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Adapted Physical Activity Quarterly, 2013, 29, 184-205 2013 Human Kinetics, Inc. Official Journal of IFAPA

www.APAQ-Journal.comRESEARCH

Creation and Validation of the Self-Efficacy Instrument for Physical Education Teacher

Education Majors Toward Inclusion

Martin E. BlockUniversity of Virginia, USA

Yeshayahu (Shayke) HutzlerZinman College at the Wingate Institute, Israel

Sharon BarakThe Edmond and Lily Safra Childrens Hospital, Israel

Aija KlavinaLatvian Sports Academy, Latvia

The purpose was to validate a self-ef!cacy (SE) instrument toward including students with disability in physical education (PE). Three scales referring to intellectual disabilities (ID), physical disabilities (PD), or visual impairments (VI) were administered to 486 physical education teacher education (PETE) majors. The sample was randomly split, and exploratory and con!rmatory factor analyses (EFA and CFA, respectively) were conducted. After deleting items that did not meet inclusion criteria, EFA item loadings ranged from 0.53 to 0.91, and Cronbachs alpha reliability was high (for ID = .86, PD = .90, and VI = .92). CFA showed that the ID scale demonstrated good goodness-of-!t, whereas in the PD and in the VI scales demonstrated moderate !t. Thus, the content and construct validity of the instrument was supported.

Keywords: inclusion, self-ef!cacy scale, preservice physical education teachers

Including students with disabilities into general education is now commonplace in the United States (USDE, 2008), and it is slowly becoming an educational model in other countries around the world (Camerini, 2011; MEHR, 2007). While the inclusion

Martin Block is with the Kinesiology Program at the University of Virginia in Charlottesville. Yeshayahu Hutzler is with the Zinman College of Physical Education and Sport Sciences at the Wingate Institute, Israel. Sharon Barak is with the Edmond and Lily Safra Childrens Hospital, the Chaim Sheba Medical Center, Israel. Aija Klavina is with the Latvian Sports Academy in Latvia.

Self-Efficacy Scale 185

process has been mandated by international legislation (United Nations, 2006), many barriers have been encountered such as inadequate teacher training and professional development, lack of competence, limited support, large class sizes, and time and administrative demands, as well as low ef!cacy to teach students with disabilities (Kodish, Kulinna, Martin, Pangrazi & Darst 2006; Konza, 2008). Moreover, higher education in Europe is currently facing a massive transformation, commonly called the Bologna process, which promotes the advancement of European institutions to the top of the world higher education markets. Therefore, faculty members teach-ing in physical education teacher education (PETE) programs have systematically reviewed their curricula in reference to the ultimate programmatic goal of preparing competent physical education (PE) teachers who will be able to teach all students within a contemporary school environment. For example, Herold and Dandolo (2009) emphasized the need to upgrade initial teacher training programs to address inclusive PE more effectively, indicating limitations of the British National Curriculum in PE as a framework for inclusion. Furthermore, a study by Filipcic (2006) revealed that PETE majors in their !nal year at the Faculty of Sport in Ljubljana (Slovenia) did not feel adequately prepared to work with children who have motor disabilities.

Accommodating students with disabilities in a general physical education (GPE) setting can be challenging for physical educators. As indicated before, one major reason why students with disabilities do not always experience suc-cess in GPE is because physical educators do not feel prepared or self-con!dent enough to make all of the above-listed accommodations (Ammah & Hodge, 2006; Chandler & Greene, 1995; Hardin, 2005; Hodge, 1998; Kowalski & Rizzo, 1996; LaMaster, Gall, Kinchin, & Siedentop, 1998; Lienert, Sherrill, & Myers, 2001). This is a concern, as a key factor in the success of any inclusive PE or recreation program is training and self-con!dence of the instructor (Block & Rizzo, 1995; Lepore, Gayle, & Stevens, 1998). Research measuring self con!dence in physical educators has been primarily descriptive and atheoretical. For example, LaMaster et al. (1998), Hardin (2005), and Ammah and Hodge (2006) had six, !ve, and two participants in their studies, respectively. These studies were qualitative in nature using interviews and in one case natural observation (Ammah & Hodge, 2006), but none of these researchers used a theoretical framework when constructing their studies or analyzing their data.

Self-Efficacy TheoryBanduras self-ef!cacy theory (Bandura, 1977, 1997) provides a useful theoreti-cal framework for understanding and measuring self-con!dence. Self-ef!cacy is a task- and situation-speci!c form of self-con!dence and is de!ned by Bandura (1997) as ones beliefs in ones capabilities to organize and execute the courses of action required to produce given attainments (p. 3). The way one approaches a task or challenge is believed to be in"uenced by his/her level of self-ef!cacy. Those with higher levels of self-ef!cacy are more likely to try a particular task (i.e., make accommodations to include a student with a disability) compared with those with lower levels of self-ef!cacy. According to this theory, two people with similar abilities may perform very differently due to their respective levels of self-ef!cacy (Bandura, 2001). For example, according to the theory physical educators with high self-ef!cacy should have a more favorable attitude toward including children

186 Block et al.

with disabilities into their classes (i.e., They will take the time to learn about each student with a disability and make the necessary accommodations to ensure the students success) than physical educators with low self-ef!cacy. In addition, those with higher self-ef!cacy should persevere in their efforts to make the students experiences successful, even when things are not going as planned.

