First Monday

Digital inequalities: Homework gap and techno-capital in Austin, Texas by Melissa Santillana, Joe Straubhaar, Alexis Schrubbe, Jaewon Choi, and Sharon Strover



Abstract
The homework gap is a term that has come to describe the 15 percent or more of American children who cannot complete their homework after the school day ends because they lack access to broadband and computers (Anderson and Perrin, 2018). This statistic encompasses different economic, socio-cultural, and geographic factors. As a result, historically underprivileged groups of children are overrepresented in the homework gap space. Children without access to high-speed Internet or computers at home face challenges in school achievement. This study investigates the cultural, social, and technological aspects that contribute to the homework gap. The results are based on data from a survey conducted in collaboration with the city of Austin, Texas and several non-profit organizations that offer Internet and technology services to disadvantaged communities. The goal of this study is to investigate the role that demographics, technological skills, and attitudes toward technology play in the homework gap. We find that education and income levels are negatively correlated with high levels of homework gap, while age is positively correlated. Moreover, the possession of intermediate levels of techno-capital is inversely correlated to parents and caregivers’ perceptions of the homework gap.

Contents

Introduction
Literature review
Research questions
Methods
Results
Discussion, theoretical, and policy implications

 


 

Introduction

The homework gap is a term that has come to describe the 15 percent or more of American children who cannot complete their homework after the school day ends because they lack access to broadband and computers (Anderson and Perrin, 2018). This statistic encompasses different economic, socio-cultural, and geographic factors. As a result, historically underprivileged groups of children are overrepresented in the homework gap space. The gap represents a severe challenge for children experiencing lack of access to high-speed Internet and computers. In 2009 the U.S. Federal Communication Commission’s Broadband Task Force reported that about 70 percent of teachers in the United States assign homework that requires access to the Internet (McLaughlin, 2016). Children without broadband or computers at home face challenges in school achievement because the majority of schools in the U.S. are dependent on digital platforms to deliver communication, distribute grades, and handle homework, tests, and other school tasks.

This study investigates the cultural, social, and technological aspects that contribute to the homework gap. The results are based on data from a survey conducted in collaboration with the city of Austin, Texas and several non-profit organizations that offer Internet and technology services to disadvantaged communities. For the past eight years the city of Austin has experienced a tech boom, with companies like Apple, Amazon, Facebook, and Google opening offices in the capital of Texas. With the increasing amount of tech companies moving their operations, Austin has been nicknamed ‘Silicon Hills’ (Bloom, 2019). Conversely, problems such as longtime residents being displaced due to high rent rates, and a growing homeless population are on the rise (Pimentel, 2019). These factors contribute to the homework gap. The goal of this study is to investigate the role that demographics, technological skills, and attitudes toward technology play in the homework gap.

 

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Literature review

Universal service public policy in the form of educational “e-rate” funding has contributed to the adoption of network technology into school systems. In districts with high poverty and also in districts facing under-connection because of rurality, the e-rate has been critical in driving the diffusion of computers and Internet throughout schools (Goolsbee and Guryan, 2006; Jayakar, 2004; Park, et al., 2007). In addition, digital school materials present advantages to school districts, and the convenience built into digital systems have also aided broad adoption. Digital materials are adaptable to change and can respond to developments in scholarship but also to demands created by the educational market. They also save time and money, replacing single-use materials like notebooks and worksheets with easy-to-grade online interfaces (Schachter, 2009; Trotter, 2007). Pearson Education, the largest education corporation in the world, recently announced it will switch production to 100 percent digital school materials (McKenzie, 2007). Another driver of technology into the classroom is educational public policy such as common core or state level educational goals incorporating benchmarks for student proficiency in digital literacies (Bebell, et al., 2014; Ditzler, et al., 2016; Gurung and Rutledge, 2014). The adoption of digital materials and the related turn to assign reading and writing that requires computer and Internet access is challenging for many low-income families.

The homework gap exists within the context of the digital divide. The first level of that divide, the most obvious, refers to at least the lack of access to the Internet (U.S. National Telecommunications and Information Administration (NTIA), 1995). Early digital divide scholarship focused on physical access to technology, or first-level digital divides, classified by linguistic, economic, educational, social, and geographic factors that were crisscrossed in scholarly examinations by categories of age, gender, and ethnicity (Attewell, 2001; Bucy, 2000; Hargittai, 2002; Hoffman, et al., 2001; Katz and Rice, 2002; Norris, 2001; Strover, 2000). Understanding first-level access barriers was the locus of early energy by activists, policy-makers, and educators, and as this study will show is still a major issue. As recently as 2018, race, age, rural living, income, and education were still predictors for whether or not an American has Internet access at home, and gender and age are predictor variables for whether or not people utilize the Internet (Straubhaar, et al., 2019; Talukdar and Gauri, 2011; Campos-Castillo, 2015). With regard to Internet service penetration and speed of service, America lags behind other developed countries. Americans experience Internet that is not only slower but more expensive than Internet in other nations of the global north (Russo, et al., 2014). The Pew Research Center reports that 89 percent of American adults use the Internet, but that only 65 percent of them have home broadband (Pew Research Center, 2019a). In major urban centers like Austin, Texas there are few regulatory protections for low income residents, so Internet access is splintered between the whole of a city and its clusters of low income neighborhoods (Straubhaar, et al., 2019).

