Appendix E

Best Practices in Educating Students With Low Vision

Kay A. Ferrell

Since 2002, policymakers, parents, and educators have called for increased accountability in how public funds are spent in K-12 education. Ultimately, this accountability focuses on student outcomes, and whether teachers teach effectively enough for students to make progress. Federal legislation requires educators to use “research-based practice,” instructional methods that are proven through research to bring about change in student behavior or performance.

Teachers of students with visual impairments and orientation and mobility specialists are not exempt from the expectation that they will use research-based practices when they instruct students with visual impairments. The problem, however, as several authors have documented (Ferrell, Buettel, Sebald, & Pearson, 2006; Ferrell, Mason, Young, & Cooney, 2006; Kelly & Smith, 2011; Parker, Grimmett, & Summers, 2008; Parker & Pogrund, 2009; Wright, Harris, & Sticken, 2010), is that the low-prevalence nature of visual impairment, combined with the heterogeneity of the population itself, makes scientifically-based research difficult to implement. These systematic searches of the literature in visual impairment have failed to identify more than a few studies that met the standards of scientifically-based research. The foundation for research-based practice in the education of students with low vision is somewhat thin.

At the request of the American Printing House for the Blind, the National Center on Severe & Sensory Disabilities (NCSSD) at the University of Northern Colorado systematically examined the educational research literature on low vision stimulation, development, and devices, seeking evidence to support teaching procedures commonly practiced by teachers of students with visual impairments and orientation and mobility specialists. The criteria used to select the evidence were strict, but they followed the definition of “scientifically-based research” contained in the No Child Left Behind Act of 2001 (2002): (a) published in an English language peer-reviewed journal between the years of 1964-2008, where the research (b) involved an intervention, (c) included a comparison group, and (d) studied participants between the ages of birth and 21 years who were visually impaired.

Through an extensive online and manual search process, 2,011 articles or other pieces of literature from 1964-2008 were located; but only 46 articles met the specified criteria. In the final analysis, however, only 31 studies were included because effect sizes could not be computed for 15 studies. Studies that used single subject designs were included in the analysis if there were at least five participants.

Effect size is an important statistic because it measures the size of the difference between the experimental and control groups and makes it possible to compare one study to another study (Thalheimer & Cook, 2002). Effect size is generally described as small (.2), moderate (.5), and large (≥ .8) (Cohen, 1988), but an effect size of .40 or larger is considered the minimum necessary to demonstrate educational significance (Forness, Kavale, Blum, & Lloyd, 1997; Walberg, 1986). For this analysis, a statistical correction was calculated on the effect sizes to account for the small sample sizes.

The Studies

The 31 qualifying articles were categorized by research topic. Fifteen (48.4%) of the qualifying studies addressed the use of low vision devices to improve reading speed and/or comprehension; 7 (22.6%) examined the use of various interventions to promote visual development, some of which used the precursor to the Barraga Visual Efficiency Program (Barraga & Morris, 1980). Two studies (6.5%) investigated regular and large print size; 2 (6.5%) examined the use of black light to enhance visual recognition; and another 2 (6.5%) studies examined print and background colors as accommodations. Another 3 (9.7%) studies did not fit any of these categories and were considered individually.

Studies were grouped together based on outcomes, and mean effect sizes were calculated if possible. Note, however, that in traditional meta-analysis, the interventions and outcomes should be equivalent; this analysis takes considerable latitude in grouping studies. For example, “improvement in visual acuity” was measured in multiple ways that were not always equivalent. The results of these somewhat arbitrary groupings are included in the tables that follow.

Low vision devices

The 15 qualifying studies that investigated low vision devices utilized different interventions and different outcome measures. Whenever possible, these outcomes are grouped together in Table E.1, and a mean effect size was calculated. Since Forness et al. (1997) states that an effect size must attain .40 to be educationally significant, only outcomes with an effect size greater than .40 are included in this table.

