Abstract
Two hundred twenty-two
school counselors from one urban (n = 90; 40%) and two suburban school
districts (n = 132; 60%) in Maryland completed a modified version of the
Computer Technology Competencies Scale (CTCS; Edwards, Portman, & Bethea,
2002) in order to determine their level of confidence and familiarity
with computer technology and their usage of computer technology to
implement school counseling tasks and activities. The results
indicated that urban school counselors’ use of email to contact parents
and teachers was significantly less than suburban school counselors’ use
of email to contact parents and teachers. Implications for future
research and practice are discussed.
School counselors’ use of technology is a relatively new
phenomenon (Bleuer
& Walz, 1983;
D’Andrea, 1995;
Van Horn, & Myrick, 2001;
Rust, 1995). Almost a decade ago,
Gerler (1995) stated that school counseling “has been particularly
slow in exploring technological advances for offering better services to
students, parents, and teachers” (p. 8). In fact, it was during the mid
1980’s and early ‘90’s when the school counseling literature began to
include more articles on school counselors’ use of computer technology
(e.g.,
Harris-Bowlsbey, 1984;
Katz & Shatkin, 1983;
Rust 1995;
Mudore, 1988).
A few empirical studies have explored school counselors’
use of computer technology. In 1992,
Moore (1992) explored school counselors’ use of computer applications and
found that about 30% of the counselors in Arkansas used computers for
counseling related tasks. In a similar study,
Owen and Weikel (1999) found that a vast majority of school
counselors in Kentucky have access to a computer in their schools. He
also found that middle and high school counselors tended to use
computers more often than did their colleagues working in elementary
schools or vocational schools. Elementary school counselors also
reported lower levels of self-confidence in utilizing computers than
their secondary counterparts. In addition, the results suggested that
computers tend to be used by school counselors for word processing and
record keeping/scheduling rather than activities related to counseling
or advocacy functions.
In 1999,
Stone and Turba (1999) argued that school counselors should use
computer technology in their student advocacy role.
Stone and Turba purported that counselors who are able to access
student data are more prepared to advocate with “facts-in-hand” and are
thus more likely to eliminate institutional barriers that interfere with
student academic progress. In other words, they proposed that school
counselors should be familiar with and utilize data analysis software to
identify areas and groups which need attention or specific services.
Sabella (1996) has even suggested specific time-saving tips and he
highlighted how counselors can utilize computers to expedite routine
tasks and manage heavy student caseloads and work loads.
Although the usage of computer technology has been
encouraged in the school counseling literature, little is known about
school counselors’ familiarity and frequency with which they use
computers as a tool in their work. Better yet, it is unclear whether or
not school counselors use of computer technology differs based on school
community (e.g., urban vs. suburban vs. rural schools). In general,
there is very little literature and research on the differences between
urban and suburban school counselors. Therefore, examining school
counselors’ technology differences based on school community would be a
much needed addition to the school counseling literature.
Hence, the present study sought to examine computer
utilization differences among school counselors in three school
districts in the state of Maryland. One of the school districts is an
urban, inner city school district while the other two school districts
were considered to be in suburban communities. The specific research
questions that were used to guide this study were as follows:
1. Is there a difference between urban and suburban school
counselors familiarity and confidence with computer
technology (e.g., email, databases, internet, word processing)?
2. How do urban and suburban school counselors compare in their use
of computer technology at work (e.g., email, creating databases, word
processing)?
3. How do urban and suburban school counselors compare in their use
of computer technology for “typical” school counseling activities?
Because this study is exploratory in
nature, the researchers did not formulate any hypotheses.
