This exploratory study examines differences in K-12 educators'
use of technology for instruction across school economic factors. Survey
data from 94 practicing K-12 teachers are analyzed. This study finds
that schools' economic factors explain variation in how teachers
use technology to promote higher-order thinking skills. Our findings
support the existence of a Second-Level Digital Divide. The study also
identifies a need for access to technology facilitators, as well as
in-service training for practicing teachers on how to use technology to
promote higher-order thinking skills.
Keywords: Higher Order Thinking Skills, K-12 Education, Second
Level Digital Divide, Technology Use, Technology Facilitator
This exploratory study investigates the Second-Level Digital Divide
as it relates to K-12 environments in a large urban area in the
Midwestern U.S. The study tests for differences across school economic
factors in K-12 teachers' use of technology for instruction. The
study investigates the extent to which teachers integrate technology to
maximize student learning by examining teachers' pedagogical and
technological practices in the classroom. A growing body of research
indicates that the Second-Level Digital Divide is a subtle, yet complex,
divide that impacts people in various ways, and which has the potential
for social exclusion (Singleton & Longley, 2009). Most research on
the Second-Level Digital Divide comes from the sociology literature
rather than the K-12 education literature. While there is some research
from within the K-12 environment, the majority have examined the general
population. This study focuses upon K-12 environments to provide greater
insight into the Second-Level Digital Divide.
The Second-Level Digital Divide describes the difference, or
"divide," in how technology is used, while the Top-Level
Digital Divide refers to the difference between the technology
"haves" and "have nots" (Hargittai, 2002). This
newer divide, referred to here as the Second-Level Digital Divide
(SLDD), is no longer a simple delineation between those who have access
to technology and those who do not. The SLDD refers to the difference in
how technology is utilized. The following literature review discusses
the complexities of the SLDD, and the factors that influence the SLDD
with respect to K-12 learning.
Overview of the Digital Divides: Factors Influencing How Technology
Gone are the days of believing that the Digital Divide is simply a
partition between those who have access to a computer and a modem, and
those who do not (Stevenson, 2009; Stevenson, 2008). Rather, researchers
have found a subtler divide that has more to do with how the technology
is used (Hargittai, 2002; Stevenson, 2009; Stevenson, 2008). The SLDD is
a complex concept of interacting physical/digital, human, and social
resources (Underwood, 2007). For consistency throughout the paper, the
terms physical/digital ,human, and social resources, respectively, will
be used as a way of classifying the different influences on the SLDD.
The factors influencing the use of technology are wide and varied.
As early as 2002 Hargittai found differences in how members of the
general population used computers to find digital information. Hargittai
(2002) found that these differences in how technology is used can be
explained, in part, by human factors including age, education level, and
amount of experience with the technology. For example, younger people
have more experience with technology and are able to use the technology
to access information that those with less experience are not able to.
It is interesting to note that the reported results in the
literature on the difference in use, based on age, are mixed. Guo,
Dobson, and Petrina (2008) found no difference in information and
communication technology (ICT) use based simply on age. Yet Prensky
(2001, 2005) argues that there is a marked difference, based on age, in
the manner in which technology is used. Prensky (2001, 2005) notes, that
younger students, whom he calls "digital natives" are more
adept at using technology relative to older individuals, whom he calls
"digital immigrants." According to Prensky (2001, 2005)
digital natives have grown up with technology and technology is a normal
part of their everyday life. Digital natives are much more comfortable,
and able, to use technology relative to the digital immigrants who are
just beginning to utilize the technology.
Jung (2008) found that a combination of physical, human, and social
factors (other than age) influence the SLDD. They include the technical
environment (home access, years of internet use, and access points), an
individual's scope and intensity of goals for using technology, and
social capital. Social capital here refers to access to others in
one's social circle to call upon when technological questions
emerge (Jung, 2008).
The concept of social capital and an additional element of cultural
identity is supported by the findings of Lewin, Mavers, and Somekh
(2003), DeGennaro and Brown (2009), Halverson (2009), and Selwyn,
Potter, & Cranmer (2009). Each found that the divide has
socio-cultural influences. More specifically, it is an issue of cultural
identity where the dominant culture identifies with the benefits of
technology, and therefore uses such technology, while the non-dominant
culture does not identify with such technology and as a result does not
use technology to the same extent.
