Children who are blind and visually impaired are expected by law (IDEA, 2004) to receive free, appropriate education just to meet their unique needs and to help them participate fully, the traditional curriculum has been expanded to include areas such as orientation and mobility, assistive technology, communication, vocational, and social skills (Corn, Hatlen, Huebner, Ryan and Sil-ler, 1995; Hatlen, 1996). However, it can be a challenge to fit these in-dividualised educational opportunities of the ex-panded core curriculum into the average school day. It is important to ensure that instructional time and resources are wisely spent. The “No Child Left Behind Act” (NCLBA, 2002) man-dates that educators consider evidence- based research when making choices for instructional interventions. The purpose of this study was to add to the evidence base regard-ing orientation and mo-bility (O&M) instruction. Specifically, this study provides a description of receipt of O&M by ele-mentary age children and addresses ques-tions about the associa-tion of O&M instruction with student performance of activities that are directly related to mobility activities
Orientation is defined as the process of using the senses to establish one’s position and relationship to objects within an environment. Mobility is the capacity, readiness, and ability to move throughout an environment (Hill and Ponder, 1976). Experts identify a wide range of O&M skills necessary for individuals with blindness and low vision, so the specific O&M skills on an IEP can vary (Wall Emerson and Corn, 2006). One key practice found in all O&M instruction is the attempt to use the natural environment for instruction and assessment. That environment can include the child’s home, classroom, school, and community. As part of O&M instruction, students are encouraged to travel safely, independently, efficiently, and gracefully through all appropriate environments. Experts in the field suggest that O&M instruction provides “fundamental and enabling life skills” (Huebner and Wiener, 2005, p. 579). A Cochrane Collaboration Review, completing a systematic search of all published research in O&M, was done in 2006 (Virgili and Rubin, 2009) and resulted in the conclusion that available research based evidence was unable to show that participation in O&M by adults was beneficial beyond normal recreation activities. In contrast, a study of adults’ spatial perception (Fiehler, Reuschel and Rosler, 2009) found that adults who were congenitally blind and started O&M instruction before the age of 12 demonstrated spatial perception that neared the levels of sighted peers, whereas those who began O&M training after age 12 had lower scores. The authors suggested that spatial abilities can be improved for blind individuals through early O&M training. These contradictions between professional opinion and the research evidence about whether O&M training is necessary and beneficial, provided the impetus for the current research.
Elementary-age students with vision loss may receive O&M instruction as a related service within their individualised educational plans (lEPs) (IDEA, 2004). The process typically begins with an assessment by an O&M specialist. An O&M assessment generally includes: a) an interview with the student, family, and teacher, b) a review of the student’s educational and medical files, c) completion of an age-appropriate assessment tool, d) observation of the student during natural routines, e) travel in familiar and unfamiliar environments, and f) demonstration of selected O&M activities (Fazzi and Petersmeyer, 2001). Assessments should be individualised and allow students the opportunity to demonstrate their highest level of independence on all mobility related activities.
The practice of O&M has kept its focus on the unique needs of the individual, and the field has not developed and tested standardised assessment tools to measure change in these skills. This is a limiting factor for conducting large scale studies of O&M efficacy. Additionally, Sauerburger (2010) expressed a concern that O&M professionals have been slow to respond to the need for curriculum updates and revisions. Many individuals and small groups have developed informal assessment protocols that are used within a particular school or area, but research-based standardised tools are not available. One widely distributed O&M assessment tool for elementary age students is available as a companion to the comprehensive curriculum, Teaching Age-Appropriate Purposeful Skills (TAPS) (Pogrund et al., 1995). It is designed to assess each student’s ability to perform a wide range of functional mobility tasks across a variety of environments. The assessment by the O&M specialist is shared with the IEP team, and if the team determines that O&M instruction is needed, goals and objectives are developed to meet the specific needs of the individual student and added to their IEP. Assessment is expected to be an ongoing part of all O&M instruction to evaluate whether progress is being made in the student’s ability to demonstrate O&M related skills (Fazzi and Petersmeyer, 2001). This criterion-referenced measure provides a starting place for the development of standardised tools, but as of yet, none have been developed.
Orientation and mobility curricula have been developed to meet the specific needs of elementary age students by individual practitioners, schools, and districts by using key resources in the field (Hill and Ponder, 1976; Jacobson, 1993; LaGrow and Weessies, 1994). As an example, the TAPS curriculum (Pogrund et al., 1993) was developed with the specific needs of students with blindness or low vision in mind. The areas of instruction target abilities to: a) travel using a sighted guide to all familiar locations; b) travel indoors using rote routes; c) travel to other school areas or other buildings using rote routes; d) create new routes between familiar places indoors; e) execute a route, given a set of verbal directions to an unfamiliar location within one building; f) execute a route, given a set of verbal directions to an unfamiliar location in another building; g) locate an unfamiliar place by using numbering systems; h) orient self to an unfamiliar room; i) solicit help to orient self to a building; and j) solicit help to orient self to a high school campus or to a workplace.
