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Development and Standardization of an AssistiveTechnology Questionnaire Using Factor Analyses: EightFactors Consisting of 67 Items Related to AssistiveTechnology PracticesSoonhwa Seok PhD a & Boaventura DaCosta PhD ba Korea University, Seongbuk-gu , Seoul , Republic of Koreab Solers Research Group , Orlando , FloridaAccepted author version posted online: 05 Mar 2013.Published online: 20 Feb 2014.

To cite this article: Soonhwa Seok PhD & Boaventura DaCosta PhD (2014) Development and Standardization of an AssistiveTechnology Questionnaire Using Factor Analyses: Eight Factors Consisting of 67 Items Related to Assistive TechnologyPractices, Assistive Technology: The Official Journal of RESNA, 26:1, 1-14, DOI: 10.1080/10400435.2013.778917

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Assistive Technology® (2014) 26, 1–14Copyright © 2014 RESNAISSN: 1040-0435 print / 1949-3614 onlineDOI: 10.1080/10400435.2013.778917

Development and Standardization of an Assistive TechnologyQuestionnaire Using Factor Analyses: Eight Factors Consistingof 67 Items Related to Assistive Technology Practices

SOONHWA SEOK, PhD1∗ and BOAVENTURA DACOSTA, PhD2

1Korea University, Seongbuk-gu, Seoul, Republic of Korea2Solers Research Group, Orlando, Florida

The purposes of this study were to identify the factors that underlie assistive technology (AT) and to validate items to be used in aninstrument to evaluate AT use. The study consisted of four phases. First, 99 items were developed though a comprehensive literature review.Second, the items were refined through three layers of review. Third, 1,467 respondents rated the results of the reviews. Fourth, exploratoryfactor analysis, and three confirmatory factor analyses (CFA) were employed to analyze the data. The results of the CFA were statisticallysignificant (root mean square error of approximation [RMSEA] = 0.036, p = 0.00) with a total of 67 items across 8 factors (effectiveness,affordability and dependability, utility, external support, operations, longevity, discomfort, and compatibility).

Keywords: assistive technology, disability, instrument development

Introduction

Many people are dependent on assistive technology (AT), andmore and more AT devices are being developed every day.However, despite the promises of this new technology, an exces-sively high rate of abandonment has been reported (Ebner, 2004;Johnston & Evans, 2005; Scherer, & Craddock, 2002). The rea-sons for this abandonment are many and include the fact that anappropriate match between the user and AT was not establishedbefore purchase (Beigel, 2000) and the user’s preference for andopinions about the AT decision were not sufficiently considered(Betsy & Hongxin, 1993).

Most of these issues could be resolved through proper eval-uation of needs and functionalities prior to and during use ofan AT device. Hutinger (1996), for example, called for appro-priate assessment and individualized programming as one of anumber of conditions necessary for a successful comprehensivetechnological program for children with disabilities. By conduct-ing an appropriate assessment and basing the evaluation andselection of AT on the use of empirically supported pedagogi-cal frameworks and understanding (Margolis & Goodman, 1999;Graham & Warnie, 2012), common pitfalls can be avoided whentechnology is used as the primary factor in driving selection.

Fortunately, AT evaluation practices are changing. For exam-ple, the Individuals with Disabilities Education Act (IDEA)definition of AT services include the concept of a functional eval-uation, in which the interactions between environments, tools,

∗Address correspondence to: Soonhwa Seok, Korea University, 145,Anam-ro, Seongbuk-gu, Seoul 136-701, Republic of Korea. Email:sunaseok@yahoo.com

and students are considered a top priority (Bryant & Bryant,2003; U.S. Department of Education Office of Special Educationand Rehabilitative Services, 2013). Although important, legalmandates alone do not magically result in an instant and mean-ingful impact on those with disabilities (Derer, Polsgrove, &Rieth, 1996). Much more is needed along the lines of researchand practice if the field of AT is to advance. Research in theevaluation in special education, including AT evaluation, forexample, seeks to make decision-making data-driven and incor-porates evidence-based practices (Peterson-Karlan & Parette,2007). There is a paucity of research on the quality of AT, suchas measurement, assessment (Judge, 2002), validation and relia-bility studies, standards, and guidelines (Seok, 2007a, 2007b).In particular, validation research is needed on the underlyingfactors and items representing them, such as AT effectiveness,maintenance, selections, adaptation, and assessments.

This type of research would enhance the quality of AT byleading to new standards and guidelines (Karmarkar et al., 2012)for accessing, selecting, adapting, implementing, and maintain-ing AT. Given the earlier discussion, we define quality of AT asthe degree to which AT implementation, or providing AT devicesor services, produces the intended or better than the intendedoutcomes or benefits.

Effective measurement of outcomes in AT practices hasbecome especially critical as special education is now mandatedto, whenever possible, make evidence-based decisions basedon iterative investigations (Council for Exceptional Children[CEC], 2008). Involving many layers of iterations is one designpractice that is appropriate here; namely, testing the modelthrough iterative interventions and evolving from the origin(Anderson & Shattuck, 2012), such as a responsiveness to the

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intervention model. Thus, measurement of AT outcomes con-tributes to identification of the current problems of AT practices,monitoring of AT implementation, investigation of the causes ofproblems with AT implementation, and, finally, documentation ofthe practice (Smith, 1996).

In an attempt to meet the need for validation research, thepresent study was designed to develop and standardize an ATquestionnaire. It specifically focused on: (a) validating qualityitems for an AT evaluation instrument and (b) identifying fac-tors underlying quality AT practice. To achieve this purpose, weposed the following research question: What are the underlyingfactors of quality AT practice?

Methods

Participants

The study took place in 2012 at 20 public and 8 private spe-cial education schools in Seoul, Kyunggi, and Chunchun, SouthKorea. The schools consisted of grades K–12 and served studentswith special needs in a number of areas, including autism andvisual impairment, as well as intellectual and physical disabili-ties. In addition, graduate and undergraduate pre-service teachersenrolled in introduction to special education courses were invitedto participate.

