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Characteristics Of Individuals Who Provide Disability Related Services To Students With Disabilities
It can be seen in Table 2 that the sex distribution for individuals responsible for providing services to students with disabilities indicates that women outnumber men by a ratio of 2:1 (i.e., 110 women and 46 men = 71% women). Values in Table 3 show that the ratio was similar in all institution types (anglophone college: 72% female, francophone college: 59%, anglophone university: 73%, francophone university: 67%).
Participants had an average of 9.25 years of experience working with students with disabilities (with a median of 9.50 and a mode of 10 years). However, years of experience ranged from less than 1 year to 26 years. A 3-way ANOVA (2 Sex (Female/Male) x 2 Institution (College/University) x 2 Language (Anglophone/Francophone) presented in Table 3 showed that anglophone service providers had more experience (M = 9.86 yr) than francophone service providers (M = 7.41 yr), F(1,143)=4.93, p<.05. Males (M = 10.73) had more experience than females (M = 8.60), F(1,143)=4.29, p<.05. The main effect for institution was not significant. Nor were any of the interactions.
See Table 3 in Appendix A
Overall, participants indicated that they were not especially knowledgeable about adaptive computer technologies. The mean score was 3.70 (SD = 1.52) on a 6-point scale, with higher scores indicating being more knowledgeable. Indeed, the scores of 12% of participants suggest that they were not at all knowledgeable, while only 9% of scores suggest that the respondent was an expert. A 3-way ANOVA (2 Sex (Female/Male) x 2 Institution (College/University) x 2 Language (Anglophone/Francophone) presented in Table 3 indicates that while there were no significant differences between males and females or between individuals from colleges and universities, francophone respondents felt that they were less knowledgeable (M = 2.97) than their anglophone colleagues (M = 3.93), F(1,143)=5.83, p<.05. Additional details are available in Table 3.
See Table 3 in Appendix A
Enrollment: Students Registered to Receive Disability Related Services in Canada's Colleges and Universities
Participants responded to the following 2 questions.
Data in Table 4 indicate that the mean percentage of students with disabilities at participating institutions was 3.58%. However, there were great discrepancies among institutions (range: <.01% to 35.64%, SD = 4.20%, median = 2.21%). Similarly, although average overall enrollment at participating postsecondary institutions was 8606, again there was great variability (range = 40 to 45,000, SD = 9559, median = 128). The same was true of the mean number of students with disabilities enrolled. While the mean was 215 students with disabilities, scores ranged from 1 to 1800 (SD = 262).
See Table 4 in Appendix A
It should be noted that an alternate form of calculation of the percentage of students with disabilities at the same 156 institutions results in a different, lower value. The computation above is based on calculating the percentage of students with disabilities for each institution and taking the mean. An alternate technique is to divide the average number of students with disabilities at the 156 institutions (M = 215) by the average overall enrollment in those schools (M = 8606). This results in the percentage dropping to 2.50%. This occurs because there are more colleges in the sample. While smaller than universities, these have a larger proportion of students with disabilities. Therefore, the two types of averages are likely to be different. To ensure that comparable figures are used when comparing studies, it is important to ascertain which computational method was used.
In addition, it should be noted that 15 of the 198 institutions on the AUCC or ACCC lists (8%) indicated that although they had a student body, they currently had no students with disabilities. To better understand the reasons for the large variability in scores we examined variables related to enrollment of students with disabilities in a variety of ways.
Differences between colleges and universities. In general, it can be seen in Table 5 that mean overall enrollment of colleges (M = 5648) was significantly lower than that of universities (M = 13,455), t(152)=5.30, p<.001. The total number of students with disabilities, however, was very similar (M = 211 and M = 217, respectively), t(150)=.13, p=ns. It is, therefore, not surprising that t-test results indicate that a significantly larger percentage of college students have a disability (M = 4.44%) than university students (M = 2.11%), t(150)=4.10, p<.001.