Progress on specific goals and objectives is reported to parents on a regular basis, with a new IEP developed by the IEP team annually. Assessments are generally administered by the same O&M specialist who has provided instruction. They are often designed by the instructor and do not use a standardised assessment tool. Although it is typical for O&M instructors to document progress for each student after O&M instruction, there are no standardised scores that verify those findings.
The low incidence of visual impairment and the heterogeneity of the population of people with visual impairments have made research with this group very difficult. As reported in 2007, less than .05 percent of children ages 6 to 21 were designated as having a visual impairment and receiving services for visual impairments under part B of the IDEA (U.S. Department of Education, 2007). The combination of these factors leaves O&M specialists with limited curriculum, intervention, or assessment resources that meet the rigorous standard of having the support of research-based evidence. Often the highest level of evidence an O&M instructor can bring with a resource is the support of expert opinion. The purpose of the current study was to add to the research base by using a large national dataset to ask whether participation in O&M is associated with demonstration of ability to perform O&M related activities for students who are elementary age.
The study involved students in the U.S. with visual impairment who participated in the Special Education Elementary Longitudinal Study (SEELS), which included a nationally representative sample of elementary and middle school students with disabilities. The sampling was taken from 245 local education authorities and 35 state-supported special schools from 1999 through 2004. It included children who ranged from 6 to 12 years of age during the first year of the study (Godard et al., 2007). Sampling methods ensured that the cases included were representative of the U.S. special education population and age cohort. Disability categories were over-sampled in this design, allowing these data to be weighted and allowing the user to make generalisations nationally. The full sample included 1,110 students with visual impairment. The sample for this study varied for different analyses, but at most, included 850 students.
The SEELS dataset was obtained from the U.S. Office of Special Education Programs. The dataset contains electronic data from parent interviews, direct or alternative assessments, school program surveys, school characteristics surveys, and teacher surveys. Data were collected longitudinally in three waves conducted over five years. For this study, the variable of participation in O&M was taken from waves 1, 2, and 3 of the parent survey. The variables for performance of mobility activities for the current study were taken from the school program survey. Demographic variables were found in the parent survey and cross index sections of the database.
This was a correlational study, using secondary data analysis of variables from the SEELS dataset using SPSS version 17. The researcher obtained approval from the Human Subjects Institutional Review Board at Western Michigan University for conducting the analysis (HSIRB #10-07-09). The first question addressed in this study asked: What is the demographic makeup of the students with visual impairments who had the opportunity to participate in O&M, and those who did not? The study then addressed the primary question: Is participation in O&M associated with improved performance of O&M activities? A third question asked if there was an association between the time (i.e., in which wave) an individual receives O&M training and performance of O&M activities.
To answer research question one, regarding student characteristics most associated with receiving O&M services, cross-tabulations were performed to examine characteristics of students who received O&M, including the existence of multiple disabilities and frequencies of other demographic variables. The independent variables were taken from the parent survey and the cross index sections of SEELS and included: visual impairment as a primary disability, number of multiple disabilities, age, gender, grade, income, ethnicity, and urbanicity (urban, suburban or rural). The dependent variable was participation in O&M during the past 12 months, taken from the parent survey.
Chi Square analyses were conducted to analyse data to answer the research question: Is participation in O&M associated with performance of O&M related activities? Participation in O&M was taken from the parent survey, and the O&M related activities were taken from the school program survey. For each of 10 O&M activities, the respondent indicated how well the student performed each of the mobility activities. The levels of response included: “Not very well,” “pretty well,” “very well.” The mobility activities were those outlined in the TAPS curriculum (Pogrund et al., 1995), and included questions about the child’s ability to:
travel using a sighted guide to all familiar locations
travel indoors using rotely learned routes,
travel to other school areas or other buildings using rotely learned routes,
create new routes between familiar places indoors,
execute a route, given a set of verbal directions to an unfamiliar location within one building,
execute a route, given a set of verbal directions to an unfamiliar location in another building,
locate an unfamiliar place by using numbering systems,
orient self to an unfamiliar room,
solicit help to orient self to a building, and
solicit help to orient self to a high school campus or to a workplace
To answer the third research question, regarding whether there was an association between the time the child begins O&M training and performance on mobility activities, chi square analyses were conducted. The independent variable for the analysis was the time O&M instruction began, which was identified from the parent survey. The times a student could have begun O&M instruction were in wave 1 or in wave 3. These data represent a difference of two years. Wave 2 data were not included because during that wave of parent surveys many of the parents of students who are blind and visually impaired did not respond, so much of the data in wave 2 is missing.
