learning basic, new, and higher-order cognitive skills cognitive skill Psychology Any of a number of acquired skills that reflect an individual's ability to think; CSs include verbal and spatial abilities, and have a significant hereditary component ; and increase student interest and motivation, parent-school communication, and parent involvement. These advantages, in turn, are expected to produce positive educational outcomes such as increased student achievement and school retention (Center for Media Education, 1996; U. S. Department of Education, 1999; Wenglinsky, 1998). Research tends to support these expectations, generally finding positive relations between school, home, and community uses of IT and a variety of academic outcomes both for socioeconomically disadvantaged This article or section may contain original research or unverified claims. Please help Wikipedia by adding references. See the for details. This article has been tagged since September 2007. (e.g., Blanton, Moorman, Hayes, & Warner, 1997; Ross et al., 1991; Sutton Sutton, outer borough (1991 pop. 164,300) of Greater London, SE England. It is mainly residential, but plastics, chemicals, radio components, and paper goods are produced. The areas of Sutton were mentioned in the Domesday Book. , 1991) and other children and youth (e.g., Campbell, Hombo, & Mazzeo, 2000; Fletcher-Flinn & Gravatt, 1995; Rocheleau, 1995; Schacter, 1999; Wenglinsky, 1998). Recent polls also indicate that parents, registered voters, elected officials, and business leaders share the belief that IT provides students with educational advantages. For example, almost 90% of polled parents agreed that access to IT assists children with their school work, and 74% of parents believed that children without access to IT are at an educational disadvantage (Turow & Nir, 2000). Over two-thirds of registered voters also agreed that educational computer uses would make a great deal or a fair amount of difference in the quality of children's education (Milken Exchange on Educational Technology, 1998). Children's and adolescent's access to and use of IT also are expected to increase future employment and earning opportunities. IT skills assist youth in researching and locating employment (NTIA, 2000). IT skills prepare youth to successfully compete in job markets in which an increasing number of occupations require such skills (U.S. Department of Education, 1999), and employers compensate workers who possess them with higher wages (Krueger, 1993). The belief among adolescents themselves that IT is important to their current and future well-being is reflected in a recent poll (Gallup Organization, 1997). Over three-fourths of the teenagers thought that owning a computer was critically important, and more than 80% of these youths believed strong computer skills and IT knowledge were necessary for them to make a good living in the future. IT not only has revolutionalized the way individuals learn and earn a living, but has provided new avenues for communicating and participating in the nation's social and civic life (Lonergan, 2000; NTIA, 2000). Daily newspapers, research, and government and private information on a variety of important social and civic topics are available online (Brown, 2000). In addition, computer and Internet technologies provide a variety of communication methods such as electronic-mail, instant messages, listserves, and chatrooms, placing youth who lack access to or skills in using IT at a social disadvantage (NTIA, 2000). The widespread belief in the benefits of IT to the educational, occupational, and social well-being of individuals, and the IT gap between the poor and non-poor and minorities and whites, have led some to characterize the "digital divide" as one of America's leading equity or civil rights issues (Brown, 2000; Lonergan, 2000; NTIA, 1999). Inequalities in IT access and use not only mirror existing patterns of social stratification, but can maintain and even widen wid·en tr. & intr.v. wid·ened, wid·en·ing, wid·ens To make or become wide or wider. wid  en·er n. current disparities between these groups in important indicators of
well-being such as academic achievement and earnings (Johnson, 2000;
Krueger, 1993; Sutton, 1991; U. S. Department of Education, 2002).