While self-ef!cacy theory has been used successfully in research with general and special education teachers (e.g., Armor et al., 1976; Ashton & Webb, 1986; Roll-Peterson, 2008; Soodak & Podell, 1993; Woolfolk Hoy & Davis, 2006) and with PE teachers (e.g., Martin & Hodges Kulinna, 2003, 2004, 2005; Stephanou & Tsapakidou, 2007), Hutzler, Zach and Gafni (2005) were the !rst and only researchers to apply self-ef!cacy theory to PETE majors in regard to the inclusion of students with disabilities in GPE. Participants (153 PETE majors in Israel) were asked to comment on their con!dence toward including students with disabilities in reference to four different disabilities: (a) physical disabilities, (b) developmental disorder, (c) attention de!cit disorders, and (d) visual impairments. Results showed variables were signi!cantly related to higher levels of self-ef!cacy, including pre-vious experience in instructing students with disabilities, attendance in a course focused on students with disabilities, and years in the PETE program. It was concluded that self-ef!cacy was related to attitudes toward teaching students with disabilities in PE. However, the authors noted several limitations with the survey, including lack of a clear description of the factor structure, lack of clear descrip-tions of disabilities, limited descriptions of the PE situations, and a relatively small sample size (Hutzler et al., 2005).

The issue of a lack of a description for each disability type was particularly troublesome in Hutzlers study. Prior research in the !eld of adapted physical educa-tion (APE) has supported !ndings that teachers attitudes and perceived competence varied depending upon the type and severity of the students disability (Block & Rizzo, 1995; Kowalski & Rizzo, 1996; Rizzo, 1984; Rizzo & Kirkendall, 1995; Rizzo & Vispoel, 1991). In addition, recommendations by Hutzler and his colleagues included controlling for disability type. A disability-speci!c instrument with clear de!nitions would allow teachers to make judgments of their self-ef!cacy beliefs in regard to a particular teaching framework. This would also allow for self-ef!cacy beliefs to be compared across disabling conditions.

The purpose of this study was to create and then analyze the properties of a survey instrumentthe Self-Ef!cacy Scale for Physical Education Teacher Edu-cation Majors toward Children with Disabilities (SE-PETE-D)which could be used to investigate self-ef!cacy beliefs of PETE majors toward the inclusion of students with speci!c disabilities in GPE. Based on previous attitude surveys in Europe and the U.S. (Downs & Williams, 1994; Hodge & Jansma, 1999; Rizzo, 1984; Rizzo & Vispoel, 1991), it was concluded that different disabilities are dif-ferentially perceived by practitioners, and that physical, intellectual, and sensory disabilities appear to create the greatest challenges when including students (Hutzler, 2003). Further studies based on student and teacher reports have supported this notion (e.g., Blinde & McCallister, 1998; Casebolt & Hodge, 2010; Goodwin & Watkinson, 2000; Hutzler, Fliess, Chacham, & Van den Auweele, 2002; Lieberman, Robinson, & Rollheiser, 2006; Place & Hodge, 2001). Therefore, in the current study it was decided to target the following three disabilities: intellectual disability (ID), physical disability (PD), and visual impairment (VI).


MethodsBased on Banduras (2006) recommendations for constructing a self-ef!cacy instru-ment, an instrument was constructed and an initial validation was performed to measure PETE majors self-ef!cacy toward including students with ID, PD, and VI in PE frameworks, including teaching skills, playing sport games, and performing !tness activities. This study involved the preliminary procedures of developing an instrument and assessing its content validity (Phase I), followed by the data collection using the developed instrument and the data analysis, to measure the instruments construct validity (Phase II).

Phase I: Preliminary Procedures-Instrument DevelopmentThe process used to construct the instrument in Phase I followed guidelines in scale development as discussed by Bandura (2006) and DeVellis (1991), and was conducted in four steps: (a) Step 1Considering content, (b) Step 2Item pool (c) Step 3Format, and (d) Step 4Expert review. Due to space limitations only part of this process is presented here. More details on each step in Phase I are available from the !rst author.

Step 1Considering content. The content being measured in the SE-PETE-D instrument is both context- (i.e., speci!c PE frameworks detailed in step 2), and situation (the three predetermined disability conditions) speci!c, as recommended by Bandura (2006).

Step 2Item pool. To generate possible items, an e-mail was sent to practicing GPE and APE teachers known to the researchers in selected counties in Virginia and Maryland asking them to respond to three questions for each of the three dis-ability contexts, regarding obstacles or challenges to inclusion for each disability, and three things good physical educators do to facilitate inclusion of each dis-ability. Each disability was described with a vignette describing a student with that type of disability (e.g., a student with a VI). Questions concerning both obstacles/challenges and things good physical educators do revolved around three speci!c situations: (a) when conducting !tness testing, (b) when teaching sport skills, and (c) when actually playing the sport.

Responses were obtained from a total of 21 general and 14 adapted physical educators. Responses for each situation and for each disability were listed and ranked from most to least cited. In total there were 1724 obstacles/challenges listed for !tness testing situation, 1921 for teaching sport skills, and 1822 for playing the sport across the three disabilities. Regarding things good physical educators should do there were 1219 skills or abilities listed for !tness testing situation, 1013 for teaching sports, and 1517 for situations when playing sports. Final items generated for the instrument were based on categories yielding the highest total responses for each question, as well as on researcher judgment of how well items represented the construct being measured. The !nal version of the SE-PETE-D used in this study included 11, 12, and 10 items in the ID, PD, and VI scales, respectively.