Descriptive summary statistics (Table 1) were generated for the 850 students in the SEELS who were identified by their parents as having a visual impairment or blindness. Variables describing the study or blindness. Variables describing the study sample included the demographic variables: blindness, visual impairment, age, grade, gender, ethnicity, income, urbanicity, and number of disabilities.
Demographics of Students with Visual Impairments Who Received O&M (N = 850)
Characteristic | N | Wave 1 |
CI | N | Wave 2 |
CI | N | Wave 3 |
CI |
---|---|---|---|---|---|---|---|---|---|
Vision | |||||||||
Blind | *290 | 65.2 | .67-.72 | 146 | 23.9 | .12-.38 | *211 | 59.7 | .52-.66 |
Vis. Impaired | *723 | 46.2 | .42-.50 | *146 | 17.5 | .12-.25 | *716 | 37.6 | .34-.41 |
Age | |||||||||
7-9 (8-10) 11-12 | 267 | 42.3 | 3.7-5.0 | 48 | 20.8 | .10-.36 | 237 | 39.2 | .32-.45 |
10-12(11-13) 13-14 | 366 | 46.7 | .46-.40 | 77 | 19.5 | .09-.28 | 288 | 39.6 | .33-.44 |
13-14(14-16) 15-17 | 105 | 50.5 | .40-.61 | 29 | 13.8 | .01-.31 | 228 | 36.4 | .30-.43 |
Grade | |||||||||
Ungraded | 58 | 60.3 | .47-.73 | 10 | 20.0 | -.14--.64 | 70 | 35.7 | .21-.44 |
1-3(1-4) 1-5 | 170 | 42.4 | .35-.50 | 37 | 16.2 | .04-.30 | 99 | 41.4 | .33-.53 |
4-5 (5-6) 6-8 | 267 | 46.1 | .40-.52 | 60 | 25.0 | .13-.36 | 374 | 39.8 | .34-.44 |
6&up 7&up 9-12 | 208 | 44.2 | .37-.51 | 40 | 15.0 | .02-. 24 | 210 | 35.7 | .29-.43 |
Gender | |||||||||
Male | 447 | 43.4 | .38-.48 | 86 | 21.1 | .12-.31 | 467 | 36.4 | .31-.40 |
Female | 291 | 49.1 | .43-.55 | 68 | 14.7 | .07-.26 | 286 | 42.0 | .36-.47 |
Ethnicity | |||||||||
White | *468 | 48.1 | .43-.53 | 103 | 19.4 | .11-.27 | 483 | 38.9 | .34-.43 |
African American | *126 | 40.5 | .33-.51 | 30 | 30.0 | .13-.49 | 122 | 36.1 | .28-.45 |
Hispanic | *113 | 48.7 | .38-.57 | 14 | 0 | - | 112 | 42.0 | .32-.51 |
Other | *30 | 20.0 | .52-.38 | 6 | 0 | - | 35 | 28.6 | .14-.47 |
Income | |||||||||
25,000 and under | 253 | 42.7 | .37-.49 | 64 | 20.3 | .12-.34 | 236 | 36.4 | .30-.42 |
25,001-50,000 | 213 | 48.8 | .42-.56 | 34 | 17.6 | .05-.34 | 193 | 38.3 | .31-.45 |
Over 50,000 | 232 | 44.8 | .39-.52 | 55 | 18.2 | .05-.27 | 308 | 39.6 | ,34-.45 |
Urbanicity | |||||||||
Rural | *33 | 39.4 | .22-.57 | 9 | 22.2 | -.17-.73 | *81 | 40.7 | .30-.52 |
Suburban | *309 | 40.1 | .35-.46 | 59 | 15.3 | .06-.26 | *327 | 30.3 | .25-.35 |
Urban | *267 | 51.5 | .45-.56 | 151 | 17.9 | .12-.31 | *340 | 45.6 | .39-.50 |
# of Disabilities | |||||||||
0 | - | - | - | - | - | 6 | 50.0 | .07-1.07 | |
1 | 248 | 44.0 | .37-.50 | 45 | 24.4 | .11-.38 | 345 | 40.6 | .35-.45 |
2 | 175 | 49.1 | .42-.58 | 28 | 14.3 | .00-.28 | 174 | 30.5 | .22-36 |
3 | 107 | 45.8 | .35-.55 | 22 | 9.1 | -.04-.22 | 113 | 40.7 | .31-.50 |
4 | 83 | 39.8 | .27-.50 | 24 | 20.8 | .03-.38 | 68 | 44.1 | .31-.56 |
5 | 68 | 1.5 | .42-.67 | 14 | 14.3 | -.07-.35 | 24 | 37.5 | .18-.61 |
6 | 33 | 42.4 | .22-.60 | 9 | 22.2 | -.12-.56 | 15 | 26.7 | .01-.52 |
7 | 16 | 31.3 | .01-.52 | 2 | 0 | - | 4 | 75.0 | .05-1.55 |
8 | 4 | 75.0 | .46-1.55 | 1 | 0 | - | 3 | 33.3 | 1.10-1.77 |