Method
Participants
Participants were 222 school counselors from one urban
(n = 90; 40%) and two suburban school districts (n = 132; 60%) in
Maryland. One-hundred ten (50%) of the participants reported that they
worked in elementary schools, 67 (30%) in middle schools, 42 (19%)in
high schools, and 3 (1%) reported that they work in “other types” of
school settings (e.g., K-12, K-8). Regarding the participants’
experience as school counselors, 93 (42%) reported that they had between
1-5 years of experience, 46 (21%) between 6-10 years of experience, 39
(18%) between 11-15 years, 23 (10%) had between 16-20 years, 7 (3%)
reported that they had between 21-25 years, and 14 (6%) had more than 26
years of experience. A majority of the participants had master’s
degrees (n = 213; 96%) while 5 (2%) reported having a bachelor’s degree
only, and 4 (2%) reported having a doctoral degree. The participants
reported their ethnicity as follows: 61 (27%) African American, 148
(67%) White/European American, 3 (1%) Asian, 6 (3%) Hispanic, 1 Native
American, (.04%), and 3 (1%) reported “other.” A total of 183 (82%) of
the participants were women.
Regarding the participants’ background in computer
technology, 63 (28%) reported that they had taken no coursework on
computer technology, 56 (25%) reported they had taken one course, 65
(29%) had taken two courses, 35 (16%) had taken three or more courses,
and 3 (1%) did not respond. A majority (n = 211; 95%) of the
participants reported that they had access to computers at work and 160
(72%) reported that they use PCs at work while 62 (28%) reported using
an Apple/McIntosh computer.
Instrument
The 20-item survey used in this study was developed by the
authors to measure school counselors’ confidence and familiarity with
computers as well as their usage of computer technology at work. The
items were based on the 15-item Technology Competencies Scale (CTCS)
developed by
Edwards, Portman, & Bethea (2002). The CTCS was created
using 12 competency areas as recommended by the Association for
Counselor Education and Supervision (ACES)
Technology Interest Network to measure an individual’s competence level
on the technology competency. The CTCS consists of a 5-point likert
scale ranging from 1 (not familiar) to 5 (very confident). The CTCS
revealed a Cronbach alpha of .93. Validity of the original CTCS is
unknown.
For this study, the CTCS was adapted for use with school
counselors. This was done by including items that were relevant to
school counselors. For instance, familiarity and confidence in
evaluating the quality of internet information was not used since school
counselors are not required to evaluate internet information. Likewise,
the CTCS item on confidence and familiarity with computerized
statistical packages was also deleted. The adapted CTCS included 10
items that required the participants to report their level of
familiarity and confidence with 10 statements regarding computer
technology (e.g., using word-processing software, developing and using
databases). A five point Likert-type scale was used to measure
familiarity and confidence, 5 = very familiar and very confident, 4 =
familiar and confident, 3 = neutral, 2 = familiar but not confident, and
1 = not familiar. The second section of the survey required the
participants to report their level of usage of 10 computer technology
activities (e.g., using email, computerized testing). Computer usage
was rated using a 5 point likert-type scale, 5 = frequently, 4 = often,
3 = sometimes, 2 = rarely, 1 = never. For this study, the confidence
and familiarity scale yielded a Cronbach alpha of .87 and the computer
usage scale yielded an alpha of .79.
A 12-item demographic questionnaire was also developed to
gather information about the participants and their computer usage.
Information obtained consisted of the participants’ gender, ethnic
background, school community, school setting, school level, years of
experience, age of computer, type of computer in office, computer
workshops attended, and types of counselor activities where computers
are used.
Procedures
Results
School Counselors’
Familiarity and Confidence with Computer Technology
To examine school counselors’ familiarity and confidence with
computer technology, means and standard deviations were computed for the
survey’s first 10 items. The ratings of familiarity and confidence for
each item, as shown in Table 1, were between “very familiar and very
confident” and “not familiar.” Overall, the participants rated
themselves to be most familiar and confident with using email (M = 4.44,
SD = .90) and word processing software (M = 4.25, SD = .96). In
contrast, the participants rated themselves to be least familiar and
confident with developing a webpage (M = 1.48, SD = .91) and using
bulletin boards/discussion boards (M = 2.45, SD = 1.37).
Table 1
Means of Familiarity and Confidence with Computer Technology
Items
Item
N M1 SD
1. Using word processing software
225 4.25 .96
3. Using bulletin boards/discussion boards
223 2.45 1.37
Decision making programs
224 2.69 1.33
5. Assisting students
via internet to
explore information such as career
training, personal information, etc.