Related to the socio-cultural influences of the SLDD, Stevenson
(2009) argues that the SLDD involves the interrelationship between
social classes, information creation, and information ownership.
Stevenson (2009) notes that there are differences between social
classes. The classes can be characterized by their relationship to
information either as producers of information, or those who simply
consume information. Classes can also be characterized by their
relationship to intellectual property rights, those who own intellectual
property rights, and those who do not (Stevenson, 2009). Singleton and
Longley (2009), in contrast, conclude that the differences in technology
usage are due to the lack of motivation to use information and
communication technology, and also material deprivation.
It is clear that researchers are unable to identify all the factors
that influence the SLDD. However, the common thread in all the research
is that the divide is not simply due to differences in access to
physical/digital technology, but rather there appears to be SLDD which
is due to differences in physical/digital, human, and social factors
that influence how members of society use the technology
(Hargittai,2002; Stevenson, 2009; Stevenson, 2008; Valadez & Duran,
2007; Warschauer, 2003). Given the differences in technology use, there
is the potential for marginalization of those who do not use technology
as effectively as do others in order to effect full participation in
democratic societies (Banister & Fischer, 2010; Blanchard, Metcalf,
Degney, Herrman, & Burns, 2008; Valadez & Duran, 2007;
Warschauer, 2003; Warschauer, 2007).
To summarize, a wide body of literature reports that the SLDD is a
serious issue and that the SLDD has the potential for social exclusion
(Hargittai, 2002; Stevenson, 2008; Valadez & Duran, 2007;
Warschauer, 2003). The researchers of the current study seek to delve
deeper into the SLDD and further investigate the K-12 environment to
gain insight into differences at the K-12 level. The purpose is to
contribute to the literature and to contribute to the understanding of
the SLDD. We discuss the literature regarding the SLDD, and the
influences on K-12 teachers below.
Second Level Digital Divide and K-12 Learning
Research indicates that there is a marked difference in how
information and communication technology (ICT) is being used within K-12
schools. Cuban, Kirkpatrick, and Peck (2001) report that there are two
general explanations for this difference. The first explanation is that
teachers are slow to adapt technology, which is a human factor. The
process takes time and is inconsistent within schools. The second
explanation has to do with physical/digital factors that include school
infrastructure, the use of time within the schools, and flawed
technology (Cuban et al, 2001). For instance, Cuban et al., (2001)
report that teachers:
did not have enough time in the school day, much less at home, to
do all of the things they were expected to do and then find time to
integrate computers and other technologies into their classroom routines
Selwyn (2006) noted that schools' limitations in physical
access to the Internet from within the school also contribute to the
divide. Mouza (2008) shows that simply having the physical access to
technology within the school does not significantly change learning
outcomes. Rather, the SLDD is a complex issue concerning physical access
as well as the personal characteristics of the teacher (such as gender,
race, ethnicity, language skills, culture, and economic background), and
the curriculum of the school or district (such as content, form and
structure) (Natriello, 2001).
Interestingly, Jackson, von Eye, Biocca, Barbatsis, Zhao, and
Fitzgerald (2006) found that students who have physical access to and
used the Internet at home more often had higher grade point averages,
and higher standardized test scores, in reading. These authors found a
difference in socio-demographic characteristics stating, "race
differences in home Internet use may serve to exacerbate existing race
differences in academic performance" (p 434). A similar
socio-cultural difference was noted by Lewin et al. (2003) who found
that there is a significant "majority who do not choose to use
technology to help them with their schoolwork on a daily or frequent
basis" (p. 47). This, then, is the impact of the issue of
socio-cultural capital--students from homes that choose to use
technology for schoolwork are more likely to have an academic advantage
over those that do not (Lewin et al., 2003).
Warschauer (2007) further explains the SLDD by enumerating five
different digital divides that include both physical and human factors.
They are: school access, home access, school use, gender gap, and
generation gap. In schools with a high percentage of students who come
from economically disadvantaged homes, the students largely use ICT for
remediation and skill reinforcement (Becker, 2000; Warschauer, Knobel,
& Stone, 2004). In sharp contrast to this, in schools in which the
majority of the students are not from economically disadvantaged homes,
the students use ICT for research, high-level analysis and for synthesis
(Becker, 2000; Warschauer, Knobel, & Stone, 2004). It is important
to note that the schools that have a higher percentage of students who
come from economically disadvantaged homes do use the Internet for
research. This Internet usage, however, is seemingly perfunctory at
best, as researchers found that often times the students are simply
using the Internet to find basic information such as the definition of
words (Warschauer, Knobel, & Stone, 2004).