Table E.1 Outcome measures, interventions, sample sizes, and effect sizes for studies involving low vision devices

Outcome Intervention Study N Mean Effect Size
(if applicable)
Improvement in visual acuity 3 different head-mounted devices with full magnification vs. one device not head-mounted Geruschat, Deremeik, & Whited, 1999 10 3.833
Individualized training program with low vision devices (LVDs) Howell, 1980 18
Provision of low vision devices Schwartzenberg, Merin, Nawratzki, & Yanko, 1988 15
Increased score on Visual Efficiency Scale Individual prescription, training, and use of low vision devices Jose & Watson, 1978 6 .803
Increased reading speed (CCTV only) Training with CCTV LaGrow, 1981 6 .803
Speed-reading training with head still method to use CCTV Rossi, 1980 10
Increased student perception of abilities on distance and near vision tasks Training in low vision devices Corn, Wall, & Bell, 2000 27-34 .714
Better quality of projective test protocols in terms of sequencing events and logical reasoning Administration of test items via CCTV Brand, 1976 18 .656
Increase in amount of reading (# of books and # of pages) Provision of low vision devices Lackey, Efron, & Rowls, 1982 55 .517
Increased reading speed (all devices) Training in low vision devices Corn et al., 2000 27-34 .582
Corn, Wall, Jose, Bell, Wilcox, & Perez, 2002 185
Training in use of magnifiers Farmer & Morse, 2007 16
Training with CCTV LaGrow, 1981 6
Different mounting systems for low vision devices Lusk, 2007 5
Speed-reading training with head still method to use CCTV Rossi, 1980 10
Increased reading speed (with devices other than CCTV) Training in low vision devices Corn et al., 2000 27-34 .542
Corn et al., 2002 185
Training in use of magnifiers Farmer & Morse, 2007 16
Spectacle-mounted near magnification optical devices Lusk, 2007 5
Lowered teachers' expectations for student performance on distance and near tasks Training in low vision devices Corn et al., 2000 27-34 .498
Improved attitude toward low vision devices Training with bioptic lens Kelleher, 1974 5 .476
Improved letter identification Adjustment of CCTV monitor by instructor Helnsley, 1986 7 .427
No difference in achievement on WRAT Spelling, Reading, and Arithmetic Training with bioptic lens Kelleher, 1974 5 .422

Effect of interventions utilizing low vision devices. Low vision devices (including closed circuit television systems), with and without formal training programs, resulted in improved visual acuity, increased reading speed, and an increase in the total amount of reading (in pages and in books) (Corn et al., 2000, 2002; Farmer & Morse, 2007; Geruschat et al., 1999; Howell, 1980; LaGrow, 1981; Lackey et al., 1982; Lusk, 2007; Rossi, 1980; Schwartzenberg et al., 1988).

Visual stimulation programs

Seven qualifying studies examined implementation of multiple procedures designed to enhance and/or improve use of vision. Some used a systematic training program, such as Barraga and Morris (1980) or Frostig (Frostig, Horne, & Miller, 1964), while others used specific procedures, such as the APH Light Box III materials or a binaural sensory aid. Results in this category were mixed. Whenever possible, outcomes are grouped together in Table E.2, and a mean effect size was calculated. Again, following the criterion of Forness et al. (1997), only outcomes with an effect size greater than .40 are included in this table.

