Assessment Of Teachers Beliefs About Classroom Use Of Critical-Thinking Activities

10.1177/0013164404267281
EDUCA
TIONAL AND PSYCHOLOGICAL MEASUREMENT
TORFF AND W
ARBURTON
ASSESSMENT OF TEACHERS’ BELIEFS ABOUT
CLASSROOM USE OF CRITICAL-THINKING ACTIVITIES
BRUCE TORFF
Hofstra University
EDWARD C. WARBURTON
University of California at Santa Cruz
This article reports five studies in which a scale for assessing teachers’ beliefs about
classroom use of critical-thinking (CT) activities was developed and its scores evaluated
for reliability and validity. The Critical Thinking Belief Appraisal (CTBA) is based on a
four-factor “advantage effect” model: the theoretical premise that teachers’ CT-related
decision making is associated with their beliefs about the effectiveness of (a) high-CT
activities for high-advantage learners, (b) high-CT activities for low-advantage learners,
(c) low-CT activities for high-advantage learners, and (d) low-CT activities for low-
advantage learners. Results indicated that the scale producedscores with high reliability;
a stable factor structure; and satisfactory discriminant, construct, and predictive validity.
The studies supported the theoretical and practical utility of the construct and measure of
teachers’ beliefs about classroom use of CT activities.
Keywords: critical thinking; classroom instruction; teachers’ beliefs; disadvantaged
learners; advantage effects
Success in adult lifedepends on, among other things, the capacityfor criti-
cal thinking (CT)—purposeful and goal-directed cognitive skills or strate-
gies that increase the likelihood of a desired outcome (Halpern, 2002). Suc-
cess in school also depends on CT skills perhaps now more than ever as high-
stakes tests increasingly present CT-rich tasks such as writing essays and ex-
plaining mathematics responses (Yeh, 2002). Accordingly, extensive bodies
of literature focus on CT (e.g., Browne & Keeley, 2001; Ennis, 1987;
Halpern, 2002; Resnick, 1987) and applications of CT in education (e.g.,
Educational and Psychological Measurement, Vol. 65 No. 1, February 2005 155-179
DOI: 10.1177/0013164404267281
© 2005 Sage Publications
155

Henderson, 2001; O’Tuel & Bullard, 1993; Pogrow, 1990, 1994; Raths,
Wasserman, Jonas, & Rothstein, 1986; Torff, 2003).
This article describes the development of a measurement instrument
designed to explore related phenomena. The goal is to identify differences
among teachers in beliefs about the conditions under which they deem it
effective to engage students in CT-rich and/or CT-lean activities. In what fol-
lows, a theoretical model of CT-use beliefs is presented accompanied by a
scale based on this model, the Critical Thinking Belief Appraisal (CTBA).
The article reports a series of five studies in which the construct and scale
were developed and the reliability and validity of the scale’s scores were
evaluated.
The Impact of Perceived Learner
Advantages on Teachers’ CT-Use Beliefs
Increasing attention in educational psychology focuses on teachers’beliefs,
which have been shown to influence their decision making concerning when
to employ CT-rich activities (e.g., debate) or comparatively CT-lean ones
(e.g., direct instruction) (Anning, 1988; Brickhouse, 1990; Calderhead,
1996; Nespor, 1987; Richardson, 1996). In particular, teachers tend to regard
CT-rich activities as more appropriate for high-advantage learners (i.e., high
in academic ability, prior knowledge, and motivation) than low-advantage
learners (Metz, 1978; Oakes, 1990; Page, 1990; Raudenbush, Rowan, &
Cheong, 1993; Zohar, Degani, & Vaakin, 2001). These findings are consis-
tent with the theory that teachers’CT-related beliefs are associated with their
perceptions of learners’ level of advantages (i.e., an “advantage effect”):
When learners are perceived to be high in advantages, CT activities are
thought to be effective and classroom CT-use levels are high; conversely,
when learners are perceived to be disadvantaged, CT activities are viewed as
ineffective and CT-use levels are comparatively low.
To further investigate the advantage effect, a new scale to assess teachers’
CT-use beliefs was developed. To date, little research has been conducted to
validate either the construct “CT-use beliefs” or the scores of measurement
instruments designed to tap these beliefs. Advantage-effect research has
included examinations of the reliability of scores from the assessments
employed but littleevaluation of the validity of the scores or the constructs on
which the assessments were based (Raudenbush et al., 1993; Zohar et al.,
2001). With the discriminant validity of the CT-use construct as yet unexam-
ined, it remains unclear the extent to which the advantage effect is an artifact
of hidden factors (such as CT ability, CT disposition, or need for social
approval—factors we discuss below). Similarly, the predictive validity of the
construct “CT-use beliefs” remains unexplored, so it is unknown the extent to
which the advantage effect is manifested in teachers’ classroom practices as
156 EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT

well as their espoused beliefs. Given the mixed results of research on the cor-
respondence of beliefs to behavior in educational research (Fang, 1996;
Wilcox-Herzog, 2002), examination of the predictive validityof a measure of
CT-use beliefs seems warranted.
Development of the CTBA
Operationalizing the CT Level in Classroom Activities
Development of the CTBA began with drafting of a series of 20
prompts—brief descriptions of classroom activities set in secondary-level
academic subjects (English, languages other than English, mathematics, sci-
ence, and social studies). Based on the theoretical premise that teachers’CT-
related decision making entails beliefs about both CT-rich and CT-lean activ-
ities, equal numbers of high-CT and low-CT prompts were included. Below
are examples of each.
High CT: A social studies class is studying the Treaty of Versailles signed
at the end of World War I. The teacher assigns learners to write “letters from
the future” to President Wilson arguing why the United States should or
should not support the treaty.
Low CT: A social studies class is studying the Industrial Revolution. The
teacher provides learners with a list of inventions, explains the impact of
these inventions during this period, and describes how they continue to influ-
ence the modern world.
Operationalizing Learner Advantages
Based on the theoretical proposition that CT-use beliefs are influenced by
teachers’ judgments of learners’ advantage level, development of the CTBA
entailed procedures to operationalize teachers’ perceptions of “high-advan-
tage” and “low-advantage” learners. We devised a contextualized assessment
scheme drawing on teachers’ conceptions of the particular characteristics
they take into consideration in attribution of a learner (or group of learners) as
high advantage or low advantage. Three such “advantage characteristics”
were nominated: ability (learners’ capacity for intellectual or academic
achievement when dealing with the specific topic to which a given prompt
refers), prior knowledge (the extent of learners’knowledge about the specific
topic to which a given prompt refers before learners participate in additional
activities), and motivation (how much interest and attention learners demon-
strate when dealing with the specific topic to which a given prompt refers)
(Archer & McCarthy, 1988; Dweck, 1986; Givvin, Stipek, Salmon, &
MacGyvers, 2001; Madon et al., 1998; Moje & Wade, 1997; Nolen &
TORFF AND WARBURTON 157

Nichols, 1994; Pintrich & Schunk, 1996; Tollefson, 2000). We nominated
these characteristics not as factors underlying CT use but as indications of
teachers’ judgments of learners as high advantage or low advantage. This
method appears to have been effective, given that factor-analytic and inter-
nal-consistency results presented below strongly supported ability, prior
knowledge, and motivation collectively as indicators of teachers’perception
of learner advantages—but not as independent factors.
For item selection purposes, the three-characteristic design yielded an ini-
tial 120-item pool in which respondents used 6-point Likert-type scales to
rate the effectiveness of each of the 20 prompts for 6 different groups of
learners—high ability, low ability, high prior knowledge, low prior knowl-
edge, high motivation, and low motivation. The use of three advantage char-
acteristics reduces response bias caused by leading questions. Were the scale
to present respondents with a prompt and then ask them to rate its effective-
ness with “high-advantage” or “low-advantage” learners, attention would be
called to the importance of advantage level, and respondents would naturally
begin to ask themselves whether advantage level ought to make a difference.
Instead, the final version of the scale (created through item selection in Study
1 below) follows each prompt with either a high- or low-advantage item for
each characteristic—for example, Prompt 1 is followed by a low-ability item
(but not a high-ability one), a low-prior-knowledge item (but not a high-
prior-knowledge one), and a high-motivation item (but not a low-motivation
one).
Study 1
To select the most effective items for use in subsequent studies, we com-
pleted three procedures. First, in preliminary pilot testing, the criterion of
ambiguity was applied to evaluatethe extent to which the 20 prompts actually
reflect high-CT and low-CT activities. Second, the criterion of irrelevance
was applied to eliminate any item that failed to discriminate between groups
known to differ in beliefs about classroom use of CT activities. Third, the cri-
terion of internal consistency was applied to delete any item that met all other
criteria but had low internal consistency reliability relative to the items with
which it was expected to be associated.
Preliminary testing. In preliminary pilot testing to assess the extent to
which the prompts successfully reflect high-CT and low-CT activities, the
prompts were presented to 20 university professors in the School of Educa-
tion and Allied Human Services at Hofstra University. Participants were
asked to rate each prompt as high CT or low CT. Given the deliberately
polarized nature of the prompts, it is no surprise that 100% of the 400 judg-
ments made by the participants correctly classified the prompts as high CT or
low CT.

Method
Participants in Study 1 were practicing secondary teachers (N = 40) on
Long Island, New York. Participating teachers were nominated by adminis-
trators at 40 randomly selected secondary schools. The administrators were
shown written descriptions of CT-rich and CT-lean lessons and then were
asked to nominate one teacher judged to strongly favor one of the levelsof CT
use. The result was two groups of 20 teachers known by supervisor nomina-
tion to differ in CT use (CT-inclined and CT-averse). Among the CT-inclined
teachers, the 8 males and 12 females had an average age of 39.9 years with
13.1 years of teaching experience ranging from 8 to 29 years. They included
5 teachers of English, 3 of languages other than English, 4 of mathematics, 5
of science,and 3 of socialstudies. Among the CT-averse teachers, the 9 males
and 11 females had an average age of 41.4 years with 12.4 years of teaching
experience ranging from 7 to 30 years. They included 4 teachers of English, 2
in languages other than English, 5 of mathematics, 4 of science, and 5 of
social studies. No administrator or teacher asked to take part declined to do
so. Participants were not compensated for participating. The 120-item pool
was administered to participating teachers at the schools at which they were
employed. They were instructed that the items had no correct answers and
that responses were confidential.
Results and Discussion
Item selection. Selection of prompts and advantage-characteristic items
for use in subsequent studies was made according to the following criteria:
(a) prompts yielding a statistically significant main effect in multivariate
analysis of group membership, (b) items with a strong association to the main
effect (i.e., statistically significant univariate F values), (c) balanced inclu-
sion of prompts (high/low CT) and advantage-characteristic items (high/low
ability, high/low prior knowledge, and high/low motivation), and (d) distri-
bution across the five secondary subjects (English, languages other than
English, mathematics, science, and social studies).
For each of the 20 prompts, a one-way between-subjects multivariate
analysis of variance (MANOVA) was performed on the six dependent vari-
ables (high ability, low ability, high prior knowledge, low prior knowledge,
high motivation, and low motivation). The independent variable was group
membership (CT-inclined or CT-averse). Results of evaluation of assump-
tions of normality of sampling distributions, linearity, and homogeneity of
variance/covariance matrices were satisfactory. There were no outliers at
alpha = .001. Twelve prompts were retained that discriminated between
groups at the conservative alpha level of .0025 (.05/20). With the use of
Wilks’s Lambda, the selected prompts yielded F values (6, 34) ranging from