The difference in preparation levels of pre-service teachers can
also magnify the divide. Thus, the need to improve technology
integration offerings at the pre-service level is important. But
pre-service teachers are not being prepared to effectively integrate
technology into their classroom (Brown and Warschauer, 2006). Most often
the technology classes focus on general use of the technology for
instruction rather than age and subject specific instruction.
Professional development for inservice teachers is also an
important practice that can improve the effective use of technology in
the classroom. Banister and Fischer (2010) found that the SLDD can be
reduced by providing continued technology support and training that
motivates teachers to utilize technology in their classroom. Thus, for
both the pre-service teacher and the veteran teacher, professional
development and support is needed to move beyond "novice uses of
technology overtime" (Banister & Fischer, 2010, p. 8) to reduce
the effects of the S LDD.
Technology facilitators can provide the additional professional
development that teachers need. Technology facilitators also provide
regular, accessible support for the use of technology in their
classrooms. The inclusion of a technology facilitator/coordinator in the
school's staffing plan is ideal. It is a form of social capital,
the same social capital discussed by Jung (2008), which can greatly aid
teachers with the successful integration of technology into their
Technology facilitators are needed to move technology from the
periphery of classroom instructional tools to a central role that
enables them to more fully impact learning (Hofer, Chamberlin &
Scot, 2004; Reinhart & Slowinski,2004). But,technology facilitators
are not simply a type of in-house "Geek squad" whose task is
to keep the school's technology up to date and running smoothly.
Technology facilitators can use standards-based approaches to move
schools towards better implementation of technology (Williamson &
Redish, 2007). Often times technology facilitators are teachers with
additional licensure that allows them to be a technology facilitator.
This extra training associated with the additional licensure allows them
to work in cooperation with classroom teachers to better integrate
technology into the curriculum in a manner that supports students'
cultural identities. Technology facilitators could also work
cooperatively with teachers in creating a school technology plan. This
technology plan can assist in narrowing the digital gaps (Uzunboylu
& Tuncay, 2010).
Overview of the Digital Divide: Influences on Teachers
The issue of the Second-Level Digital Divide is an important one
for teachers who learned their craft back in the 20th century. The
current task of these teachers is to prepare their students to be the
workforce of the 21st century. Yet, teaching strategies and assessments
of learning are apparently not in line with the current age (Underwood,
2007). Since the composition of the workforce in the 21st century is,
and will continue to be, very different than the composition of the
workforce of the 20th century, this is a daunting task. Teachers need to
be able to apply technological innovations to the teaching and learning
process to prepare their students for working in the 21st century and
for being effective producers of information (Morse, 2004; Uzunboylu
& Tuncay, 2010). This is important given that students must develop
computer technology skills to be full participants in our society and to
be able to realize the potential this technology possesses to improve
their academic achievement (Morse, 2004, p. 277).
Without teachers effectively applying technological innovation in
this way, there is a real potential for the marginalization of students
who are not prepared to be active participants in the 21st century
workforce. Hence, there needs to be a major shift in the role of
The above literature review provides evidence, which supports the
need to investigate if there is a difference between teachers'
technology use and the following:
* Physical/digital factors regarding access,
* Human factors such as teacher knowledge, teacher demographics,
and participation in technology-related professional development,
* Social factors such as school demographics, socioeconomics, and
access to a technology facilitator, and
* School curriculum such as content form and structure.
This exploratory study investigated physical/digital and social
factors and their influence on how teachers use technology in the
classroom. The researchers teach at a private university in a large
Midwestern city. The research participants are practicing teachers that
work in that same city, its suburbs, and in the outlying rural areas. At
the time of the study, the research participants were enrolled in the
graduate school of the university at which the researchers teach. While
the research participants work in diverse settings, the sample is a
convenience sample, which is both a benefit, and a limitation, of the
study. The benefit is that the researchers were able to gather data for
this exploratory study in an efficient and cost effective manner. The
limitation is that the sample may not be representative of all teachers.
