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Professional school counselors' approaches to technology.

Existing literature in the field of school counseling discusses how technology may be used for service delivery" however, the translation of this knowledge to practice among school counselors has been minimally examined. Three hundred eighty-one school counselors in Colorado, Iowa, and New York completed a survey regarding their comfort with and use of technology. Findings indicate that the majority of those surveyed were very comfortable with technology. Implications for school counselors are presented.

A common theme in the school counseling literature includes the use of technology, specifically an argument that school counselors need to utilize technology to improve their program and delivery of services (Hebert & Neumeister, 2001; Kuranz, 2002; Sears & Granello, 2002). It is suggested that effective and efficient uses of technology among school counseling professionals are necessary for making guidance and counseling programs more comprehensive and an integral part of our schools (Sabella, 2000; Sabella & Booker, 2003). The sophistication of modern information and communication tools (e.g., film, video, personal digital assistants, virtual communities, multimedia presentations, and e-mail) influences the manner in which students are educated and counseled (Casey, 1995; Hebert & Neumeister; Sabella & Halverson, n.d.; Sabella & Isaacs, 2002; Tyler & Sabella, 2004).

Furthermore, program accountability is enhanced by and dependent upon the efficient and dynamic communication of program goals and strategies to all stakeholders (American School Counselor Association, 2002). For instance, electronic mail is fast becoming a universal means of communication and is rapidly replacing traditional means of sharing information (Van Horn & Myrick, 2001). Computer technology--particularly multimedia presentations, Web site development, electronic newsletters, and electronic journals--is useful in communicating messages about the profession and specific programs without the barriers of time and space (Sabella & Booker, 2003; Van Horn & Myrick). This technological paradigm shift is an important topic for exploration in the field of school counseling (Cabaniss, 2002).

Although there is a respectable amount of literature regarding the utility of using computers in the work of school counselors, much less is written about the extent to which school counselors actually do utilize computer technology (Owen & Weigel, 1999). One stud), completed during the early days of the computer boom found that 30% of school counselors in the sample reported using computers for counseling-related tasks (Moore, 1992). We expect that this percentage today would be higher given the surge in societal reliance upon technology. Although graduate programs recently have increased focus on technology competencies, the literature indicates that limited education and training may be one mitigating variable in the expected increase of computer use and that adequate training is one serious limitation to more wide-scale use of computer technology by school counselors (Edwards, Portman, & Bethea, 2002; LaTurno-Hines, 2002; Owen & Weigel; Quinn, Hohenshil, & Fortune, 2002; Van Horn & Myrick, 2001).

This study employed a mailed survey as a means of exploring technology training and usage among practicing school counselors in three states. Following are the specific research questions addressed:

1. What is the sell-reported comfort level of school counselors with computer usage, software, and electronic mail?

2. What are the most common types of technology and software used by school counselors?

3. What degree and type of computer training are reported by school counselors?

4. What relationships exist among the above variables and select demographic variables?

The remainder of this article shares the general findings gathered by means of the survey and presents implications for the field. Specific information regarding the instrument and statistics may be obtained by contacting the authors.

FINDINGS

Surveys were sent to 902 school counselors. There were 381 usable surveys returned for a 43% return rate. Participants were asked to respond to a number of demographic variables including age, gender, race, and professional experience. Age of the participants ranged from 24 to 69 with a mean of 45.57 and a standard deviation of 9.80. Women made up 66% (n = 253) of the sample, while 34% (n = 128) were men. The sample presented racially homogenous with 315 (82.7%) Caucasian, 8 (2.1%) Hispanic/Latino, 2 (.5%) Black, 1 (.3%) Native American/Alaskan Native, 10 (2.6%) other, and 45 (11.8%) not responding to the item.