See Table 5 in Appendix A
Differences among provinces and territories. Summary data on student enrollments broken down by province and college versus university status are available in Table 4. Means and standard deviations in Table 4 show that, with the exception of 1 outlier score, the average percentage of students with disabilities at participating institutions ranges from 2% to 6% in all provinces. The outlier is Québec, where the percentage of students with disabilities is substantially lower: approximately 0.55% (i.e., only 1/2 of 1%). A 1-way ANOVA (10 Provinces) comparison of all provinces indicates that there was a significant difference among the provinces in the proportion of their students with disabilities, F(9,148)=4.27, p<.001. The Tukey HSD test shows that only 2 scores are significantly different (p<.05) from each other. These show that Québec enrolled a significantly lower percentage of students with disabilities than either Alberta or Ontario. None of the other provinces were significantly different from each other. To ascertain whether this difference was due to language or to differences in provincial policies we conducted a series of analyses on provincial and linguistic variables.
Colleges and universities in Québec and the rest of Canada. First, we examined differences between institutions in Québec and in provinces in the rest of Canada by conducting a series of 2-way analysis of variance (ANOVA) comparisons (2 Institution (College/University) x 2 region (Quebec/Rest of Canada)). Dependent variables were: total enrollments, enrollments of students with disabilities, and percentage of students with disabilities. Of interest are main effects for region and interactions with the region variable. Means and test results presented in Table 6 indicate that the average enrollment in postsecondary institutions in Québec (M=7886) and the rest of Canada (M = 8795) do not differ significantly. There was, however, a significant interaction of region and institution on this variable showing that, on average, Québec's colleges are relatively smaller and Québec's universities relatively larger than those in the rest of Canada, F(1,150)=4.13, p<.05.
See Table 6 in Appendix A
The situation was somewhat different when enrollment of students with disabilities was considered. Here, data in Table 6 show only that the mean number of students with disabilities enrolled in postsecondary institutions is significantly lower in Québec (M = 48) than in the rest of Canada (M = 263), F(1,148)=15.93, p<.001.
Perhaps the most compelling difference was found on the percentage of students with disabilities. Results in Table 5 show a significant main effect for region, F(1,148)=23.66, p<.001. In addition, the interaction effect approached significance, F(1,148)=3.80, p=.05. As the means and Figure 1 indicate, Québec has a substantially smaller percentage of students with disabilities both at the college (M = 0.62% vs. M = 5.66%) as well as at the university levels (M = 0.41% vs. M = 2.56%), with the difference being most pronounced in colleges.
See Figure 1 in Appendix B
Linguistic differences across Canada. Are the scores in Québec related to linguistic differences or to differences in provincial policies and practices? To answer this question we conducted another series of ANOVAs, this time using language rather than region (2 Institution (College/University) x 2 Language (Anglophone/Francophone)). Of interest are main effects for language and interactions with the language variable. Data in Table 6 and Figure 2 show that although none of the interactions were significant, the results were very similar to those on region, except that differences were generally somewhat smaller.
See Figure 2 in Appendix B
Because most of the francophone institutions are from Québec (N=31 vs. N=8 outside the province), the previous analysis was not a compelling test. Therefore, we conducted 3 series of comparisons examining the dependent variables in: francophone institutions in Québec and elsewhere; anglophone institutions in Québec and elsewhere; and in anglophone and francophone institutions in Québec. We conducted separate evaluations for francophone colleges and for francophone universities in Québec and the rest of Canada because the number of francophone universities outside Québec (N=2) was too low for inferential statistical analysis.
In the case of francophone colleges inside and outside Québec we performed a t-test. The significance test here is very stringent because of the sample sizes. The number of francophone colleges was 21 in Québec but only 6 in the rest of Canada. Means and test results in Table 7 show that while mean overall enrollment in francophone colleges in Québec (M = 3093) was significantly greater than in francophone colleges elsewhere in Canada (M = 515), t(25)=3.41, p<.01, the mean number of students with disabilities enrolled did not differ significantly (M = 17 and 23, respectively), t(25)=.32, p=ns. The test on the percentage of students with disabilities in Québec colleges, however, approached significance and showed that the mean percentage of students with disabilities was substantially lower in Québec francophone colleges than in francophone colleges outside Québec (M = 0.59% and 4.91%, respectively), t(25)=3.83, p<.001.