There may also be bias associated with the sample, as the teachers in
the study are all working on their graduate degree, and so are actively
expanding their professional knowledge in the field. Only the social and
physical factors within the teacher's schools are being
This research study addresses the following research questions:
1. How do K-12 teachers use technology in their classroom?
2. Is there a difference in how technology is being used based upon
socio-economic factors? (a social factor)
a. If there is a difference in technology use by teachers based on
school economic factors, then what other factors differ based on these
school economic factors?
i. Access to the latest technology? (a physical/digital factor)
ii. The presence of a technology facilitator at their school? (a
social capital factor)
As noted previously, the research participants are teachers that
work in the city, the suburbs, and in rural areas. At the time of the
data collection, the participants were graduate students enrolled in ten
education courses at a private university. Participants were surveyed at
the beginning of a required "Technology for Educators" course
in their major. The response rate was 64%, with 94 students voluntarily
responding. Human subjects approval was granted for this study. The
sample was a convenience sample comprised solely of students enrolled in
the researchers' university and who were also taking the
"Technology for Educators" class.
The diverse teaching experiences of the teachers who enroll in this
graduate class have prompted the researchers' interest in further
studying the SLDD. The participants range in age from 21-60 with the
median age of 28. Participants were asked to report their years of
teaching experience in year ranges. The median range of teaching
experience reported by the participants was between 4-8 years.
Research participants were asked to complete the inventory during
the first two weeks of the "Technology for Educators" class.
As the research participants completed the inventory, they were asked to
answer each question based on their current teaching experiences within
the K-12 setting.
The survey instrument was an inventory constructed and evaluated by
four experts in the field of teacher education and instructional
technology. The pedagogy portion of the inventory was found to be
reliable at 0.70. The pedagogy portion included a list of common
teacher-led pedagogical practices (e.g., demonstration), common
inquiry-based approaches (e.g., problem-based learning), and common
student specific pedagogies (e.g.. use of learning centers). These
sub-scales were found to be reliable at 0.51,0.42 and 0.61,
respectively. Additionally, respondents were able to report other
pedagogies that they used but were not specified in the inventory.
The technology portion of the inventory was found to be reliable at
0.73. The technology portion of the inventory included five sub-scales:
Web 2.0 (i.e., classroom use of blogs;), Gadgets (i.e., classroom use of
GPS ;), Basic Use of Technology (i.e., teaching students how to save and
organize files), Promotion of Higher-Order Thinking Skills (i.e.,
teaching students analysis skills with spreadsheets), and Perceptions of
Technology Use (i.e., technology integration abilities). The five
technology sub-scales were found to be reliable at 0.37,0.58,0.75,0.61,
and 0.66, respectively. Sub-scales are the averages of individual
responses. Prior to averaging the subscales each data point was
standardized to enable analysis.
The data analysis consisted of calculating descriptive statistics
for the technology use sub-scale. Seven analyses of variances (ANOVAs)
were conducted to determine if there was a significant difference in the
means for each of the three respective social economic groups.
Differences were examined separately for the presence of technology
facilitators, availability of interactive whiteboards, and the various
types of technology-use sub-scales.
Descriptive statistics were calculated for each technology-use
sub-scale (see Table 1). Scores are on a scale of 1-4, with 1
representing less of the construct, and 4 representing more. Descriptive
statistics are presented in Table 1. The subsample results are reported
in Tables 3 and 4. Test Statistics for differences across groups are
reported in Tables 2 and 5.
Research Question 1: How do teachers use technology in their
It is clear from Table 1 that in the full sample, on the four-point
scale, the mean of the responses for Basic Use of Computer Technology is
2.60, while it is only 1.41 for Use of Web 2.0 in the classroom.
Research Question 2. Is there a difference in how technology is
being used based upon socio-economic factors?
One-way Analysis of Variances (ANOVAs) were conducted to test
whether there was a difference in technology use by teachers across
school economic factors. Five separate one-way ANOVAs were completed in
which the factor was a school's economic factors and the dependent
variable was one of the five technology sub-scales. Of the five one-way
ANOVAs that were conducted, only one had a significant result.
Significant results were found for the "Promotion of Higher-Order
Thinking Using Technology," which was significant at a 0.039 level
(see Table 2.)