Disparities in academic achievement might widen because low-income and
minority youth are unable to take full advantage of the educational
benefits of IT. Inequalities in earnings might increase as a result of
poor and minority youth being less prepared to compete for higher paying
jobs that require IT skills, or result from the link between academic
achievement and subsequent educational attainment Educational attainment is a term commonly used by statisticans to refer to the highest degree of education an individual has completed.[1]The US Census Bureau Glossary defines educational attainment as "the highest level of education completed in terms of the and future earnings (Jencks & Phillips, 1999). Critiques of IT Not all educators and researchers are enthusiastic about the recent trend in the widespread use of IT among children and youth. Those who criticize crit·i·cize v. crit·i·cized, crit·i·ciz·ing, crit·i·ciz·es v.tr. 1. To find fault with: criticized the decision as unrealistic. See Usage Note at critique. this trend argue that research has not convincingly demonstrated that IT is effective in enhancing academic outcomes (Oppenheimer, 1997). Moreover, youth frequently use IT for recreational purposes such as playing video-games, which might increase social withdrawal among socially marginal youth, encourage impulsive im·pul·sive adj. 1. Inclined or tending to act on impulse rather than thought. 2. Motivated by or resulting from impulse. im·pul and aggressive behaviors (Lin & Lepper, 1987), or displace dis·place tr.v. dis·placed, dis·plac·ing, dis·plac·es 1. To move or shift from the usual place or position, especially to force to leave a homeland: traditional instruction in the school and academic activities in the home (such reading and completing homework) that enhance academic achievement (Colaric & Jonassen, 2001; Johnson, 2000; Lepper & Gurtner, 1989). Arguments against the widespread use of IT among children and adolescents might be especially applicable to poor youth. Although most children and adolescents use the computer primarily for recreational purposes such as playing games, E-mail, and listening to music, rather than for academic learning (Becker, 2000; Giacquinta & Lane, 1990; Kafai & Sutton, 1999), a Gallup Poll Gallup Poll Noun a sampling of the views of a representative cross section of the population, usually used to forecast voting [after G H Gallup, statistician] Gallup poll n → (1997) found that a higher percentage of low-income youth used the computer to play video games See video game console. daily, compared to their wealthier peers. Other research suggests that socioeconomically disadvantaged youth would be less likely to use IT for academically productive purposes because their parents are less able to provide educational software, computer hardware, technical assistance, and supervision, compared to wealthier parents (Attewell & Battle, 1999; Becker, 2000; Giacquinta & Lane, 1990). A similar argument has been applied to low-resource schools, to which poor and minority youth are more likely to attend. Low teacher-student ratios, outdated out·dat·ed adj. Out-of-date; old-fashioned. outdated Adjective old-fashioned or obsolete Adj. 1. technology, and teachers with few IT skills, factors that are associated with low-resource schools, would likely result in low levels of supervision and unproductive educational uses of IT (Becker, 2000; Ryan, 1991; Wenglinsky, 1998). Despite the existing disparities in IT access and use between poor and non-poor youth and the allocation The apportionment or designation of an item for a specific purpose or to a particular place. In the law of trusts, the allocation of cash dividends earned by a stock that makes up the principal of a trust for a beneficiary usually means that the dividends will be treated as of billions of federal dollars to increase IT access and use (Lonergan, 2000; Roberts, 2000), few studies have used a multivariate approach to examine the independent impact of poverty on home computer ownership and type of IT use. Such results could provide the basis for policy development focused on addressing specific and clearly identified effects of the digital divide. Recent data from a national sample of young adolescents are used to examine four specific research questions: Controlling for the youth's race/ethnicity, age, gender, and the marital status marital status, n the legal standing of a person in regard to his or her marriage state. and education of the youth's mother (1) are poor youth less likely to have access to a home computer, (2) are poor youth less likely to use their home computer for academic purposes, (3) do poor youth use any computer less often for academic purposes, and (4) do poor youth use any computer more often for non-academic purposes, compared to non-poor youth? Method Data and Sample Data were drawn from the National Longitudinal lon·gi·tu·di·nal adj. Running in the direction of the long axis of the body or any of its parts. Survey of Youth (NLSY NLSY National Longitudinal Survey of Youth (USA) ) and the NLSY mother/child data sets. The original NLSY, initiated in 1979, included 12,686 individuals between 14 and 21 years of age, including oversamples of African American, Latino, and economically disadvantaged youth. Respondents In the context of marketing research, a representative sample drawn from a larger population of people from whom information is collected and used to develop or confirm marketing strategy. were interviewed annually from 1979 through 1994, and biannually bi·an·nu·al adj. 1. Happening twice each year; semiannual. 