9 | 2 | 50.0 | 5.85-6.85 | 1 | 0 | - | 1 | 100 | - |
10 | 2 | 100 | - | - | - | - | - | - | - |
Note. *p< .05 and 95% confidence intervals (CIs)
Number of Disabilities for each student were reported from the parent survey
These variables were analysed using chi square statistics to identify significant associations of each variable with whether a student participated in O&M. Significant findings are indicated in Table 1 with an asterisk. There were significant associations between receipt of O&M and blindness, visual impairment, ethnicity, and urbanicity (school in an urban, suburban or rural area) (see Table 2 for X2 values). Students, who were identified as blind, were more than 2 times as likely to get O&M as their visually impaired peers. Students in urban areas were between 1.6 and 1.9 times more likely to receive O&M than their peers living in suburban areas. Students in urban areas were between 1.2 and 1.6 times more likely to receive O&M than their peers in rural areas. When odds ratios were calculated for the significant association related to ethnicity found in wave 1, White and Hispanic students received O&M at about the same rate. These students received O&M at almost one and a half times the rate of their African American peers. During wave 2, there was a steep decline in the number of participants. Due to the low numbers available for analysis, a decision was made to include only wave 1 and wave 3 in the remaining analyses.
Demographic Variables Associated with Receipt of O&M
X2(dF, N) | P | ||
---|---|---|---|
Wave 1 | Blindness | X2(1, N=290) = 73.276 | p = .000 |
Visual Impairment | X2(1, N=723) = 4.64 | p = .037 | |
Urbanicity | X2(2, N=609) = 9.334 | p = .009 | |
Ethnicity | X2(3, N=737) = 10.837 | p = .013 | |
Wave 2 | Visual Impairment | X2(1, N=146) = 4.716 | p. = .030 |
Wave 3 | Blindness | X2(1, N=211) = 55.653 | p = .000 |
Visual Impairment | X2(1, N=716) = 5.469 | p = .016 | |
Urbanicity | X2(2, N=748) = 16.745 | p = .000 |
Percentage of Student Activity Performance Associated with Time of O&M Instruction
Both | Wave 1 | Wave 3 | None | ||
---|---|---|---|---|---|
w1 - w3 | w1 - w3 | w1 - w3 | w1 -w3 | ||
Travel Using Sighted Guide: Familiar Locations | |||||
Not Very Well | 1.2 - 8.4 | 7.1 - 8.4 | 0 - 0 | 4.5 - 0 | |
Pretty Well | 19.8 - 14.5 | 35.7 - 16.7 | 0 - 15.8 | 22.7 - 22.6 | |
Very Well | 79 - 77.1 | 57.1 - 75.0 | 100 - 84.2 | 72.7 - 77.4 | |
n | 81 83 | 28 12 | 7 19 | 22 21 | |
Wave 1, X2 (6) = 8.92 p = .178 | Wave 3, X2 (6) = 5.24, p = .514 | ||||
Travel Indoors: Rotely Learned Routes | |||||
Not Very Well | 5.1 - 4.6 | 9.4 - 4.0 | 0-6.7 | 3.8-1.4 | |
Pretty Well | 28.3 - 30.6 | 18.8-16.0 | 7.7-6.7 | 17-11.3 | |
Very Well | 66.7 - 64.8 | 71.9-80.0 | 92.3 - 86.7 | 79.2 - 87.3 | |
n | 99 108 | 32 25 | 13 30 | 53 71 | |
Wave 1, X2 (6) = 7.18 p = .304 | Wave 3, X2 (6) = 16.91 p = .010* | ||||
Travel to Other Areas: Other Learned Routes | |||||
Not Very Well | 13.4 - 12.4 | 20.0 - 7.7 | 0 - 6.9 | 7.8 - 4.4 | |