Table E.2 Outcome measures, interventions, sample sizes, and effect sizes for visual development studies

Outcome Intervention Study N Mean Effect Size
(if applicable)
Mental scores ratio on Bayley Scales of Infant Development (Bayley, 1969) maintained over course of treatment Visual stimulation program Leguire, Fellows, Rogers, Bremer, & Fillman, 1992 29 1.476
Improved visual evoked responses (increase in patterned and flash VER latency) Visual stimulation program Leguire et al., 1992 29 1.435
Increased scores on test or inventory Planned program of visual stimulation Barraga, 1965 20 1.400
Training using Light Box III materials Moore, 1989 31
No differences in test or inventory score Visual function training using Barraga & Morris (1980) vs. Frostig (1964) Lopez-Justicia & Martos, 1999 20 1.124
Improved visual acuity Binaural sensory aid (BSA) exposure Ferrell,1984 18 1.045
Visual function training using Barraga & Morris (1980) vs. Frostig (1964) Lopez-Justicia & Martos, 1999 20
Systematic structured program of planned visual stimulation (investigator-designed) Mamer, 1999 10
Lower performance on cross-modal transfer task BSA exposure Ferrell, 1984 18 1.027
No differences in any outcome based on binaural sensory aid exposure BSA exposure Ferrell, 1984 18 .860
No difference in frequency of gaze shifts after training Systematic structured program of planned visual stimulation (investigator-designed) Mamer, 1999 10 .638
Leveling-sharpening significantly increased after training Tachistoscopic training to improve visual perception Geffen, 1971 21 .555
No difference in frequency of reaching to stimuli Systematic structured program of planned visual stimulation (investigator-designed) Mamer, 1999 10 .476
No difference in frequency of eye blinks after training Systematic structured program of planned visual stimulation (investigator-designed) Mamer, 1999 10 .400

Effects of interventions employing visual development programs and procedures. The effects of visual development programs and procedures are mixed. Some studies demonstrate increased scores on test inventories (Barraga, 1965; Moore, 1989), increased visual acuity (Mamer, 1999), and increased visual evoked responses (Leguire et al., 1992), while other studies found no differences in test scores (Lopez-Justicia & Martos, 1999). Some studies attributed increases in visual acuity following treatment to maturation (Ferrell, 1984; Lopez-Justicia & Martos, 1999).

Print size

Two qualifying studies specifically examined print size. Sykes (1971) concluded that students with better acuity experienced less visual fatigue when using large print. Bock (1971) concluded that large print was more effective in facilitating reading skills than standard print used with a magnifier. Whenever possible, outcomes are grouped together in Table E.3, and a mean effect size was calculated. Again, following the criterion of Forness et al. (1997), only outcomes with an effect size greater than .40 are included in this table.

Table E.3 Outcome measures, interventions, sample sizes, and effect sizes for studies involving print size

Outcome Intervention Study N Mean Effect Size
(if applicable)
VI elementary school readers read faster and more accurately in large print than in standard print with magnification Large print and standard print with magnification Bock, 1971 44 .753
Overall performance significantly better with large print

Students read faster and more accurately in large print than in all other conditions
Standard (10 pt.) vs. large print (18 pt.) Sykes, 1971 41 .697
Standard print vs. standard print with magnification vs. large print vs. large print with magnification Bock, 1971 44
VI elementary school readers read faster and more accurately with standard print than standard print with magnification Standard print vs. standard print with magnification Bock, 1971 44 .595

Effects of comparisons of large print, standard print, and standard print with magnification. Large print results in faster and more accurate reading performance in comparison to standard print with and without magnification.

These findings appear to contradict the qualifying studies in Table E.1 that examined the effects of low vision devices. In those studies, standard print was used with magnification; Bock (1971) and Sykes (1971) concluded that standard print with and without magnification resulted in poorer performance. It is also possible the training program usually associated with the provision of low vision devices may be responsible for the difference in performance.

Black light

Two (2) qualifying studies investigated the use of black light conditions with students who were visually impaired. Whenever possible, outcomes are grouped together in Table E.4, and a mean effect size was calculated. Again, following the criterion of Forness et al. (1997), only one study is included in this table as it had an effect size greater than .40.

Table E.4 Outcome measures, interventions, sample sizes, and effect sizes for studies involving black light

Outcome Intervention Study N Effect Size
Best response in black light/ fluorescent orange stimulus/black background; participants with higher acuity achieved higher scores Black light + fluorescent orange stimulus LaGrow, Leung, & Leung, 1998 30 1.219

Effect of interventions utilizing black light. Black light enhanced visual recognition behaviors for students with higher acuities in one study.