See Table 7 in Appendix A
It was not appropriate to conduct inferential statistical tests when evaluating francophone universities and anglophone colleges and universities inside and outside Québec because of sample sizes. For example, there were only 2 francophone universities outside Québec and only 2 anglophone colleges and 2 anglophone universities inside Québec. Means and standard deviations for these comparisons are, however, available in Table 7.
In general, these show that on average, universities in Québec, both francophone and anglophone, have substantially greater overall enrollment than those in the rest of Canada. Anglophone colleges in Québec and the rest of Canada are, however, similar in size. When it comes to the percentage of students with disabilities, however, regardless of language or college or university status, the proportion of students with disabilities in Québec institutions is substantially lower. These relationships can best be seen in Table 8 and Figure 3, which compare anglophone and francophone colleges and universities inside and outside Québec and illustrate the percentage of students with disabilities enrolled in a bilingual institution as well as in distance education. As Figure 3 clearly shows, both the province as well as the language are related to the percentage of students with disabilities, with both province and language having independent effects. This results in Québec francophone institutions having the lowest proportions of students with disabilities.
See Table 8 and Figure 3 in Appendix B
Synthesis. The results show that there is a smaller proportion of students with disabilities in Québec colleges and universities than in institutions in the rest of Canada. Analyses which attempted to unconfound language and province factors were only partially successful in answering the question," Is the difference due to language or to differences in provincial policies?" because of the limited number of anglophone institutions inside Québec and the limited number of francophone institutions outside Québec. The closest approximation to an answer than we can propose is that most of the difference is due to provincial policies and practices, with a smaller but independent role for language.
Important differences were found between colleges and universities, suggesting that data from colleges and universities should be analyzed separately. In addition, there were substantial differences between anglophone and francophone institutions as well as between institutions inside and outside Québec.
Because there is no way to unconfound province of origin and language, and because there were important differences found, here we will analyze data for anglophone and francophone colleges and universities separately. Although "Québec" and "francophone" are confounded, as are "rest of Canada" and "anglophone," the alternative of doing province by province analyses on anglophone and francophone colleges and universities is impractical due to sample size limitations. Thus, all references to linguistic differences could also be construed as differences between Québec and the other provinces - at this point there is no way to examine these separately.
Is The Size Of The Institution Related To The Percentage Of Students With Disabilities?
Because of substantial differences in total enrollments we wanted to find out whether institution size was related to the proportion of students with disabilities. To explore this possibility we correlated the percentage of students with disabilities with total enrollment for all institutions as well as for anglophone and francophone colleges and universities separately. Pearson product-moment correlation coefficients in Table 9 indicate a weak but significant negative relationship between overall enrollment and the percentage of students with disabilities, r(152)=-.229, p<.01. This indicates that the larger the institution, the smaller the percentage of students with disabilities. When this relationship was examined separately for colleges and universities, the coefficients show that while the relationship was significant for anglophone institutions, it was nonsignificant for francophone universities and only approached significance for francophone colleges.
See Table 9 in Appendix A
In a previous investigation we found that the relationship between the size of Québec's colleges and the percentage of students with disabilities was not significant (ref ITAC). Therefore, the analysis was redone based on the 21 Québec francophone colleges in the current sample. In this case, the correlation between the size of Québec's colleges and the percentage of students with disabilities was not significant, r(19)=-.055, p=ns. This suggests that the findings which showed that the correlation approached significance for francophone colleges is due to the influence of colleges outside Québec. Thus, it appears that there is a significant negative relationship between institution size and the percentage of students with disabilities for anglophone colleges and universities, with larger institutions enrolling smaller proportions of students with disabilities. In the case of francophone institutions, there is no significant association between institution size and the proportion of students with disabilities.
Institutions With And Without Computer And Adaptive Computer Technologies On Campus For Students With Disabilities
Of the 154 non-distance education respondents, 132 (86%) indicated that they had equipment for students with disabilities and 22 (14%) indicated that they did not. It can be seen in Table 10 that there were few - and nonsignificant - differences between comparable anglophone and francophone institutions. However, colleges (81%) were significantly less likely than universities (93%) to have computers for their students with disabilities, X2(1)=4.00, p<.05.