American children disproportionately live in poverty, and at the time of the 2010 census, children made up 24 percent of the population, but 36 percent lived in poverty. Poverty is related to the homework gap because clusters of poverty intersect with persistent barriers to other critical services and infrastructures like health care, communications services, and quality schools (Miller and Weber, 2003; Strange, et al., 2012) Poverty rates also have historical and strong relationships that intersect with race and ethnicity, and at the time of the 2010 census, 27.4 percent of blacks and 26.6 percent of Hispanics were poor, compared to 9.9 percent of non-Hispanic Whites and 12.1 percent of Asians.

Broadband access at home is a particular issue, since many lower income and minority populations depend on smartphones to go online. The study highlights a modern perspective of first level divides because cell phone adoption is widespread, and many families depend on smartphone as their only point of access (Pew Research Center, 2019b). Cell phone dependence creates its own divide, since many aspects of homework cannot be done with a smartphone. Home broadband subscriptions have dropped from a peak 75 percent of households in 2015 to 65 percent in 2018. Concurrently, the number of people relying solely on smartphones as an Internet connection has grown (Horrigan and Duggan, 2015).

Another aspect of the digital divide and related to the homework gap concerns the role of skills, meaningful, and intended use of the Internet, and further, which populations faced challenges developing these skills (Hargittai, 2002; Hargittai and Walejko, 2008). Jung, et al. (2001), and van Dijk and van Deursen (2011) construct empirical frameworks to investigate the homework gap which considers skills, intended and meaningful use, and places them into the context of social and economic conditions of households.

Digital or computer literacy is a foundational component of meaningful use that describes the breadth and depth with which an individual can engage with digital materials (Livingstone, 2007, 2004; Livingstone and Helsper, 2009). Building on skills and meaningful use narratives, some scholars link Internet use to Bourdieu’s (1990) theories of habitus and multiple capitals, suggesting that individuals’ dispositions toward technology are influenced by the social milieu of their lived reality (Brock, et al., 2010; Kvasny, 2006; Robinson, 2011, 2009; Rojas, et al., 2012; Schradie, 2012; Tufecki and Wilson, 2012).

Building on literatures of Bourdieu’s theory of capital, digital literacy, field, and participatory culture, are the forms of technological capabilities that constitute individuals’ ‘techno-capital’, or digital capital (Rojas, et al., 2012; Ignatow and Robinson, 2017). Bourdieu (1984) developed three different types of capital: economic capital or assets, social capital or useful social networks, and cultural capital, that is learned from school and family. All are assets that can be acquired, learned or developed in specific fields of competition for resources or positions of power (Bourdieu, 1984). Over the years, scholars have also applied the core concept of capital to identify and theorized technological (Emmison and Frow, 1998; Rojas, et al., 2003; Sterne, 2003) or digital capitals (Ignatow and Robinson, 2017). All these capitals are related and can be converted, like wealth can buy education, and education as cultural capital can be convertible into wealth by enabling access to better jobs. For Bourdieu, ‘actors’ positions within various social fields correspond with the volumes of the different forms of capital they possess (Ignatow and Robinson, 2017).

Cultural capital is a major part of what we think of as social class or status, but is specifically related to cultural knowledge, consumption preferences and tastes passed down by an individual’s parents together with their own education and continued learning (Bourdieu, 1984). Without a base of cultural capital, it is hard to acquire advanced knowledge and skills in digital technology (Tufekcioglu, 1999). Both middle and upper class families and high-quality schooling tend to pass on digital access and skills as part of a child’s overall formation of cultural capital. While working class or poor children tend to receive less access and less skill, as well as the time, support, and conditions to develop an attitude of serious play that enable greater technological learning (Robinson, 2009). Some have seen information technology as a form of cultural capital (Emmison and Frow, 1998), or more specific alternatives, such as informational capital (van Dijk, 2005).