222 2.81 1.39
7. Using computer-related CD ROMS
225 3.21 1.38
8. Developing and using databases
225 2.55 1.33
9. Using presentation software
225 2.52 1.38
10. Developing webpage
225 1.48 .91
Note.
(1) The greater an item’s mean, the greater the familiarity and
confidence of computer technology of the participants. Scale used: 1 =
Not familiar, 2 = Familiar but not Confident, 3 = Neutral, 4 = Familiar
and confident, 5 = Very familiar and very confident.
A one-way multivariate analysis
of variance (MANOVA) was conducted to determine the effect of school
community (i.e., urban vs. suburban) on the dependent measures, the 10
familiarity and confidence with computer technology items. Significant
differences were found between counselors in urban and suburban schools
on the dependent measures, Wilk’s l = .82, F(20, 410) = 2.11, p <
.01, the multivariate h2 based on Wilk’s was not strong, .09. Table 2
contains the means and standard deviations on the dependent variables
for the two types of school communities.
Analyses of variance (ANOVA) on each dependent variable were
conducted as follow-up tests to the MANOVA. Using the Bonferroni
Method, each ANOVA was tested at the .01 level. The ANOVAs on two items
were significant: “using email” F(2, 214) = 5.20, p< .01, n2 =
.05 and “using the internet” F(2, 214) = 5.10, p < .01, n2 =
.05.
Post hoc analyses to the univariate ANOVA for the confidence
and familiarity items consisted of conducting pairwise comparisons to
find which school community affected confidence and familiarity items
most strongly. Each pairwise comparison was tested at the .01 level.
The urban school counselors rated their familiarity and confidence with
the use of email significantly lower than suburban school counselors.
Urban and suburban school counselors’ familiarity and confidence on all
of the other items were not significantly different from each other.
School Counselors’
Usage of Computer Technology
Means and standard deviations were computed for the items in
section 2 of the survey in order to examine school counselors’ usage of
computer technology. Table 3 consists of the participants’ ratings of
how often they use computer technology for each item in section 2. The
participants’ ratings for computer usage were between “never” and
“frequently.” The participants gave highest ratings to items regarding
the usage of word processing software (M = 4.33, SD = 1.05) and email
for contacting teachers (M = 3.89, SD = 1.56). Participants gave the
lowest usage ratings to developing webpages (M = 1.21, SD = .64), using
email for contacting students (M = 1.66, SD = 1.14), and using bulletin
boards/discussion boards (M = 1.71, SD = 1.09).
Table 3
Means and Standard Deviations of the Use of Computer
Technology Items
Item
N M SD
1. Using word-processing software
224 4.33 1.05
2a. Using email to contact parents
224 2.96 1.60
2b. Using email to contact students
222 1.66 1.14
2c. Using email to contact teachers
223 3.89 1.56
3.
Using bulletin boards/discussion boards
225 1.71 1.09
5. Assisting students
via the Internet to
explore information
such as careers,
employment, training,
etc. 224
2.08 1.13
6.
Using counseling related listservs
225 1.91 1.15
7. Using computer related CD ROMS
224 2.23 1.19
8.
Developing and using databases
225 2.28 1.34
9.
Using presentation software
225 2.00 1.16
10. Developing a webpage `
225 1.21 .64
Note.
(1) The greater an item’s mean, the greater the participants’ usage of
computer technology.
Scale used: 1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 =
Frequently.
A series of one-way analyses of variance was conducted
to evaluate the relationships between school counselors’ usage of
computer technology and their school community (i.e., urban, suburban).
The dependent variables were the usage items from the survey.
Significant relationships were found for two items, using email to
contact parents, F(2, 220) = 18.73, p < .01, h2 = .15, and using email
to contact teachers, F(2, 219) = 45.20, p < .01, h2 = .29. The strength
of relationship between school community and school counselors’ use of
email to contact parents, as assessed by h2, was moderate, with the
school community variable accounting for 15% of the variance of the
dependent variable. The strength of relationship between school
community and school counselors’ use of email to contact teachers, as
assessed by h2, was strong, with the school community variable
accounting for 29% of the variance of the dependent variable. Table 4
includes the means and standard deviations for urban and suburban school
counselors' usage of computer technology.