12.11 to 77.96 (ps < .0025). Univariate analyses were performed as post hoc
procedures to follow up on statistically significant multivariate effects (see
Table 1). The selected prompts contained 36 items that maximally discrimi-
nated between the two groups, with univariate F values (1, 38) ranging from
3.35 to 51.9. Univariate effect sizes (eta-squared statistics) ranged from .11
to .61 with an average of .29.
The resulting 36-item scale is balanced with 6 high-CT prompts and 6
low-CT ones. Each prompt is followed by three items (6-point Likert-type
scales)—one each for ability, prior knowledge, and motivation. The scale is
also balanced for the three advantage characteristics with each one appearing
12 times—6 referring to high-advantage learners and 6 referring to low-
advantage ones.
As expected, analysis of variance (ANOVA) procedures revealed that the
two groups produced divergent scores on the 36-item scale, with CT-inclined
teachers favoring high-CT prompts and CT-averse teachers preferring low-
CT ones. On high-CT prompts for high-advantage learners, the difference
between CT-inclined teachers (M = 5.38, SD = 0.56) and CT-adverse teachers
(M = 4.18, SD = 0.83) was statistically significant, with F(1, 38) = 26.11, p <
.0001 (eta-squared = .43). On high-CT prompts for low-advantage learners, a
statistically significant difference was found between CT-inclined teachers
(M = 3.67, SD = 0.97) and CT-adverse ones (M = 2.47, SD = 0.94), with F(1,
38) = 14.76, p < .0001 (eta-squared = .30). On low-CT prompts for high-
advantage learners, the difference between CT-inclined teachers (M = 3.12,
SD = 1.1) and CT-adverse ones (M = 4.41, SD = 0.83) was statisticallysignifi-
cant, with F(1, 38) = 13.26, p < .001 (eta-squared = .27). Finally, on low-CT
prompts for low-advantage learners, a statistically significant difference was
found between CT-inclined teachers (M = 2.25, SD = 0.90) and CT-adverse
ones (M = 4.36, SD = 0.67), with F(1, 38) = 68.59, p < .0001 (eta-squared =
.65).
Internal consistency. Tests of internal consistency indicated that the 36
selecteditemsexhibited an acceptabledegree of interrelatedness (where such
interrelatedness is expected given the theoretical distinctions drawn between
high versus low CT use and high versus low learner advantages). The overall
alpha level for the scale was .89 based on averages for the items expected to
be associated. Satisfactory levels of internal consistency were obtained
among the items measuring (a) high-CT prompts for high-advantage learners
(alpha = .91), (b) high-CT prompts for low-advantage learners (alpha = .79),
(c) low-CT prompts for high-advantage learners (alpha = .96), and (d) low-
CT prompts for low-advantage learners (alpha = .92).
Internal consistency computations also supported the efficacy of the three
advantage characteristics (ability, prior knowledge, and motivation) as meth-
(text continues on page 164)

161
Table
1
Among
Critical
Thinking
(CT)–Inclined
and
CT-Averse
Teachers
Taking
the
Critical
Thinking
Belief
Appraisal
(CTBA)
in
Study
1
(N
=
40),
Means,
Standard
Deviations,
Univariate
F
Statistics,
Effect
Sizes
(Eta-Squared
Statistics),
and
Reliability
Estimates
(Correlation
Coefficients)
for
Retained
Items
Advantage
CT
Inclined
CT
Averse
Eta-
Item
Prompt
Characteristic
M
(SD)
M
(SD)
F
Value
Squared
Correlation
Q1
(low
CT):
An
English
class
is
studying
the
sonnet,
a
form
of
English
poetry.
The
teacher
explains
its
history
and
structure,
lists
prominent
sonnet
writers,
and
asks
individual
students
to
read
aloud
several
classic
sonnets.
L_ABL
4.50
(1.1)
2.15
(0.9)
50.51***
.52
.63
L_PKN
4.55
(1.2)
2.35
(0.9)
40.42***
.29
.76
H_MTV
3.35
(1.3)
2.00
(1.0)
13.70**
.57
.44
Q2
(low
CT):
A
social
studies
class
is
studying
the
Industrial
Revolution.
The
teacher
provides
students
with
a
list
of
inventions,
explains
the
impact
of
these
inventions
during
this
period,
and
describes
how
they
continue
to
influence
the
modern
world.
L_ABL
4.85
(1.4)
2.65
(1.0)
34.64***
.47
.70
L_MTV
5.20
(1.2)
3.05
(1.3)
30.21***
.44
.71
L_PKN
4.45
(1.5)
2.30
(0.9)
25.40***
.39
.56
Q3
(high
CT):
A
mathematics
class
is
studying
single-variable
algebra.
The
teacher
poses
a
problem
requiring
single-variable
algebra,
asks
students
to
invent
a
way
to
write
down
the
problem
and
then
to
compare
their
notations
to
the
algebraic
ones
writtin
on
the
board.
H_ABL
5.05
(0.9)
3.55
(1.2)
19.48***
.33
.67
L_PKN
3.15
(1.2)
2.00
(0.8)
5.55*
.18
.70
L_MTV
3.55
(1.2)
1.95
(0.9)
13.92***
.29
.80
Q4
(low
CT):
An
Italian
class
is
studying
the
vocabulary
involved
in
ordering
food
in
a
restaurant.
The
teacher
writes
several
new
words
on
the
board,
defines
them,
asks
students
to
repeat
them,
and
provides
a
handout
on
which
students
add
them
to
sample
sentences.
H_ABL
4.20
(1.2)
2.55
(0.9)
19.84***
.34
.75
H_PKN
4.45
(1.3)
2.95
(0.9)
16.47**
.31
.65
L_MTV
4.95
(1.1)
2.50
(1.1)
51.90***
.61
.67
(continued)