See Table 10 in Appendix A
To determine whether institutions which did and did not have computer equipment for students with disabilities on campus differed in enrollment, we conducted a series of independent t-tests on enrollment statistics. Because virtually all universities had students with disabilities, we did this only for colleges. While the means in Table 11 suggest that colleges with equipment were larger, had more students with disabilities, and had a larger proportion of students with disabilities than those which did not have equipment, the t-tests on these variables were not significant. Given the enormous standard deviations, this is not surprising.
See Table 11 in Appendix A
Only 23% of respondents indicated that they had a multidisciplinary advisory/steering committee which deals with the accessibility of computer technologies for students with disabilities. It can be seen in Table 12 that while 34% of universities had such a committee, only 17% of colleges did so. Neither distance education institution had a committee. Linguistic differences favored anglophone institutions, although the differences were not significant.
See Table 12 in Appendix A
All advisory/steering committees had a representative of the office for students with disabilities. Most (88%) had an administrator, a student with a disability (81%) and a faculty member (78%). However, very few had nondisabled students (31%). It is especially noteworthy that only 1/4 (25%) of committees had staff from computer services.
Table 12 reveals that the priority placed upon computer related services was moderately high (when weighted against all other disability-related support services), with a mean of 2.25 (SD =.87) on a 4-point scale where 1 indicates very high priority, 2 indicates high priority, 3 indicates low priority, and 4 indicates very low priority). Table 12 also shows that most colleges and universities accorded high priority to computer related services (65% of institutions accorded this either "high" or "very high" priority), but that universities accorded somewhat higher priority to computer related services than colleges. The 2 distance education institutions followed suit, with the distance education university placing higher priority (score = 2) than the distance education college (score = 3). Francophone and anglophone institutions were quite similar. A 3-way ANOVA (2 Institutions x 2 Language x 2 Computer Technologies on Campus (Yes/No)) showed no significant main effects or interactions. This indicates that colleges and universities with and without computer technologies on campus did not differ on priority rating.
Provincial/regional computer technology loan programs to institutions. Of the 132 institutions which indicated that they had computer technologies on campus for their students, 35 (27%) indicated that a provincial/regional loan program supplied some of the computer and/or adaptive computer technologies on campus. Mean response to the question inquiring about perceptions of the adequacy of resources provided by the loan program in meeting the needs of students with disabilities was 4.72 (SD = 1.43) on a 6-point scale, indicating considerable satisfaction. There was no significant difference on this variable between colleges and universities or between anglophone or francophone institutions. Indeed, only 16% of respondents indicated that the equipment provided failed to meet students' needs.
Good Institutional Computer and Adaptive Computer Technologies
A key item was rating, on a 6-point Likert scale, on the following item.
"Overall, the computer and/or adaptive computer technology needs of students with disabilities at my institution are adequately met."
It can be seen in Table 13 that the computer related needs of students were moderately well met at their institutions (mean = 4.20 on a 6-point scale, SD = 1.40, range 1-6, median = 5). Means and the 2-way ANOVA (2 Institution x 2 Language) presented in Table 13 shows that there was no significant difference between colleges and universities or between anglophone and francophone institutions. The interaction between language and institution was also nonsignificant.
See Table 13 in Appendix A
Correlates of good institutional computer and adaptive computer technologies. To explore institutional factors important in adequately meeting the computer related needs of students we computed a series of Pearson product-moment correlation coefficients between scores on variables in the structured interview and scores on the item concerning the overall rating about how well students' computer related needs were met. This was done for all institutions combined as well as for anglophone and francophone colleges and universities separately. It can be seen in Table 14 that neither the size of the institution, nor the number or percentage of students with disabilities was related consistently to the adequacy of meeting students' computer and adaptive computer technology needs.
See Table 14 in Appendix A
Comparisons of non distance education institutions with (N = 132) and without computers (N=22) on campus for students with disabilities on overall adequacy in meeting students' computer and adaptive computer technology needs are presented in Table 15. These show that, surprisingly, there was no significant difference between institutions that did and those that did not have equipment on campus for their students, t(136)=1.63, p=ns.