Pretty Well | 32.0 - 34.0 | 13.3 - 19.2 | 28.6 - 20.7 | 15.7 - 14.7 | |
Very Well | 54.6 - 53.6 | 66.7 - 73.1 | 71.4-72.4 | 76.5 - 80.9 | |
n | 97 97 | 30 26 | 14 29 | 51 68 | |
Wave 1, X2(6) = 12.36, p = .054 | Wave 3, X2 (6) = 14.64 p = .023* | ||||
Create New Routes: Familiar Places Indoors | |||||
Not Very Well | 27.3 - 28.7 | 15.6 - 12.0 | 6.3 - 13.3 | 18.5 - 9.5 | |
Pretty Well | 38.6 - 33.0 | 40.6 - 32.0 | 25.0 - 6.7 | 16.7 - 20.3 | |
Very Well | 34.1 - 38.3 | 43.8 - 56.0 | 68.8 - 80.0 | 64.8 - 70.3 | |
n | 88 94 | 32 25 | 16 30 | 54 74 | |
Wave 1, X2(6) = 18.51, p = 005* | Wave 3, X2 (6) = 28.12 p = .000* | ||||
Execute Route within Building with Verbal Directions | |||||
Not Very Well | 36.0 - 32.2 | 23.1 - 12.5 | 6.7 - 11.1 | 27.5 - 17.8 | |
Pretty Well | 25.6 - 33.3 | 34.6 - 50.0 | 40.0 - 25.9 | 17.6 - 19.2 | |
Very Well | 38.4 - 34.4 | 42.3 - 37.5 | 53.3 - 63.0 | 54.9 - 63.0 | |
n | 86 90 | 26 24 | 15 27 | 51 73 | |
Wave 1, X2 (6) = 9.87 9.87, p = .130 | Wave 3, X2 (6) = 22.43 p = .001* | ||||
Execute Route in another Building with Directions | |||||
Not Very Well | 30.8 - 41.6 | 42.9 - 21.7 | 14.3 - 11.12.2010 28.6 - 44.4 | 16.0 - 21.7 | |
Pretty Well | 28.2 - 35.1 | 14.3 - 52.2 | 16.0 - 17.4 | ||
Very Well | 41.0 - 23.4 | 42.9 - 26.1 | 57.1 - 44.4 | 68.0 - 60.9 | |
n | 39 77 | 14 23 | 7 27 | 25 69 | |
Wave 1, X2 (6) = 7.05, p = .316 | Wave 3, X2 (6) = 32.24 p = .000* | ||||
Locate Unfamiliar Place by Numbering System | |||||
Not Very Well | 58.5 - 47.8 | 47.1 - 30.0 | 22.2 - 21.7 | 51.6 - 22.6 | |
Pretty Well | 30.2 - 32.8 | 23.5 - 40.0 | 33.3 - 47.8 | 16.1 - 15.1 | |
Very Well | 11.3 - 19.4 | 29.4 - 30.0 | 44.4 - 30.4 | 32.3 - 62.3 | |
n | 53 67 | 17 20 | 9 23 | 31 53 | |
Wave 1, X2 (6) = 10.30, p = .113 | Wave 3, X2 (6) = 29.69 p = .000* | ||||
Orient Self to Unfamiliar Room | |||||
Not Very Well | 31.9 - 30.5 | 44.1 - 8.0 | 6.7 - 3.3 | 8.1 - 10.5 | |
Pretty Well | 36.2 - 43.2 | 17.6 - 60.0 | 33.3 - 33.3 | 33.9 - 20.9 | |
Very Well | 31.9 - 26.3 | 38.2 - 32 | 60 - 63.3 | 58.1 - 68.6 | |
n | 94 95 | 34 25 | 15 30 | 62 86 | |
Wave 1, X2 (6) = 25.89, p = .000* | Wave 3, X2 (6) = 47.51 p = .000* | ||||
Solicit Help to Orient Self to Building | |||||
Not Very Well | 39.6 - 36.4 | 33.3 - 18.2 | 16.7 - 20.8 | 18.0 - 19.4 | |
Pretty Well | 25.3 - 33.0 | 33.3 - 40.9 | 50.0 - 16.7 | 32.0 - 20.8 | |
Very Well | 35.2 - 30.7 | 33.3 - 40.9 | 33.3 - 62.5 | 50.0 - 59.7 | |
n | 91 88 | 30 22 | 12 24 | 50 72 | |
Wave 1, X2 (6) = 10.40, p = .109 | Wave 3, X2 (6) = 19.00 p = .004* | ||||
Solicit Help to Orient Self to Campus or Workplace | |||||
Not Very Well | 66.7 - 42.9 | 45.5 - 16.7 | 20.0 - 16.7 | 31.3 - 18.4 | |
Pretty Well | 14.3 - 21.4 | 36.4 - 33.3 | 0 - 16.7 | 6.3 - 16.3 | |
Very Well | 19.0 - 35.7 | 18.2 - 50.0 | 80.0 - 66.7 | 62.5 - 65.3 | |
n | 21 56 | 11 12 | 5 18 | 16 49 | |
Wave 1, X2 (6) = 16.26, p = .012* | Wave 3, X2 (6) = 14.22 p = .027* |
Note. Significance *p<.05, w1-w3 = percentage of students receiving that rating during wave 1 followed by the percentage of students receiving that rating during wave 3.