The author conducted post hoc comparisons using the
Dunnet’s C test, a test that does not assume equal variances among the
two groups. There were significant differences in the means between
urban school counselors and suburban school counselors' usage of email
to contact parents and teachers. Suburban school counselors used email
to contact parents and teachers significantly more than urban school
counselors. The 95% confidence intervals for the pairwise differences,
as well as means and standard deviations for the school community groups
are reported in Tables 5 and 6.
Table 6
95% Confidence
Intervals of Pairwise Differences in Mean Changes in Usage of Email to
Contact Teachers
School Community M
SD Urban Suburban
Urban 2.88
1.70 -2.18 to –1.23
Suburban 4.58
.97 1.23 to 2.18
School
Counselors’ Usage of Computer Technology for Typical School Counseling
Activities
Frequencies were computed to determine whether school
counselors use computer technology for typical school counseling tasks
or activities. Over 90% of the participants reported using computer
technology to write letters and reports. In addition, over 60% of the
participants reported that they use computer technology to organize
student data, implement classroom guidance, and to contact and locate
community resources. Less than 40% reported that they use computer
technology for note taking or for personal/social counseling and group
counseling.
Chi square analyses were implemented in order to determine
whether there was any difference, based on school counselors’ school
community, in the usage of computer technology for common school
counseling tasks/activities. The analyses revealed significant
differences between urban and suburban school counselors’ use of
computer technology to contact parents, Pearson
c2(1, 222) = 21.57, p =
.000, Cramer’s V = .31 and to contact teachers, Pearson
c2(1, 222) =
56.55, p = .000, Cramer’s V = .50. Table 7 highlights the prevalence of
school counselors' use of computer technology for typical school
counseling tasks.
Discussion
The primary purpose of this study was to examine school
counselors’ familiarity and confidence with computer technology and
their use of computer technology in urban and suburban schools. Results
indicated that school counselors’ familiarity and confidence with
computer technology varies according to the type of activity performed
on the computer. For instance, school counselors rated their
familiarity and confidence with word processing higher than their
familiarity and confidence with developing webpages, using bulletin
boards, and using listservs. These findings are consistent with
Owen and Weikel’s (1999) study which found that school counselors
are most competent with word processing. Likewise, school counselors’
usage of computer technology varies according to the type of activity.
School counselors’ usage of word processing is “frequent” while
counselors spend little time developing webpages and using email to
contact students. This variation in computer usage is also similar to
Owen and Weikel (1999) findings that suggested that school
counselors in Kentucky use computers most often for word processing and
record keeping rather than for activities related to student guidance or
counseling functions.
Quinn, Hohenshil, and Fortune (2002). found this same variation to
be true of counselor educators in CACREP-accredited counseling
programs. They found that counselor educators use computer technology
for communication (e.g., emailing colleagues) than for listservs.
Perhaps among the most interesting results of this study was the
difference between the participants’ computer usage according to their
school community. The suburban school counselors in this study
reported that they use email to contact parents and teachers
significantly more than urban school counselors. Although urban
school counselors in this study have access to computers, it appears
that they are not using email to contact parents and teachers as often
as suburban counselors. This finding could be due to a lack of an email server
in urban schools. Needless to say, this finding is disturbing since the
email function can be a means for building relationships and
partnerships with parents and teachers. Communicating with teachers and
parents has been identified as an important role for school counselors,
especially in light of education reform initiatives where
community-building is an important task and has been linked to student
achievement (Haynes
& Comer, 1993). The impact of counselors not using email to contact
parents and teachers warrants further investigation.
Another goal of this study was to assess urban and
suburban school counselors’ usage of computer technology for “typical”
school counseling activities. A majority of the participants reported
that they use computers for writing letters and reports, organizing
student data, implementing classroom guidance, and contacting/locating
community resources. Less than half of the participants reported that
they use computers for note taking, personal/social counseling and group
counseling. These findings are similar to previous studies (e.g.,
Moore, 1992;
Owen & Weikel, 1999) that indicated that school counselors tend to
use computer technology for word processing related tasks rather than
counseling related tasks. When comparing urban and suburban school
counselors’ usage of computer technology for typical school counseling
tasks, there was a significant difference between their usage of email
to contact parents and teachers. Once again, suburban school counselors
used computer technology to contact parents and teachers significantly
more than urban school counselors. This finding makes sense given the
preceding results regarding the use of email to contact parents and
teachers. Clearly, this difference between urban and suburban school
counselors’ use of technology to contact parents and teachers is
noteworthy and should be investigated further to determine the reasons
for the difference in usage.