Another black light study did not achieve an effect size of .40 or greater and is not shown in Table E.4. That study found that drawings copied under black light conditions were completed faster but less accurately (Tavernier, 1992). Based on these limited results, it is not clear if there is educational value to the use of black light. Black light by definition requires an altered environment that does not resemble either the home or school environment. Studies are needed that investigate the generalization of visual skills developed under black light conditions to everyday environments and tasks.

Color accommodations

Two (2) qualifying studies examined interventions that are most easily described as changes in the presentation of materials, where the text or background color was changed and compared to the standard black text on white background. Myers (1969) examined more combinations of text and background colors than did Gardner (1985), and the results are given in Table E.5. Outcomes are grouped together, and a mean effect size was calculated. Table E.5 includes all outcomes, including those with effect sizes less than .40.

Table E.5 Outcome measures, interventions, sample sizes, and effect sizes for studies involving color accommodations

Outcome Intervention Study N Mean Effect Size
(if applicable)
Black text on white background = significantly better recognition and focus at greater distances White text on yellow background Myers, 1969 30 .837
Black text on purple background .746
Yellow text on white background .679
Purple text on blue background .612
Blue text on black background .580
Purple text on black background .587
Red text on blue background .837
Blue text on purple background .746
White text on blue background = better recognition and focus at greater distances than black text on white background, but not significantly White text on blue background Myers, 1969 30 .153
Yellow text on black background = increase in ability to identify words and letters Yellow text on black background Gardner, 1985 30 .120
Yellow text on blue background = better recognition and focus at greater distances than black text on white background, but not significantly Yellow text on blue background Myers, 1969 30 .108
White text on purple background = better recognition and focus at greater distances than black text on white background, but not significantly White text on purple background Myers, 1969 30 .073
Yellow text on purple background = better recognition and focus at greater distances than black text on white background, but not significantly Yellow text on purple background Myers, 1969 30 .035
Blue text on white background = better recognition and focus at greater distances than black text on white background, but not significantly Blue text on white background Myers, 1969 30 .025
Mixed outcome for white text on black background:

White text on black background = better recognition and focus at greater distances, but not significantly
White text on black background Myers, 1969 30 .029
White text on black background = small loss in ability to identify words and letters Gardner, 1985 18 .064

Effect of color changes in text and background. From these results, it appears that black text on a white background is the color combination resulting in the best discrimination and clarity. None of the other combinations resulted in an effect size greater than .40. Some of the color combinations warrant further investigation: (a) white and yellow text on black, blue, and purple backgrounds; and (b) blue text on white backgrounds.

These color combinations might be viewed as the place to start to determine individual preferences, when standard black text on white backgrounds is difficult to discriminate. Note, however, that the two studies found opposite results with white text on black background (the reversal of the usual black text on white background); Gardner (1985) found a small loss in the ability to identify words and letters with white text on black background, while Myers (1969) found that white text on black backgrounds was perceived at greater distances than black text on white backgrounds. Neither of these findings, however, were significant, and the effect size was negligible and did not approach educational significance.

Uncategorized qualifying studies

Three (3) qualifying studies were not easily categorized. Similar to Moore (1989), Harley and Merbler (1980) evaluated an intervention by using pre- and post-tests on an instrument designed specifically for the intervention (the Peabody Mobility Scale). Performance for all participants improved significantly from pre-test to post-test, and effect sizes exceeded 1.0 for scores in the vision and motor domains, as well as for the total score. The effect size for concepts was .894, and for mobility, .521, both of which are considered educationally relevant.

