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K-12 teachers: technology use and the second level digital divide.
Article Type:
Report
Subject:
Digital divide (Technology) (Research)
Educational technology (Research)
Authors:
Reinhart, Julie M.
Thomas, Earl
Toriskie, Jeanne M.
Pub Date:
09/01/2011
Publication:
Name: Journal of Instructional Psychology Publisher: George Uhlig Publisher Audience: Academic; Professional Format: Magazine/Journal Subject: Education; Psychology and mental health Copyright: COPYRIGHT 2011 George Uhlig Publisher ISSN: 0094-1956
Issue:
Date: Sept-Dec, 2011 Source Volume: 38 Source Issue: 3-4
Topic:
Event Code: 310 Science & research Computer Subject: Technology in education
Geographic:
Geographic Scope: United States Geographic Code: 1USA United States

Accession Number:
289619980
Full Text:
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.

Literature Review

Overview of the Digital Divides: Factors Influencing How Technology is Used

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 (p. 828).

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).

Professional Development

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 Facilitator

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 curriculum.

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 teachers.

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.

Methodology

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 investigated.

Research Questions

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)

Participants

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.

Data Collection/Procedure

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.

Instrumentation

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.

Data Analysis/Design

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.

Results

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 classroom?

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 facilitator.

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 classroom.

Results

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.

Conclusion

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 Divide.

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 thinking.

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 technology facilitator.

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.

Acknowledgement

The authors wish to thank Leonard Lundstrum and Norma Grassini-Komara for their advice and assistance with this research study.

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Correspondence concerning this article should be addressed to Dr. Julie M. Reinhart at jreinhart@sxu.edu

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.
Table 1
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
skills with
computer technology
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

Table 2
One-way ANOVA Examining the Various Technology Factors by
School Economic Factors

                        Sum of    df   Mean      F      Sig.
                        Squares        Square

Web 2.0 use
Between groups            .019     2   .010      .124   .884
Within groups            6.690    87   .077
Total                    6.709    89

Gadget use
Between groups            .816     2   .408     1.567   .214
Within groups           22.653    87   .260
Total                   23.469    89

Basic use of computer
technology
Between groups            .023     2   .012      .037   .963
Within groups           28.066    90   .312
Total                   28.089    92

Promotion of higher
order thinking skills
with technology
Between groups           1.750     2   .875     3.369   .039 *
Within groups           23.369    90   .260
Total                   25.118    92

General philosophical
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.

Table 3
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

Table 4
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

Table 5
One-way ANOVA, Technology Specialist by School Economic Factors and
Classroom Interactive Whiteboard by School Economic Factors

                        Sum of    df   Mean     F       Sig.
                        Squares        Square

Technology Specialist
  Between groups        2.263      2   1.131    5.087   .008 **
  Within groups         20.017    90   0.222
  Total                 22.280    92
Classroom Interactive
Whiteboard
  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.
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