See Table 15 in Appendix A
Correlations between scores on variables in the structured interview and scores on the item concerning the overall rating about how well students' computer related needs were met are presented in Table 16. Coefficients based on all institutions combined as well as on anglophone and francophone colleges and universities separately show the following.
See Table 16 in Appendix A
Aspects important in meeting the computer related needs of students with disabilities are:
To evaluate whether having computer equipment on campus for students with disabilities was related to these aspects we conducted a series of t-tests on appropriate variables. Means and test results presented in Table 15 show that only 1 of 13 comparisons were significant. After a Bonferroni correction to the alpha level, even this failed to attain significance.
The presence of computer equipment on campus for students with disabilities was not related to factors important in meeting the computer related needs of students
"Actual Situation": Adequacy Of Various Aspects Of Computer Technologies At Colleges and Universities In Meeting The Computer Related Needs Of Students With Disabilities
Respondents’ scores on the adequacy of various aspects of computer technologies at colleges and universities in meeting the computer related needs of students with disabilities are presented in Table 13.
Funding for the institution's computer technologies. Scores in Table 13 indicate a mean of 3.50 on a 6-point scale on a question about the adequacy of funding for the institution's computer technologies, with higher scores indicating more favorable responses. In fact, 19% of respondents strongly disagreed with the statement that the level of funding at their institution for computer and adaptive computer technologies was adequate in meeting students’ needs, with an additional 20% disagreeing moderately. 6% disagreed slightly. Only a little more than half of the respondents indicated that funding was adequate.
Access to adaptive computer technologies. Table 13 also shows that of the factors related to access, the hours of access to computers and the extent to which they were up-to-date were reasonably good (scores greater than 4 on a 6-point scale). The availability of adaptive computer technologies in general use computer laboratories was however, seen as less than adequate (score =< 3). Only 76 institutions indicated that they had an off campus computer technology loan program for students.
Internet/library and adaptive computer technologies. When it came to internet and library access issues, the data in Table 13 indicate that internet based distance education was seen as inadequate in meeting the needs of students with disabilities (score =< 3). It should be noted, however, that many participants reported that their institutions did not offer internet based distance education courses.
Support for adaptive computer technologies. Table 13 also shows that the only favorable aspect of support for adaptive computer technologies was the administration's positive response (score greater than 4 on a 6-point scale). Other aspects of support were seen as somewhat or very problematic. For example, available technical support, the presence of an adaptive computer technologist on campus, and the ability of computer support staff to service adapted computer technologies had ratings between 3 and 3.49, as did opportunities for employees to learn about computer and adaptive technologies. The degree to which individuals who provide services to students with disabilities are consulted when computer infrastructure decisions are made and the existence of an advisory/steering committee that deals with computer accessibility were seen as inadequate in meeting the needs of students with disabilities. As noted earlier, only 23% of institutions had an advisory/steering committee that deals with computer accessibility.
Faculty and computer accessibility. Table 13 also reveals that, according to the participants, computer based teaching materials used by professors are only minimally accessible. In addition, when faculty are trained to use computer technologies in their courses, making their courses accessible to students with disabilities is rarely part of the curriculum (score less than 2).
Outside the institution factors. As for factors that pertained to variables outside the institution, it can be seen in Table 13 that disability service providers generally felt that outside agencies provide students with appropriate equipment, although they were somewhat less positive about the training provided to students by these agencies.
Similarities and differences between anglophone and francophone colleges and universities. Mean scores on the adequacy of various aspects of computer technologies in meeting the needs of students with disabilities at anglophone and francophone colleges and universities are also presented in Table 13. Here we present F test results for a series of 2-way multivariate and univariate analysis of variance comparisons (MANOVAs and ANOVAs) to compare linguistic and institutional factors (2 Institution (College/University) x 2 Language (Anglophone/Francophone). The means and the test results indicate that while institution type was important in some cases (a near significant finding on 1 of the 5 MANOVAs), language was clearly a more important variable (significant findings on 3 of the 5 MANOVAs and on the single ANOVA not included in any of the MANOVAs). None of the MANOVA interaction effects were significant, indicating that language and institution type did not interact to affect scores. Examination of the ANOVAs shows significant or near significant findings only on 6 of the 22 institution variables investigated. When language was examined, 12 of the 22 comparisons were significant or approached significance. In general the results suggest that universities fare somewhat better than colleges (5 of the 6 significant or near significant comparisons favor universities) and francophone institutions fare better than anglophone institutions (10 of the 11 comparisons favor francophone institutions). Figure 4 illustrates the findings.