To examine whether the likelihood that the school has a technology
facilitator varies by school economic factors, the sample was
partitioned into three subsamples based upon the school economic factors
(SEF). The researchers report the presence/absence of a technology
facilitator for each SEF subsample in Table 3. There is a significant
difference between SEF and technology facilitators at the 0.008 level;
while 88% of high SEF have a facilitator, only 53% of low SEF do (see
Table 5). Therefore schools with a lower percentage of students who
received free and reduced lunch were more likely to have a technology
Table 4 reports whether the teacher has an interactive whiteboard
and compares the possession of this technology tool to the economic
status of the school. A significant difference in classrooms equipped
with interactive whiteboards was found at the 0.049 level, 27% for high
SEF and 52% for low SES (see Table 5). Therefore schools with a higher
percentage of students who received free and reduced lunch were
significantly more likely to have interactive whiteboards in the
The results support the existence of a Second-Level Digital Divide.
The manner in which technology is being used in the schools to promote
higher-order thinking is found to be significantly different across
school economic factors. This supports the findings by Becker (2000) and
Warschauer et al. (2004), who found similar results in the K-12
environment. Schools with a lower percentage of students who receive
free and/ or reduced lunch use technology in a way that promotes
higher-order thinking. This finding supports Stevenson's (2009)
finding about a similar phenomenon between social classes and their
relationship to either information producers or information consumers.
Students who use higher-order thinking are most likely information
producers while students who do not use higher-order thinking are most
likely consumers of existing information.
Second, technology facilitators are also found to be concentrated
at schools with a lower percentage of students receiving free and
reduced lunch. This means that schools with students who have more
wealth also have more access to technology facilitators.
These two findings suggest a link between the presence of a
technology facilitator and the students using higher-order thinking
skills. This is consistent with the idea that technology facilitators
are meeting the needs of the faculty for additional training on how to
use technology to promote higher-order thinking skills, and are
functioning as important social capital for those teachers in the
schools which have a low number of students who receive free and reduced
lunch. Technology facilitators are available to provide support when
teachers have technology-related questions. The technology facilitators
have the instructional technology knowledge that teachers tap into to
improve their own instruction, and to improve attendant learning
experiences for their students. This social capital (i.e. access to a
school professional who has extensive knowledge in instructional
technology) allows teachers to improve the use of technology within the
context of their own classroom and to create instruction that is
relevant to their own students.
Schools need to promote higher-order thinking in a way with which
students can identify. This means that, as suggested by DeGennaro and
Brown (2009), schools need to do more than simply provide students with
a "situation that reflects how dominant cultures use and learn
technology" (p. 28). Instead they need to relate learning about the
use of technologies "to an individual's view of him or herself
as well as their group's relation to technological
participation" (p. 28). Further, as Halverson (2009) suggested,
there is a need to take what students know and map it onto "skills
and competencies that will help them to become successful adults"
(p. 75). As mentioned above, the presence of a technology facilitator
that knows the culture of the school can assist with creating relevant
technology-related activities for the students.
The findings also support the assertion that the Top-Level Digital
Divide, while documented in past, has now largely diminished. This
follows given the significant finding that teachers in schools with a
higher percentage of students who receive free and/ or reduced lunch are
more likely to have interactive whiteboards in their classroom when
compared to teachers in schools with a lower percentage of students who
receive free and/or reduced lunch. The researchers find that while the
technology is available in schools with a higher percentage of students
who receive free and/or reduced lunch, it seems that these teachers are
not using the technology to promote higher-level thinking skills at the
same challenging level as teachers in schools with fewer students
receiving free and reduced lunch.
This study concludes that access to the latest technology does not
imply that teachers will effectively use the technology to promote
higher-order thinking. Rather, it appears that training and support from
technology facilitators aids teachers with using technology to promote
higher-order thinking. Schools with a high percentage of free and
reduced lunch are less likely to have technology facilitators. Much of
the lack of teaching higher-order thinking skills may be attributed to
the absence of what appears to be essential to effectively teach these
higher-order skills, mainly the presence of technology facilitators.
Therefore the teaching of higher-order thinking skills requires more
than just access to technology, but the evidence suggests that it seems
to require a local technology facilitator.
Finally, it is interesting to note that teachers' general
perception of their technology skills (mean of 2.78) exceeds the means
found in a detailed analysis of the actual technology skills they employ
(means ranging from 1.41-2.67). While this particular finding is not
statistically significant in the research sample, it is still important
to note that teachers' perception with respect to technology use
does not correspond to the reality.