Table 3 shows the percentage of students at each performance level in wave 1 and wave 3 for each of the 10 O&M skills broken down by whether students received O&M in both waves, just during wave 1, just during wave 3, for each of the 10 O&M skills broken down by whether students received O&M in both waves, just during wave 1, just during wave 3, or never. Chi squares were performed on data for all the children in the sample using four levels of receipt of O&M (during both waves, during wave 1 only, during wave 3 only, and none) and on three levels (“not very well,” “pretty well,” and “very well”) for performance on an O&M activity. These analyses were performed for each of the 10 O&M activities. Table 3 shows the number of students for whom there was a performance measure in waves 1 and 3 and the percentage of these in each of the performance categories.
Chi Square analyses revealed that students who did not receive O&M services were rated as performing better on O&M activities. At wave 3, there were significant associations between no participation in O&M and higher performance for all activities except travel using a sighted guide (see Table 3). In wave 1, higher performance ratings on activities including travel to other areas, other learned routes, create new routes, familiar places indoors, orient self to unfamiliar room, and solicits help to orient self to campus or workplace were associated with no O&M training at statistically significant levels. Chi Square results are found in Table 3, for example, for travel using a sighted guide in familiar locations, Wave 1, X2(6) = 7.18, p = .304 and Wave 3, X2 (6) = 5.24, p = .514.
From this analysis, a few trends could be identified in wave 1. Looking at the first four skills, receiving training seems to increase the number of students who do “very well.” Within the next four skills, those same children, who received training during wave 1 only, increase in the occurrences of “pretty well,” while decreasing in both “not very well” and “very well.” For the “soliciting help” skills, all students seemed to have a rating increase, whether they received O&M or not.
These findings led to a further inspection of the data. It became clear that a large percentage of the students who did not receive O&M (and presumably were not judged to need such services) were rated as performing “very well” for all 10 activities. This introduced an artifact that showed not receiving O&M to be associated with the highest performance ratings. Because these students began as high performers and stayed in that category, they acted as a constant within the analysis. When the sample of students was limited to those receiving O&M during wave 1 and those who received it during wave 3, the numbers became too small (less than 100) to perform the planned multilevel hierarchical regression analysis. Chi squares were conducted instead to answer the question: Is when you begin O&M associated with performance of O&M activities? No significant associations were found. The findings were as follows: travel using a sighted guide: familiar indoor locations, x2 (2) = 1.66, p =.435, travel indoors, rotely learned routes, x2 (2) = 1.34, p =.051, travel to other areas, rotely learned routes, x2 (2) = .03, p = .986, create new routes to familiar indoor places, x2 (2) = 5.97, p = .051, executes route within building with verbal directions, x2 (2) = 3.61, p = .164, execute route within a building with directions, x2 (2) = 2.19, p = .334, locate familiar place by numbering system, x2 (2) = .43, p = .805, orients self to unfamiliar room, x2 (2) = 5.41, p = .067, solicits help to orient self to building, x2 (2) = 3.45, p = 1.78, solicits help to orient self to campus or workplace, x2 (2) = 1.19, p = .551. Performance of two of the activities approached statistical significance, but in this analysis, student performance was not associated with O&M instruction that occurred at a specific time. Orientation and Mobility instruction earlier does not impact skill performance for students whose performance is reported on during their elementary years.
A more in-depth study of the performance ratings followed. Table 4 shows the counts of students and the change in their performance on each O&M skill between wave 1 and wave 3. The five possible options for any individual were to drop two categories (-2; from very well to not very well), drop one category (-1), remain the same (0), increase one category (+1), or increase two categories (+2). The highest percentages for both groups of students (those that got O&M training and those that did not) are those that stayed the same from wave 1 to wave 3, followed by students whose ratings increased by one level and then by those whose ratings decreased by one level. The numbers whose ratings either decreased or increased two levels were about the same, and at similar rates for both the students with no O&M and the O&M participants (including those who received O&M at any time during the study). This distribution reveals, essentially, similar rates of change in ratings between the two groups. Figure 1 represents the summary impacts found in Table 4.