Step 3format. Following Banduras (2006) guidelines, content validity was evidenced by phrasing the questions in terms of can do rather than will do. Item scaling deviated from Banduras recommendation for a 010 scale based

188 Block et al.

on recent evidence by Feltz, Short, and Sullivan (2008); Myers et al. (2008); and Myers, Wolfe, and Feltz (2005), suggesting that a 14 or 15 scale is as effective when measuring self-ef!cacy as a 010 scale. As a result, a 15 scale was used with the following criteria: 1 = no con!dence, 2 = low con!dence, 3 = moderate con!dence, 4 = high con!dence, and 5 = complete con!dence.

Step 4Expert review. Step four involved sending the newly created survey instrument to ten university professors from the U.S. and Europe with expertise in self-ef!cacy theory, test construction, and/or expertise in APE, as well as to !ve graduate students. Experts were asked to critique the readability, clarity, conciseness, and layout of each section of the survey, including the directions, the self-ef!cacy scale itself, and demographic questions and each scale. While a different group of experts were previously asked to review the de!nitions of ID, PD, and VI, the new panel of experts was also asked to review these de!nitions. Feedback from experts further contributed to content and face validity evidence (DeVellis, 1991).

Phase II: ParticipantsThe total sample for phase II was 486 participants (170 females; 316 males). The participants ages ranged from 19 to 46 years. As two sets of factor analyses were conducted, the sample was randomly split into two groups of 243 cases. The number of items in the ID, PD, and VI scales was 11, 12, and 10, respectively. Therefore, the ratio of number of cases per item in the ID, PD, and VI scales was 22, 20, and 24, respectively. According to Tabachnick and Fidell (2001), this sample size satis!es the minimum amount of data and is considered good for factor analysis.

The distribution of participants across the years enrolled in college was 31 in the !rst year, 50 in the second year, 181 in the third year, 190 in the fourth year, and 34 in the !fth year or above. Fifty-!ve participants reported having attended two APE courses or more, 263 reported one APE course, 83 reported not having attended any APE course, and 85 participants did not report their attendance in APE courses. Sixty-four participants reported participation in two APE practicum sessions or more, 328 reported having participated in one APE practicum session, 82 reported not having participated in any APE practicum session, and one par-ticipant did not report.

Phase II: Data CollectionInstrumentation. The SE-PETE-D included three different scales but with a similar structure. After a detailed description of the purpose of the survey and how to complete the survey, three scales followed, each preceded by a vignette dem-onstrating a student with an ID, PD, or VI, who would be attending a GPE class. Below is an example of the vignette for a student with ID:

Noah is a high school student with an intellectual disability, so he doesnt learn as quickly as his classmates. Because of his intellectual disability, he also doesnt talk very well, so sometimes it is hard to understand what he is saying. However, he will point or gesture to help people know what he wants. He also has trouble understanding verbal directions, particularly when the directions have multiple steps. Noah likes playing the same sports as his classmates,


but he does not do very well when playing actual games. Even though he can run, he is slower than his peers and tires easily. He can throw, but not very far, and he can catch balls that are tossed directly to him. He likes soccer, but he cannot kick a ball very far, and he never can remember where to go on the !eld. He also likes basketball, but he does not have enough skill to dribble without losing the ball, and he is not coordinated enough to make a basket. He also does not really know the rules for basketball or other team sports, and he easily gets distracted and off task during the game.

Following the vignette, three sets of questions with varying numbers were presented focusing on how con!dent the respondent felt in the speci!c context of conducting !tness testing (34 questions), teaching sport skills (35 questions), and organizing the actual playing of a sport (34 questions), totaling 1012 questions in each scale. Demographic questions were included at the end of the instrument. An example of a !tness testing question was, How con!dent are you in your ability to keep Noah on task during !tness testing? An example of a question targeting teaching a sport skill was, How con!dent are you in your ability to modify the actual skills to help Noah when teaching sport skills? Finally, an example of a question targeting organizing the actual sport with the class was, How con!dent are you in your ability to modify the rules of the game for Noah? As noted above, participants rated their degree of con!dence to complete these situational-speci!c GPE activities for each of the targeted disabilities on a scale of 1 (no con!dence) to 5 (complete con!dence).

Test administration. After receiving approval from the !rst authors institutional review board, paper surveys were sent to professors in APE from !ve universities, representing four states that had undergraduate PE teacher education programs. Surveys were administered by professors during APE, PE pedagogy or motor devel-opment courses. There was no effort to determine response rate. Rather, professors informed the lead researcher how many students were in a targeted undergradu-ate class or who had a minor in APE and that many surveys were then sent to the professor. In total 486 questionnaires !lled in by the PETE majors were collected.

Phase II Data AnalysisThe expectationmaximization (EM) algorithm (Dempster, Laird, & Rubin 1977) was used for estimating missing values in returned questionnaires.

Construct validity. An integrated con!rmatory and exploratory factor analysis approach (CFA and EFA, respectively; see Marsh et al., 2009) was followed. The data were randomly divided into two (n = 243 cases in each half). Overall, 3.7% of the values were missing (9 values in the ID scale and 9 values in the PD scale). In addition, the missing data mechanism was missing completely at random. Because only a trivial number of values were missing, and the missing pattern was random, it is reasonable to hypothesize that the remaining cases are representative of the entire sample and that missing cases are no different than nonmissing cases in terms of the analysis being performed (Little & Rubin, 1987). Therefore, we implemented an ad hoc deletion of missing data.