162
Q5
(high
CT):
A
science
class
is
studying
the
sun.
The
teacher
asks
students
to
write
down
several
ways
in
which
the
sun
influences
everyday
life
and
then
to
predict
what
would
happen
if
the
sun
stopped
shining.
L_ABL
4.55
(1.5)
3.00
(1.1)
11.56**
.16
.68
H_PKN
4.80
(1.2)
3.40
(1.4)
12.41**
.23
.54
H_MTV
5.00
(1.2)
4.00
(1.3)
5.43**
.26
.48
Q6
(low
CT):
An
English
class
is
studying
For
Whom
the
Bell
Tolls
by
Ernest
Hemingway.
The
teacher
overviews
Hemingway’s
life
and
work,
explains
the
history
and
significance
of
the
novel,
and
describes
Hemingway’s
influence
on
contemporary
authors.
L_ABL
4.80
(1.3)
2.75
(1.2)
27.09***
.42
.65
L_PKN
4.30
(1.3)
2.40
(1.0)
24.07***
.38
.61
L_MTV
4.95
(1.1)
3.65
(1.3)
12.00**
.26
.56
Q7
(high
CT):
A
social
studies
class
is
studying
the
Treaty
of
Versailles
signed
at
the
end
of
World
War
I.
The
teacher
assigns
students
to
write
“letters
from
the
future”
to
President
Wilson
arguing
why
the
United
States
should
or
should
not
support
the
treaty.
H_ABL
5.60
(0.6)
4.45
(1.0)
21.16***
.37
.62
H_PKN
5.55
(0.6)
4.95
(1.0)
5.72*
.14
.57
H_MTV
5.50
(0.7)
4.40
(0.8)
23.22**
.39
.69
Q8
(high
CT):
A
mathematics
class
is
studying
how
to
calculate
the
area
of
a
triangle.
The
teacher
assigns
students
to
evaluate
several
possible
formulas
for
calculating
the
area,
determine
which
formula
is
the
correct
one,
and
explain
why
they
answered
as
they
did.
L_ABL
3.74
(1.6)
2.10
(1.0)
12.47**
.14
.68
L_PKN
3.42
(1.2)
2.15
(1.1)
6.53*
.14
.70
H_MTV
5.52
(0.6)
4.70
(1.4)
5.48**
.23
.59
Table
1
(continued)
Advantage
CT
Inclined
CT
Averse
Eta-
Item
Prompt
Characteristic
M
(SD)
M
(SD)
F
Value
Squared
Correlation

163
Q9
(low
CT):
A
Spanish
class
is
studying
the
conjugation
of
verbs
in
the
preterit,
a
form
of
past
tense.
The
teacher
provides
a
handout
explaining
the
conjugation
rules,
conjugates
several
sample
verbs
on
the
blackboard,
and
then
gives
students
a
handout
to
practice
them.
H_ABL
4.00
(1.5)
2.65
(1.1)
9.29**
.19
.65
H_PKN
4.40
(1.5)
2.85
(1.1)
13.16**
.26
.65
H_MTV
4.00
(1.5)
2.65
(1.1)
9.29**
.19
.62
Q10
(high
CT):
An
English
class
is
studying
Jack
London’s
short
story
To
Build
a
Fire.
The
teacher
asks
students
to
read
all
but
the
last
section
and
then
write
their
own
versions
of
the
final
section.
H_ABL
5.45
(0.6)
4.26
(1.3)
13.86**
.28
.61
H_PKN
5.40
(0.6)
4.05
(1.3)
17.34**
.32
.56
L_MTV
4.40
(1.3)
2.26
(1.2)
11.37**
.24
.83
Q11
(high
CT):
A
French
class
is
studying
adjectives
used
to
describe
clothing.
The
teacher
provides
a
handout
featuring
advertising
photos
with
captions
that
include
the
adjectives,
and
then
gives
a
second
handout
with
intentionally
incorrect
captions,
asking
students
to
make
corrections.
L_ABL
4.05
(1.4)
2.50
(1.4)
12.69**
.29
.69
L_PKN
3.55
(1.4)
2.15
(1.4)
9.86**
.23
.67
L_MTV
3.85
(1.4)
2.25
(1.2)
15.13**
.32
.64
Q12
(low
CT):
A
mathematics
class
is
studying
how
to
convert
fractions
to
decimals.
The
teacher
explains
how
to
make
this
conversion,
completes
sample
problems
using
an
overhead
projector,
and
then
gives
an
in-class
assignment
in
which
students
solve
similar
problems.
H_ABL
3.20
(1.4)
2.30
(1.1)
5.01*
.11
.57
H_PKN
3.75
(1.5)
2.95
(1.3)
3.35*
.08
.55
H_MTV
3.40
(1.4)
3.45
(1.2)
5.38*
.12
.60
Note.
Respondents
were
instructed
to
rate
the
effectiveness
of
each
of
the
scenarios
listed
above
using
a
1
to
6
Likert-type
scale
(highly
effective
to
highly
ineffective).
Advantage
characteris-
tics
are
coded
as
follows:
H_ABL
=
high
ability,
L_ABL
=
“low
ability,”
H_PKN
=
“high
prior
knowledge,”
L_PKN
=
“low
prior
knowledge,”
H_MTV
=
“high
motivation,”
and
L_MTV
=
“low
motivation.”
For
F
value
statistics:
df
=
(1,
38),
*p
<
.05,
**p
<
.001,
***p
<
.0001.
Item
correlation
coefficients
reflect
the
degree
of
association
between
the
target
item
and
the
mean
of
other
items
with
which
it
is
expected
to
be
associated.