People and groups engage in a constant competition within the fields that they occupy. Those can be fields of work, like getting a job in the tech sector, or more intermediate fields, like the field of education in general, or learning about technology in specific. Habitus and disposition may serve or hinder players in navigating various fields, as in Robinson’s (2009) study of youth in school and their learning about digital technology. We are particularly interested in this study in the relationships of economic capital (income), cultural capital (in terms of education), technological or techno- capital (in terms of digital technology skills, knowledge and capabilities) and in the relationship of all of them with concerns by parents or guardians with the homework gap faced by their children or grandchildren.

 

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Research questions

1. What proportion of parents and caretakers feel that their children do not have good enough access to the Internet and computers to complete homework in a city where the percentage of homes with broadband is over 90 percent?

1.a. Are there differences between perceptions of problems with access to the Internet and with computers to complete homework? If so, why?

1.b. What are the descriptive characteristics of parents who experience the homework gap? Do income, education, race/ethnicity, cultural capital, and techno-capital all have a relationship with families presently experiencing the homework gap? Are some characteristics more significant than others?

1.c. Are there any demographic factors besides income level that directly influence parents and care-takers perceptions of the ability of their children to finish their homework because of lack of access to the Internet or computers?

1.d. Are there any attitudes toward technology, such as their perceptions of their own ability to help their children with technology, that directly influence parents and care-takers feelings about the ability of the children under their care being able to finish their homework because of lack of access to the Internet?

 

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Methods

This study consists of a mailed survey to a random sample of 12,000 households in Austin, Texas. In order to capture disadvantaged populations that do not usually respond to mailed surveys we purposefully directed 3,000 surveys to residential addresses within the most underprivileged zip codes in the Austin area and some extraterritorial jurisdictions on the east side of Austin. The purpose of this survey was to examine the relationship between homework gap, cultural, economic, and techno capital, as well as other demographic variables. The research team used the Dillman method (Dillman, 1978) by first mailing a postcard notifying residents about the study and about a subsequent mail containing the survey, this first contact was conducted in March 2018. The letter included information about the study, a paper version of the survey, and an online link for completing the survey online. Every participant was given the option of entering into a raffle for three Dell tablets as an incentive for their participation. The response rate of 8.31 percent was determined to be acceptable, if lower than desired (Holbrook, et al., 2007) for the 997 surveys included in the study. Surveys that were left incomplete or answered by residents outside the Austin city boundaries, plus four selected zip codes to its east, [1] were discarded.

Nine questionnaire items were formulated to find out to which degree parents or grandparents, or other full-time caregivers felt that the children under their care could successfully complete their school assignments. Out of the 997 participants in the sample, 36 percent (n = 358) reported having children under their care. For the purposes of this study, the information presented here was compiled with information only from those participants. The homework items asked participants to rank their level of agreement to different statements regarding their children or grandchildren’s access to the Internet, computers, technical skills, and ability to complete their homework (See Table 1). Key indicators about techno-capital are the respondents’ education, and their level of agreement to “I know enough to guide my child or grandchildren in setting their educational goals,” and “I know enough to guide my children or grandchildren in setting their career or work goals and plans.”

 

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Results

Demographic characteristics, adoption rates, and places of access

In order to assess Internet use and device ownership, the survey asked participants to indicate whether they have an Internet connection at home, and the type of devices typically used to access the Internet they own. Table 1 shows a demographic breakdown and adoption rates. Respondents with less than high school had the lowest percentage of home Internet connection (86 percent), the same was true for those age 65 and above (55 percent), respondents with a less than $US10K income (61 percent) and African Americans (89 percent). For comparison, the average percentage for the whole city was 95 percent.

When it comes to desktop computer ownership, female respondents reported a lower percentage of ownership (35 percent) as compared to male respondents (58 percent). Likewise, people with less than high school (38 percent), or high school education (30 percent), and people age 25–34 (14 percent) also reported low ownership numbers. Desktop computer ownership was also low for people in the less than $US10K income category, and those making from $US10K to $US49,999. In general, electronic device ownership was lower for female respondents, those in 65 and above age category, respondents with less than high school or high school education, lower income, and African Americans.

Cellphone ownership was almost 100 percent for all demographic categories, except for those age 65 and above (84 percent) and those making less than $US10K (71 percent). Similarly, smartphone ownership is even lower for those in the older age categories, and low income. Yet, it is important to note that online activities are limited depending on the device. Desktop and laptop computers allow users to access the Internet to complete work-related tasks and more complex homework assignments. Moreover, studies have indicated there is a relationship between having a home computer and higher high school graduation rates (Fairlie, et al., 2010).