Eighty respondents (21% of the sample) reported no teaching experience. Total years of teaching experience ranged from 0 to 38 with an average of 9.92 years. One hundred sixty-eight respondents (44.9% of the sample) indicated at least some elementary school counseling experience, 116 (31%) middle school counseling experience, 89 (23.7%) junior high, and 209 (56%) high school counseling experience. Total years of professional school counseling experience ranged from 0 to 34 with an average of 10.87 years. Respondents also were asked to report years of counseling experience at each level. Mean years of experience at the elementary level equaled 3.3 years; at the middle school level, 2.06 years; at the junior high level, 2.23 years; and at the high school level, 5.88 years of experience.

Comfort Levels

Participants were asked to rate their comfort level with computer hardware. Of the 379 usable responses to this item, 174 (45.7%) indicated that they were very comfortable, 179 (47%) somewhat comfortable, 25 (6.6%) somewhat anxious, and 1 (3%) indicated they were very anxious. These results indicate that most of the sample (92.7%) was at least somewhat comfortable with using computers.

The survey item related to comfort with utilizing a variety of software yielded different results. Of the 365 respondents to this item, 13 (3.4%) indicated that they were very comfortable with a variety of software, 59 (15.5%) somewhat comfortable, 200 (52.5%) somewhat anxious, and 93 (24.4%) indicated they were very anxious. This item indicates that unlike participant comfort with computer use, 76.9% of the sample was somewhat anxious or very anxious when it comes to using a variety of software.

The third comprehensive comfort item measured participant comfort with using technology other than computers. Such technology included, but was not limited to, televisions, videocassette recorders, audiocassette recorders, and projectors. Three hundred seventy participants responded to this item, and 95 (24.9%) indicated that they were very comfortable with other technology, 217 (57%) somewhat comfortable, 51 (13.4%) somewhat anxious, and 7 (1.8%) indicated they were very anxious.

Three hundred seventy-nine participants responded to the e-mail use item, with 367 (96.3%) participants reporting that they used e-mail and 12 (3.1%) reporting they did not. These figures are germane to the e-mail comfort discussion as only those using e-mail were asked to complete the comfort items. To ascertain more clearly the nature of such comfort, participants were asked to respond to a series of items including comfort receiving e-mail, sending email, sending attachments, receiving attachments, using an address book, using management tools, using list-serves, and engaging the Internet interface. A global e-mail comfort scale score was computed by summing all responses to the individual e-mail activities. Three hundred fifteen participants indicated usable responses for all e-mail activities. The possible range for the global e-mail comfort scale score is 8-32. More specifically, respondents who indicated they were very anxious on all of the activities would attain a global score of 8, while respondents indicating they were very comfortable on all activities would attain a global score of 32. The range for all usable respondents is 12-32 with a mean of 27.10 and a standard deviation of 4.21. This shows that the sample as a whole indicated a rather high comfort level with e-mail usage, and most of the respondents (74%) indicated that they were at least somewhat comfortable with all aspects of e-mail use. The global e-mail comfort scale score was utilized in the subsequent correlation analysis.

A global technology comfort scale score was computed by summing all of the responses for comfort-related items. These items included comfort with computers, with a variety of software, and with all eight e-mail activities. Subsequently, the global comfort score could have a range of 11-44. The analysis revealed 304 usable cases with a mean of 32.23 and a standard deviation of 4.33. Upon examination of the frequency table, it was noted that 155 (51%) of the sample generated a global comfort score placing them in the somewhat to very comfortable range. The global technology comfort scale score was utilized when examining relationships among variables.

Usage Patterns

Survey respondents were asked to indicate where they accessed computer technology. Possible access included at home, at work, at school, at a friend's house, or other. It was discovered through comments by participants that there was some confusion regarding the school and work categories because participants worked in school environments. To clean the data, a new variable (school or work use) was computed by transforming an affirmative response in either category to an affirmative response in the new variable. Of the 381 usable observations for these variables, 322 (84.5%) indicated that they used a computer at home, 368 (96.6%) at work or school, 36 (9.4%) at a friend's house, and 6 (1.6%) indicated they accessed a computer somewhere else. To create a global computer usage score for subsequent analysis, a summation score of these four activities was computed for each participant.