Implications, Limitations, and Conclusions
Implications
One of the important implications of the current study is the
need to address the lack of email usage among urban school counselors
and counselors in schools with high percentages of ethnic minority
students. In light of new legislation such as the “No Child Left Behind
Act” and other school reform initiatives focused on improving the
achievement of minority and urban students, it seems fitting that
counselors in schools with these populations would be using computer
technology such as email to strengthen school-family-community
partnerships. Further exploration of why school counselors are not
using email as a mode of parent and student contact should be undertaken
and the effect of using email as a source of communication with parents
and students on student achievement should be examined. Research (e.g.,
Haynes & Comer, 1993;
Jeynes, 2003;
Pezdek, Berry, & Renno, 2002;
Rutter & Maughan, 2002) suggests that increasing parent involvement
increases the achievement of minority, and low-income students.
Likewise, the literature (e.g.,
Bloch, 2002;
Kruger, et al., 2001) suggests that email can be used to create and
sustain relationships. It is also possible that this lack of email
usage in urban schools is perpetuating the “digital divide” among
racial, socioeconomic, and cultural groups. For this reason, this
discrepancy should be a focus of urban school counselor professional
development and training.
Another implication of this study for school counseling
practice is the low usage of computers for some counselor tasks.
Further professional development for existing counselors on the ways in
which computer technology can be utilized to enhance counseling groups,
individual counseling, and other counseling activities would be
beneficial. In addition, school counselor education programs must begin
introducing ways in which computer technology can be utilized to enhance
school counseling programs and school counselor outreach to communities,
particularly minority and urban communities. Research on the training
of “computer competent” school counselors in both urban and suburban
schools is warranted.
A critical research implication of this current study was the
need for more empirical research that focuses on the practices of
counselors in urban schools. There is a paucity of literature and
research that focuses on the issues and practices of counselors who work
in urban settings. The findings of this study suggests that there is a
significant difference among the computer technology practices of
counselors according to their school/community and as stated
previously, this is an area for further research and exploration.
Limitations
Although the results of the present study are interesting and partially
encouraging, they should be interpreted within the context of its
limitations. Foremost among these limitations is the nonrandom
selection of participants. The study was dependent on volunteers
sending mail-in responses. Participants in this study could have
differed from the larger population in a variety of potentially
important aspects (e.g., school district resources). In addition, the
data were self-report and therefore can be questioned regarding honesty,
understanding the instructions, and social desirability. Another
limitation is the limited scope of the school counselors invited to
participate. The school counselors in this study live in the same state
and in the same region of the state. In other words, the counselors in
this study could be more representative of school counselors in this
region of Maryland and not school counselors in general.
Conclusions
Given the importance of computer technology in the role of
school counselors, future investigations should examine the present
study’s variables in order to understand their potential influence on
school counselors’ usage of computer technology in their work. Although
additional research is needed to understand the computer practices of
school counselors, results from this study can help counselors and
counselor educators make informed decisions about training and
professional development needs of existing as well as future school
counselors.
References
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Kruger, L. J., Struzziero, J., Kaplan, S.
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Pezdek, K., Berry, T., & Renno, P.
A. (2002). Children’s mathematics achievement: The role of
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Rutter, M., & Maughan, B. (2002).
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Sabella, R. A. (1996).
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Stone, C. B., & Turba, R. (1999).
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Author's
Biography
Cheryl
Holcomb-McCoy
is an Associate Professor in the Department of Counseling and Personnel
Services at the University of Maryland at College Park. She teaches
School Counseling and Counselor Education courses. She can be reached
at:
cholcomb@umd.edu.
Appendix
Internet
Resources for School Counselors