 

Table 1: Demographic characteristics and adoption rates.
Note: Percentage, n = 358.
 Home Internet connectionDesktop computer ownershipLaptop ownershipTablet ownershipCellphone ownershipSmartphone ownership
GenderMale9558637610098
Female9435636510094
EducationLess than high school863819639593
High school9830624710094
Some college8754798610097
College10056917310098
Postgraduate/ professional degree10059938710097
Age18–241001001000100100
25–3497144579100100
35–4498417156100100
45–549782719410098
55–649460827310087
65 and above554135378469
Income ($US)Less than $10K611222127170
$10K–$19,9999523941100100
$20K–$29,9991001212100 100100
$30K–$39,99961112850 10061
$40K–$49,999100237377100100
$50K–$74,9999189627010098
$75K and over9859948610097
Race/EthnicityWhite (non-Hispanic)935468729894
Hispanic9441447710095
African American89274325100100
Asian100659595100100
Other978249510097

 

Table 2 shows a demographic breakdown and the sites respondents indicated to use daily or several times a week as sites for accessing the Internet. Most relevant for this study are those using public places and public libraries for frequent Internet access. Specifically, because they include those seen as a free and accessible place for their children to do homework. Respondents who have less than high school (19 percent), age 45–54 (27 percent), less than $US10K (39 percent), Hispanics (17 percent) and African Americans (23 percent) reported accessing the Internet at public places at higher rates than other demographic groups. On the other hand, respondents with high school education (15 percent), those making less than $US10K (41 percent), and African Americans (16 percent) reported to use a public library as frequent sites for accessing the Internet.

 

Table 2: Frequently used sites for access by gender, education, age, income, and race.
Notes: Percentage, n = 358; * Percentage of access several times a week or daily.
 At homeAt workRetail placesPublic placesPublic library
GenderMale776726130
Female866113135
EducationLess than high school613819190
High school7546231515
Some college82796100
College97752770
Postgraduate/ professional degree1009219102
Age18–241000000
25–34614617127
35–4495611580
45–54959436271
55–6483861370
65 and above4520770
Income ($US)Less than $10K221203941
$10K–$19,999952020
$20K–$29,999126030
$30K–$39,999531912180
$40K–$49,99977811990
$50K–$74,999898039270
$75K and over949535101
Race/EthnicityWhite (non-Hispanic)917122140
Hispanic765017170
African American6138162316
Asian9222330
Other2422330

 

Homework gap

Table 3 shows the percentages of the participants who “Strongly Agree” or “Agree” with the following statements: (1) I feel that my children or grandchildren cannot complete their homework because they do not have Internet access; (2) I feel that my children or grandchildren cannot complete their homework because they do not have access to computers; (3) I feel that my computer skills are good enough to help my children or grandchildren complete their homework; (4) My children or grandchildren have good enough computer skills to complete their homework on their own; (5) My children or grandchildren are learning computer skills at school that will prepare them for the future; (6) My children or grandchildren access the Internet at a public or school library; (7) My children or grandchildren can safely access public libraries; (8) I know enough to guide my child or grandchildren in setting their educational goals; and, (9) I know enough to guide my children or grandchildren in setting their career or work goals and plans.

The responses indicate that 12 percent of participants feel that their children or grandchildren cannot complete their homework because they do not have access to the Internet. While 20 percent feel their children or grandchildren cannot complete their homework for lack of a computer, significantly higher than the number concerned about lack of Internet access. This answers research question 1a, which asked whether Internet or computer access would be seen as a bigger problem for their children by parents/guardians. This fits with the fact that many lower income and minority families are dependent on smartphones for all their Internet access, which became clear in the larger citywide survey from which this study is taken (Straubhaar, et al., 2019). Smartphones as a device do not necessarily have some of the key affordances required for homework, such as writing papers, reading texts, taking online tests, and interacting with Web sites (Orr, 2010).

Moreover, 50 percent say that their children or grandchildren access the Internet at a public or school library. This is interesting because libraries supply both connectivity and computer access needs, both important as noted above. An ethnographic study underway by some of the authors in Austin indicates that for the last several years, some children come to the library with their own devices to use free WiFi (and in some cases, charge up their devices) but that many also come to use the computers for tasks such as writing papers, to do math assignments, and to take tests. Most also seem to feel that their children are learning important computer skills at school, which address the second and third levels of digital divide issues of knowledge and skills, not just access per se.

The question of skills, as raised in the literature review, is also very important, once children and their parents/guardians get access to connectivity and devices. A number of parents (22 percent) felt that their children did not have the computer skills to complete their homework. Somewhat fewer (16 percent) worried that their children were not learning the computer skills they need at school. A slightly larger number (24 percent) felt their own computer skills were not good enough to help their children. Table 3 also shows how respondents feel about having the necessary computer skills to help the children under their care with homework, and how prepared they feel to guide them and help them set goals for the future.