2. Occurring every two years; biennial. bi·an thereafter. Beginning in 1986 and every two years afterwards af·ter·ward also af·ter·wards adv. At a later time; subsequently. afterwards or afterward Adverb later [Old English æfterweard] Adv. 1. , a number of assessments were administered to the original NLSY female participants and to their biological children. By 2000, the most recent data available for this analysis, 8,323 children had been born to the 4,113 interviewed female respondents (Center for Human Resource Research, 2001). Young adolescent ad·o·les·cent adj. Of, relating to, or undergoing adolescence. n. A young person who has undergone puberty but who has not reached full maturity; a teenager. children of the original NLSY female cohort cohort /co·hort/ (ko´hort) 1. in epidemiology, a group of individuals sharing a common characteristic and observed over time in the group. 2. who were interviewed in 2000 comprise the sample used in this analysis. These adolescents were 10 through 14 years of age, were attending public school, and answered at least one survey question related to computers and their use. The sample was limited to youth between the ages of 10 through 14 years because only children in this age range were evaluated with the self-administered survey that provided the computer variables for this analysis. To meet the assumption of statistical independence, only one young adolescent was selected randomly from families with more than one child. The remaining sample of 1,029 young adolescents included 288 Black, 166 Hispanic Hispanic Multiculture A person of Mexican, Puerto Rican, Cuban, Central or South American, or other Spanish culture or origin, regardless of race Social medicine Any of 17 major Latino subcultures, concentrated in California, Texas, Chicago, Miam, NY, and elsewhere , and 575 non-Hispanic, White youth (hereinafter here·in·af·ter adv. In a following part of this document, statement, or book. hereinafter Adverb Formal or law from this point on in this document, matter, or case Adv. 1. referred to as "African American," "Latino," and "white"). Measures Independent variables. Poverty was measured by comparing family income reported by the female respondent In Equity practice, the party who answers a bill or other proceeding in equity. The party against whom an appeal or motion, an application for a court order, is instituted and who is required to answer in order to protect his or her interests. during the 2000 interview (which refers to income in 1999) to 185% of the official poverty threshold The poverty threshold, or poverty line, is the minimum level of income deemed necessary to achieve an adequate standard of living. In practice, like the definition of poverty, the official or common understanding of the poverty line is significantly higher in developed for the family size measured at the interview date. If total family income for a given family size fell below 185% of the official threshold, the youth was categorized cat·e·go·rize tr.v. cat·e·go·rized, cat·e·go·riz·ing, cat·e·go·riz·es To put into a category or categories; classify. cat as poor, and as non-poor otherwise. Defining poverty as 185% of the poverty thresholds is consistent with federal government eligibility guidelines guidelines, n.pl a set of standards, criteria, or specifications to be used or followed in the performance of certain tasks. for a free or reduced-price lunch and with other studies examining the relation between low income and computer access and use (e.g., Cattagni & Westat, 2001; Wenglinsky, 1998). Other independent variables included the youth's age (10, 11, 12, 13, and 14); gender; race/ethnicity, based on the mother's racial/ethnic identification (African American; Latino; and white); mothers' marital status (married, spouse spouse A legal marriage partner as defined by state law present; all other types) and mothers" years of education (less than 12 years; 12 years; more than 12 years). The youth's age and the mother's marital status and educational attainment were measured at the 2000 interview date. Variables indicating location of residence (urban vs. rural and region of the country) initially were evaluated in the models presented in the Results