Olson, Harlow, and Williams (1977) included both blind students and large print readers in a 16-hour training program teaching McBride’s approach to rapid reading. Olson et al. reported the data in such a way that effect sizes could be calculated separately for large print readers, whose informal reading rate significantly increased on informal tests after training (effect size = 1.209). When tested on the Spache Diagnostic Reading Scales (Spache, 1963), comprehension and reading rate also demonstrated a significant improvement over the pre-test, with effect sizes of .718 and .717, respectively.

The Bane and Birch (1992) study—on its surface—does not appear to be related to educational interventions. However, the use of forced choice preferential looking (FPL) techniques to measure children’s visual resolution is often used to measure changes in visual abilities. The researchers found a difference between children with and without nystagmus. There was greater agreement between FPL acuities and visual evoked potential (VEP) acuities for children with nystagmus who were trained with horizontal bar stimuli that mimicked VEP patterns (mean effect size = .901), but the effect did not extend to children without nystagmus.

Conclusion

This analysis of low vision educational research demonstrates that we still have a lot to learn, both about our field and about how we conduct research. The studies reported here exhibit the same weaknesses evident in previous meta-analyses, most notably, the extreme heterogeneity of the participants in terms of (a) visual acuities, (b) additional disabilities, (c) cognitive levels, (d) gender, and (e) ethnicity. Specialized schools, once the greatest source of research samples, no longer offer the homogeneous population and curriculum they once did, as the largest proportion of students with visual impairments (87.28%) now attend general education classes in public schools (U.S. Department of Education, Office of Special Education and Rehabilitative Services, Office of Special Education Programs, 2009, Table 2-21). Random selection is difficult to achieve when the population is geographically dispersed, and researchers are forced to utilize samples of convenience, or participants known to them through their employment or within travel distance of their homes. While there are research designs that can ameliorate the lack of randomization (e.g., regression discontinuity designs, single factor within subjects designs), they are seldom utilized by researchers.

Several studies failed to report sufficient detail about the participants that would allow generalization to the larger population of children with visual and/or multiple impairments. For example, only three of the seven studies on visual development indicated that the participants had additional disabilities, and only two specifically addressed the cognitive abilities of the participants. Only one visual development study addressed participants’ gender or ethnicity, which may be attributable to the increased emphasis on ethnicity and gender in recent years (i.e., today, such demographic characteristics of subjects are expected in published articles).

Heterogeneity of participants is a difficult characteristic to overcome when one conducts research on children with low vision. The expense of research with a population that is dispersed across wide geographic regions leads many researchers to select samples who are either convenient geographically or with whom they already have a relationship (such as through a school or agency). This is evident in the range of ages involved in the studies, as well as in the description of vision loss, which often covers a broad range of visual abilities. Some researchers provided more specific descriptions than others (e.g., “light perception to 6/200” vs. “diagnosed ‘legally blind’”). One study reported visual acuity of 10/30 to no light perception. In almost every case, the range of participants’ visual functioning in the studies was quite broad.

Evidence-based practices

In spite of these limitations, several themes emerged from the qualifying studies. Gersten et al. (2005) proposed criteria to determine what is an evidence-based practice in special education:

  • There are at least four acceptable quality studies, or two high quality studies that support the practice; and
  • The weighted effect size is significantly greater than zero. (p. 162)

Based on these criteria, the evidence is great enough to establish the following as evidence-based practices:

  • Low vision devices, with and without formal training programs, can improve visual acuity, increase reading speed, and increase the total amount of reading (Corn et al., 2000, 2002; Farmer & Morse, 2007; Geruschat et al., 1999; Howell, 1980; LaGrow, 1981; Lackey et al., 1982; Lusk, 2007; Rossi, 1980; Schwartzenberg et al., 1988).
  • When compared to standard print with or without magnification, large print results in better overall performance (reading rates, reading accuracy, and comprehension) among elementary and secondary students (Bock, 1971; Sykes, 1971).
  • Black text on white backgrounds generally produces better results than most other color combinations (Gardner, 1985; Myers, 1969).