Of the 1,500 participants solicited to participate, 1,472 volun-teered to do so. Of these 1,472, 17.9% comprised undergraduatestudents, 5.8% comprised graduate students, 24.4% comprisedspecial education teachers (SETs) at the elementary school level,23.8% comprised SETs at the middle school level, 24.7% com-prised SETs at the high school level, and 3.4% chose not tospecify. In terms of gender, 34.2% reported being male, whereas65.8% reported being female. Number of years of teaching expe-riences was reported as follows: 11.5% comprised 0 year, 18.5%comprised 1–2 years, 10.7% comprised 3–4 years, 10.6% com-prised 5–6 years, 9.3% comprised 7–9 years, 9.2% comprised10–12 years, 6.9% comprised 13–15 years, and 23.3% comprisedmore than 16 years. In terms of the types of AT that participantsused in their classroom and with individuals with disabilities,27% comprised PC (tablet), 5.5% comprised smartphone, 42.1%comprised computers, 5% comprised AT devices for people withvisual disabilities, 2.7% comprised AT devices for people withhearing disabilities, 16.1% comprised wheelchairs, and finally1.5% chose not to specify (see Table 1).

Materials

A 99-item survey was developed/selected for the present studybased on a review of the literature conducted to identify itemspertaining to the concept and characteristics of AT and qualityAT, specifically, items measuring evaluation (Seok, 2007a). Thequestionnaire was divided into two parts. In the first part, partici-pants were asked to rate their agreement with 99 statements usinga 7-point Likert scale (strongly disagree, disagree, more or lessdisagree, neutral, more or less agree, agree, and strongly agree)to “mark the level of agreement on how much this item wouldcontribute to the quality of AT, device, and service.” Although agood amount of research has used a 5-point Likert scale, a 7-pointLikert scale was used for the present study because both 5- and

Table 1. Demographic information of participants (N = 1,472).

%

Job Undergraduate students 17.9Graduate students 5.8SET at elementary school level 24.4SET at middle school level 23.8SET at high school level 24.7Not specified 3.4

Gender Male 34.2Female 65.8

# of years of teachingexperience

0 year 11.51–2 year 18.53–4 year 10.75–6 year 10.67–9 years 9.310–12 years 9.213–15 years 6.9More than 16 years 23.3

Types of AT used inclassroom

Computers 42.1PC (tablet) 27.0Wheelchairs 16.1Smartphone 5.5AT devices for the students with

visual disabilities5.0

AT devices for the students withhearing disabilities

2.7

Not specified 1.5

Note. SET = Special education teacher.

7-point Likert scales yield greater average scores than a 10-pointLikert scale (Dawes, 2008).

In the second part of the questionnaire, participants wereasked to provide demographic information by answering severalquestions. Specifically, they were asked to specify their age, gen-der, job, numbers of years of teaching and AT experiences, thelevel of their knowledge of AT, and the types of AT devices theyused.

The questionnaire was developed, administered, and reportedin the Korean language, although the literature was reviewedin English. Those involved in the literature review and theinitial development/selection of the items were native Koreanspeakers with English as a second language. The developmentand standardization process in this research was similar to thedevelopment and validation of an instrument for student eval-uation of Web-based instruction using factor analysis (Stewart,2001).

Items developed/selected were refined in three consecutivepasses. First, language was refined for each of the items byan individual proficient in the Korean language; second, itemswere reviewed by undergraduate students with teaching expe-rience who had recently completed their practicum; and third,items were reviewed by special education teachers holdingmaster’s degrees and having more than 10 years of professionalexperience.

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Development of AT Questionnaire 3

Procedure

A month before the summer break of the special schools in2012, the principal researcher of the study sent the princi-pal, vice principal, and researcher teacher at the schools aletter to solicit their participation in the validation research.They agreed to participate in the research and respondentswere promised in return a gift certificate of 5,000 won(the equivalent of between $4.00–$5.00) as an honorarium.Permission to conduct the study was obtained from the schoolsystem. Participants consented by volunteering to partake inthe study. All participants were treated in accordance withthe American Psychological Association’s Ethics in Researchwith Human Participants (American Psychological Association,2002).

The questionnaire was developed and presented in Korean andall information was self-reported. The paper-and-pencil–basedsurvey was administered over a 3-week period by principals, viceprincipals, and research teachers at each of the 28 participat-ing schools. The principle researcher provided informal, verbaltraining to the volunteers in how to administer the questionnaire.

Data Analysis

Reliability tests and exploratory factor analysis (EFA) were con-ducted on the responses to survey items; results were discussed,item categories reviewed and named; and three confirmatory fac-tor analyses (CFA) were performed to validate the items andmake final item selections (Byrne, 2010; Jung, 2010). Statisticalanalysis was conducted using AMOS 18.0.

Results

Consistency of Items

Cronbach’s alpha was used for the internal consistency (α =0.973, n = 99). Item-total statistics are presented in Table 2.

Exploratory Factor Analysis

EFA explores and defines factors underlying measurement instru-ments and ascertains which items should be included andexcluded (Byrne, 2010; Jung, 2010; Green & Salkind, 2003).First, we extracted factors from a correlation matrix to makeinitial decisions about the number of factors underlying a setof measures. EFA with unweighted least-squares extraction wasconducted to obtain the initial Eigen values of the 99 items.The Kaiser-Guttman criterion of Eigen values greater than 1 wasadopted. As a result, a measurement with eight factors wasconsidered adequate. The items with Eigen values greater than1 were selected. With the eight-factor model, EFA was performedby means of Varimax, the principal components analysis. Thiswas chosen because it is generally used for validation studies.After rotation, 26 out of the 99 items with a factor loading scoreof less than .40 were eliminated. Table 3 shows the results ofEFA, which addressed the validity of 73 items of each factor. Thecorrelation matrix of Varimax extracted eight factors, which theresearchers intended to include in the first place (see Table 3).