Participants were asked to indicate what types of technology they employed in their work. Specific technology included in the checklist on the survey instrument were cassette recorder, desktop computer, laptop computer, Web camera, camcorder, LCD panel, overhead projector, filmstrip projector, video-cassette recorder (VCR) and monitor, 16-mm film projector, data projector, and computer lab. The most common type of technology" reportedly used by the respondents was a VCR and monitor (85%). Other types of technology commonly used were desktop computer (82.7%), overhead projector (68%), and cassette recorder (52.2%). Less commonly used were the computer lab (49.9%), camcorder (33.3%), laptop computer (21.3%), filmstrip projector (16.3%), 16-mm film projector (11.5%), LCD panel (9.4%), Web camera (6.8%), and data projector (4.5%).

A total technology use scale score was computed by summing the number of different technologies used by each respondent. Three hundred eighty-one participants indicated usable responses for all technology items. The possible range for the total technology score is 0-12. More specifically, respondents who indicated that they did not use any of the listed technologies would attain a global score of 0, while respondents indicating they used all of the listed technologies would attain a total technology score of 12. The range for all usable respondents was 0-12 with a mean of 4.41 and a standard deviation of 2.0. This total technology use scale score was used in all correlation analyses involving technology usage.

Another section of the survey asked participants to indicate which software programs they used. The survey checklist included Microsoft Word, Cord Presentations, Netscape, SASSI, Word Perfect, Microsoft PowerPoint, Internet Explorer, Microsoft Excel, Quattro Pro, and SIS. Participants also were allowed to write in up to two additional software programs that they used extensively. The most common software program reported by the respondents was Microsoft Word (68.5%). Other types of software commonly used were Netscape (64.8%), Microsoft PowerPoint (35.7%), Microsoft Excel (27.3%), and Internet Explorer (24.1%). Less commonly used software included Word Perfect (14.7%), SASSI (13.4%), SIS (5.5%), Corel Presentations (1.8%), and Quattro Pro (0.8%). Popular write-in software programs among the 380 respondents included Claris Works (51), Choices (49), Works (15), and Apple Works (12). Due to the exorbitant number of possible software programs and the limitations inherent in a survey instrument such as this, types of software usage were not included in any relational analyses.

Training Experience

Participants were asked to indicate the number of computer courses they had completed at the high school and college level as well as courses taken through special training or continuing education. It is important to note that respondents were not asked about the length or intensity of each course. Of the 380 respondents to the item concerning high school courses taken, 315 (82.7%) responded that they had taken no courses, 42 (11.0%) one course, 18 (4.7%) two, 3 (.8%) three, I (.3%) four, and I (.3%) had taken six high school computer courses. Three hundred seventy-two participants responded to the college course item, and 228 (59.8%) indicated that they had taken no courses, 77 (20.2%) one course, 34 (8.9%) two, 15 (3.9%) three, 9 (2.4%) four, 5 (1.3%) five, 1 (.3%) six, and 3 (.8%) had taken 10 college-level computer courses.

The most popular type of computer training reported by this sample included outside or continuing education courses. Three hundred sixty participants responded to this item, and 224 (62.2%) reported taking at least one such course. More specifically, 107 (28.1%) reported taking one course, 46 (12.1%) two, 28 (7.3%) three, 11 (2.9%) four, 15 (3.9%) five, and 17 (4.7%) indicated more than five such courses. A summation of all courses taken constituted the global training score used in the subsequent relational analysis.

Relationships Among Variables

Pearson correlations were used to examine the relationship among years of teaching experience, years of counseling experience, global training, global comfort, computer usage, and other technology usage. A correlation matrix of these variables is presented in Table 1. Critical to the discussion of these results is the understanding that statistical significance does not necessarily indicate practical significance, and the existence of a large N (281 in this case) can result in statistical significance even when relationships among variables are weak. According to the r family of effect sizes, an r of. 10 indicates a "smaller than typical" relationship, an r of .30 indicates a "typical" relationship, and an r of .50 indicates a "larger than typical" relationship (Morgan, Gliner, & Harmon, 2006).