Promising vs. emerging practices

Gersten et al. (2005) also suggested guidelines for determining when a practice might be considered promising:

  • There are at least four acceptable quality studies, or two high quality studies that support the practice; and
  • There is a 20% confidence interval for the weighted effect size that is greater than zero. (p. 162)

Rather than suggest promising practices—which could not be identified in this analysis because so few studies were replicated and the 20% confidence interval was unavailable—this analysis proposes that emerging practices are a legitimate standard for the field of visual impairment. The criterion used to designate an emerging practice is

  • At least one high quality study whose results have the potential to impact the manner in which students with low vision are educated.

Additional evidence in the form of replications or further studies leading to the same outcomes are required before these can be adopted as evidence-based practices.

  • Head mounted devices at full magnification and contrast enhancement may increase contrast sensitivity (Geruschat et al., 1999).
  • Training with low vision devices may transfer to improved reading speed and more accurate distance tasks in conditions when low vision devices are not being used (Howell, 1980).
  • Standard correction with spectacle mounted magnifiers may improve reading speeds (Lusk, 2007).
  • Individualized prescription, training, and use of low vision devices may increase visual efficiency scores (Jose & Watson, 1978).
  • Binaural sensory aid use may be counter-indicated for students who rely on residual vision and lead to both lower performance on cross-modal transfer tasks and shorter fixation periods to visual and visual-auditory stimuli in moving and stationary conditions (Ferrell, 1984).
  • Visual skills may improve over time in the absence of specific training programs (Ferrell, 1984; Lopez-Justicia & Martos, 1999).
  • Responses to black light conditions are affected by visual acuity and may be more effective for students with better acuity (LaGrow et al., 1998).
  • Black light may increase speed in completing tasks, but at the expense of accuracy (Tavernier, 1992).
  • White text on blue or purple backgrounds and yellow text on black, blue, or purple backgrounds may be perceived as well as or better than black text on white background (Gardner, 1985; Myers, 1969).
  • The McBride approach to rapid reading may increase the reading rate and comprehension of adolescent students reading large print (Olson et al., 1977).
  • Training in programmed orientation and mobility materials may improve scores in the vision, motor, concept, and mobility portions of the Peabody Mobility Scale (Harley & Merbler, 1980).
  • Training with horizontal bar stimuli that simulate visual evoked potential (VEP) patterns may result in closer agreement between forced choice preferential looking (FPL) acuities and VEP acuities for children with nystagmus (Bane & Birch, 1992).

It is important to remember that emerging practices are not the same as evidence-based practices. In time and with further research, emerging practices may become evidence-based; but for now, educators and orientation and mobility specialists must rely on their experience, intuition, and clinical practice to determine which practices are best suited for which student.

For a complete report of information in this Appendix, please see A Meta-Analysis of Educational Applications of Low Vision Research by Ferrell, Dozier, and Monson (2011).

white text on blue background

yellow text on black background

yellow text on purple background

black text on white background

References

References marked with an asterisk indicate studies included in the meta-analysis.

*Bane, M. C., & Birch, E. E. (1992). Forced-choice preferential looking and visual evoked potential acuities of visually impaired children. Journal of Visual impairments & Blindness, 86, 21-24.

*Barraga, N. C. (1965). Effects of experimental teaching on the visual behavior of children with low vision. American Journal of Optometry and Archives of American Academy of Optometry, 42, 557-561.

Barraga, N. C., & Morris, J. E. (1980). Program to develop efficiency in visual functioning: Diagnostic Assessment Procedure. Louisville, KY: American Printing House for the Blind.

Bayley, N. (1969). Manual for the Bayley scales of infant development. New York: Psychological Corp.

*Bock, J. (1971). Reading performance of visually impaired print readers using standard print, large print and magnification. (Unpublished master’s thesis). Michigan State University, East Lansing, Michigan.