See Figure 4 in Appendix B
"Actual" vs. "desired situation:" adequacy of various aspects of computer technologies at colleges and universities in meeting the computer related needs of students with disabilities. To help compare "actual" and "desired" situations when it comes to the adequacy of meeting the computer related needs of students with disabilities Table 17 provides "actual situation" means as well as uncorrected means for the series of "desired situation" items ("It would be helpful if…"). It should be noted, however, that "desired situation" scores need to be interpreted in the context of the "actual situation" in each institution. That "desired situation" scores need to be interpreted in the light of actual realities is made evident by test results in Table 17. These show that scores on 11 of the 12 "paired" items (i.e., paired "actual situation" and "desired situation" items) are significantly negatively correlated with each other (e.g., the less likely it is that computer support personnel can service adaptive computer technologies, the more desired it is for them to be able to do so). Table 17 also shows that all 12 paired t-tests comparing "actual" and "desired" situation means were significant. All of these show that "desired" scores are significantly greater than "actual" ones (e.g., the mean "actual situation" score for the item that deals with the presence of a specialist in adaptive computer technologies on campus is 3.06 while the mean for the "desired situation" score is 5.28). The most pronounced differences were on items related to support for adaptive computer technologies.
See Table 17 in Appendix A
What do individuals responsible for providing services to students with disabilities who have poor "actual situations" feel would be most helpful for them? To answer this question we divided the sample, based on their responses to the "actual" item, into those whose "actual situation" did or did not meet the needs of students with disabilities (i.e., score between 4 and 6 vs. score between 1 and 3). We then compared the scores of the 2 groups using independent t-tests. Means and test results presented in Table 18.
See Table 18 in Appendix A
The findings indicate that there are differences which are significant or approach significance on 10 of the 12 variables examined. These indicate that service providers whose existing conditions fail to meet the needs of students with disabilities wish to have the situation rectified.
In particular, those whose current situation fails to meet the needs of students with disabilities want:
In addition to comparing the means, it is also interesting to examine the proportion of individuals who feel that their "actual situation" on specific variables does or does not meet students’ needs. In this regard it is noteworthy that, as can be seen in Table 19, there were similar percentages of respondents who indicated that their situation meets the computer related needs of their students on 5 of the 12 items. There were substantially more respondents who indicated that the needs of students were met when it came to 2 variables. On the remaining 5 items, substantially more respondents indicated that their situations did not meet the needs of their students.
See Table 19 in Appendix A
Examination of the proportion of individuals who felt that their "actual situation" on specific variables did or did not meet students’ needs in anglophone and francophone colleges and universities is presented in Table 20. These indicate that participants in francophone institutions, both colleges and universities, were more satisfied than their anglophone counterparts on most of the variables examined. Anglophone universities were the least satisfied with their existing situations.
See Table 20 in Appendix A
Wish list of personnel who provide services to students with disabilities. It can be seen in Table 21 that, overall, disability service providers wish that students were better equipped and prepared for the postsecondary experience. For example, 3 of the 4 highest ranked items express the wish for students to be more knowledgeable computer users, for students to be able to get subsidized computer technologies for home use more easily; and for students to have better access to computers off campus. The next group of highly ranked items relate to the need for accessibility of computer based teaching materials used by professors and for support services.
When only the responses of participants who felt that their current situation does not meet the needs of students with disabilities were considered, the top ranked item was the need for more favorable response from administration. The need for accessible materials from professors, for a person to train students, for more space for the equipment, for more professional development time and more funding top the list. Additional details are presented in Table 20.