section. Because none of the residence coefficients were statistically significant nor substantively affected the size or significance of other coefficients, the variables were removed from the final models. Respondents provided complete information on all the independent variables, with the exception of family income (approximately 15% of respondents had missing income information). For respondents with missing income data, poverty status was imputed Attributed vicariously. In the legal sense, the term imputed is used to describe an action, fact, or quality, the knowledge of which is charged to an individual based upon the actions of another for whom the individual is responsible rather than on the individual's using the matching procedures available in Interactive LISREL LISREL Linear Structural Relations (du Toit & du Toit, 2001). Dependent variables. The first dependent variable measured whether the youth had a home computer. Those youth who had a home computer indicated which of seven activities they used their computer for most often. Based on findings from a principal components analysis of similar items (explained in the next paragraph) an academic home computer use dichotomous di·chot·o·mous adj. 1. Divided or dividing into two parts or classifications. 2. Characterized by dichotomy. di·chot variable was formed by grouping two items indicating academic use (school or homework; learn/practice a skill such as art, music or another language) and five items indicating non-academic use (entertainment, such as games and recreation; writing letters and correspondence; references or looking things up; accessing the Internet or using E-mail; other uses). The other two dependent variables were the frequency of youth's academic and non-academic use of any computer. These variables were measured by the youth rating (0 = never to 4 = almost every day) how often they used any computer for 13 specific purposes. In order to determine whether these items could be reduced to conceptually coherent sets of variables, indicating academic and non-academic computer use, a principal components analysis was conducted (Dunteman, 1989). The analysis yielded two components. The first component indicated academic computer use (writing stories, reports, compositions, or papers; doing math, graphs, or computation Computation is a general term for any type of information processing that can be represented mathematically. This includes phenomena ranging from simple calculations to human thinking. ; doing reading or spelling; doing science problems; learning, practicing, or making music; doing art work or graphics; creating or writing computer programs; and analyzing data). For the academic use component, Cronbach's alpha Cronbach's  (alpha) has an important use as a measure of the reliability of a psychometric instrument. It was first named as alpha by Cronbach (1951), as he had intended to continue with further instruments. = .84; lowest factor loading = .50. The second
component indicated non-academic computer use (writing letters; looking
up things or using references; playing games; reading or sending E-mail;
and accessing the Internet or other on-line networks or services). Alpha
= .75; lowest factor loading = .52. Additive additiveIn foods, any of various chemical substances added to produce desirable effects. Additives include such substances as artificial or natural colourings and flavourings; stabilizers, emulsifiers, and thickeners; preservatives and humectants (moisture-retainers); and scales were created to measure the frequency of academic and non-academic computer use (scores ranged from 0 to 20 for academic use, and from 0 to 18 for non-academic use). Data Analysis Data analysis was conducted in two steps. First, weighted descriptive statistics descriptive statistics see statistics. for the study sample and dependent variables were computed. Second, multivariate models for the dichotomous variables (home computer ownership and home computer academic use) were estimated using logistic regression In statistics, logistic regression is a regression model for binomially distributed response/dependent variables. It is useful for modeling the probability of an event occurring as a function of other factors. , the preferred analysis of binary Meaning two. The principle behind digital computers. All input to the computer is converted into binary numbers made up of the two digits 0 and 1 (bits). For example, when you press the "A" key on your keyboard, the keyboard circuit generates and transfers the number 01000001 to the dependent variables (Allison, 1999). Multivariate logistic regression allows for examining the effect that each independent variable contributes to the log odds that the respondent had a home computer (versus no home computer) and used the home computer most often for academic purposes (versus non-academic purposes), while adjusting for the effects of the other