*Brand, H. J. (1976). The use of closed-circuit television as an aid in the administration of psychological tests to partially sighted children. Education of the Visually Handicapped, 8(2), 53-57.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.

*Corn, A., Wall, R., & Bell, J. (2000). Impact of optical devices on reading rates and expectations for visual functioning of school-age children and youth with low vision. Visual impairments Research, 2(1), 33-41.

*Corn, A. L., Wall, R. S., Jose, R. T., Bell, J. K., Wilcox, K., & Perez, A. (2002). An initial study of reading and comprehension rates for students who received optical devices. Journal of Visual impairments & Blindness, 96, 322-334.

*Farmer, J., & Morse, S. E. (2007). Project magnify: Increasing reading skills in students with low vision. Journal of Visual impairments & Blindness, 101, 763-768.

*Ferrell, K. A. (1984). A second look at sensory aids in early childhood. Education of the Visually Handicapped, 16, 83-101.

Ferrell, K. A., Buettel, M., Sebald, A. M., & Pearson, R. (2006). American Printing House for the Blind mathematics research analysis [Technical Report]. Greeley, CO: University of Northern Colorado, National Center on Low-Incidence Disabilities. Available at http://www.unco.edu/ncssd/research/math_meta_analysis.shtml

Ferrell, K. A., Dozier, C., & Monson, M. (2011). A meta-analysis of educational applications of low vision research. Greeley, CO: University of Northern Colorado. Available at http://www.unco.edu/ncssd/research/LowVisionMeta-Analysis.shtml

Ferrell, K. A., Mason, L., Young, J., & Cooney, J. (2006). Forty years of literacy research in blindness and visual impairment [Technical Report]. Greeley, CO: University of Northern Colorado, National Center on Low-Incidence Disabilities. Available at http://www.unco.edu/ncssd/research/literacy_meta_analyses.shtml

Forness, S., Kavale, K. A., Blum, J. M., & Lloyd, J. (1997). Mega-analysis of meta-analyses: What works in special education and related services. TEACHING Exceptional Children, 29, 4-9.

Frostig, M., Horne, D., & Miller, A. M. (1964). The Frostig program for the development of visual perception. Chicago: Follett Educational Corp.

*Gardner, L. R. (1985). Low vision enhancement: The use of figure-ground reversals with visually impaired children. Journal of Visual impairments & Blindness, 79, 64-69.

*Geffen, L. F. (1971). Relationships between visual deficiencies and cognitive factors before and after tachistoscopic training. (Unpublished doctoral dissertation). Peabody College for Teachers of Vanderbilt University, Nashville, Tennessee.

Gersten, R., Fuchs, L. S., Compton, D., Coyne, M., Greenwood, C., & Innocenti, M. S. (2005). Quality indicators for group experimental and quasi-experimental research in special education. Exceptional Children, 71, 149-164.

*Geruschat, D. R., Deremeik, J. T., & Whited, S. S. (1999). Head-mounted displays: Are they practical for school-age children? Journal of Visual impairments & Blindness, 93, 485-497.

*Harley, R. K., & Merbler, J. B. (1980). Development of an orientation and mobility program for multiply impaired low vision children. Journal of Visual impairments & Blindness, 74, 9-14.

*Helnsley, G. J. (1986). The application of contrast sensitivity data for adjustment of closed circuit television systems used by the visually impaired (functional vision, reading efficiency). (Unpublished doctoral dissertation). The Florida State University, Tallahassee, Florida.

*Howell, J. L. (1980). Evaluation and testing of a low vision aid training program: A plan for increasing functional vision efficiency of visually impaired elementary school students. (Unpublished doctoral dissertation). Brigham Young University, Dept. of Educational Psychology, Provo, Utah.

*Jose, R. T., & Watson, G. (1978). Increasing reading efficiency with an optical aid/training curriculum. Review of Optometry, 115(2), 41-48.