 

Table 3: Homework, access, and computer skills.
Note: * Percentage of n over total N = 358.
Homework itemsPercentage*n
Feel that their children or grandchildren cannot complete their homework because they do not have Internet access1242
Feel that their children or grandchildren cannot complete their homework because they do not have access to computers2071
Say that their children or grandchildren access the Internet at a public library or school library50178
Feel that their children’s or grandchildren’s computer skills are not good enough to complete their homework2236
Feel that their computer skills are not good enough to help their children or grandchildren complete their homework2484
Don’t feel that their children or grandchildren are learning computer skills at school that will prepare them for the future1863
Feel that their children or grandchildren cannot safely access public libraries1656
Don’t feel they know enough to guide their children or grandchildren in setting their educational goals1552
Don’t feel they know enough to guide their children or grandchildren in setting their career or work plans and goals2381

 

Likewise, Figure 1 shows respondents who “Strongly Agree” or “Agree” with the statements about computer skills divided by race and ethnicity. The figure shows that Hispanics (48 percent) and African American respondents (53 percent) reported the lowest percentages towards feeling that their children or grandchildren have computer skills good enough to complete their homework, compared to Whites (65 percent) or Asians (59 percent). In contrast, Hispanics (68 percent) and African Americans (72 percent) also reported the highest percentages towards feeling that their children or grandchildren are learning computer skills at school that will prepare them for the future, which may indicate that they are relying more on schools to teach those skills.

 

Homework skills by race and ethnicity
 
Figure 1: Homework skills by race and ethnicity.
 

 

Figure 2 focuses on questions about access to the Internet in public libraries and public schools and respondents’ feelings about having enough skills to guide the children under their care to set career goals and educational paths. In that regard, African American and Asian respondents reported that their children or grandchildren access the Internet at public schools and libraries at a higher rate than White and Hispanic respondents. However, White and Asian respondents reported that their children or grandchildren can safely access public libraries at higher rates than Hispanics and African Americans.

Returning to the question of skills raised above, Whites and Hispanics were more likely to report that they learn computer and Internet skills from family members than African Americans and Asians. Additionally, White and Asian respondents were also more likely to agree that they feel they know enough to help guide their children or grandchildren in setting educational goals and career paths.

 

Homework, access, and skills by race
 
Figure 2: Homework, access, and skills by race.
 

 

Homework gap, cultural, economic, and techno-capital

Like race, income levels also have a significant relationship with the homework gap related items. Respondents who reported making less than $US10K in 2017 were more prone to “Strongly Agree” or “Agree” that they feel their children or grandchildren cannot complete their homework because they do not have access to the Internet. An analysis of variance (ANOVA) [2] was conducted to further examine the factors at play describing the homework gap in Austin. The analysis only considered respondents who indicated having children under their care (n = 358). The analysis considers how variables in four separate questions differed according to the income level of respondents. The questions asked whether respondents who are full time caretakers of children if they feel their children cannot finish their homework because of: 1) lack of access to the Internet; 2) lack of access to computers; 3) lack of computer skills to help their children/grandchildren; and, 4) whether their children/grandchildren had enough skills to complete their homework on their own. (This test only examined responses from those who are parents or guardians of school-age children.) The results show significant variances among different income levels for all homework gap items examined [3]. Figure 3 plot the mean scores of the two main questions for different income levels.

 

Mean plot of homework access and income
 
Figure 3: Mean plot of homework access and income. Note: *1= strongly disagree, 5= strongly agree.
 

 

As expected, there is an inverse relationship between income and homework gap perceptions. As income increases, fewer respondents report that the children under their care are unable to complete their homework due to lack of access to the Internet or computers. One apparent outlier to the curve of the overall relationship is that the lower middle-class population with an income of $US30K–39K were less likely to express concerns over Internet connection and computer availability for their children.

Cultural and techno-capital

Cultural capital as theorized by Bourdieu relies on the ability of being familiar with the dominant culture in a society and understanding and using the educated language of that culture. Arguably, possession of higher levels of education translate into higher levels of cultural capital. Similarly, techno-capital refers to the ability and knowledge to utilize technologies.