odological tools for operationalizing teachers’perception of learners’advan-
tage level. For high-CT prompts, acceptable levels of correlation were
obtained as follows (all correlations in this paragraph, p < .05): between
high-ability and high-prior-knowledge items (.91), between high-ability
and high-motivation items (.90), between high-prior-knowledge and high-
motivation items (.97), between low-ability and low-prior-knowledge items
(.74), between low-ability and low-motivation items (.74), and between low-
prior-knowledge and low-motivation items (.90). Similarly, for low-CT
prompts, satisfactory levels of correlation were obtained among high-ability
and high-prior-knowledge items (.94), high-ability and high-motivation
items (.96), high-prior-knowledge and high-motivation items (.86), low-
ability and low-prior-knowledge items (.96), low-ability and low-motivation
items (.91), and low-prior-knowledge and low-motivation items (.90).
Study 2
In Study 2, exploratory factor analysis was employed to identify factors
underlying teachers’ CT-use beliefs. With the assessment of a larger and
more homogeneous population of practicing secondary teachers, it was
expected that the salient pattern and structure coefficients of the items would
represent a tendency among teachers to support CT-rich and CT-lean activi-
ties according to learners’ perceived advantages.
Method
Practicing secondary teachers (N = 381) in New York, Connecticut, and
Massachusetts participated in Study 2. They were selected at random from
faculty at 39 randomly selected secondary schools. Among the participating
teachers, 199 were female with a mean age of 37.7 years, and 182 were male
with a mean age of 38.6 years. In keeping with teacher-expertise benchmarks
set out by Berliner (1992), participants had a minimum of 5 years of teaching
experience, which ranged from 7 to 35 years with an average of 13.7 years.
Participants included 23 prospective teachers of business, 49 of English, 25
of fine arts, 27 of health, 42 of languages other than English, 55 of mathemat-
ics, 48 of music, 47 of science, and 65 of social studies. They were not com-
pensated for participating, and no teachers asked to participate declined to do
so. All participants completed the 36-item CTBA at the schools at which they
were employed. Verbal instructions emphasized that there were no correct
answers and that responses were confidential.

Principal axis factoring was used to evaluate the number of factors, pres-
ence of outliers, absence of multicollinearity, and factorability of the correla-
tion matrices. (Use of a principal components method yielded highly similar
results.) The Kaiser-Meyer-Okin measure of sampling adequacy was .73.
There were no outliers at alpha = .001. When oblique factor rotation was
attempted, the highest correlation obtained (between factors interpreted as
low CT/high advantage and low CT/low advantage) was .25. Because this
correlation fell below the benchmark of .32 for inclusion in nonorthogonal
factor rotation (Tabachnick & Fidell, 2001), varimax rotation was chosen.
The number of candidate factors was determined by eigenvalues greater
than one, examination of the scree plot, and a parallel analysis. Ten factors
yielded eigenvalues greater than one, and examination of the scree plot sug-
gested a possible range of 4 to 6 factors. Because the eigenvalue-greater-
than-one rule tends to overestimate the number of factors, and the scree plot
entails some inherent subjectivity, the parallel analysis was employed as a
generally more accurate assessment of the number of factors (Henson,
Capraro, & Capraro, 2001; Henson & Roberts, 2001). The parallel analysis
was employed using the syntax for SPSS provided by Thompson and Daniel
(1996). This analysis produced a set of 6 factors—that is, there were 6 factors
for which the eigenvalue in the actual data exceeded the associated
eigenvalue in the random data generated for parallel analysis. These 6 factors
accounted for 70% of the variance. However, only the first 4 factors provided
theoretically relevant and interpretable information about teachers’ CT-
related beliefs. These factors accounted for a high percentage of the variance
(62%) and could be readily interpreted in accordance with the theoretical
aims of the instrument—that is, to assess teachers’beliefs about high-CT and
low-CT activities depending upon learners’ advantage level (high versus
low). In contrast, the 5th and 6th factors explained only a small portion of
additional variance (8%) and were not readily interpretable given the CTBA’s
theoretical design. Hence, the 5th and 6th factors were excluded from further
analyses in Study 2.
Table 2 presents pattern/structure coefficients, communalities, and per-
centages of variance and covariance, with interpretative labels for each of the
four remaining factors suggested in bold type. As indicated by squared mean
correlations, all four factors were internally consistent and well defined by
the items; the lowest of the squared mean correlations for factors from items
was .95. The reverse was also true: The items were well defined by this factor
solution. Communality values were moderate to high. With a cutoff of .40 for
inclusion of an item in interpretation of a factor (Tabachnick & Fidell, 2001),
all 36 items loaded on one—and only one—of the four factors.
As noted, the pattern/structure coefficients and the distribution of items
suggest that the items represented teachers’ reported tendency to support

