Orientation and mobility instruction and its association with performance of mobility activities for elementary age children

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

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.

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.

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.

Figure 1

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.

Figure 2

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.

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 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.