To examine the question of techno-capital empirically, the survey used a scale of 19 items about digital literacy and capabilities, using five-point Likert scales, developed jointly by the researchers and Austin Free-Net, a large digital divide non-profit agency. The questions had been validated initially in an earlier study of public housing residents in Austin (Chen, et al., 2016). (The questions can be seen in Appendix III). Through a factor analysis of these questions from the larger general sample (n=997) (see Table 4), the research team identified three levels of techno capital, basic, intermediate, and advanced (Choi, et al., 2020). Basic techno-capital includes the ability to use a smartphone, apps, and accessing the Internet on mobile devices. In contrast, intermediate techno-capital includes the ability of accessing, consuming and uploading information for general purposes, and being able to use technology for basic work and personal productivity. While the advanced techno-capital refers to the knowledge and skills concerning privacy and cybersecurity, as well as deeper interaction with technologies such as creating a Web site and coding. The factor analysis is shown in Table 4.

From the three factors shown in Table 4, we constructed an analysis that labels Factor One as consisting of basic skills (smartphone use, uploading content, downloading apps, bookmarking, creating a social media profile, determining the accuracy of information, using GPS/map software). Some Factor Two items partially overlapped each other, but we placed the items on factor with the higher loading. Factor Two seemed to contain office or personal productivity skills or capabilities (basic computer tasks, productivity software, online banking, job related, and health information searches). Factor Three seemed to contain advanced capabilities (dealing with malware, or spam, or phishing, creating a Web site, protecting privacy, creating content, or coding).

 

Table 4: Techno-capital factor analysis.
Note: Principal Component Analysis (Varimax with Kaiser Normalization); Loadings greater than .4 displayed.
ItemsFactor loadings
Factor 1Factor 2Factor 3
Smartphone use.818  
App download.805  
Upload.775  
Bookmark.722.450 
Profile.630 .542
Accuracy.607.487 
GPS/Map.495.453 
Basic task.407.811 
Productivity software .781 
Online banking.490.682 
Job related.456.665 
Health info. search .650 
Malware .625.501
Web site  .780
Spam  .772
Content  .715
Privacy  .712
Phishing .576.592
Coding  .488
Cronbach’s alphaα = .923α = .891α = .863
% of variance53.668.736.12

 

Homework gap, techno-capital, other capitals, and demographics

To test the correlation between cultural, economic, and techno capital as well as some basic demographic variables like age and gender, a standard multiple linear regression was conducted. A homework gap index was composed creating a mean composite variable from the two main variables: “I feel that my children or grandchildren cannot complete their homework because they do not have access to the Internet,” and “I feel that my children or grandchildren cannot complete their homework because they do not have access to computers.” The multiple linear regression used the homework gap index as the dependent variable, while gender, level of education, age, income, and the three levels of techno capital were used as the independent variables.

The proposed regression model was statistically significant [F(7, 312) = 23.658, p < .001], explaining 34.6 percent of the variance in homework gap perception. The model indicates that education, age, income, and techno-capitals are strong predictors of homework gap perception. As expected, education (β = -.438, p < .001) and income (β = -.121, p < .05) are inversely correlated to perceptions of homework gap. As levels of education and income decrease, the perception of homework gap increases. This confirms the results from other tests above that better educated and more wealthy parents/guardians are less likely to perceive a homework gap for their children, probably since they are more likely to have computers and broadband at home.

Age, on the other hand, is positively correlated to homework gap (β = .147, p < .01), which is not surprising since as indicated in Table 1, those age 65 and up reported the lowest levels of technological device adoption, indicating that the children they care for are less likely to have devices and connectivity in their homes. When it comes to techno-capitals, the intermediate techno-capital, which includes the skills for consuming and access information online for general purposes is inversely correlated to homework gap (β = -.223, p < .05). In the general survey of Austin from which this study is drawn, those with intermediate techno-capital tended to be better off economically and better educated (Straubhaar, et al., 2019). However, advanced levels of techno-capital are positively associated with perceptions of homework gap (β = .281, p < .001). This is harder to explain but in the general sample survey, those with advanced cultural capital tended to be younger, varied in education and income, so their home access for children might also be varied.

 

Table 5: Multiple regression results of gender, age, education, income, and techno-capital on the homework gap index.
Note: p < .05*; p < .01**; p < .001***.
Variables
(N = 319)
Multiple regression model
BSEβt
DV: Homework gapF(7, 312) = 23.658***, R2 = .346
Gender.007.121.003.056
Age.015.005.147**2.931
Education-.375.062-.438***-6.025
Income-.072.035-.121*-2.061
Basic techno-capital.224.148.141.512
Intermediate techno-capital-.276.129-.223*-2.14
Advanced techno-capital.372.099.281***3.745

 

 

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Discussion, theoretical, and policy implications

Several results stand out in this study. One is that while a number of parents and guardians were concerned about the lack of Internet access (12 percent), more (20 percent) were concerned about the lack of access to computers. A notable part of the population pivots toward use of and even dependence on smartphones with data plans. This is reflected in a decline in the number of people with computers at home in our study. In this change, the fact that children depend on computers to write up homework and other more complex school tasks may be overlooked. At issue, too, is that for lower income people, a smartphone — which may be shared among multiple people — is their first access to the Internet. Educators, school systems, policy-makers, and parents will all need to think about how to address the need for computer or tablet access that this reflects.

