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«The purpose of this qualitative study was to examine how communication preferences, learning preferences, and perceptions about online learning ...»

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Locations of Exposure Adding another piece to the digital puzzle is the fact that a user’s exposure to computers and Internet in K-12 education does not necessarily negate the existence of digital inequality. A little over six years ago, there were huge gaps in computer use and access due to economics. In high poverty schools, nine students shared one computer, but in low-poverty schools, only six students shared a computer (Warschauer, 2003). While there was one computer for every 5.3 students in high poverty communities, there was a computer for every 4.9 students in low poverty communities (2004). Now, these gaps have nearly diminished due to government funding which provided over two billion dollars for telecommunication and Internet access at schools, allowing impoverished schools to purchase more computers and greatly increase Internet access (Warschauer, 2010).

Despite these technological improvements in elementary and secondary schools, home usage has more of an impact on digital inequality than K-12 school access (Zhao, Lu, Huang, & Wang, 2010). In other words, a student’s home use, directly impacts his college performance. When students enter colleges, they bring their experiences and preferences with them. Zhao et al. (2010) found that students who learned about computer usage from parents at home had a greater impact on student Internet efficacy in college more than earlier school usage, even if household usage was nonacademic in nature. In addition, students with prior Internet home usage reported better overall academic performances in the college years.

While digital inequality can stem from usage in households; it also can spawn from institutions of higher learning as well. Fok, Hartman, and Zee (2008) contend that gaps in access and uses are definitely found across college campuses. In the early part of the millennium, African Americans were at an extreme disadvantage in use in higher education. As early as 2002, William H. Gray, III, President and CEO of the United Negro College Fund reported how the digital divide in higher education was greater than the divide in households. Eight years ago, Gray reported that there was a 45 percent gap between White American households and African American households, along with a 72 percent gap between United Negro College Fund (UNCF) students who own computers and higher education institution (HEI) students (Armstrong, 2002). These gaps still exist today. Hawkins and Rudy (2008) found that on private college campuses, students reported owning more computers than on public college campuses with fewer resources and lower degrees. There are still over 30 percent of student college populations who do not own computers at all (Hawkins & Rudy, 2008).

Historically Black Colleges and Universities and Online Learning As one would expect, the gaps on college campuses directly impacts online learning. The student population at HBCUs is shown to have a higher percentage of first generation, low income, and underprepared students (Ukoha & Buzzetto-More, as cited in Buzeeto-Moore, 2008). Warschauer (2010) noted that those who benefit from online learning often exclude ethnic minorities and groups from lower socioeconomic backgrounds due to financial constraints and diversity in learning preferences.

Furthermore, Buzzetto-More (2008) indicate that though HBCUs have the same infrastructure and programs as predominately White institutions (PWI), attitudes about technology are different on HBCU campuses. While less than 25 percent of HBCU faculty and students bring laptops to campus, Whites at PWIs transport laptops at significantly higher rates (Buzetto-Moore, 2008).

Even within school systems, divides and inequality exist among online students.

In her study which focused on five HBCUs and one other ethnic minority serving institution in North Carolina, Price (2009) found that Whites were more likely to participate in distance education. While Whites constituted 73.3 percent of distance education courses, African Americans made up 17.7 percent of the distance education population, though 34.5 percent were willing to participate (Price, 2009). Moreover, students at HBCUs took far less distance education courses than at nonminority institutions.

Age Horrigan (2010) cited that young African Americans, 30 and younger, are much more likely to have Internet access. Prensky (2001) also showed how the younger generation is much more likely to embrace emergent technologies. Gaps in technology usage are much more likely to be found with older generations.

More specifically, Prensky (2001) narrowed computer users into two groups:

digital natives and digital immigrants. Using language immigrants as an analogy, Prensky discussed how computer use is much easier for digital natives than digital immigrants.

According to Prensky, digital natives are born into the digital world. As a result, they think differently and process information much faster than digital immigrant users.

Prensky (2001) goes on to say that digital natives enjoy multitasking and parallel processing, prefer graphs over text, and prefer hyperlinks and instant gratification. Unlike digital immigrants, digital natives enjoy “games” over “serious work.” (p. 2).

On the other hand, digital immigrants were not born into the digital age, but technologies were adopted later in their lives (Prensky, 2001). As a result, digital immigrants prefer traditional means of processing information and cannot process information as quickly as digital natives. For example, digital immigrants prefer to print the information and bring people into the office as opposed to sending an email. In addition, digital immigrants may even call e-mail recipients by phone to insure that they received the e-mail.

Differences in how different generations prefer to use technology have been delineated even further by a Sydney Jones and Susannah Fox in a Pew Internet & American Life Project Memo (2009). In this memo, Jones and Fox (2009) showed how various generations—Generation Y (1977-1990), Generation X (1965-1976), Young Boomers (1955-1964), Older Boomer (1946-1954), the Silent Generation (1937-1945), and the GI Generation (1936 and earlier) are using the Internet. Generation Y uses the internet for entertainment purposes and communication with friends (Jones & Fox, 2009).

Many from Generation Y play games online, explore virtual worlds, watch videos, and download music. They enjoy blogging, social networking, and sending instant messages.

Generation X uses the Internet to shop, bank, e-mail, and research. Young Boomers, Older Boomers, and the Silent Generation send and receive e-mail information; however, the GI Generation uses the Internet to look for health information more than any other group (Jones & Fox, 2009).