This study finds that there exists a Second-Level Digital Divide
that has profound implications for the persistent technological
marginalization of economically disadvantaged students. Schools with a
majority of students from low socioeconomic conditions were more likely
to be taught by teachers who only provided instructional support, and
guidance for student use of technologies in the most basic ways. In
sharp contrast, schools that had more affluent students were provided
instructional support by teachers in ways that integrated technologies
and fostered the development of higher-order thinking skills that went
beyond teaching just the basic skills. These pedagogical differences
signal a notable dynamic in sorting out the "haves and the have
not's" as these students attempt to gain the knowledge and
skills to compete in a global market that undoubtedly will demand the
ability to integrate technologies and critical-thinking skills.
Although teachers in this study did report using technologies to
supplement instructional practices, it was their limited use of
available technologies and the weak methods by which these technologies
were used to promote student learning that were of the utmost concern.
Such inadequate teaching practices can only be changed through greater
educator awareness concerning the shaping of the Second-Level Digital
As teachers become enlightened about this new digital divide, it is
imperative that robust systems of ongoing professional development be
implemented. Professional development that supports pedagogical changes
in teacher practices over-time is necessary. These changes primarily
concern the integration of technologies in instruction, and student
development of higher-order thinking skills. A special focus for such
teacher training should be on teachers in schools with large numbers of
students from low socioeconomic conditions. School districts should
consider the use of technology facilitators to support teachers in such
schools with the necessary training and support. The research findings
suggest that the social capital that technology facilitators can provide
to teachers can greatly improve the integration of technology in their
classrooms in a manner that promotes students' higher-order
In conclusion, the skilled technocrats of the future reside in the
pool of students being taught today. These technocrats of the future
will provide the leadership in a technological world that demands highly
developed critical thinking skills. This study demonstrates that a
minority of students constitutes the pool for these future skilled
technocrats. This minority of students more than likely resides in
affluent conditions, have access to technology, and are being taught in
ways that support the integration of technologies and the higher skills
of critical thinking. The teachers in these more affluent schools are
not ignoring how these students ultimately will shape the world, and
have regular professional assistance in achieving this goal through
access to a technology facilitator.
Teachers from less affluent schools, on the other hand, are more
likely teaching in ways that do not foster the integration of
technologies in a manner that promotes higher-order thinking skills.
While teachers from these less affluent schools may have the needed
technological equipment they perhaps do not have the technology
facilitators to aid them with using technologies in ways that promote
higher-order thinking skills. This is the disturbing reality of the
Second-Level Digital Divide and it is something that appears to be
preventable through professional development and the support of a
The Second-Level Digital Divide shapes the future for all students
as they attempt to navigate a technologically advanced global village.
Is it conscionable that students of a lower socioeconomic status be
relegated to a lesser role in the future by educators whose teacher
practices have failed to be upgraded to seamlessly integrating
technology skills into the curriculum while promoting higher-order
thinking skills? Perhaps it is everyone's duty to demand that all
students regardless of school economic factors or condition be
instructed in ways that provide equity of future opportunity, resulting
in critical-thinking skills that prepare these students to navigate an
increasingly technological world.
Finally, instructional equity for the future demands that teachers
view their primary role as supporting the integration of teaching
practices and technologies in ways that challenge all students to learn.
It also demands that teachers emphasize the integration of technology
and utilize teaching practices in ways that help students become better
problem solvers and more analytical in their approaches to learning.
The results of this exploratory study provide evidence for the SLDD
in K-12 environments. Further studies need to be conducted that delve
deeper into the factors influencing the SLDD. In particular, studies
that investigate pedagogical practices that enhance higher-order
thinking skills that utilize technology would be most beneficial to
improving practices within the teaching profession.
The authors wish to thank Leonard Lundstrum and Norma
Grassini-Komara for their advice and assistance with this research
Banister, S., & Fischer, J. (2010). Overcoming the digital
divide: The story of an urban middle school. Mid-Western Educational
Researcher, 23(2), 2-9. Retrieved from EBSCOhost (accession number:
Becker, H. (2000). Who's wired and who's not:
Children's access to and use of computer technology. The Future of
Children, 10(2), 44-75. Retrieved from
Blanchard, M., Metcalf, A., Degney, J., Herrman, H., & Bums, J.