A second major result is that a number of parents and guardians are concerned about skills as well as access. Fully 22 percent feel that their children or grandchildren’s computer skills “are not good enough to complete their homework.” While parents also respond that their children are generally learning computer skills at school, a notable percentage (18 percent) are concerned about it. And almost a quarter (24 percent) feel that their own skills are ‘not good enough” to help their children or grandchildren complete their homework. This reflects a class gap among parents in the study. Middle and upper middle-class parents probably have the skills to help their children at home. Our regression analysis showed that those with intermediate techno-capital or digital literacy — abilities focused on office skills common to the U.S. middle class — were less concerned about the homework gap. However, almost a quarter of respondents feel they do not have the skills they need to help their children. Educators, policy-makers and non-profits need to address the skills gap directly by programs for children at school, or after-school, and indirectly by helping raise the skills of lower income parents so that they can also help their own children.

A third key result is that half (50 percent) of parents and guardians said their children or grandchildren accesses the Internet at public libraries and computer access centers. This is much higher than the general population surveyed in Austin, where less than five percent of the general population used a public library at least several times a week (Straubhaar, et al., 2019). Austin City policy-makers and non-profits have already provided widespread public libraries and quite a few public access centers (Straubhaar, et al., 2012). This study clearly shows a continuing need for public access sites. The future challenge is providing public access for lower income people who are being pushed out of the city’s jurisdiction by gentrification, rising home prices, taxes, and rent. As those people are pushed into more rural or exurban parts of neighboring counties and smaller towns, a geographically wider policy-making process is needed to make sure services, like public access to high-speed Internet and computers continue to reach them.

In demographic terms, several statistical measures, including a multiple regression, show that age, education, and income are all related to the homework gap. Older people, lower income people and less educated residents of the city are all significantly more likely to perceive that their children or grandchildren lack access to the Internet or to computers to do their homework. Homework gap related programs need to particularly target those populations. Race or ethnicity was significant on some measures, but not in the multiple regression. This was probably due to a flaw in the sample, which had an under-representation of both Latino and African American residents. Those from those groups that did respond tended to be disproportionately better off and better educated (Straubhaar, et al., 2019). We are in the process of doing another survey that targets those populations directly, which will probably yield a more accurate sample and perhaps a better understanding of the groups’ profiles and needs.

In theoretical terms, we wanted to see if techno-capital, our theoretical approach to digital literacy, was significantly related to the homework gap. In a first measure, for the general population survey, we conducted a factor analysis of a large (18 items) set of digital literacy or potential measures of techno-capital. We found that the items did group, or scale well together overall as a set of related measure, but more interestingly we found that three distinct factors or groups emerged. One was a set of respondents with very basic digital or techno-capital, largely focused on smartphone and basic Internet use. Since almost everyone had this level of techno-capital, we found little variation and little relationship to the homework gap in our regression analysis. A second set of respondents had intermediate, or work, office, and personal productivity oriented digital or techno-capital. We found that those respondents who were lower on this set of digital or techno-capital did express concern that their children did not have sufficient access to the Internet and computers. So, too, those who were high on advanced techno-capital, related to advanced skills in privacy protection and creativity. End of article

 

About the authors

Melissa Santillana is a Ph.D. student in the Department of RadioTelevisionFilm at the University of Texas at Austin.
Direct comments to: melissa [dot] santillana [at] utexas [dot] edu

Joe Sraubhaar is the Amon G. Carter Centennial Professor of Communications in the School of Journalism at The University of Texas at Austin.
E-mail: jdstraubhaar [at] austin [dot] utexas [dot] edu

Alexis Schrubbe is a Ph.D. candidate in the Department of RadioTelevisionFilm at the University of Texas at Austin.
E-mail: adschrubbe [at] utexas [dot] edu

Jaewon Choi is a Ph.D. student in the Department of RadioTelevisionFilm at the University of Texas at Austin.
E-mail: jaewonrchoi [at] utexas [dot] edu

Sharon Strover is the Philip G. Warner Regents Professor in Communication and Director of the Technology and Information Policy Institute at the University of Texas at Austin.
E-mail: sharon [dot] strover [at] austin [dot] utexas [dot] edu

 

Acknowledgements

The authors extend their gratitude to the city of Austin and the personnel and leadership of the Office of Telecommunications and Regulatory Affairs, particularly John Speirs. This project was supported by the City of Austin Project Title: 2017 City of Austin Residential Technology Survey, Analysis, and Final Report Award #:NI170000025, UTA17-001114.