166
Table
2
Among
In-Service
Teachers
Taking
the
Critical
Thinking
Belief
Appraisal
(CTBA)
in
Study
2
(N
=
381),
Pattern/Structure
Coefficients
(Loadings),
Communalities,
and
Percentages
of
Variance
and
Covariance
for
Principal
Axis
Factoring
and
Varimax
Rotation
Pattern/Structure
Coefficients
Prompt
Advantage
Characteristic
Factor
1
Factor
2
Factor
3
Factor
4
Communalities
Low
CT
×
High
Advantage
Q1:
An
English
class
H_MTV
.52
–.20
.22
–.21
.41
Q4:
An
Italian
class
H_ABL
.79
.17
.03
–.01
.66
H_PKN
.82
–.02
.15
–.12
.71
Q9:
A
Spanish
class
H_ABL
.86
–.14
–.10
–.01
.77
H_PKN
.85
.00
.01
–.02
.72
H_MTV
.74
.15
.07
–.13
.60
Q12:
A
mathematics
class
H_ABL
.80
–.04
–.04
–.14
.66
H_PKN
.80
–.10
–.11
–.03
.66
H_MTV
.77
–.01
–.04
.00
.60
Low
CT
×
Low
Advantage
Q1:
An
English
class
L_ABK
–.12
.63
–.18
–.08
.41
L_PKN
–.05
.69
–.11
.15
.66
Q2:
A
social
studies
class
L_ABL
–.05
.74
–.29
–.09
.71
L_PKN
–.09
.73
.14
–.16
.77
L_MTV
–.01
.61
.24
.13
.72
Q4:
An
Italian
class
L_MTV
.24
.50
.02
–.02
.60
Q6:
An
English
class
L_ABL
.28
.62
.02
.07
.66
L_PKN
.18
.55
–.16
.09
.66
L_MTV
.12
.55
–.03
.13
.60

167
High
CT
×
Low
Advantage
Q3:
A
mathematics
class
L_PKN
.00
.07
.68
–.18
.45
L_MTV
–.10
.09
.60
.16
.52
Q5:
A
science
class
L_ABL
–.21
–.11
.40
.10
.64
Q8:
A
mathematics
class
L_ABL
–.08
.01
.70
–.04
.59
L_PKN
–.08
.04
.69
–.02
.45
Q4:
An
English
class
L_MTV
–.12
.08
.40
.21
.35
Q11:
A
French
class
L_ABL
.07
–.21
.57
.18
.47
L_PKN
.14
–.14
.61
–.20
.37
L_MTV
.15
–.08
.63
.16
.34
High
CT
×
High
Advantage
Q3:
A
mathematics
class
H_ABL
–.21
–.12
.20
.40
.30
Q5:
A
science
class
H_PKN
–.25
–.14
.06
.49
.39
H_MTV
–.13
–.17
.21
.55
.41
Q7:
A
social
studies
class
H_ABL
–.07
.08
–.16
.78
.66
H_PKN
.00
–.19
.04
.76
.62
H_MTV
.00
–.20
.11
.65
.48
Q8:
A
mathematics
class
H_MTV
–.21
.11
–.18
.40
.25
Q10:
A
French
class
H_ABL
–.04
–.13
–.21
.62
.49
H_PKN
–.11
–.18
–.07
.56
.40
Percentage
of
variance
17.22
11.22
10.69
10.50
Percentage
of
covariance
34.70
22.61
21.54
21.15
Eigenvalues
6.56
5.36
3.73
2.23
Note.
Interpretative
labels
suggested
for
each
of
the
four
factors
are
in
bold
type.
CT
=
critical
thinking;
H_ABL
=
high
ability;
L_ABL
=
low
ability;
H_PKN
=
high
prior
knowledge;
L_PKN
=
low
prior
knowledge;
H_MTV
=
high
motivation;
L_MTV
=
low
motivation.
Percentages
of
variance,
percentages
of
covariance,
and
eigenvalues
are
postrotation.

high-CT and low-CT activities depending upon learners’ advantage level
(high versus low). The items were equally distributed across the four factors
(nine items each), and all of the items on the four factors were positively
weighted. The CTBA yielded four scale scores with satisfactory reliability:
(a) high-CT activities for high-advantage learners (M = 4.75, SD = .88,
alpha = .88), (b) high-CT activities for low-advantage learners (M = 3.19,
SD = .76, alpha = .78), (c) low-CT activities for high-advantage learners (M =
4.14, SD = .90, alpha = .88), and (d) low-CT activities for low-advantage
learners (M = 2.91, SD = .79, alpha = .83).
Study 3
To replicate the factor structure obtained in Study 2, a third study was con-
ducted in which the CTBA was administered to a group of preservice second-
ary teachers. As a group with negligible experience in teaching, preservice
teachers’CT-use beliefs may differ from those of seasoned in-service teach-
ers. Moreover, preservice teachers comprise a self-selected population likely
to be targeted in future CTBA research.
Method
Participants in Study 3 included randomly selected undergraduate-level
preservice teachers (N = 308) at three postsecondary institutions on Long
Island, New York (Hofstra University, Adelphi University, and Dowling Col-
lege). Among the participants, 161 were female and 147 were male, with a
mean age of 21.2 years. They included 1 preservice teacher of business, 56 of
English, 25 of fine arts, 27 of health, 38 of languages other than English, 46 of
mathematics, 30 of music, 31 of science, and 54 of social studies. No partici-
pants were compensated, and none declined when asked to take part. All par-
ticipantscompleted the 36-item CTBA, with verbal instructions emphasizing
that there were no correct answers and that responses were confidential. In
Study 3, a factor analysis was conducted in the same manner as in Study 2
because the two studies examined populations that may plausibly be expected
to differ (in-service and preservice teachers), raising the need to employ a
consistent set of data-analytic procedures.
Factor-analytic results obtained in Study 3 were similar to those of Study
2. In Study 3, principal axis factoring and principal components analysis
again yielded similar results. The principal axis factoring produced a Kaiser-
Meyer-Okin measure of sampling adequacy of .72 and no outliers at alpha =
.001. Oblique rotation yielded low correlations (the highest of which was