(2008). Rethinking the digital divide: Findings from a study of
marginalised young people's ICT use. Youth Studies Australia,
27(4), 35-42. Retrieved from EBSCOhost (accession number: 35693932).
Brown, D., & Warschauer, M. (2006). From the university to the
elementary classroom: Students' experiences in learning to
integrate technology in instruction. Journal of Technology & Teacher
Education, 14(3), 599-621. Retrieved from EBSCOhost (accession number:
Cuban, L., Kirkpatrick, H., & Peck, C. (2001). High access and
low use of technologies in high school classrooms: Explaining an
apparent paradox. American Educational Research Journal, 38(4), 813-834.
Retrieved from http://www.jstor.org/stable/3202504.
DeGennaro, D., & Brown, T. (2009). Youth voices: Connections
between history, enacted culture and identity in a digital divide
initiative. Cultural Studies of Science Education, 4(1), 13-39. doi:
Guo, R., Dobson, T., & Petrina, S. (2008). Digital natives,
digital immigrants: An analysis of age and ICT competency in teacher
education. Journal of Educational Computing Research, 38(3), 235-254.
Hargittai, E. (2002). Second level digital divide: Differences in
people's online skills. First Monday,7(4). Retrieved March 5, 2010
Halverson, E. (2009). Shifting learning goals: From competent tool
use to participatory media spaces in the emergent design process.
Cultural Studies of Science Education, 4(1), 67-76.
Hofer, M., Chamberlin, B., & Scot, T. (2004). Fulfilling the
need for a technology integration specialist. T.H.E. Journal, 32(3),
34-39. Retrieved from EBSCOhost (accession number: 15340051)
Jackson, L., von Eye,A., Biocca, F., Barbatsis, G., Zhao, Y., &
Fitzgerald, H. (2006). Does home Internet use influence the academic
performance of low-income children? Developmental Psychology, 42(3),
429-435. doi: 10.1037/0012-16188.8.131.529
Jung, J. (2008). Internet connectedness and its social origins: An
ecological approach to post-access digital divides. Communication
Studies, 59(4), 322-339. doi: 10.1080/10510970802467387
Lewin, C., Mavers, D., & Somekh, B. (2003). Broadening access
to the curriculum through using technology to link home and school: A
critical analysis of reforms intended to improve students'
educational attainment. Curriculum Journal, 14(1), 23. Retrieved from
EBSCOhost (accession number: 10088807)
Morse, T. E. (2004). Ensuring equality of educational opportunity
in the digital age. Education and Urban Society, 36(3), 266-279. doi:
Mouza, C. (2008). Learning with laptops: Implementation and
outcomes in an urban, underprivileged school. Journal of Research on
Technology in Education, 40(4), 447-472. Retrieved from EBSCOhost
(accession number: 32589307).
Natriello, G. (2001). Bridging the second digital divide: What can
sociologists of education contribute? Sociology of Education, 74(3),
260-265. Retrieved from EBSCOhost (accession number: 5020128)
Prenksy, M. (2001). Digital natives, digital immigrants. On the
Horizon, (9)5, 1-6. doi: 10.1108/10748120110424816
Prensky, M. (2005). Listen to the natives. Educational Leadership,
(63)4, 8-13. Retrieved from EBSCOhost (accession number: 19270008)
Reinhart, J., & Slowinski, J. (2004). K-12 technology
coordinators: Expectations and realities. In Simonson & Crowford
(Eds.) Conference Proceedings for the Association for Educational
Communications and Technology, 27th, Chicago, 8, 719-726. Retrieved from
EBSCOhost (accession number: ED485035)
Singleton, A., & Longley, P. (2009). Linking social deprivation
and digital exclusion in England. Urban Studies, (46)7, 1275-1298. doi:
Selwyn, N. (2006). Exploring the 'digital disconnect'
between net-savvy students and their schools. Learning, Media and
Technology, (31) 1, 5-17. doi: 10.1080/17439880500515416
Selwyn, N., Potter, J., & Cranmer, S. (2009). Primary
pupils' use of information and communication technologies at school
and home. British Journal of Educational Technology, 40(5), 919-932.