Orientation and Mobility instruction and its association with performance of mobility activities for elementary age children
Because top performers would have less room for change, the top performers for both groups were removed from the dataset. This left in the dataset only those students who could improve in performance from wave 1 to wave 3. This total number of students are the highest points on the compound bars in Figure 2. It includes the numbers for students who did and did not participate in O&M during waves 1 and 3 with performance ratings for each of the 10 activities that were either 1 or 2, leaving room for improvement. Those receiving O&M outnumbered those who were not receiving O&M by more than two times.
Students change in performance for O&M activities
For students who did not receive any O&M instruction, it was possible to detect the number of students who received the highest 2 rankings during wave 3. Figure 2 shows the number of students who began with a rank of 1 or 2 (“not very well” or “pretty well”). The shaded section of each bar shows the students who completed wave 3 with scores in the 2 or 3 categories (“pretty well” or “very well”). The clear part of the bar denotes the students who stayed the same or received lower ratings. Up to 100% of the students increased their performance on at least two activity levels. These data show that students who are participating in O&M activities are demonstrating im-proved performance within each skill area.
A national picture of elementary age students who received O&M instruction between 1999 and 2004 is documented. The study showed that, for the most part, children across most of the identified demographic variables received O&M at equitable rates. In a time when there are chronic shortages of O&M instructors, it is surprising that no significant differences could be found by age, grade, gender, income, and number of disabilities. The study provided odds ratios, showing that students who are blind were receiving O&M at double the rate of their visually impaired peers. It can be expected that children who are blind participate in more O&M than their peers because they often demonstrate a more critical need and may require more compensatory skills to learn to become safe, efficient, independent, and graceful travellers.
Variance in Student Performance Ratings in Mobility Activities: Wave 1 to Wave 3 (no O&M = 125; O&M = 238)
Skill | O&M | -2 | % | -1 | % | 0 | % | 1 | % | 2 | % | missing |
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | no | 1 | 0.8 | 2 | 1.6 | 122 | ||||||
yes | 3 | 1.26 | 41 | 17.23 | 8 | 3.36 | 186 | |||||
2 | no | 2 | 1.6 | 18 | 14.4 | 2 | 1.6 | 1 | 0.8 | 102 | ||
yes | 10 | 4.20 | 55 | 23.11 | 15 | 6.30 | 158 | |||||
3 | no | 3 | 2.4 | 15 | 12 | 1 | 0.8 | 1 | 0.8 | 105 | ||
yes | 1 | 0.42 | 15 | 6.30 | 45 | 18.91 | 16 | 6.72 | 162 | |||
4 | no | 2 | 1.6 | 4 | 3.2 | 11 | 8.8 | 4 | 3.2 | 104 | ||
yes | 2 | 0.84 | 9 | 3.78 | 41 | 17.23 | 18 | 7.56 | 3 | 1.26 | 165 | |
5 | no | 4 | 3.2 | 12 | 9.6 | 5 | 4 | 1 | 0.8 | 103 | ||
yes | 3 | 1.26 | 8 | 3.36 | 44 | 18.49 | 15 | 6.30 | 168 | |||
6 | no | 3 | 2.4 | 4 | 3.2 | 3 | 2.4 | 115 | ||||
yes | 1 | 0.42 | 8 | 3.36 | 12 | 5.04 | 4 | 1.68 | 2 | 0.84 | 211 | |
7 | no | 1 | 0.8 | 2 | 1.6 | 3 | 2.4 | 2 | 1.6 | 1 | 0.8 | 114 |
yes | 4 | 1.68 | 2 | 0.84 | 22 | 9.24 | 10 | 4.20 | 3 | 1.26 | 197 | |
8 | no | 4 | 3.2 | 5 | 4 | 16 | 12.8 | 8 | 6.4 | 1 | 0.8 | 91 |
yes | 2 | 0.84 | 21 | 8.82 | 31 | 13.03 | 19 | 7.98 | 3 | 1.26 | 162 | |
9 | no | 1 | 0.8 | 4 | 3.2 | 11 | 8.8 | 5 | 4 | 1 | 0.8 | 98 |
yes | 6 | 2.52 | 10 | 4.20 | 21 | 8.82 | 15 | 6.30 | 5 | 2.10 | 181 | |
10 | no | 1 | 0.8 | 1 | 0.8 | 1 | 0.8 | 1 | 0.8 | 121 | ||
yes | 4 | 1.68 | 8 | 3.36 | 2 | 0.84 | 2 | 0.84 | 222 | |||
totals | no | 8 | 5 | 29 | 17 | 93 | 55 | 31 | 18 | 7 | 4 | |
yes | 23 | 4 | 86 | 15 | 320 | 56 | 122 | 21 | 18 | 3 |
Key: -2 signifies drop in 2 rating levels; -1 signifies drop in 1 rating level; 0 signifies no change;
1 signifies raise in 1 rating level; 2 signifies raise in 2 rating levels.