independent variables. Multivariate (Ordinary Least Squares) regression regression, in psychology: see defense mechanism. regression In statistics, a process for determining a line or curve that best represents the general trend of a data set. models were estimated for the frequency of academic and non-academic computer use. As recommended by the Center for Human Resource Research (2001), the regression analyses were conducted using unweighted data. The race/ ethnicity ethnicity Vox populi Racial status–ie, African American, Asian, Caucasian, Hispanic variables controlled for the oversamples of minority respondents included in the NLSY. Results Weighted means and standard deviations In statistics, the average amount a number varies from the average number in a series of numbers. (statistics) standard deviation - (SD) A measure of the range of values in a set of numbers. or percentages for the study sample and variables are presented in Table 1. Although more than 87% of non-poor youth had a home computer, only 55.89% of poor youth had a computer. Among the 710 youths who had access to a home computer and answered the item related to computer use, only 26 (3.32%) reported that they did not use their home computer. There were no significant differences in using versus not using their home computer between poor and non-poor youth, [chi square chi square (kī), n a nonparametric statistic used with discrete data in the form of frequency count (nominal data) or percentages or proportions that can be reduced to frequencies. ](1, N = 710) = .075, p = .784. Table 1 also indicates large differences in computer ownership between white (84.13 %) and African American (51.76%) and Latino (59.16%) youth. A relatively low percentage of youth (19.63%) reported using their home computer most for academic purposes, a percentage that is similar for poor (22.33%) and non-poor (23.16%) youth. A larger percentage of African Americans (33.02%) and Latinos (30.67%), however, reported using their home computer for academic use, compared to whites (21.51%). Youth also reported using any computer more frequently for non-academic (M = 8.88) versus academic uses (M = 5.86). Means for frequency of academic computer use are almost identical for poor and non-poor youth, but poor youth reported using any computer less often for non-academic purposes (M = 7.83) than did non-poor youth (M = 9.30). As compared to whites, African Americans and Latinos reported using any computer more often for academic purposes and less often for non-academic purposes. Results of the multivariate logit analysis of poverty and other factors associated with home computer ownership and youth academic use of their home computer appear in Table 2. Controlling for the effects of all other variables in the model, the odds ratio for poverty indicates that poor young adolescents were .36 times as likely to have a home computer as non-poor youth. African American (odds ratio = .28) and Latino (odds ratio = .37) youth also were less likely to have a home computer compared with white youth. Results of the second multivariate logit model indicate that poor youth were about equally as likely to report using their home computer most often for academic purposes as were non-poor youth. African Americans (odds ratio = 1.78) and Latinos (odds ratio = 1.88) also were more likely to report using their home computer most often for academic purposes compared to whites. Table 3 presents the results of the multivariate (OLS OLS Ordinary Least Squares OLS Online Library System OLS Ottawa Linux Symposium OLS Operation Lifeline Sudan OLS Operational Linescan System OLS Online Service OLS Organizational Leadership and Supervision OLS On Line Support OLS Online System ) regression analyses of poverty and other factors associated with the time young adolescents spent on academic and non-academic uses of any computer. Poor youth did not significantly differ in the frequency of their computer use for academic purposes compared with non-poor youth, but poor youth reported using a computer significantly less often for non-academic purposes (b = -.96, p < .05). African Americans (b = 2.24, p < .001) and Latinos (b = .85, p < .10) reported using a computer more frequently than whites for academic purposes and less frequently for nonacademic purposes (b = -1.15, p < .01, for African Americans; b = -1.23, p < .01, for Latinos). Absence of a statistically significant difference in frequency of academic computer use between poor and non-poor youth, as well as the negative relation between poverty and frequency of non-academic use, might result from poor youth's more restricted access to computers. Since poor youth are less likely to have access to a home computer, they must use computers in schools or in other community locations where their computer use probably would be more restricted and monitored. If poor youth did have comparable access to a home