.19), so varimax rotation was employed. In Study 3, 10 factors had eigen-
values greater than one, and examination of the scree plot suggested a possi-
ble range of 4 to 6 factors. Parallel analysis produced 6 factors that accounted
for 72% of the variance. However, as in Study 2, only 4 factors provided use-
ful measures of teachers’CT-related beliefs. The first 4 factors accounted for
63% of the variance and could be readily interpreted in accordance with the
theoretical design of the CTBA, whereas the 5th and 6th factors explained
only a small additional portion of the variance (9%) and provided little theo-
retically relevant or interpretable information about teachers’ CT-related
beliefs. Hence, only the first 4 factors were included in further analyses in
Study 3.
Pattern/structure coefficients, communalities, and percentages of vari-
ance and covariance are presented in Table 3 with interpretative labels sug-
gested for each of the four remaining factors in bold type. Analysis of the
squared mean correlations indicated that all four factors had satisfactory
internal consistency and were well defined by the items (.93 to .98); con-
versely, the items were well defined by this factor solution. Moderate to high
communality values were obtained. All 36 items loaded on one of the four
factors (with a cutoff of .40 for inclusion of an item in interpretation of a
factor).
The pattern/structure coefficients and the distribution of items indicated
that the four-factor model represented teachers’tendency to support high-CT
and low-CT activities according to learners’ advantage level (high versus
low), as in Study 2. The 36 items were equally distributed across the four fac-
tors (9 items each), and all of the items on the four factors were positively
weighted. The resulting four scale scores had satisfactory reliabilities: (a)
high-CT activities for high-advantage learners (M = 4.94, SD = .68, alpha =
.84), (b) high-CT activities for low-advantage learners (M = 3.79, SD = .91,
alpha = .82), (c) low-CT activities for high-advantage learners (M = 3.55,
SD = .99, alpha = .92), and (d) low-CT activities for low-advantage learners
(M = 2.78, SD = .83, alpha = .84).
Study 4
To investigatethe discriminant validityof scores yielded by the CTBA, we
conducted a fourth study to determine the extent to which the scale tapped
constructs that were distinguishable from three constructs hypothesized to be
associated with CT-use beliefs. The first construct was CT ability—an indi-
vidual’s capacity to engage successfully in CT-rich tasks (Ennis, 1987;
Facione, Facione, & Giancarlo, 2000; Kuhn, 1999). To explore the possibil-
ity that individuals with a high level of CT ability favor the use of such skills
in the classroom, we administered a test of CT ability, the California Critical
Thinking Skills Test Form 2000 (CCTST) (Facione et al., 2000), along with
the CTBA. The CCTST includes 34 multiple-choice items with four to six

170
Table
3
Among
Preservice
Teachers
Taking
the
Critical
Thinking
Belief
Appraisal
(CTBA)
in
Study
3
(N
=
308),
Pattern/Structure
Coefficients
(Loadings),
Communalities,
and
Percentages
of
Variance
and
Covariance
for
Principal
Axis
Factoring
and
Varimax
Rotation
Pattern/Structure
Coefficients
Prompt
Advantage
Characteristic
Factor
1
Factor
2
Factor
3
Factor
4
Communalities
Low
CT
×
High
Advantage
Q1:
An
English
class
H_MTV
.55
.07
.08
–.09
.32
Q4:
An
Italian
class
H_ABL
.73
.11
.16
–.12
.59
H_PKN
.79
–.01
.17
–.13
.67
Q9:
A
Spanish
class
H_ABL
.86
.05
–.02
–.06
.75
H_PKN
.86
–.03
.01
–.06
.75
H_MTV
.79
.04
.05
–.03
.63
Q12:
A
mathematics
class
H_ABL
.80
–.04
–.03
–.16
.67
H_PKN
.82
–.10
–.05
–.13
.72
H_MTV
.81
–.07
–.06
–.02
.67
Low
CT
×
Low
Advantage
Q1:
An
English
class
L_ABK
–.07
.59
–.06
–.17
.38
L_PKN
.05
.58
–.07
.05
.35
Q2:
A
social
studies
class
L_ABL
–.10
.79
–.17
–.13
.67
L_PKN
–.09
.75
–.05
.13
.59
L_MTV
–.04
.67
.12
–.26
.57
Q4:
An
Italian
class
L_MTV
.26
.57
–.18
.19
.48
Q6:
An
English
class
L_ABL
.16
.69
.26
–22
.62
L_PKN
.09
.60
–.16
–.19
.40
L_MTV
–.02
.61
.25
–.06
.45

171
High
CT
×
Low
Advantage
Q3:
A
mathematics
class
L_PKN
.02
–.02
.61
.05
.40
L_MTV
.00
–.07
.58
.08
.35
Q5:
A
science
class
L_ABL
.26
.12
.40
.05
.35
Q8:
A
mathematics
class
L_ABL
–.19
.18
.45
.10
.39
L_PKN
.04
.13
.51
.07
.35
Q4:
An
English
class
L_MTV
.23
.09
.40
.05
.35
Q11:
A
French
class
L_ABL
.00
.01
.71
.08
.52
L_PKN
.14
–.02
.67
.10
.47
L_MTV
.09
.03
.78
.00
.62
High
CT
×
High
Advantage
Q3:
A
mathematics
class
H_ABL
–.22
.04
.04
.55
.39
Q5:
A
science
class
H_PKN
–.26
.05
.23
.40
.38
H_MTV
–.19
–.16
.24
.40
.32
Q7:
A
social-studies
class
H_ABL
.00
.07
.07
.85
.73
H_PKN
–.04
–.13
.14
.70
.53
H_MTV
–.01
.14
.03
.79
.66
Q8:
A
mathematics
class
H_MTV
–.23
.01
.14
.40
.27
Q10:
A
French
class
H_ABL
.00
–.02
.26
.52
.39
H_PKN
–.10
–.20
.07
.40
.27
Percentage
of
variance
16.72
11.22
10.44
9.69
Percentage
of
covariance
34.78
23.34
21.92
20.16
Eigenvalues
6.45
5.02
3.48
2.36
Note.
Interpretative
labels
suggested
for
each
of
the
four
factors
are
in
bold
type.
CT
=
critical
thinking;
H_ABL
=
high
ability;
L_ABL
=
low
ability;
H_PKN
=
high
prior
knowledge;
L_PKN
=
low
prior
knowledge;
H_MTV
=
high
motivation;
L_MTV
=
low
motivation.
Percentages
of
variance,
percentages
of
covariance,
and
eigenvalues
are
postrotation.