EFA were conducted on the !rst half of the data (group = 0) and CFA were conducted on the second half (group = 1). All analyses were conducted separately

190 Block et al.

for each of the three scales (ID, PD, and VI), as each subgroup addressed a dif-ferent disability context (i.e., one EFA and one CFA were conducted for each of the three scales).

Exploratory factor analyses. The EFA was conducted via the principal compo-nent analyses (PCA) extraction method, followed by orthogonal (varimax) rotation to maximize variance. Before conducting the PCA, various statistical assumptions necessary for PCA were tested (Field, 2005). The Kaiser-Meyer-Olkin (KMO) index of sampling adequacy was set at > 0.75. Bartletts test of sphericity has to be highly signi!cant (p < .001; Tabachnick & Fidell, 2001). In addition, multicollinearity was examined via the variance in"ation factor (VIF). A VIF of > 2.5 and above might indicate a multicollinearity problem (Allison, 1999). The optimal number of factors was determined by latent root criteria (eigenvalues > 1.0, the Kaisers criterion K1) and inspection of the scree plot (Field, 2005; Velicer & Fava, 1998). Per factor, three variables are the minimum, as a factor with fewer than three items is generally weak and unstable (Costello & Osborne, 2005). An item with com-munality of less than 0.40 was removed from the analysis (Velicer & Fava, 1998) and the PCA was computed again. Crossloading of items was evaluated as well. A crossloading item was de!ned as an item that loads at 0.32 or higher on two or more factors (Costello & Osborne, 2005). Crossloading items were dropped from the analysis and the PCA was reconducted. In addition, to assess the !t of the factor models, we examined the differences between the model-based correlations and the observed correlations. No more than 50% of the residuals should be greater than 0.05 (Field, 2005). Once no communalities, crossloading or residual issues were identi!ed, the PCA was completed. The PCA procedure was conducted with IBM SPSS 15 software (IBM Corporation, NY, USA).

Confirmatory factor analysis. Based on the EFA results, CFA was performed with IBM SPSS-Amos 19 (IBM Corporation, NY, USA). The goodness-of-!t of each model was assessed using chi-square, normal !t index (NFI), comparative !t index (CFI; Bentler, 1990) and root-mean-square error of approximation (RMSEA; Steiger, 1990). Nonsigni!cant chi-squares are considered as an acceptable model !t (Joreskog & Sorbom, 1981). Values greater than 0.90 are considered as an accept-able model !t for the NFI and CFI (Bentler & Bonett, 1980). RMSEA values below 0.05 are considered to re"ect good !t to the model, values 0.050.10 moderate !t, and values greater than 0.10 bad !t (Hair, Black, Babin, & Anderson, 2009).

ResultsThis section describes the outcomes of the data collection and analysis performed to establish SE-PETE-Ds construct and predictive validity, following the estab-lishment of the instruments content validity that had been reached within the four steps of initial instrument development. The total collection of items in the three separate scales and their loadings is described in Table 1. The items accepted by the EFA are described in Table 1. In both tables scale items are designated with alphabetical labels for facilitating orientation throughout the manuscript. These labels do not necessarily identify similar items across scales.

191

Tabl

e 1

Fact

or s

truc

ture

s of

the

Situ

atio

nal-S

peci

fic S

elf-

Effi

cacy

and

Incl

usio

n S

tude

nts

With

Dis

abili

ties

in

Phy

sica

l Edu

catio

n by

Exp

lora

tory

Fac

tor A

naly

sis

Sca

les

Sig

nIte

ms

Fact

or L

oadi

ngs

Tota

l va

rian

ce

expl

aine

dF1

F2F3

IDH

Inst

ruct

pee

rs to

hel

p N

oah

whe

n te

achi

ng s

port

ski

lls.

0.88

0.13

CIn

stru

ct p

eers

to h

elp

Noa

h du

ring

!tn

ess

test

ing.

0.81

0.01

KIn

stru

ct p

eers

to h

elp

Noa

h du

ring

the

gam

e.0.

780.

30

JH

elp

Noa

h st

ay o

n ta

sk d

urin

g th

e ga

me.

0.18

0.83

DM

odif

y yo

ur in

stru

ctio

ns to

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p N

oah

unde

rsta

nd w

hat t

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whe

n te

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spor

t ski

lls.

0.10

0.82

EH

elp

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h st

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n ta

sk w

hen

teac

hing

spo

rt s

kills

.0.

100.

69A

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p N

oah

on ta

sk d

urin

g !t

ness

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0.64

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st fo

r Noa

h.0.

130.

20

FM

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IM

odif

y ru

les

of th

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me

for N

oah.

0.24

0.28

vari

ance

exp

lain

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33.1

6%68

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192

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Not

es: I

D =

inte

llect

ual d

isab

ility

; PD

= P

hysi

cal d

isab

ility

, VI =

vis

ual i

mpa

irm

ent;

F, F

acto

r; in

ID, F

1 =

peer

s in

stru

ctio

n, F

2 =

stay

ing

on ta

sk; i

n PD

F1

= sp

eci!

c ad

apta

tions

, F2

= pe

ers

inst

ruct

ion,

F3

= sa

fety

; in

VI

F1 =

spe

ci!c

ada

ptat

ions

, F2

= pe

ers

inst

ruct

ion;

ext

ract

ion

met

hod-

prin

cipa

l com

pone

nt a

naly

sis;

rot

atio

n m

etho

d- v

arim

ax; f

acto

r loa

ding

s

0.32

are

sho

wn

in b

old;

item

s w

hich

wer

e re

mov

ed o

n ac

coun

t of l

ow c

omm

unal

ity (l

ess

than

0.4

), cr

ossl

oadi

ng is

sues

(ite

ms

that

lo

ad a

t 0.3

2 or

hig

her o

n tw

o or

mor

e fa

ctor

s) a

nd/o

r col

linea

rity

issu

es a

re re

pres

ente

d in

the

gray

cel

ls. A

ll ite

ms

star

t with

the

phra

se

How

con!d

ent a

re y

ou in

you

r ab

ility

to.