To compare wish lists of anglophone and francophone service providers from colleges and universities a 2-way between groups MANOVA was performed on the 16 "desired situation" items. Table 22 shows that both main effects and the interaction were significant. Therefore, the MANOVA was followed by a series of 2-way ANOVAs (2 Institution (College/University) x 2 Language (Anglophone/Francophone)).
See Table 22 in Appendix A
Table 22 shows that the main effect of language was significant for all 16 variables. In all instances participants from anglophone institutions had higher scores than those from francophone institutions (i.e., anglophone service providers wanted more services/resources). The main effect of institution was significant on 8 comparisons and a 9th comparison approached significance. Here the results are inconsistent, with some comparisons showing colleges to have higher scores while others showing that universities have higher scores. This is explained, in part by the finding that 12 of the 16 interaction effects were significant while a 13th approached significance. These all show that while anglophone institutions had higher scores than francophone institutions, this is especially true of universities. Figure 5 presents these data most clearly.
See Figure 5 in Appendix B
Because of discrepancies in language and institution type, Table 23 presents the wish lists of anglophone and francophone colleges and universities separately.
See Table 23 in Appendix A
Faculty And Staff With Disabilities
Participants responded to the following questions:
We are also interested in studying faculty, professionals and other employees at colleges and universities. To the best of your knowledge, how many employees with disabilities, including yourself if applicable, are there at your institution? _______
If at least 1:
a. ____ If they need computer-related services/accommodations, are you (your office/service) expected to provide these services to them? Yes/No
If "no" to item "a":
b. ____ If not you (your office/service), whom do you think does or is supposed to provide services if these are needed?
Presence on campus. To study the presence of faculty and staff with disabilities at Canadian colleges and universities two variables were examined. First we obtained a frequency count of the number of employees in each institution. Institutions varied tremendously in size. Therefore, we also examined the ratio of number of employees with disabilities to the total student enrollment.
Only 106 disability service providers were able to answer the question about the number of individuals with disabilities employed on campus. It can be seen in Table 24 that there was an average of 13 employees with disabilities per institution reported (SD = 28). The range of scores was 0 to 200, with a median of 3 and a mode of 0. Comparable proportion data (i.e., number of employees with disabilities per 1000 students) are as follows. The range of scores is 0/1000 to 20/1000, with a mean of 2/1000, a median of 0.9/1000 and a mode of 0/1000 employees with disabilities. Data in Table 24 provide a breakdown of the number and proportion of employees with disabilities in the various provinces and territories of Canada. These indicate that the 2 provinces with the greatest proportion of employees with disabilities are New Brunswick (4/1000) and British Columbia (4/1000). Those with the lowest proportion are Québec (.6/1000) and Prince Edward Island (0/1000). Distance education institutions also fared poorly in this regard, with a proportion of only 1/1000.
See Table 24 in Appendix A
Data in Table 25 indicate that, as was the case for students with disabilities, both the number and the proportion of employees with disabilities in francophone institutions is significantly lower (F(1,99)=9.95, p<.01, and F(1,99)=5.73, p<.05, respectively). Neither the number nor the proportion of faculty and staff with disabilities in colleges and universities differed significantly. Nor were the interactions significant.
See Table 25 in Appendix A
Who should provide computer related services/accommodations to faculty and staff with disabilities? It can be seen in Table 26 that although many individuals were uncertain about what would happen if an employee with a disability needed computer related services/accommodations, of those who were able to answer 23% indicated that they or their office would provide this. 77% indicated that this was not the case. The Chi Square test indicates no significant difference as a function of either language X2=.605, p=ns, or institution, X2=.362, p=ns.
See Table 26 in Appendix A
So who, then, is expected to provide computer related services to employees with disabilities? 90 respondents provided 100 responses. These are detailed in Table 27 and indicate that the most frequently cited response (cited by 37 respondents) is "Human Resources." This is followed by the employee's department (cited by 13 respondents) or the employee himself or herself (cited by 10 respondents). Eight disability service providers did not know. Other responses noted by several (4 to 7 respondents) are: computer services; the institution's administration; an employment equity/human rights committee; rehabilitation services external to the institution; and occupational health and safety.
See Table 27 in Appendix A