computer as do non-poor youth, they might use computers for academic purposes less frequently and perhaps use computers for non-academic purposes more frequently than non-poor youth. In order to test this possibility, two additional variables were entered into the regression models. The first measured whether the youth had and used a home computer (versus did not have or did not use an available home computer). In both models, coefficients for this variable were positive and significant, indicating that youth who had and used a home computer used a computer more frequently for both academic (b = 1.02, p < .05) and non-academic (b = 2.98, p < .001) uses, compared to youth who did not have or did not use an available home computer. In addition, the coefficient coefficient /co·ef·fi·cient/ (ko?ah-fish´int) 1. an expression of the change or effect produced by variation in certain factors, or of the ratio between two different quantities. 2. for the poverty variable in the non-academic computer use model was no longer significant, suggesting that differences in the frequency of non-academic use between poor and non-poor youth were due to differences in the use of a home computer. When the home use variable was entered into the regression model, African Americans (b = 2.58, p < .001) and Latinos (b = 1.12, p < .05) were still more likely to report using any computer for academic purposes, compared to whites. The race/ethnicity coefficients were not statistically significant in the non-academic use model. The second variable, an interaction between poverty status and the previously defined home computer variable, tested whether poor youth who used a home computer used any computer more frequently for academic or non-academic purposes than did non-poor youth. The interaction term was not statistically significant in either model, indicating that poor youth who use a home computer do not differ from non-poor youth in the time they spend on academic or non-academic computer uses. Conclusions and Discussion The objectives of this study were to examine disparities in home computer ownership and in academic and non-academic uses of computers between poor and non-poor youth, using data from a national sample of young adolescents between the ages of 10 through 14 years. Study findings indicate that poor youth were .36 times as likely to have a home computer compared to non-poor youth. Indeed, there is a "digital divide" between poor and non-poor young adolescents in home computer access that is independent of any effects of the youth's age, gender, race/ethnicity, and the marital status and education of the youth's mother. However, when a home computer was present, poor youth were just as likely to use the home computer for academic purposes as were non-poor youth. A failure to find a significant interaction between poverty and use of an available home computer and type of computer use adds to the validity of this finding. Whether home computer use or type of IT use translates into better academic outcomes for children and adolescents, however, has not been adequately studied (Lauman, 2000) and is an area for future research. On the other hand, research has produced little evidence that home computer use results in socioemotional problems for youth or displaces more academically beneficial activities such as reading or completing homework (for a review of this literature, see Subrahmanyam, Greenfield Greenfield, town (1990 pop. 18,666), seat of Franklin co., NW Mass., at the confluence of the Deerfield and Green rivers, near their junction with the Connecticut; settled 1686, set off from Deerfield and inc. 1753. , Kraut kraut n. 1. Sauerkraut. 2. often Kraut Offensive Slang Used as a disparaging term for a German. [German; see sauerkraut.] Noun 1. , & Gross, 2001). This research, in conjunction with the findings of the current study, suggests that increasing poor youth's access to home computers will not cause harm, but might allow these youth to accrue To increase; to augment; to come to by way of increase; to be added as an increase, profit, or damage. Acquired; falling due; made or executed; matured; occurred; received; vested; was created; was incurred. a variety of social, employment, and possible academic benefits (NTIA, 2000; Lonergan, 2000). The findings of the current study indicating that poor youth do not use any computer for academic purposes less often than do non-poor youth, regardless of whether they have a home computer, are consistent with the finding for the use of a home computer. These results suggest that increasing poor youth's access to computers in the community most likely will result in poor youth using IT for academic purposes as often as their wealthier peers. Although poverty was associated with using any computer less frequently for non-academic use, this relation appears to be the result of poor youth being less likely to own home computers. If