Rem

ark:

Fol

low

ing

item

s re

mov

al, a

n ad

ditio

nal E

FA w

as c

ondu

cted

on

each

scal

e. T

he se

cond

ary

EFA

dem

onst

rate

d th

at in

the

vari

ous s

cale

s the

pro

port

ion

and

vari

ance

exp

lain

ed b

y ea

ch fa

ctor

did

not

sig

ni!c

antly

alte

r. A

dditi

onal

info

rmat

ion

and

exac

t res

ults

of t

he s

econ

dary

EFA

ana

lysi

s w

ill b

e pr

esen

ted

upon

requ

est.

Tabl

e 1

(con

tinue

d)


Exploratory Factor AnalysisBefore conducting the PCA, we tested several of the statistical assumptions for such analyses. The KMO index ranged from 0.825 (ID) to 0.870 (VI) and Barletts test of sphericity was statistically signi!cant (p < .0001). These results indicated that the sample size was adequate and the extracted factors accounted for substantial observed variance. The descriptive statistics (mean and STD) of the question-naires items and scales Cronbachs reliability coef!cients are presented in Table 2. Cronbachs alpha reliability for all items in each of the scales was high (for ID = .86, PD = .90 and VI = .92).

Intellectual Disability (ID) scale. The ID scale originally included 11 items; however, an initial examination of the items using PCA revealed very low com-munalities (< 0.4) in items B and I. Subsequent analysis demonstrated that items A, F, and G were crossloading. Accordingly, items A, B, F, G, and I were removed from the PCA, and a total of six items were retained in subsequent analyses. The K1-criterion and scree plot indicated a two-factor solution explaining 68.14% of the variance. The communalities ranged from 0.49 (item D) to 0.79 (item H). The !rst and second factors both consisted of three items each. For factor load-ings, see Table 2. Judged by the items content, the !rst factor was comprised of items describing Peers Instruction (PI); the second factor was comprised of items describing Staying on Task (ST).

Physical Disability (PD) scale. The PD scale originally included 12 items; however, the VIF test indicated a multicollinearity problem in items I and J (VIF > 2.5). Therefore, these two items were dropped from the analyses, and a total of 10 items were retained in subsequent analyses. The K1-criterion and the scree plot resulted in a three-factor solution explaining 74.43% of the variance. After removing items I and J from the analyses, communalities ranged from 0.57 (item E) to 0.88 (item L). The !rst, second, and third factors consist of four, three, and three items, respectively (see Table 3). The !rst factor included items addressing Speci!c Adaptations (SA); the second factor included items related to Peers Instruction (PIalso appearing in the ID scale); and the third factor included items addressing Safety (S).

Visual Impairment (VI) scale. The VI scale originally included 10 items. However, item F had a low communality (< 0.4) and therefore was not included in the PCA, resulting in the retention of nine items in subsequent analyses. The K1-criterion and the scree plot resulted in a two-factor solution explaining 70.52% of the variance. The communalities ranged from 0.50 (item C) to 0.84 (item H). The !rst factor consisted of !ve items, whereas the second factor consisted of four items (see Table 3). Although we labeled the !rst factor Speci!c Adaptations (SA), items H and G were logically more likely to be within the safety factor, which was not generated in the VI scale. The second factor was labeled Peers Instruction (PI), but included item B, which was originally intended to be within the ST factor and was not generated in the VI scale.

194

Tabl

e 2

Des

crip

tive

Sta

tistic

s of

Sca

le It

ems

and

Cro

nbac

hs

Rel

iabi

lity

Scal

eS

ign

Item

Mea

nSD

Scal

e

IDH

Inst

ruct

pee

rs to

hel

p N

oah,

whe

n te

achi

ng s

port

ski

lls.

3.85

0.81

PIC

Inst

ruct

pee

rs to

hel

p N

oah

duri

ng !

tnes

s te

stin

g.3.

970.

77PI

KIn

stru

ct p

eers

to h

elp

Noa

h du

ring

the

gam

e.3.

780.

82PI

.81

JH

elp

Noa

h st

ay o

n ta

sk d

urin

g th

e ga

me.

3.44

0.83

STD

Mod

ify

your

inst

ruct

ions

to h

elp

Noa

h un

ders

tand

wha

t to

do w

hen

teac

hing

spo

rt s

kills

.3.

780.

78ST

EH

elp

Noa

h st

ay o

n ta

sk w

hen

teac

hing

spo

rt s

kills

.3.

470.

77ST

.73

PDB

To M

odif

y th

e [!

tnes

s] te

st fo

r Ash

ton.

3.93

0.82

SAA

Cre

ate

indi

vidu

al g

oals

for A

shto

n du

ring

!tn

ess

test

ing?

4.10

0.86

SAE

Mak

e m

odi!

catio

ns to

spo

rts

skill

s if

Ash

ton

cann

ot p

erfo

rm s

port

ski

lls w

hen

teac

hing

sp

ort s

kills

?3.

800.