Table 2. Item-total statistics.

>

Scale mean ifitem deleted

Scale varianceif item deleted

Correcteditem-totalcorrelation

Cronbach’salpha if item

deleted

Q1 515.3167 4840.872 0.366 0.973Q2 515.7290 4831.739 0.386 0.973Q3 515.7515 4824.945 0.399 0.973Q4 515.0314 4830.995 0.468 0.973Q5 515.1235 4828.015 0.479 0.973Q6 514.9898 4829.357 0.496 0.973Q7 515.1529 4828.168 0.463 0.973Q8 515.0007 4831.982 0.453 0.973Q9 514.8628 4837.927 0.469 0.973Q10 515.3823 4823.818 0.482 0.973Q11 515.0280 4831.734 0.481 0.973Q12 515.7932 4825.653 0.440 0.973Q13 514.9147 4822.965 0.553 0.973Q14 515.8000 4840.819 0.283 0.973Q15 515.4962 4815.801 0.500 0.973Q16 515.4253 4819.829 0.492 0.973Q17 515.3843 4813.561 0.541 0.973Q18 515.2314 4822.607 0.498 0.973Q19 514.7986 4826.956 0.558 0.973Q20 515.0942 4817.927 0.543 0.973Q21 515.5147 4803.253 0.514 0.973Q22 515.5372 4806.900 0.504 0.973Q23 515.1427 4814.979 0.557 0.973Q24 515.2061 4805.641 0.595 0.973Q25 515.1959 4803.883 0.574 0.973Q26 515.6082 4820.584 0.422 0.973Q27 514.9447 4801.866 0.573 0.973Q28 515.2867 4780.967 0.569 0.973Q29 515.2908 4784.791 0.585 0.973Q30 515.4137 4785.378 0.561 0.973Q31 515.4833 4784.022 0.598 0.973Q32 515.0457 4791.772 0.628 0.973Q33 515.3911 4790.480 0.596 0.973Q34 515.0928 4824.107 0.507 0.973Q35 516.2184 4824.060 0.387 0.973Q36 515.8608 4814.619 0.423 0.973Q37 515.2997 4832.569 0.391 0.973Q38 515.6150 4829.826 0.361 0.973Q39 515.5802 4800.406 0.530 0.973Q40 515.3734 4788.346 0.598 0.973Q41 515.7911 4788.365 0.542 0.973Q42 515.7461 4815.788 0.487 0.973Q43 515.3918 4811.738 0.514 0.973Q44 515.3747 4802.538 0.581 0.973Q45 515.5652 4808.369 0.520 0.973Q46 515.0382 4807.534 0.576 0.973Q47 515.0915 4830.580 0.443 0.973Q48 515.6580 4822.140 0.417 0.973Q49 515.5181 4820.966 0.469 0.973Q50 515.4362 4829.402 0.404 0.973Q51 514.8778 4811.304 0.563 0.973Q52 514.9775 4798.067 0.605 0.973Q53 515.7877 4812.035 0.477 0.973Q54 515.8785 4819.534 0.430 0.973

(Continued)

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Table 2. (Continued)

>

Scale mean ifitem deleted

Scale varianceif item deleted

Correcteditem-totalcorrelation

Cronbach’salpha if item

deleted

Q55 515.5085 4815.127 0.493 0.973Q56 515.1147 4795.888 0.627 0.973Q57 515.0089 4819.154 0.527 0.973Q58 515.4737 4796.084 0.581 0.973Q59 515.6000 4795.117 0.581 0.973Q60 515.1181 4795.324 0.653 0.973Q61 515.1747 4792.015 0.659 0.973Q62 514.9911 4802.088 0.604 0.973Q63 515.2457 4795.050 0.607 0.973Q64 515.3529 4802.593 0.552 0.973Q65 515.4273 4794.769 0.575 0.973Q66 514.8703 4807.396 0.580 0.973Q67 516.0805 4821.626 0.290 0.974Q68 515.4266 4818.134 0.463 0.973Q69 515.4942 4807.338 0.377 0.973Q70 516.0143 4813.984 0.428 0.973Q71 515.0362 4797.021 0.598 0.973Q72 515.3959 4798.942 0.555 0.973Q73 515.1836 4801.773 0.597 0.973Q74 515.3399 4816.196 0.498 0.973Q75 515.0253 4805.347 0.621 0.973Q76 515.7488 4811.419 0.457 0.973Q77 515.5433 4822.382 0.439 0.973Q78 515.6614 4815.029 0.461 0.973Q79 515.5604 4801.573 0.545 0.973Q80 515.7290 4802.136 0.471 0.973Q81 515.5611 4803.047 0.535 0.973Q82 515.1406 4793.327 0.631 0.973Q83 515.0587 4801.591 0.621 0.973Q84 514.7468 4808.413 0.622 0.973Q85 514.7468 4805.427 0.623 0.973Q86 515.3679 4795.939 0.527 0.973Q87 515.3447 4797.857 0.520 0.973Q88 515.6055 4810.989 0.472 0.973Q89 514.9536 4800.999 0.606 0.973Q90 515.5188 4788.093 0.579 0.973Q91 514.9488 4809.419 0.589 0.973Q92 514.8853 4817.522 0.569 0.973Q93 514.8587 4819.731 0.585 0.973Q94 514.9249 4826.692 0.503 0.973Q95 514.9700 4817.580 0.577 0.973Q96 514.8908 4820.335 0.573 0.973Q97 514.8928 4819.637 0.567 0.973Q98 514.8212 4825.326 0.551 0.973Q99 514.6867 4826.861 0.527 0.973

The information in Table 3 is expanded on in Figure 1 using ascree plot. The factors were named as follows: Factor 1 (F1) = ATeffectiveness; Factor 2 (F2) = affordability and dependability;Factor 3 (F3) = AT utility; Factor 4 (F4) = AT external support;Factor 5 (F5) = AT operations; Factor 6 (F6) = AT longevity;Factor 7 (F7) = AT discomfort; and Factor 8 (F8) = ATcompatibility. The Kaiser-Mayer-Olkin (KMO) measure of sam-pling was also tested to investigate the degree to which the

items were correlated and EFA worked for the research. Thevalue of KMO was 0.966, showing that the item selection wasappropriate.