The results showed that less than 50% of students with visual impairments received O&M instruction. It is clear from this study that a few students may demonstrate high levels of performance of O&M activities, and therefore, may need only minimal O&M training. However, there are many more that have room to improve and may benefit from training if it were provided. Improved access to O&M in rural and suburban areas continues to be a need. More research may need to be done related to ethnicity, as indicated by the finding that one wave of data shows that children who are African American receive O&M at lower rates than their White and Hispanic peers.
The Chi Square analysis did not show an association using the variables in the SEELS dataset between receipt of O&M and improved O&M skills. Although, the results from this study showed that not receiving O&M instruction is associated with higher performance of some O&M activities, causality should not be assumed. Rather, this finding could be a result of several factors. It is likely that the students with visual impairment who demonstrate the highest level of travel skills are not being recommended for O&M. If that is the case, their good performance does not reveal anything about O&M training. We already know that most general-education students develop independent travel skills without the need of specialised training. However, many individuals with visual impairment struggle to become safe, proficient, and independent travellers. In those cases, individuals have enhanced their skills through direct instruction with an O&M specialist. The limit of these findings is they do nothing to inform us about the performance of those who may require O&M instruction to enhance their skills.
This study was not able to distinguish between O&M instruction that began during wave 1 and that which began at wave 3. That may simply be a limitation of this study. The question of when O&M instruction began was not directly reported and the study spanned only five years. When Fiehler, Re-ushcel and Rosler (2009) found O&M instruction at an earlier age to improve spatial perception for individuals with congenital blindness, they were testing adults, and only those who had received O&M and rated themselves as excellent travellers. In future research, rather than ratings that may be relative to a child’s age and for which no reliability has been establish, studies should include direct assessment of a child’s actual performance on specific orientation and mobility skills. This study pointed to the need for better measurement tools to directly assess O&M skills.
Because this study did not show an association between O&M instruction and performance of O&M skills, that fundamental question is left to be answered in future research. One approach may be to link the topics of O&M instruction and instructional strategies to improved performance of specific skills. That will require instructional curriculum and intervention practices that are repeatable and assessment tools that have the specificity and validity necessary to measure performance of O&M skills. If future studies are to include data from O&M assessments, it would be useful to have the tool standardised in its use. Tools that assess for individual skills sets need to be developed, validated, and implemented across the profession. The development and use of standardised assessment tools are vital if the curricula, intervention, or assessment resources in O&M are to meet the rigorous standards required by special education law.
The strengths of this study include the use of data from a large national sample of students with visual impairment. Also, the longitudinal nature of the study allowed research questions to look at change over time for individual students. Most importantly, it contained variables specific to the field of vision. For this study, the data on participation in O&M and the O&M activities with performance indicators across five years of development were found in a national database.
The limitations also relate to the database. The manner in which the variables were collected made it impossible to differentiate between the students who required O&M instruction to progress in their skill development, and those who were likely to progress in a similar fashion without intervention. It included no information about indicators related to the quantity or quality of O&M instruction received by each student. These variables may account for the variance in performance measures but could not be identified from the variables available in the dataset. The measures of performance were not taken from an assessment and were imprecise, which may have made the reporting unreliable. There was also no indication of which topics were covered during O&M instruction for each student. Thus, no direct correlation could be made between instruction in an area and performance of the skill. When the dataset was merged and limited to include only the students of interest, data for particular measures often were missing, making the numbers too small to perform the desired analysis and making questions about longitudinal change almost impossible to answer
The study revealed that elementary age children across the country were receiving O&M instruction at equitable rates across many of the demographic variables. Those who are blind received it at twice the rate as those with low vision. Students within rural areas, as well as those who are African American were receiving O&M instruction at lower rates than their peers. Not receiving O&M instruction was shown to be associated with higher performance of mobility activities, but no causality should be assumed. Follow up studies may include the use of assessment data to identify the specific contribution O&M instruction has on performance of functional mobility for individuals with blindness and low vision. If researchers wish to investigate the efficacy of O&M services, other research methods may be required that exert more controls than a national data collection effort can accomplish. That is, understanding the association between performance of O&M activities and participation in O&M may require a more directed study of interventions, using standardised assessments and curricula.