83SA

GM

odif

y eq

uipm

ent t

o he

lp A

shto

n w

hen

teac

hing

spo

rt s

kills

.3.

950.

88SA

.81

LIn

stru

ct p

eers

to h

elp

Ash

ton

whe

n du

ring

the

gam

e.3.

870.

83PI

HIn

stru

ct p

eers

to h

elp

Ash

ton

whe

n te

achi

ng s

port

ski

ll.3.

810.

79PI

CIn

stru

ct p

eers

to h

elp

Ash

ton

duri

ng !

tnes

s te

stin

g.3.

810.

83PI

.89

DM

ake

the

envi

ronm

ent s

afe

for A

shto

n du

ring

!tn

ess

test

ing.

4.20

0.84

SF

Mak

e th

e en

viro

nmen

t saf

e fo

r Ash

ton

whe

n te

achi

ng s

port

ski

lls.

4.08

0.82

SK

Mak

e th

e en

viro

nmen

t saf

e fo

r Ash

ton

duri

ng th

e ga

me.

4.07

0.90

S.8

4V

IH

Mak

e th

e en

viro

nmen

t saf

e fo

r So!

a du

ring

the

gam

e.3.

761.

08SA

GM

ake

the

envi

ronm

ent s

afe

for S

o!a

duri

ng !

tnes

s te

stin

g.3.

990.

94SA

JM

odif

y ru

les

of th

e ga

me

for S

o!a.

3.78

0.82

SAA

Mak

e th

e en

viro

nmen

t saf

e fo

r So!

a du

ring

!tn

ess

test

ing.

3.88

0.96

SAD

Mod

ify

inst

ruct

ions

to h

elp

So!a

whe

n te

achi

ng s

port

ski

lls.

3.70

0.85

SA0.

88B

Inst

ruct

pee

rs to

hel

p So!a

dur

ing !t

ness

test

ing.

3.96

0.81

PII

Inst

ruct

pee

rs to

hel

p So!a

dur

ing

the

gam

e.3.

830.

88PI

EIn

stru

ct p

eers

to h

elp

So!a

whe

n te

achi

ng s

port

ski

lls.

3.87

0.83

PIC

Mod

ify

the !t

ness

test

ing

requ

irem

ents

for S

o!a

duri

ng !

tnes

s te

stin

g.3.

890.

88PI

0.86

Leg

end:

ID

, Int

elle

ctua

l dis

abili

ty; P

D, p

hysi

cal d

isab

ility

; VI,

visu

al im

pair

men

t; PI

, pee

rs

inst

ruct

ion;

S, s

afet

y; S

A, s

peci!c

ada

ptat

ions

; ST,

sta

ying

on

task

; ST

D,

stan

dard

dev

iatio

n.


Confirmatory Factor AnalysisCFA were performed for the models that were found by EFA. The results of the CFA can be seen in Figure 1. To improve the model-data !t, the Amos software automatically created a modi!cation index, which suggested several errors (residuals, designated as an e + number in Figure 1) to be correlated. These cor-related variables share some content, such as, for example, the instruction in items K and D and the game in items K and J of the ID scale (see Table 2).

Although the chi-square was signi!cant (compromising model !t) in all models except for the ID, other goodness of !t measures demonstrated acceptable model !t. For instance, in the three evaluated models the NFI and CFI exceeded the 0.90 cutoff criteria. Moreover, in the ID subgroup the RMSEA demonstrated good !t, whereas in the PD and in the VI subgroups only moderate !t.

To better understand the reduced model !t in the PD and VI subgroups, an EFA was conducted to the group that was used in the CFA (group = 1). The results suggested that there was an agreement between group 0 and group 1 in the EFA regarding the number of factors and the items in each factor. However, the order of the items in each factor in terms of loading was not always similar (see Table 3).

DiscussionThe purpose of this study was to create and validate the content and construct of a new disability-speci!c self-ef!cacy instrument labeled SE-PETE-D, comprised of three disability speci!c scales addressing the ID, PD, and VI conditions. As reported in the Methods section regarding the !rst stage of the instrument development, con-tent validity of these scales was established by an expert panel. Cronbachs reliability analyses, performed in each of the factors and the total s generated, con!rmed their internal consistency after deleting items that did not satisfy statistical requirements. The factor structure, which appeared in each of the scales during Phase II, in both the EFA and the CFA, was not consistent with the PE situational contexts developed in Phase I. However, these scales generated factors consisting of groups of items representing what good physical educators do while engaging in such situations, which were proposed in Step 2 of Phase I. In total, four factors were generated: (a) instructing peers to assist the student with disability (PI), across all three scales; (b) coping with speci!c adaptation requirements (SA) across the ID and VI scales; (c) assuring the safety of the students with disability (S), only in the PD scale; and (d) adapting instructions to keep students with disability staying on task (ST), only in the PD scale. The generation of these factors provides, for the !rst time, empirical evidence for what PETE majors perceive as signi!cant expertise domains while considering inclusion of students with disabilities in general PE classes. The link-ing of residuals performed according to the modi!cation index proposed within the CFA procedure also represents cross-factorial relationships, such as speci!c adaptations and peer instruction items to the VI scale, which represent the intensive use of peer instruction while including students with VI (Lieberman et al., 2006).

Overall, the statistical procedures indicated good data model !t in the ID scale and moderate-to-good data model !t in the PD and VI scales.