Three Times of Confirmatory Factor Analysis

CFA 1

The first CFA was conducted after the EFA and reliability tests.Table 4 shows the results of three confirmatory factor analy-ses. CFA 1 showed that the standardized regression weights ofall the items measured were above 0.5, meaning all the selecteditems had validity. The root mean square error of approximation(RMSEA) and goodness-of-fit (GFI) were not produced becausethe fitness of model was low when all the originally selecteditems were included.

CFA 2

Items 66, 85, and 84 of F1 and items 11 and 13 of F3 wereremoved. The value of AIC became smaller; thus, the model wasimproved after removal of the items that had lower factor loadingscores. The results of CFA 2 showed χ2 = 114973.56, GFI =0.786, and RMR = 0.113 (see Table 4—CFA 2).

The results of CFA 2 showed that the correlation between eachitem and its factors was significant (p < 0.05) and all the t val-ues were higher than 1.965. The standardized regression weights(SRW) of all the items were higher than 0.5, except for Item14. Thus, the results were statistically significant (p < 0.05; seeTable 5). Item 14 which had lower factor loading scores wasexcluded from the analysis, leading to even greater improvementof the fitness of the model.

CFA 3

The third analysis of model CFA 3, as the final model, was con-ducted without item 14. The results showed χ2 = 5986.188, df =2059, p = 0.000, CMIN/DF = 2.907, RMSEA = 0.036, and CFI= 0.924. Thus, the fitness indices were high because CMIN/DFwas less than 3 (CMIN/DF < 3) and RMSEA was less than 0.05(RMSEA < 0.05; see Table 4—CFA 3). Table 6 shows the def-inition of each factor and the finally selected items as well asthe definition of quality AT used to describe the factors and theirrelationship with the overall quality of AT.

The results of CFA 3 showed that the correlation between eachitem and its factor was statistically significant (p < 0.05), all thet with higher than 1.965 (t > 1.965) were statistically significant.All SRWs were higher than 0.5. Thus, the results of CFA 3 werestatistically significant (p < 0.05) and had validity (see Table 7).A total of 67 items of 8 factors were finally selected to evalu-ate the quality of AT practices: F1 includes 9 items, F2 includes12 items, F3 includes 10 items, F4 includes 9 items, F5 includes8 items, F6 includes 6 items, F7 includes 7 items, and F8 includes6 items as shown in Table 7. Table 7 explains each item level.

Figure 2 shows the results of the final analysis. In the model,covariance between error variables was added to improve theindex of fitness. The model shows that path coefficient wasbelow 1.

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Development of AT Questionnaire 5

Table 3. Factor loading for eight factors of assistive technology (AT) from exploratory factor analysis.

Factor loading

Items 1 2 3 4 5 6 7 8

98. The AT device helps improve my students’ academic motivation. 0.76896. The AT device helps my students learn content areas. 0.75592. The AT device has improved students’ academic achievement. 0.7597. The AT device helps my students learn how to learn. 0.74893. The AT device meets the students’ academic needs. 0.72794. The AT device motivates the students’ learning. 0.69499. The AT device helps my students become independent. 0.65495. The interface of the AT device is efficient for the students. 0.63191. Learning strategies are used in implementing AT for students’

learning.0.63

66. The device meets the specific needs of the student. 0.50585. The AT device has safety features (e.g., emergency brakes). 0.49684. The AT device is safe to operate. 0.4830. The likely cost of repair is affordable. 0.81529. The likely cost of maintenance is affordable. 0.80828. The price of the AT device is appropriate. 0.80231. The AT device is covered by public or private insurance (or other

financing programs).0.686

27. The AT device demonstrates ease of portability across settings. 0.63732. There are warranties on the AT device. 0.62940. Spares have been provided for the purpose of repair. 0.59133. The AT device operates independently. 0.55339. The device has special design features (e.g., plug-in modules)

that can reduce the difficulty of repairs.0.487

56. Maintenance is easily handled by the student (or personalassistant).

0.473

89. The AT device can be adapted to hook up in different locations. 0.45941. The device is dependable. 0.4574. I have the ability to help my student achieve academically using

technology.0.714

5. I am aware of my students’ specific academic needs. 0.6836. I am aware of my students’ needs related to their disabilities. 0.6822. I feel confident in my ability to participate in an AT assessment. 0.6167. I feel confident in my ability to use AT for transition planning for

my student.0.615

1. I feel confident in my ability to assess student’ need for assistivetechnology (AT).

0.593

8. The AT device can help students access the general educationcurriculum.

0.584

9. The AT device and services can help students achieve their IEPgoals.

0.583

11. The information is presented in an effective way (including useof speech, music, graphics, text, and animation).

0.554

3. I have access to somebody whom I can consult with regarding AT. 0.53210. The use of AT device and services can be monitored by the AT

team to ensure successful implementation by the AT team.0.501

13. The AT device is appropriate for the stated objectives. 0.47455. Other kinds of devices/furniture are required to complete the

system (e.g., special tables, wall mountings).0.649

54. Test equipment (e.g., computer, multimeter, oscilloscope) isrequired for start-up or calibration.

0.636

48. The supplier will assemble and/or install the AT device. 0.63453. Special tools are required for assembly, installation or start-up. 0.60250. A technician or engineer is required for initial assembly or

installation.0.602

(Continued)

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Table 3. (Continued)

Factor loading

Items 1 2 3 4 5 6 7 8

43. A special room environment is required (e.g., heating, cooling,dust free, low or high humidity).

0.57

47. Care and maintenance is necessary in order for the AT device tolast throughout (and beyond) its expected life.

0.531

45. Problems can arise if the equipment is not operated according toprescribed operating instructions.

0.494

57. Routine maintenance is necessary. 0.49364. The manufacturer addressed the function of the device. 0.62259. The maintenance record forms are adequate. 0.58461. The instruction book spells out all maintenance routines to be

followed.0.56

65. The device functions as claimed by the manufacturer. 0.55558. Maintenance record forms are provided. 0.55460. Operation and maintenance manuals are included with the AT

device0.548

62. The instructions are effective. 0.54363. There are adequate precautions for sterilization of the device

(e.g., gas or steam) to prevent infection.0.51

36. It is reasonable to expect me to carry out some of repairs. 0.72938. Training is required for the student or assistant to repair the

device.0.624

35. The AT device is likely to become obsolete in the near future dueto compatibility problems with devices now being developed.