Stevenson, S. (2009). Digital divide: A discursive move away from
the real inequities. Information Society, 25(1), 1-22. doi:
Stevenson, O. (2008). Ubiquitous presence, partial use: The
everyday interaction of children and their families with ICT.
Technology, Pedagogy & Education, 17(2), 115-130. Doi:
Underwood, J. (2007). Rethinking the digital divide: Impacts on
student-tutor relationships. European Journal of Education, 42(2),
213-222. doi: 10.111 l/j.1465-3435.2007.00298.x
Uzunboylu, H., & Tuncay, N. (2010). Divergence of digital world
of teachers. Educational Technology & Society, 13(1), 186-194.
Retrieved from EBSCOhost (accession number: 48315010)
Valadez, J., & Duran, R. (2007). Redefining the digital divide:
Beyond access to computers and the Internet. High School Journal, 90(3),
Warschauer, M. (2003). Technology and Social Inclusion: Rethinking
the Digital Divide. Cambridge, MA: MIT Press.
Warschauer, M., Knobel, M., & Stone, L. (2004). Technology and
equity in schooling: Deconstructing the digital divide. Educational
Policy, 18(4), 562-588. doi: 10.1177/0895904804266469
Warschauer, M. (2007). A teacher's place in the digital
divide. Yearbook of the National Society for the Study of Education
(Wiley-Blackwell), 106(2), 147-166. doi: 10.1111/j.
Williamson, J., & Redish, T. (2007). Building technology
facilitators and leaders: A standards-based approach. Learning &
Leading with Technology, 35(1),22-26. Retrieved from EBSCOhost
(accession number: 261460
Correspondence concerning this article should be addressed to Dr.
Julie M. Reinhart at firstname.lastname@example.org
Dr. Julie M. Reinhart, Associate Professor, School of Education and
STEM Educator Center Coordinator, Saint Xavier University--Chicago. Dr.
Earl Thomas, Associate Professor, School of Education, Saint Xavier
University--Chicago. Sister Jeanne M. Toriskie, OSF, Ph.D., Adjunct
Professor, School of Education and STEM Education Center Coordinator,
Saint Xavier University-Chicago.
Descrintive Statistics for Technology Use
N Mean Std. Dev.
Teachers' perception of how 92 2.78 0.640
they use technology
Basic use of computer technology 93 2.60 0.553
Promotion of higher-order thinking 93 2.30 0.523
Use of technology gadgets 90 1.42 0.514
in the classroom
Use of Web 2.0 in the classroom 90 11.41 1.275
One-way ANOVA Examining the Various Technology Factors by
School Economic Factors
Sum of df Mean F Sig.
Web 2.0 use
Between groups .019 2 .010 .124 .884
Within groups 6.690 87 .077
Total 6.709 89
Between groups .816 2 .408 1.567 .214
Within groups 22.653 87 .260
Total 23.469 89
Basic use of computer
Between groups .023 2 .012 .037 .963
Within groups 28.066 90 .312
Total 28.089 92
Promotion of higher
order thinking skills
Between groups 1.750 2 .875 3.369 .039 *
Within groups 23.369 90 .260
Total 25.118 92
use of technology
Between groups .657 2 .328 .800 .452
Within groups 36.516 89 .410
Total 37.173 91
* Significance found at the 0.05 level.
Number of Reported Technology Specialists by School Economic Factors
School Economic Factors (number of
students receiving fre/reduced lunches)
Technology Specialist 0-33% 34-66% 67-100% Total
Yes 37 23 10 70
No 5 8 8 21
Do not know 0 1 1 2
Total 42 32 19 93
Number of Teachers with an Interactive Whiteboard in Their Main
Classroom by School Economic Factors
School EcoFactors (numof students
receiving free/reduced lunches)
Interactive whiteboard -0-33% 34-66% 67-100% Total
Yes 11 7 10 28
No 30 26 9 65
Do not know 0 0 0 0
Total 41 33 19 93
One-way ANOVA, Technology Specialist by School Economic Factors and
Classroom Interactive Whiteboard by School Economic Factors
Sum of df Mean F Sig.
Between groups 2.263 2 1.131 5.087 .008 **
Within groups 20.017 90 0.222
Total 22.280 92
Between groups 1.269 2 0.635 3.121 .049 *
Within groups 18.301 90 0.203
Total 19.570 92
** Significant at the 0.01 level.
* Significant at the 0.05 level.