In the following sections, the factors and items of each scale will be discussed according to the frequency in which they appear in the scale: Peer instruction (all

196

Figu

re 1

1

a: In

telle

ctua

l dis

abili

ty s

cale

; 1b:

Phy

sica

l dis

abili

ty s

cale

; 1c:

Vis

ual i

mpa

irm

ent s

cale

.

197

Tabl

e 3

Phy

sica

l Dis

abili

ty a

nd V

isua

l Im

pair

men

t Sub

grou

ps It

ems

Ord

er (F

rom

the

Hig

hest

to th

e Lo

wes

t Fa

ctor

Loa

ding

s) in

Sub

grou

ps 0

and

1

Phys

ical

Dis

abili

ty (F

acto

r Loa

ding

s)Vi

sual

Impa

irmen

t (Fa

ctor

Loa

ding

s)

Fact

or 1

Fact

or 2

Fact

or 3

Fact

or 1

Fact

or 2

Gro

up 0

Gro

up 1

Gro

up 0

Gro

up 1

Gro

up 0

Gro

up 1

Gro

up 0

Gro

up 1

Gro

up 0

Gro

up 1

BB

LH

DD

HH

BB

AA

HL

FF

GG

IE

EE

CC

KK

JJ

EI

GG

AA

CC

DD

Not

es. G

roup

0 re

pres

ents

the

expl

orat

ory

fact

or a

naly

sis

that

was

con

duct

ed o

n th

e !r

st h

alf o

f the

dat

a; g

roup

1 re

pres

ents

the

con!

rmat

ory

fact

or a

naly

sis

that

was

co

nduc

ted

on th

e se

cond

hal

f of t

he d

ata;

sha

ded

cells

repr

esen

t mis!t

bet

wee

n gr

oups

0 a

nd 1

in it

ems

fact

or lo

adin

gs o

rder

; ite

m la

bels

app

ear i

n Ta

ble

1.

198 Block et al.

three scales), followed by speci!c adaptations (in PD and VI), and then safety and staying on task, which only appear in one of each condition (VI and ID, respectively).

Peers Instruction (PI)This factor was validated in all three scales across all three contexts. The useful-ness of instructing peers to assist students with disability has been demonstrated in many scholarly contributions (see a summary review in Block & Obrusnikova, 2007). Thus, it is important for PETE graduates to master the peer tutoring pro-cess. Utilizing peers as a natural support might facilitate interactions between students with and without disabilities, while also providing individualized teaching instructions (Block, 2007; Klavina & Block, 2008; Murata & Jansma, 1997). More speci!cally, using peer rather than adult support is important when addressing the behavior change goals (Block & Zeman, 1996; Slininger, Sherrill, & Jankowski, 2000; Vogler, Koranda, & Romance 2000). Studies demonstrated that peer tutoring can be effective in increasing physical participation, instructional assistance and positive social interactions for students with severe ID and PD (Klavina & Block, 2008), and in increasing active learning time and skilled performance in students with VI (Wiskochil, Lieberman, Houston-Wilson, & Petersen, 2007). Having a valid instrument for assessing the SE of PETE in peer tutoring may be useful in both teaching design and program assessment.

Specific Adaptations (SA)The outcomes of our analysis grouped SE perceptions toward adapting tasks, envi-ronment, methods and equipment while including students with PD and VI (e.g., Block, 2007; Lieberman & Houston-Wilson, 2011; van Lent, 2006) in a factor labeled speci!c adaptations (SA). Recent surveys done in Eastern and Western European countries demonstrated that PE teachers have a lack of knowledge on how to adequately adapt the environment and the limited resources to acquire adapted equipment when including students with disabilities (Klavina & Kudlacek, 2011). In the VI scale, SA items re"ected all three contextual frameworks. However, in the PD scale (unlike the PI and S contextual frameworks), SA items re"ected only the contexts of !tness testing and skill instructions, probably due to the omission of items I and J (con!dence in the ability to modify rules of the game and equipment to help during the game, respectively). From the EFA it appeared that the omitted items were interrelated. A revised description of adaptation within the game context for PD is warranted and should be included in future research.

Safety (S)This factor was considered for the PD and VI scales, and con!rmed by CFA across all three situational contexts only in PD. Accommodating students with PD has been reported to cause instructional and safety concerns, particularly when creating modi!cations to team sports such as basketball and soccer (Casebolt & Hodge, 2010). The construction of a speci!c factor accounting for SE while adapting safety precautions during the preparation of PETE majors to inclusion of students


with PD appears very useful for assisting practitioners to maintain an accountable teaching framework. In the VI scale three items including safety statements (A,G, and H) were included in the SA factor, probably due to prioritizing the need of modi!cation in these items, while PETE programs were envisioning these tasks. This ambiguity was also demonstrated in the modi!cation index generated in this scale, which linked interfactorial item residuals. Further work is required to enable the construction of safety precautions within the adaptations provided for students with VI.

Staying on Task (ST)This factor was generated only in the ID scale. Children with ID have been reported to be lacking the motivation to maintain sport activity or a designated exercise protocol for suf!cient periods of time (Fernhall, Tymeson, & Donaldson, 1988; Fernhall, Tymeson, Millar, & Burkett, 1989; Vashdi, Hutzler, & Roth, 2008). Simi-larly, Temple and Walkley (1999) found that children with ID were less physically active compared with their peers without ID in inclusive PE settings. Therefore, having a speci!c factor in the ID scale focusing on keeping their attention on task re"ects a major teaching concern for general physical educators. The scale items con!rmed in this study exhibit contexts of skill learning and game participation, but not of !tness testing, where item A (keeping on task during !tness testing) had to be excluded due to high overlapping variance with the PI factor. This overlapping may be due to using peer tutoring while keeping the participant with ID on task during training and measuring !tness (Stanish & Temple, 2012). Clarifying this aspect requires future research and is warranted due to the importance of !tness in school children with ID (Sit, McManus, McKenzie, & Lian, 2007).