0.619

14. The AT device is free of gender, cultural, or racial bias. 0.55826. The AT device is appropriate for future use. 0.52649. The student (or personal assistant) can reasonably be expected to

carry out some portion of the assembly or installation.0.523

70. The students independently go through all start-up anddiagnostic routines.

0.512

86. Use of the AT device disrupts internal physiologic functions(e.g., normal flow of blood or urine).

0.712

80. The AT device causes pain or discomfort. 0.69487. The AT device is likely to cause infection or other adverse

physiologic reaction.0.693

81. The AT device makes noises that are irritating to the ear orphysical sensations that are irritating to the skin.

0.671

78. Students would be embarrassed by some aspects of the device(e.g., physical appearance or unusual sounds).

0.501

88. The AT device depends upon an external power supply or otherhook-up.

0.482

76. Certain tests or readjustments have to be made when theequipment is used during the initial warm-up/ use phase.

0.453

21. The student has sufficient overall technology literacy to use thedevice.

0.638

22. The students have keyboarding proficiency (if applicable). 0.63423. The angle of vision is appropriate for the student. 0.56724. The visual distance is appropriate for the student. 0.56320. The student is able to learn to use the AT device during the

orientation.0.486

17. The student sustained attention using the AT device. 0.469Initial Eigen values 21.569 4.791 3.522 2.476 2.306 1.845 1.616 1.331Extracting sums of squared loading, % of variance 10.088 9.533 7.671 6.373 6.085 5.404 5.091 3.805Extraction sums of squared loadings, cumulative % 10.088 19.62 27.291 33.664 39.749 45.153 50.244 54.049

Note. Items in italics were removed from final inclusion. Kaiser-Meyer-Olkin measure of sampling adequacy = 0.966; Bartlett’s test of sphericity = 58204.305;df = 2628; p = 0.000.

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Fig. 1. Scree plot of EFA of 99 items.

Table 4. Analyses of fitness of model.

Confirmatory Factory Analysis (CFA)

CFA 1 Model χ 2 AIC BCCBasic Model 122468.629 122962.6 122988.8

CFA 2 Model χ 2 RMR GFI AIC BCCBasic model 114973.56 0.113 0.786 115301.6 115317.7

CFA 3 Model χ 2 Df P CMIN/DF GFI AGFI IFI TLI CFI RMSEABasic model 5986.188 2059 0.000 2.907 0.883 0.871 0.924 0.918 0.924 0.036

Note. AIC = Akaike information criterion; AGFI = Adjusted Goodness of Fit Index; CFI = Comparative Fit Index; CMIN/DF = Chi-square divided by its degreesof freedom; BCC = Browne-Cudeck criterion. The BCC and AIC both represent the extent to which the observed covariance matrix differs from the predictedcovariance matrix—like the chi-square statistic—but include a penalty if the model is complex, with many parameters. GFI = goodness of fit; IFI = IncrementalFit; RMSEA = root mean square error of approximation; TLI = Tucker Lewis Index.

Discussion

This research was intended to validate the quality of itemsmaking up an AT evaluation instrument and identify factorsunderlying quality AT practice. Specifically, the research ques-tion was: What are the underlying factors of quality AT practice?All in all, the results of three confirmatory factor analyses werestatistically significant (RMSEA = 0.036, p = 0.0). A total of67 items across 8 factors were finally selected to evaluate thequality AT practices.

When conducting research using factor analysis, it is nec-essary to have clear distinctions between factors and concepts(Green & Salkind, 2003). The results of this study showed thateight distinctive factors are underlying AT practices: AT effec-tiveness, affordability and dependability, AT utility, AT externalsupport, AT operations related to support, AT longevity, ATdiscomfort, and AT compatibility.

F1: AT Effectiveness (9 Items)

Effectiveness refers to a device’s ability to accomplish its statedpurpose. AT devices are prescribed for one overriding purpose—to help a person to be successful in an activity, whether inthe classroom, on the job, in a recreational setting, and soforth. Bryant (1994) noted that any adaptation, including ATadaptations, must be successfully employed to be worthwhile.The items within this factor, such as helping students meettheir academic needs, motivating student learning, and becom-ing independent learners, all relate to the effectiveness of theAT devices being used. Consistent with previous studies, wefound the first factor—effectiveness—was the primary goal ofAT practices. However, most of the previous studies exam-ined it using elderly people in home settings (Hoenig, Taylor,& Sloan, 2003) or settings other than classrooms (Agree &Freedman, 2001). Unlike these studies, we focused on evidence

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Table 5. Regression weights and standardized regression weights.