The findings from this study indicate that other technology use yields statistically significant correlations with all of the other variables, generating coefficients ranging from .12 to .31; however, the practical significance of these findings is limited considering the small correlation coefficient coupled with the large sample size. Those relationships indicating a "typical" relationship according to effect-size interpretation include only global training with technology use (r = .266) and global comfort with technology use (r = .309). The implications for this are that according to this particular sample, those who reported more training and greater comfort with technology also reported more use of other technology.

Limitations/Discussion

Several limitations exist for this particular study. Mailed questionnaire designs always introduce the possibility of respondent misunderstanding and delivery to unintended participants. Parallel but not identical sampling procedures were used in all three states. This raises concern about the representative nature of the sample; however, the size of the sample mitigates this limitation to some degree. In addition, the weakness of this particular instrument lies in a lack of extensive validity testing or piloting. One must be cautious when making inferences from results based on this instrument.

IMPLICATIONS FOR PROFESSIONAL SCHOOL COUNSELORS

The importance of this study to the field of school counseling is connected to the technological literacy of school counselor practice. If the societal trend toward greater dependence on technology for communication and collaboration continues at the current accelerated pace, school counselors will be required to continue increasing their use of technology. Following are implications for counseling practice.

1. Most school counselors are comfortable with using computers; however, a majority of these professionals are anxious about using a variety of software. Therefore, actual hands-on experiential work with new software may increase comfort levels among school counselors.

2. The majority of school counselors in the study had a high comfort level with using e-mail and indicated that they were at least somewhat comfortable with all aspects of e-mail use. The professional implication for this finding may very well be an increase in the reliance upon e-mail for job-related tasks such as scheduling. In addition, practical methods of communicating to stakeholders through e-mail and considerations regarding the ethical use of electronic communication may need to be discussed at professional conferences.

3. The most common type of technology reportedly used by the respondents was a VCR and monitor (85%). This may be indicative of transfer from home technology use to use in the workplace because of comfort through familiarity. Perhaps training in the use of such technologies as data projectors and digital video will increase their utility for school counselors.

4. The most popular type of computer training reported by this sample included outside or continuing education courses. The implication for this finding is twofold. First, school counselor preparation programs must begin to include training in technology usage for their students to be effective school counselors. The finding that the degree of technology training had an effect on the predicted comfort level of school counselors regarding technology usage supports this premise. Second, professional organizations must be cognizant of selecting or soliciting technology training workshops for their annual conference programs.

5. The affective variable of comfort with use of technology appeared to be a more critical determinant of school counselor use of computers than age or years of experience.

6. School counselors with greater comfort levels and more training were more apt to use a variety of software. Thus, exposure and experience appear to increase usage.

CONCLUSION

Challenges exist for school counselors who are transferring technology skills into practice to meet the demands of comprehensive school counseling programs and the developmental needs of students. Before the school counseling profession can address such issues with the goal of advancement, it must know the current state of technology training, comfort, and usage by practicing professional school counselors. The results of this study indicate that the majority of school counselors are already using technology to carry out their professional duties, and there still exists a need for further technology training for practicing school counselors.

References

American School Counselor Association. (2002). The ASCA national model: A framework for school counseling programs. Alexandria, VA: Author.

Cabaniss, K. (2002).Computer-related technology use by counselors in the new millennium. Journal of Technology in Counseling, 2(2). Retrieved December 5, 2005, from http://jtc.colstate.edu/vol2_2/index.htm

Casey, J. A. (1995). Developmental issues for school counselors using technology. Elementary School Guidance & Counseling, 30, 26-34.

Edwards, Y, Portman, T., & Bethea, J. (2002). Counseling student computer competency skills: Effects of a technology course in training. Journal of Technology in Counseling, 2(2). Retrieved December 5, 2005, from http://jtc. colstate.edu/vol2_2/index.htm

Hebert, T. P., & Neumeister, K. L. S. (2001). Guided viewing of film: A strategy for counseling gifted teenagers. Journal of Secondary Gifted Education, 14, 224-235.