LimitationsThe preliminary phase of construction of the SE-PETE-D was based on collective assumptions and an item pool regarding all types of disabilities included in the three scales. This may have impacted the need to delete some of the items in each scale. A differential and speci!c construction of item pools for each disability may have changed the structure of the !nal scale and should be explored in future studies.

A primary consideration in scale development is the choice of the number of response categories (Shaftel, Nash, & Gillmor, 2012). Accordingly, it has been argued that the number of response categories is an important factor in"uencing the scales reliability, validity, and stability (Andrews, 1984; Comrey, 1988; Preston, & Colman, 2000). However, others have also stated that after four or !ve response categories, the bene!ts to reliability obtained from additional scale points diminishes (Andrews, 1984; Lozano, Garcia-Cuento, & Muniz, 2008). Our scale construction followed this rationale. Due to the need to further validate the PD and VI scales, more responses may be expected in future research.

Another concern was that the modi!cation index proposed in the CFA Models included linking of residuals across factors in the PD and VI scales. However, this appears to be related to the complex interaction of adaptations required in these situations for enhancing learning and performance of both the students with and those without the disability, while assuring their safety.

200 Block et al.

ConclusionIn agreement with Banduras postulation of situation and context speci!city, it appears that indeed the scales of the SE-PETE-D instrument each have a unique structure based on differences in how respondents perceive the attributes of each disability and the impact of these attributes on the inclusion practice. These scales should be further explored with GPE and APE PETE students and PE practitioners. Furthermore, revised versions of the scales may include more detailed vignettes to increase the consistency of disability perception by respon-dents (e.g., various mobility patterns in PD). Nevertheless, the individual factors internal consistency (Cronbach reliability) ranged from .73 to .89, which is acceptable to good. Therefore, these particular scales with the items con!rmed exhibit signi!cant construct validity evidence; however, to be used for exploring the impact of different programs on SE in PETE students, more external valida-tion studies are required.

Recommendations for Future ResearchBased on the !ndings of this study, it is suggested that all three scales of the SE-PETE-D can be used to identify the discriminative power of demographic variables hypothesized to be meaningful predictors of PETE majors SE, including teaching experience, academic course work, practicum and nonteaching speci!c exposure to students with disability. In addition, the results of this study imply several follow-up research studies to further understand the SE of PETE students toward including students with disabilities. Speci!cally, research should compare PETE students who had an undergraduate minor in APE and the more traditional PETE programs that provide only one APE course. It would seem rather obvious that students who minor in APE would have more course work and practical experiences with students with disabilities, and as a result students with APE minors should have higher levels of self-ef!cacy toward inclusion.

In addition, qualitative studies using interviews and focus groups are needed to better understand the reasons behind self-ef!cacy of PETE students. For example, what speci!c information, readings or practical experiences had the greatest impact on self-ef!cacy toward inclusion, and why? What elements in the PETE training program were missing that PETE students believe would improve self-ef!cacy toward inclusion? These more detailed questions would provide a deeper under-standing of how PETE programs can contribute to the development of self-ef!cacy. It would be particularly interesting to interview students who have an APE minor and to have them explain in more detail which coursework and experiences were most helpful when it came to accommodating students with disabilities who are included in GPE. While some experiences may be helpful in understanding and feeling comfortable with students with disabilities in general (e.g., working with a child one-on-one in a laboratory setting), are there speci!c experiences or activi-ties that help PETE students learn how to include one child with a disability into a GPE class?

Third, research should examine the effects of a speci!c APE course on improv-ing self-ef!cacy of PETE students toward inclusion. As noted earlier, the typical model for PETE programs is to have one APE course, and it is assumed that this


one course adequately prepares PETE students to accommodate students with dis-abilities into GPE classes. Most would agree that one APE course is not enough to prepare PETE students for inclusion, particularly when the course is a survey course that focuses on information about disability (e.g., what is cerebral palsy, what is an intellectual disability) rather than the constraints presented by these disabilities and how to accommodate these students with these disabilities in GPE. Interesting research could focus on prepost self-ef!cacy after an APE course. Further research could examine prepost self-ef!cacy in APE courses that are more general in content compared with those which have a more practical focus.

Finally, research should examine the effects of a practicum experience on self-ef!cacy toward inclusion. There is no doubt that hands-on experience with children with disabilities will improve the understanding and comfort level of PETE students toward students with disabilities (Hodge, Davis, Woodard, & Sherrill, 2002; Hodge & Jansma, 1999; Hodge, Tannehill, & Kluge, 2003). However, does a one-on-one experience in a university-based swim-and-gym program help PETE students develop the skills (and ultimately the self-ef!cacy) toward including one child with a disability into a GPE class of 3040 students without disabilities? Again, such information could be obtained from survey data collected prepost practicum experiences. However, it would be interesting to include interviews of students to determine what speci!cally in their practicum did they !nd most help-ful, and how the practical experiences could be modi!ed to better prepare PETE students for inclusion.

Acknowledgment

Authors would like to thank Professor Gershon Tenenbaum from the College of Education, Florida State University for his constructive remarks concerning the statistical analysis.

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Creation and validation of scale for physical education teachers inclusion.pdf