Variables

Estimate ofregression

weights

Estimate ofstandardizedregression

weights S.E. C.R. P

Q98 <— F1 1 0.805Q96 <— F1 1.008 0.796 0.029 34.5 ∗∗∗

Q92 <— F1 1.044 0.794 0.03 34.411 ∗∗∗

Q97 <— F1 1.024 0.793 0.03 34.35 ∗∗∗

Q93 <— F1 0.985 0.789 0.029 34.076 ∗∗∗

Q94 <— F1 0.918 0.688 0.032 28.502 ∗∗∗

Q99 <— F1 0.883 0.693 0.031 28.809 ∗∗∗

Q95 <— F1 0.903 0.696 0.031 28.956 ∗∗∗

Q91 <— F1 0.961 0.695 0.033 28.895 ∗∗∗

Q30 <— F2 1 0.828Q29 <— F2 0.982 0.842 0.025 39.439 ∗∗∗

Q28 <— F2 1.026 0.831 0.027 38.631 ∗∗∗

Q31 <— F2 0.845 0.736 0.026 32.294 ∗∗∗

Q27 <— F2 0.744 0.725 0.024 31.633 ∗∗∗

Q32 <— F2 0.758 0.737 0.023 32.367 ∗∗∗

Q40 <— F2 0.735 0.663 0.026 28.102 ∗∗∗

Q33 <— F2 0.74 0.677 0.026 28.872 ∗∗∗

Q39 <— F2 0.615 0.548 0.028 22.188 ∗∗∗

Q56 <— F2 0.638 0.641 0.024 26.929 ∗∗∗

Q89 <— F2 0.627 0.639 0.023 26.789 ∗∗∗

Q41 <— F2 0.691 0.567 0.03 23.116 ∗∗∗

Q4 <— F3 1 0.734Q5 <— F3 1.024 0.74 0.038 27.213 ∗∗∗

Q6 <— F3 0.981 0.745 0.036 27.432 ∗∗∗

Q2 <— F3 0.9 0.555 0.044 20.288 ∗∗∗

Q7 <— F3 0.934 0.655 0.039 24.052 ∗∗∗

Q1 <— F3 0.817 0.541 0.041 19.762 ∗∗∗

Q8 <— F3 0.852 0.614 0.038 22.492 ∗∗∗

Q9 <— F3 0.757 0.61 0.034 22.359 ∗∗∗

Q3 <— F3 0.866 0.507 0.047 18.515 ∗∗∗

Q10 <— F3 0.801 0.555 0.039 20.286 ∗∗∗

Q55 <— F4 1 0.673Q54 <— F4 1.065 0.658 0.048 22.262 ∗∗∗

Q48 <— F4 0.996 0.616 0.047 20.97 ∗∗∗

Q53 <— F4 1.046 0.66 0.047 22.308 ∗∗∗

Q50 <— F4 0.893 0.583 0.045 19.973 ∗∗∗

Q43 <— F4 0.9 0.608 0.043 20.753 ∗∗∗

Q47 <— F4 0.792 0.575 0.04 19.712 ∗∗∗

Q45 <— F4 0.928 0.613 0.044 20.903 ∗∗∗

Q57 <— F4 0.772 0.577 0.039 19.789 ∗∗∗

Q64 <— F5 1 0.655Q59 <— F5 1.08 0.694 0.046 23.383 ∗∗∗

Q61 <— F5 1.108 0.784 0.043 25.854 ∗∗∗

Q65 <— F5 0.974 0.618 0.046 21.176 ∗∗∗

Q58 <— F5 1.072 0.694 0.046 23.401 ∗∗∗

Q60 <— F5 1.07 0.772 0.042 25.548 ∗∗∗

Q62 <— F5 0.961 0.684 0.042 23.088 ∗∗∗

Q63 <— F5 1.022 0.685 0.044 23.117 ∗∗∗

Q36 <— F6 1 0.724Q38 <— F6 0.841 0.623 0.039 21.341 ∗∗∗

Q35 <— F6 0.827 0.61 0.04 20.918 ∗∗∗

Q14 <— F6 0.643 0.439 0.042 15.234 ∗∗∗

(Continued)

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Table 5. (Continued)

Variables

Estimate ofregression

weights

Estimate ofstandardizedregression

weights S.E. C.R. P

Q26 <— F6 0.706 0.544 0.038 18.762 ∗∗∗

Q49 <— F6 0.72 0.617 0.034 21.146 ∗∗∗

Q70 <— F6 0.824 0.6 0.04 20.595 ∗∗∗

Q86 <— F7 1 0.769Q80 <— F7 0.95 0.694 0.036 26.232 ∗∗∗

Q87 <— F7 0.984 0.759 0.034 28.889 ∗∗∗

Q81 <— F7 0.871 0.724 0.032 27.454 ∗∗∗

Q78 <— F7 0.694 0.564 0.033 20.958 ∗∗∗

Q88 <— F7 0.711 0.566 0.034 21.023 ∗∗∗

Q76 <— F7 0.686 0.532 0.035 19.69 ∗∗∗

Q21 <— F8 1 0.64Q22 <— F8 0.94 0.612 0.047 19.916 ∗∗∗

Q23 <— F8 0.904 0.702 0.041 22.227 ∗∗∗

Q24 <— F8 0.957 0.72 0.042 22.663 ∗∗∗

Q20 <— F8 0.836 0.653 0.04 20.994 ∗∗∗

Q17 <— F8 0.831 0.619 0.041 20.098 ∗∗∗

∗∗∗p = 0.000

Table 6. Quality of assistive technology (AT).

Factor Definition Items (#)

AT effectiveness The device’s ability to accomplish itsstated purpose.

98, 96, 92, 97, 93, 94, 99, 95, 91(9 items)

Affordability and dependability How expensive and consistent the devicesare.

30, 29, 28, 31, 27, 32, 40, 33, 39, 56, 89, 41(12 items)

AT utility The extent to which the AT device assistsAT team members.

4, 5, 6, 2, 7, 1, 8, 9, 3, 10(10 items)

AT external support The extent to which the AT user relies onothers for upkeep, maintenance, andproper functioning of the device.

55, 54, 46, 53, 50, 43, 47, 45, 57(9 items)

AT operations The extent to which conditions are inplace for successful ATimplementation.

64, 59, 61, 65, 58, 60, 62, 63(8 items)

AT longevity The amount of time the AT devices can beused effectively.

36, 38, 35, 26, 49, 70(6 items)

AT discomfort Any distress that accompanies a deviceand results in the user being reluctant touse the device.