*Kelleher, D. (1974). A pilot study to determine the effect of the bioptic telescope on young low vision patients’ attitude and achievement. American Journal of Optometry and Physiological Optics, 51, 198-205.

Kelly, S. M., & Smith, D. W. (2011). The impact of assistive technology on the educational performance of students with visual impairments: A synthesis of the research. Journal of Visual Impairment & Blindness, 105, 73-83.

*Lackey, G. H., Jr., Efron, M., & Rowls, M. D. (1982). For more reading: Large print books or the visolett? Education of the Visually Handicapped, 14, 87-94.

*LaGrow, S. J. (1981). Effects of training on CCTV reading rates of visually impaired students. Journal of Visual impairments & Blindness, 75, 368-373.

*LaGrow, S. J., Leung, J.-P., & Leung, S. (1998). The effects on visually impaired children of viewing fluorescent stimuli under black-light conditions. [Feature]. Journal of Visual impairments & Blindness, 92, 313-321.

*Leguire, L. E., Fellows, R. R., Rogers, G. L., Bremer, D. L., & Fillman, R. D. (1992). The CCH vision stimulation program for infants with low vision: Preliminary results. [Feature]. Journal of Visual impairments & Blindness, 86, 33-37.

*Lopez-Justicia, M. D., & Martos, F. J. (1999). The effectiveness of two programs to develop visual perception in Spanish schoolchildren with low vision. Journal of Visual impairments & Blindness, 93, 96-103.

*Lusk, K. M. E. (2007). The effects of various mounting systems of near magnification on reading performance and preference in students with low vision. (Unpublished doctoral dissertation). Vanderbilt University, Nashville, Tennessee.

*Mamer, L. (1999). Visual development in students with visual and additional impairments. Journal of Visual impairments & Blindness, 93, 260-369.

*Moore, S. B. (1989). A study of the effectiveness of selected training materials to enhance the visual functioning of 4-, 5-, and 6-year-old visually impaired children. (Unpublished doctoral dissertation) University of Louisville, Louisville, Kentucky.

*Myers, W. A. (1969). Discriminability of selected color combinations for partially seeing children. (Unpublished master’s thesis). University of Southern California, Los Angeles, California.

No Child Left Behind Act of 2001, Pub. L. No. 107-110, 1201-1226, 115 Stat. 425 (2002).

*Olsen [sic], M. R., Harlow, S., & Williams, J. (1977). Evaluation of McBride’s approach to rapid reading for braille and large print readers. Education of the Visually Handicapped, 9, 16-23.

Parker, A. T., & Pogrund, R. L. (2009). A review of research on the literacy of students with visual impairments and additional disabilities. Journal of Visual Impairment & Blindness, 103, 635-648.

Parker, A. T., Grimmett, E. S., & Summers, S. (2008). Evidence-based communication practices for children with visual impairments and additional disabilities: An examination of single-subject design studies. Journal of Visual Impairment & Blindness, 102, 540-552.

*Rossi, P. (1980). Closed circuit television—a method of reading. Education of the Visually Handicapped, 12, 90-94.

*Schwartzenberg, T., Merin, S., Nawratzki, I., & Yanko, L. (1988). Low-vision aids in Stargardt’s disease. Annals of Ophthalmology, 20, 428-430.

Spache, G. (1963). Diagnostic reading scales. Monterey, CA: CTB/McGraw-Hill.

*Sykes, K. S. (1971). A comparison of the effectiveness of standard print in facilitating the reading of visually impaired students. Education of the Visually Handicapped, 3, 97-106.

*Tavernier, G. G. F. (1992). The effect of object fluorescence on visual-motor performance in partially sighted children. Journal of Vision Rehabilitation, 6(1), 15-22.

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Kay Alicyn Ferrell, PhD, is professor emerita at the School of Special Education and Director of the National Center on Severe and Sensory Disabilities, College of Education and Behavioral Sciences, at the University of Northern Colorado, Greeley.