Kuranz, M. (2002). Cultivating student potential. Professional School Counseling, 5, 172-179.

LaTurno-Hines, P. (2002). Student technology competencies for school counseling programs. Journal of Technology in Counseling, 2(2). Retrieved December 5, 2005, from http://jtc.colstate.edu/vol2_2/index.htm

Moore, R. L. (1992). Computer applications by Arkansas school counselors in conducting K-12 guidance and counseling programs. Dissertation Abstracts International, 52, 2824. (UMI No. AAC9204727)

Morgan, G. A., Gliner, J. A., & Harmon, R. J. (2006). Understanding and evaluating research in applied and clinical settings. Mahwah, N J: Lawrence Erlbaum Associates.

Owen, D. W., Jr., & Weigel, W. J. (1999). Computer utilization by school counselors. Professional School Counseling, 2, 170-182.

Quinn, A. C., Hohenshil, T., & Fortune, J. (2002). Utilization of technology in CACREP approved counselor education programs. Journal of Technology in Counseling, 2(2). Retrieved December 5, 2005, from http://jtc.colstate.edu/ vol2_2/index.htm

Sabella, R. A. (2000). School counseling and technology. In J. Wittmer (Ed.), Managing your school counseling program: K-12 strategies (pp. 337-357). Minneapolis, MN: Educational Media Corporation.

Sabella, R. A., & Booker, B. L. (2003). Using technology to promote your guidance and counseling program among stakeholders. Professional School Counseling, 6, 206-213.

Sabella, R. A., & Halverson, B. (n.d.). Building virtual communities in school counseling. Unpublished manuscript, Florida Gulf Coast University. Retrieved June 5, 2004, from http://www.schoolcounselor.com/pubs/building% 20virtual%20communitites%20in%20school% 20counseling.pdf

Sabella, R. A., & Isaacs, M. (2002, January/February). Personal digital assistants: School counselors beam into the 21st century. ASCA School Counselor. Retrieved June 5, 2004, from http://www.schoolcounselor.com pubs/ hand%20held%20computers%20in%20school% 20counseling.pdf

Sears, S. J., & Granello, D. H. (2002). School counseling now and in the future: A reaction. Professional School Counseling, 5, 164-171.

Tyler, J. M., & Sabella, R. A. (2004). Using technology to improve counseling practice. Alexandria, VA: American Counseling Association.

Van Horn, S. M., & Myrick, R. D. (2001). Computer technology and the 21st century school counselor. Professional School Counselor, 5, 124-130.

Laurie A. Carlson, Ph.D., is an assistant professor, Counseling and Career Development, Colorado State University, Fort Collins. E-mail: laurie, carlson@ colostate.edu

Tarrell Awe Agahe Portman is an assistant professor, Division of Counseling, Rehabilitation and Student Development, University of Iowa, Iowa City.

Jan R. Bartlett is an assistant professor, Counseling Psychology and Community Counseling, Oklahoma State University, Stillwater.
Table 1. Intercorrelations of Technology Use, Computer Use, Global
Comfort, Global Training, Years Counseling, and Years Teaching

Measure TU CU GC GT

1. Technology use (TU) --
2. Computer use (CU) .214 ** --
3. Global comfort (GC) .309 ** .230 ** --
4. Global training (GT) .266 ** .092 .178 ** --
5. Years counseling (YC) .124 * -.128 * -.042 -.074
6. Years teaching (YT) .244 ** -.023 -.019 .030

Measure YC YT

1. Technology use (TU)
2. Computer use (CU)
3. Global comfort (GC)
4. Global training (GT)
5. Years counseling (YC) --
6. Years teaching (YT) .247 ** --

Note. Listwise, N = 281.

* p < .05, two-tailed. ** p < .01, two-tailed.
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Title Annotation:PERSPECTIVES FROM THE FIELD
Author:Bartlett Jan R.
Publication:Professional School Counseling
Geographic Code:1USA
Date:Feb 1, 2006
Words:3586
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