86, 80, 87, 81, 78, 88, 76(7 items)

AT compatibility The degree to which the AT device “fits”a person’s strengths.

21, 22, 23, 24, 20, 17(6 items)

Quality of AT The degree to which AT implementationor providing AT devices or servicesproduces the intended or better thanintended outcomes or benefits.

from elementary and secondary SETs. Seven out of nine itemsaddressed effectiveness of learning. The results showed thatSETs made efforts to enhance students’ academic motivation andachievement and implemented learning strategies by using AT.

F2: Affordability and Dependability (12 Items)

Affordability and dependability refer to how expensive and con-sistent the devices are. AT devices are often associated with acost-benefit ratio. That is, how much does a device cost now

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Table 7. Regression weights and standardized regression weights.

Variables

Estimate ofregression

weights

Estimate ofstandardizedregression

weights S.E. C.R. P

Q98 <— F1 1 0.787Q96 <— F1 1.021 0.788 0.032 32.397 ∗∗∗

Q92 <— F1 1.018 0.759 0.033 30.811 ∗∗∗

Q97 <— F1 1.004 0.761 0.027 36.605 ∗∗∗

Q93 <— F1 0.976 0.763 0.031 31.097 ∗∗∗

Q94 <— F1 0.944 0.69 0.034 27.601 ∗∗∗

Q99 <— F1 0.916 0.702 0.033 28.174 ∗∗∗

Q95 <— F1 0.942 0.709 0.033 28.495 ∗∗∗

Q91 <— F1 0.97 0.684 0.036 27.275 ∗∗∗

Q30 <— F2 1 0.73Q29 <— F2 0.995 0.748 0.023 43.696 ∗∗∗

Q28 <— F2 1.034 0.738 0.026 39.605 ∗∗∗

Q31 <— F2 0.961 0.732 0.032 29.81 ∗∗∗

Q27 <— F2 0.85 0.724 0.031 27.023 ∗∗∗

Q32 <— F2 0.875 0.745 0.031 27.836 ∗∗∗

Q40 <— F2 0.869 0.687 0.034 25.595 ∗∗∗

Q33 <— F2 0.875 0.701 0.033 26.249 ∗∗∗

Q39 <— F2 0.756 0.592 0.035 21.288 ∗∗∗

Q56 <— F2 0.765 0.675 0.031 24.71 ∗∗∗

Q89 <— F2 0.746 0.667 0.03 24.86 ∗∗∗

Q41 <— F2 0.827 0.594 0.037 22.12 ∗∗∗

Q4 <— F3 1 0.739Q5 <— F3 0.968 0.705 0.038 25.164 ∗∗∗

Q6 <— F3 0.928 0.711 0.037 25.379 ∗∗∗

Q2 <— F3 0.84 0.525 0.045 18.78 ∗∗∗

Q7 <— F3 0.92 0.651 0.039 23.359 ∗∗∗

Q1 <— F3 0.783 0.522 0.042 18.742 ∗∗∗

Q8 <— F3 0.823 0.597 0.039 21.22 ∗∗∗

Q9 <— F3 0.755 0.613 0.034 22.002 ∗∗∗

Q3 <— F3 0.851 0.502 0.047 17.997 ∗∗∗

Q10 <— F3 0.816 0.57 0.04 20.475 ∗∗∗

Q55 <— F4 1 0.652Q54 <— F4 1.002 0.604 0.045 22.214 ∗∗∗

Q48 <— F4 0.985 0.589 0.051 19.438 ∗∗∗

Q53 <— F4 1.032 0.631 0.05 20.561 ∗∗∗

Q50 <— F4 0.871 0.55 0.048 18.297 ∗∗∗

Q43 <— F4 0.953 0.623 0.047 20.428 ∗∗∗

Q47 <— F4 0.845 0.595 0.043 19.436 ∗∗∗

Q45 <— F4 0.978 0.625 0.048 20.488 ∗∗∗

Q57 <— F4 0.78 0.57 0.042 18.734 ∗∗∗

Q64 <— F5 1 0.622Q59 <— F5 1.088 0.663 0.052 21.125 ∗∗∗

Q61 <— F5 1.143 0.768 0.049 23.44 ∗∗∗

Q65 <— F5 0.999 0.601 0.044 22.956 ∗∗∗

Q58 <— F5 1.062 0.658 0.051 20.987 ∗∗∗

Q60 <— F5 1.104 0.758 0.048 23.197 ∗∗∗

Q62 <— F5 1.013 0.686 0.047 21.694 ∗∗∗

Q63 <— F5 1.069 0.68 0.045 23.564 ∗∗∗

Q36 <— F6 1 0.712Q38 <— F6 0.789 0.583 0.039 20.201 ∗∗∗

Q35 <— F6 0.86 0.625 0.041 20.742 ∗∗∗

(Continued)

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Table 7. (Continued)

Variables

Estimate ofregression

weights

Estimate ofstandardizedregression

weights S.E. C.R. P

Q26 <— F6 0.711 0.538 0.038 18.493 ∗∗∗

Q49 <— F6 0.758 0.638 0.036 21.119 ∗∗∗

Q70 <— F6 0.816 0.587 0.04 20.232 ∗∗∗

Q86 <— F7 1 0.712Q80 <— F7 1.011 0.684 0.046 22.075 ∗∗∗

Q87 <— F7 0.98 0.7 0.028 34.499 ∗∗∗

Q81 <— F7 0.908 0.699 0.04 22.475 ∗∗∗

Q78 <— F7 0.85 0.64 0.043 19.969 ∗∗∗

Q88 <— F7 0.776 0.572 0.04 19.319 ∗∗∗

Q76 <— F7 0.826 0.598 0.044 18.686 ∗∗∗

Q21 <— F8 1 0.617Q22 <— F8 0.931 0.585 0.044 21.326 ∗∗∗

Q23 <— F8 0.888 0.666 0.044 20.182 ∗∗∗

Q24 <— F8 0.941 0.683 0.046 20.594 ∗∗∗

Q20 <— F8 0.88 0.663 0.043 20.275 ∗∗∗

Q17 <— F8 0.88 0.632 0.045 19.555 ∗∗∗

∗∗∗p = 0.000

and in the future, and how much benefit do individuals receivefrom having the device? The answers to these questions pro-vide a major influence on whether AT devices are prescribed.Such issues as device cost, cost of repairs and maintenance,whether warranties exist, and so forth, contribute greatly tothe affordability and dependability of the device. Consistentwith existing studies, our results showed that affordabilityand dependability was another important consideration in ATdecision making. Similar to previous research, affordabilityand dependability were discussed in terms of cost of repair(Gelderblom & de Witte, 2002), maintenance, device portability,warranties, and dependability.