 

Notes

1. Four extra zip codes to the east of Austin’s city limits were included in the sample to try to find former Austin residents pushed east out of the city by gentrification, risings rents, house prices, and property taxes.

2. An Analysis of Variance (ANOVA) is a statistical test that allows comparisons between the means of three or more groups of data to establish whether there is significant difference between them.

3. Full SPSS result table of the analysis available in the Appendix.

 

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Appendix

 

Appendix I: Homework gap ANOVA results.
 Sum of SquaresdfMean SquareFSig.
Can’t complete homework because no InternetBetween Groups69.75779.9656.844.000
Within Groups452.8343111.456  
Total522.591318   
Can’t complete homework because no computerBetween Groups136.676719.52514.208.000
Within Groups446.6263251.374  
Total583.303332   
Have good enough computer skills to help children get homework doneBetween Groups357.054751.00837.129.000
Within Groups469.8433421.374  
Total826.897349   
My children’s computer skills are good enough to get homework doneBetween Groups128.474718.35316.310.000
Within Groups362.3333221.125  
Total490.807329   

 

 

Appendix II: Tukey HSD post-doc table.
* Note: Columns represent groups with significant differences
Homework gap itemSubset for alpha = .05
Income ($US)N1234
Can’t complete homework because no Internet
$30K – $39,999171.5810   
$75K and over1151.72471.7247  
$40K – $49,999142.25332.25332.2533 
$50K – $74,999712.41302.41302.4130 
$10K – $19,999432.58082.58082.5808 
$20K – $29,99932 2.82122.8212 
Less than 10K17  3.0341 
Can’t complete homework because no computer
$30K – $39,999171.3220   
$75K and over1151.5810   
$40K – $49,999181.68551.6855  
$50K – $74,999752.12802.12802.1280 
$20K – $29,99932 2.67722.67722.6772
Less than 10K17  2.82122.8212
$10K – $19,99943  2.95662.9566
3.2978
Have good enough computer skills to help children get homework done
$20K – $29,999321.3440   
$10K – $19,99943 2.3465  
$30K – $39,99917  3.8196 
Less than 10K17  4.2100 
$40K – $49,99921  4.2372 
$75K and over124  4.2456 
$50K – $74,99979  4.2657 
My children’s computer skills are good enough to get homework done
$20K – $29,999322.4097   
$10K – $19,999432.83232.8323  
$30K – $39,99912 3.47813.4781 
$40K – $49,99914 3.52073.5207 
Less than 10K17 3.56543.5654 
$75K and over117  3.8466 
$50K – $74,99978  4.1794 

 

 

Appendix III: Digital literacy survey scale items keywords and descriptions.
Item keywordDescription
UploadUploading content like videos or photos to a Web site
SpamBlocking spam
PrivacyAdjusting privacy settings online
BookmarkBookmarking a Web site or adding a Web site to my list of favorites
AccuracyComparing different sites to check the accuracy of information
ProfileCreating and managing my own personal profile on social network site
Web siteCreating my own personal Web site
App downloadDownloading an app on my mobile device/cell phone
PhishingRecognizing a phishing attempt
ContentMaking my own content like videos, photos, or music
Health information searchSearching for health-related information online
GPS/MapUsing GPS or map software for location services (e.g., Google Maps, Cap Metro)
Turn/Log onTurn on your computer, log on, and do basic tasks
MalwareProtecting your computer from malware, spyware, ransomware, etc.
Online bankingManaging your banking and finances online
Productivity softwareUse computer productivity software like Word, Excel
CodingWrite computer code in any language
Job relatedWrite a work resume, post online for a job opening
SmartphoneUtilize a smartphone, getting and using apps, access Internet

 

 


Editorial history

Received 6 June 2020; accepted 9 June 2020.


Copyright © 2020, Melissa Santillana, Joe Straubhaar, Alexis Schrubbe, Jaewon Choi, and Sharon Strover. All Rights Reserved.

Digital inequalities: Homework gap and techno-capital in Austin, Texas
by Melissa Santillana, Joe Straubhaar, Alexis Schrubbe, Jaewon Choi, and Sharon Strover.
First Monday, Volume 25, Number 7 - 6 July 2020
https://firstmonday.org/ojs/index.php/fm/article/download/10860/9569
doi: http://dx.doi.org/10.5210/fm.v25i7.10860