increasing access to home computers resulted in poor youth using the computer more often for non-academic purposes than they currently do, some research suggests that even non-academic uses of computers might have educational benefits. For example, recreational games can encourage and develop the use of complex cognitive processes Cognitive processes Thought processes (i.e., reasoning, perception, judgment, memory). Mentioned in: Psychosocial Disorders , which might transfer to academic situations that require problem-solving abilities (Pillay, Brownlee, & Wilss, 1999). Although not the main focus of this study, the racial/ethnic differences found in IT access and use are noteworthy. Differences in home computer access between whites and African Americans and Latinos have been established by past studies (NTIA, 2002; Wenglinsky, 1998), and these differences remain in this study even after controlling for poverty and other demographic factors (e.g., mother's marital status and educational level). These racial/ethnic disparities in computer ownership might be explained by variations in the depth of poverty or in attitudes toward the benefits of computer ownership between whites and African Americans and Latinos. Future research is needed to explore these results and also to explore the findings that African American and Latino youth use IT for academic purposes more than whites. Perhaps African American and Latino parents are more likely to monitor and restrict their young adolescents' home computer use. The current findings indicate that if increasing IT access and use result in better academic outcomes and job opportunities, these benefits would be particularly important for African Americans and Latinos. This study has a number of limitations. Among the most important is the reliance on young adolescents' self-reports of computer access and use, which might not be reliable. The restricted age range of the youth limits the generalizability of the study findings. If additional information on IT access and use were available in the NLSY (e.g., presence of an Internet connection or educational software in the home), this information could have contributed to better understanding differences in IT access and use between poor and non-poor youth. Despite these limitations, two main policy implications can be drawn from the findings of this study. First, the federal government should continue efforts to achieve its stated "vitally important national goal" of increasing the number of Americans who use IT (NTIA, 2002) by continuing programs (e.g., the Education-rate and Community Technology Centers Program) to assist low-resource communities and schools in increasing access, use, and quality of IT applications (Roberts, 2000). Largely due to such efforts, progress has been made in decreasing, and even eliminating, disparities between poor and non-poor and minority and white youth in IT access and use in public schools (U. S. Department of Education, 2002; NTIA, 2002). Current programs should be continued and expanded to include assisting low-income families to purchase home computers (e.g., through a tax credit), and increasing research funds to understand and ameliorate a·mel·io·rate tr. & intr.v. a·me·lio·rat·ed, a·me·lio·rat·ing, a·me·lio·rates To make or become better; improve. See Synonyms at improve. [Alteration of meliorate. factors that block access to home computer ownership among ethnic minority youth. Unfortunately, the current administration's budget proposal for 2003 (Executive Office of the President of the United States The Executive Office of the President (EOP) consists of the immediate staff of the President of the United States, as well as multiple levels of support staff reporting to the President. , 2002) calls for eliminating such programs. One of the most important of these is the Community Technology Centers Program, which provides grants to economically distressed areas to assist residents in gaining access to IT in community locations such as libraries and public housing facilities (Roberts, 2000). Second, if government officials and the general public consider access to IT important to the education, future job opportunities, and social and civic participation of our nation's youth, this study indicates that establishing eligibility guidelines for obtaining relevant government assistance at even 185% of official poverty thresholds might be too low. Since poverty thresholds were established in 1965, debates have continued regarding adequate measures of economic hardship. Many researchers contend that at least one poverty measure should reflect the economic resources necessary to participate in the "activities of normal living" (Glennerster, 2002). Not only should federal policies continue to assist IT "have-nots" in obtaining access to computer technologies, but must ensure realistic eligibility guidelines for obtaining such assistance.