F3: AT Utility (10 Items)

The utility of AT devices refers to the extent to which theyassist AT team members, including teachers and students, usethe device effectively. Utility is related to the user’s chal-lenges as they pertain to disability conditions (the search fora person–device match), assessment, and planning (Bryant,Bryant, & Raskind, 1998). Again, consistent with some previ-ous models of AT utility, the present study addressed the bestmatch between students, AT, and environments through evidence-based assessment. Most of the existing research has focused ondevices and service in certain environment regardless of teach-ers’ capability. However, the items in this study emphasizedteachers’ capability and confidence in assessing students’ needs,AT selection, and knowledge about AT assessment, and deviceservices.

F4: AT External Support (9 Items)

External support (i.e., the extent to which the AT user relieson others for upkeep, maintenance, and proper function ofthe device) is a major influence on whether an AT device is

prescribed. A primary purpose of AT devices and services isto promote personal independence across life’s contexts. Beingdependent on others for setup or routine use or needing specialfurniture for device use are major deterrents to AT implementa-tion. The items of F4 examined the ease of installing, calibrating,assembling, and maintaining AT devices.

F5: AT Operations (8 Items)

Related to support, operations refers to the extent to which con-ditions are in place for successful AT implementation. Whensituations exist that encourage an individual to use a device(e.g., manufacturer information provided or maintenance rou-tines clearly established), it is more likely to be used to its fullcapability. In other words, such conditions serve to reduce bar-riers to timely acquisition and use of devices (Bryant, Seok,Bryant, & Shih, 2010). This factor focused on the operationalservices from the manufacturer and the AT manual.

Little research has addressed F4 and F5 because they are abouttechnology design and service. However, the results showed thatin AT practices and decision-making, AT design and servicesare some of the major considerations in AT selection (Dewsburyet al., 2003).

F6: AT Longevity (6 Items)

Longevity, the amount of time the AT devices can be usedeffectively, is a critical factor in determining whether a devicewill be purchased. Disabilities, if developmental, occur across thelifespan. Alternately, if the disabilities are acquired, they typicallyare long lasting. Thus, the longer AT devices last and improvethe functional capabilities of their users, the more cost efficientand cost effective they become. Consequently, issues such asobsolescence, ease of assembly, and bias-reduced are of criticalimportance.

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Fig. 2. Final CFA model (standardization path coefficient model).

F7: AT Discomfort (7 Items)

This factor addresses any distress (e.g., physical pain, anxiety,or embarrassment) that accompanies a device and will likelyresult in the user being reluctant to use the device because

AT devices are meant to increase productivity. This factor alsoaddressed efforts to find the perfect match between AT, students,and environments. As such, it emphasizes a student-centeredapproach in AT practices.

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F8: AT Compatibility (6 Items)

Compatibility, in this case, refers to how the AT device “fits”with a person’s strengths. AT devices, by their nature, shouldtap into a person’s strengths to help compensate for existingchallenges (Bryant, Bryant, & Rieth, 2002). Almost always,AT devices require training, and the extent to which the personhas prerequisite skills (e.g., keyboarding proficiency and properrelation to sight angles and visual distance) to use the devicedetermines whether the device will be used effectively.

As illustrated in Figure 2, the relationships among fac-tors showed that high-quality AT has higher effectiveness,affordability, dependability, utility, external support, operation,longevity, and compatibility, as well as a lower discomfort. Eachfactor underscores that AT should be ecologically considered inpursuing the best match between a given student and a device in agiven environment along with teachers’ ability to implement ATand the presence of external supports.

In addition, the final CFA model (standardization path coeffi-cient model) addressed that there are relations between factors.In brief, consistent with the results of previous studies, the find-ings of the present study showed that special education teachersprefer the functional and ecological evaluation (FEA) to use aperson-centered approach. Thus, it can be said there are highlypositive correlations between FEA and evidence-based practices.

Conclusion

Given the prevalence of AT devices and practices and the increas-ing numbers of users, special teachers and AT practitioners needevidence to back their data-driven AT decision-making to sub-stantiate quality practices in AT. Currently, however, althoughincreasing, resources for data-driven AT decision-making arevery limited.

In response to the need for evidence-based practices, thisresearch identified 8 factors of AT practice along with 67 itemsconsidered to ensure the quality of AT practice. The quality ofAT practices must be measured from multiple perspectives. Forthis research, the items were validated only from special educa-tion teachers’ perspectives. Thus, it is recommended that futureresearch identify factors of the quality AT practice and validateitems from the students’ or users’ perspectives. Another rec-ommendation is to investigate the relationships between eachfactor.

If an AT device were selected with these eight factors inmind, it would contribute to students’ independence and growthbecause the device was selected based on the considerations ofecology between students, environment, and devices. In conclu-sion, the results of this study underscore that a quality assess-ment instrument enhances evidence-based practices and therebyreduces AT abandonment.

Funding

This study was made possible with funds granted by theNational Research Foundation in Korea under the title,Development and Validation of Functional, Ecological, andMatching Evaluation Instrument for Assistive Technology andStudents With Disabilities at the Elementary and Secondary

Levels by Applying Multidimensional Scaling, numberB00078.

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