Nevertheless, a digital divide may still be present among youth because one cannot take for granted that digital natives’ desire and know how in using new technologies in education (Kennedy, Krause, Judd, Churchward, & Gray, 2008). Using a group of students in Australia, Kennedy et al. (2008) learned that many digital natives were still not savvy with technology’s use in education. One example that the researchers cited was the use of Podcasts for learning. Though many educators were very excited about their students’ abilities to use podcasts to listen to lectures, the authors noted how some students were not able to download MP3 files into their computers and still others did not own memory sticks. Hargiatti (2001) discovered that youth from more privileged backgrounds were able to use the Web in more advanced ways with more activities.

African Americans’ Online Usage When the term digital divide was defined eight years ago, African Americans were found to use technology significantly less than Whites (Jackson, Ervin, Gardner, & Schmidt, 2001). Now it appears that African Americans are making huge progress in their use of technology as a vehicle of learning. In fact, the FCC’s October-November 2009 survey found that African Americans are online more than Whites. While 19 percent is the national average for daily Internet use, African Americans’ rate is 29 percent (Horrigan, 2009). Furthermore, African Americans are the most active mobile Internet users (Horrigan, 2009). While the national average of mobile Internet use is 32 percent, African Americans’ average is 48 percent. In addition, African Americans are the largest users of Twitter, a social networking site which allows users to send up to 140 character messages, representing 25 percent of its population (Frazier, 2010). In summary, African Americans are narrowly behind Whites in overall Internet access (Jones & Fox, 2009). While Whites are at a 59 percent usage rate, African Americans are at 49 percent (Jones & Fox, 2009).

The FCC reports that African Americans are more likely to take a class online for credit, 37 percent versus the 26 percent national average (Horrigan, 2009). The nation’s largest university, the University of Phoenix (Horrigan, 2009), an online for-profit institution of higher learning, reported that 30 percent of its 420,700-member student population is African American. Shockingly, online usage for for-profit universities like the University of Phoenix, Strayer, Kaplan, Capella, and Walden grant more PhDs to African Americans than HBCUs (Hall, 2010). Even still, one cannot ignore the ironies of African American’s technology use. On one hand, African Americans are wellrepresented in online courses at for-profit online schools (Hall, 2010); however, when it comes to HBCUs, African Americans take far less distance education courses (Price, 2009). Price’s (2009) dissertation concerning distance education courses and minorityserving institutions in North Carolina revealed that African Americans are slightly more likely to enroll in online courses than Whites though technological infrastructure constraints at HBCUs often inhibit them from doing so.

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According to a recent review of the literature by Uzner (2009), there have been over 27 studies, two of which were dissertations, which focused on culture and distance learning in asynchronous learning networks (ALNs). While twelve of these studies were qualitative, seven were quantitative, and eight used mixed-methods. The majority of the studies involved international students as participants. In fact, many of the studies focused on Asians and their perceptions about and uses of technology in global distance education courses. Overall, Uzner’s (2009) review of the literature revealed how culture is important to online learning and that effective online courses must take into account cultural issues, language, and needs of students from diverse backgrounds.

Uzner’s (2009) review also echoed the conclusions of Chisholm (1998) and McLoughlin (2001), two of a handful of researchers that I found who have studied online learning and African Americans. Similar to Uzner’s (2009) review of the literature about culture and distance education, Chisholm (1998) and McLoughlin (2001) supported the idea that African American culture must be taken into account when designing and teaching online courses.

More recently, Okumba, Walker, Hu, and Watson (2010) conducted research on students’ attitudes toward online learning. Through the administration of the Online Tutoring Attitudes Scale administered to 124 African American student participants from a positive youth development program, the researchers found that African American students had positive attitudes about computers, but they lacked self-confidence and experienced anxiety during online learning. In addition, Flowers, Moore, and Flowers (2008) cited how the greater the number of distance education courses African American students took, the more they enjoyed online learning. Another study concerning African American students’ experiences in online learning was completed by Rovai et al. (2005).

Their research findings indicated that African American graduate students posted little on discussion boards compared to Whites in graduate classes because they needed auditory and visual communication threads.

Finally, while there have been a number of online courses offered at American colleges and universities with research studies related to them being conducted by various researchers, Flowers et al. (2008) acknowledged the limitations of this research. For example, much of the research has not focused on African American college students. In fact, Rovai and Ponton (2005) concurred that there is very little research or information that exists concerning how African American students experience and perceive online learning.

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The purpose of this chapter was to review the literature and theories that relate to the research study I conducted. The first section included a review of adult learning theory. Following this review, considerations of culture on communication and learning, with particular attention to African American speech and dialogue as well as African American learning styles were discussed. Since the study related to nontraditional students’ participation in online learning, ways of access, time of use, locations of exposure, education and economic status—specifically through the environment of HBCUs and online learning, as well as age were shared within the overarching topic of digital inequality. Additionally, within this chapter, African Americans’ online usage was also explored. Finally, studies related to culture and online learning were highlighted.

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This chapter begins with an explanation of the qualitative methodology that was chosen for this study—the instrumental case study. The first section provides a description of the study’s research design. The next section includes a description of the context of the study and its participants, followed by a description of the data collection and data analysis procedures. The role of the researcher is also addressed. Finally, I explain the establishment of trustworthiness.

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