Table 1
Weighted Means (Standard Deviations) or Percentages for the Study
Sample and Variables (N = 1,029) (a)
Dependent Variables
Academic
Home Home
Study Computer Computer
Variable Sample Ownership Use
Independent variables
Poverty (less than 185%
of official threshold)
Poor 29.57% 55.89% 22.33%
Non-poor 70.43 87.18 23.16
Youth/Mother Characteristics
Youth age (years)
Ten 21.15% 76.32% 18.81%
Eleven 20.51 80.84 22.28
Twelve 22.71 77.05 23.28
Thirteen 22.75 77.95 24.19
Fourteen 12.88 77.36 28.15
Youth gender
Female 47.36% 76.30% 23.07%
Male 52.64 79.37 22.90
Youth race/ ethnicity
African American 14.21% 51.76% 33.02%
Latino 6.66 59.16 30.67
White 79.13 84.13 21.51
Mothers' marital status
Married, spouse present 69.43% 84.73% 21.82%
All other types 30.57 62.46 26.79
Mothers' years of education
Less than 12 years 13.42% 54.19% 30.70%
12 years 39.21% 70.37% 23.49%
More than 12 years 47.37 90.89 21.43
Dependent Variables
Home computer ownership
(n = 1,002)
Yes 77.92%
No 22.08
Academic home computer use
(n = 690)
Yes 19.63%
No 80.37
Frequency academic computer
use (n = 894) 5.86
(4.99)
Frequency non-academic
computer use (n = 894) 8.88
(4.86)
Dependent Variables
Frequency
Frequency Non-
Academic Academic
Computer Computer
Variable Use Use
Independent variables
Poverty (less than 185%
of official threshold)
Poor 5.90 7.83
(5.08) (4.79)
Non-poor 5.85 9.30
(4.94) (4.83)
Youth/Mother Characteristics
Youth age (years)
Ten 5.58 7.58
(5.16) (4.58)
Eleven 5.66 8.29
(5.20) (4.76)
Twelve 5.96 8.86
(4.75) (4.99)
Thirteen 5.76 9.96
(4.89) (4.83)
Fourteen 6.60 9.93
(4.85) (4.66)
Youth gender
Female 5.97 8.79
(4.90) (4.98)
Male 5.76 8.96
(5.06) (4.75)
Youth race/ ethnicity
African American 7.75 7.69
(6.30) (4.94)
Latino 6.45 7.50
(5.46) (4.63)
White 5.50 9.19
(4.61) (4.82)
Mothers' marital status
Married, spouse present 5.77 9.25
(4.85) (4.78)
All other types 6.08 7.98
(5.28) (4.95)
Mothers' years of education
Less than 12 years 6.65 7.96
(5.16) (5.01)
12 years 6.00 8.62
(5.22) (4.96)
More than 12 years 5.54 9.33
(4.70) (4.69)
Notes: Weights adjust for oversamples of African American and
Latino youth.
(a) Sample size is unweighted and varies depending on the number
of responses on the dependent variable.
Table 2
Multivariate Logit Analyses of the Effect of Poverty and Other Factors
on Home Computer Ownership (N = 1,022) and Academic Home
Computer Use (N = 690) Among Young Adolescents
Home Computer Academic Home
Ownership Computer Use
Logit Odds Logit Odds
Variable Coefficient Ratio Coefficient Ratio
Poor (non-poor) -1.03 *** .36 -.13 .88
Youth age (14 years)
Ten -.34 .71 -.42 .66
Eleven .03 1.03 -.22 .80
Twelve -.20 .82 -.25 .78
Thirteen -.22 .81 -.20 .82
Youth male .15 1.16 -.20 .82
Youth race/ethnicity (white)
African American -1.27 *** .28 .58 * 1.78
Latino -1.00 *** .37 .63 * 1.88
Mother married, spouse .34 1.41 -.09 .91
present (other types) ([dagger])
Mothers' years of education
(more than 12 years)
12 years -1.20 *** .30 .08 1.09
Less than 12 years -1.48 *** .23 .06 1.06
Notes: Reference categories are in parenthesis.
([dagger]) p < .10; * p < .05; ** p <. 01; *** p <.001
Table 3
Multivariate Regression Analyses of the Effect of Poverty and
Other Factors on Frequency of Young Adolescent Academic and
Non-Academic Computer Use (N = 894)
Frequency Frequency
Academic Non-academic
Computer Use Computer Use
Variable b b
Poor (non-poor) -.12 -.96 *
Youth age (14 years)
Ten -.91 -2.26 ***
Eleven -.92 -1.85 ***
Twelve -.42 -.83
Thirteen -.79 -.04
Youth male .05 .24
Youth race/ethnicity (white)
African American 2.24 *** -1.15 **
Latino .85 ([dagger]) -1.23 **
Mother married, spouse present .41 .27
(other types of marital status)
Mothers' years of education (more
than 12 years)
12 years .67 -.62 ([dagger])
Less than 12 years 1.11 * -.77
Notes: Reference categories are in parenthesis.
([dagger]) p < .10 * p < .05; ** p < .01; *** p < .001
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