response options. As an ability measure, the CCTST has correct and incor-
rect answers—unlike the other assessment instruments employed in this
study (including the CTBA), which are opinion measures with no correct
answers.
The second construct considered for the purposes of assessing the
discriminant validity of the CTBA was CT disposition—an individual’s pro-
pensity to engage in CT in everyday situations and professional contexts.
Individuals who are inclined to think critically may seek situations that
require it (Perkins, Jay, & Tishman, 1993). To investigate the possibility that
teachers with high CT disposition favor CT activities in the classroom, we
administered the Need for Cognition Scale (NCS) (Cacioppo & Petty, 1982;
Cacioppo, Petty, Feinstein, & Harvis, 1996). The NCS has 18 itemsscored on
4-point scales, with 9 items worked for reverse scoring.
The third construct was need for social approval—an individual’s inclina-
tion to behave in ways that he or she perceives to be agreeable to others.
Schooling that is rich in CT may be viewed by members of our society as
preferable to forms of direct instruction, which are frequently regarded as
tedious and ineffective (Blumenfeld, Hicks, & Krajcik, 1996; Kagan &
Tippins, 1991; Putnam & Borko, 1997; Woolfolk Hoy & Murphy, 2001). To
explore the possibility that the CTBA operates as a proxy for need for social
approval, we administered the Marlowe-Crowne Social Desirability Scale
(MCSDS) (Crowne & Marlowe, 1964). The MCSDS includes 33 true-false
items, with 14 items worked for reverse scoring.
Method
Participants were drawn randomly from preservice secondary teachers (N =
100) in the School of Education and Allied Human Services at Hofstra Uni-
versity on Long Island, New York. The 59 females and 41 males had a mean
age of 20.8 years and included 1 prospective teacher of business, 21 of Eng-
lish, 10 of health, 15 of languages other than English, 17 of mathematics, 13
of science, and 23 of social studies. Participants were not compensated, and
none declined when asked to take part. All participants completed the CTBA,
CCTST, NCS, and MCSDS. Verbal instructions indicated that (a) there were
no correct answers for CTBA, NCS, or MCSDS; (b) there were correct
answersontheCCTST,and(c)responsesonallinstrumentswereconfidential.
High alpha coefficients provided evidence for the reliabilities of the
CCTST (.82), NCS (.90), and MCSDS (.94) with this group of participants.
Table 4 presents correlations between these measures and the four sets of
scores produced by the CTBA (employing true factor scores, not unit

weighted scores based on salient items). As expected, near zero correlations
(at the .05 level) were found between the MCSDS and the four CTBA score
sets, indicating that the CTBA tapped a construct distinguishable from need
for social approval. Similarly, correlations were very small between the NCS
and all four CTBA score sets, demonstrating that the CT-use construct was
distinct from participants’ CT disposition.
Small or near zero correlations were found between the CCTST and two
score sets of the CTBA, low-CT prompts for high-advantage learners and
low-CT prompts for low-advantage learners. Slightly larger correlations
were found between the CCTST and the remaining two CTBA score sets:
high-CT prompts for high-advantage learners (r = .28, p < .05) and high-CT
prompts for low-advantage learners (r = .31, p < .05). Neither of these corre-
lation coefficients reached the .32 level, which was used to judge a meaning-
ful contribution to the variance (Tabachnick & Fidell, 2001). However, the
obtained correlations indicate that participants’CT ability was slightly asso-
ciated (9.7% of the variance) with their beliefs about the effectiveness of
high-CT prompts for both high-advantage and low-advantage learners.
These results suggest that the CTBA tapped a construct that was, perhaps,
related to but distinguishable from CT ability.
Study 5
A fifth study was conducted to investigate the predictive validity of scores
produced by the CTBA. At issue is the strength of association between
CTBA results and teachers’ observed classroom practice.
Method
Participating teachers (N = 72) were randomly selected from faculty ros-
ters at 35 schools that were randomly selected from a list of all secondary
Table 4
Correlation Coefficients for Critical Thinking Belief Appraisal (CTBA), Marlowe-Crowne
Social Desirability Scale, Need for Cognition Scale, and the California Critical Thinking
Skills Test (CCTST) in Study 4 (N = 100)
CTBA Score Marlowe-Crowne Need for Cognition CCTST
HICT × HIADV .04 .12 .29*
HICT × LOADV .07 .02 .31*
LOCT × HIADV .02 .10 .06
LOCT × LOADV .05 .03 .18
Note. HICT = high critical thinking; HIADV = high advantage; LOADV = low advantage; LOCT= low critical
thinking.
*p < .05; otherwise p > .10.

schools on Long Island, New York. The 38 women and 34 men included 16
teachers of English, 10 of languages other than English, 15 of mathematics,
17 of science, and 14 of social studies. All had 5 or more years of teaching
experience (Berliner, 1992). Participants’ ages ranged from 27 to 56 years
with a mean of 37.7. Teaching experience ranged from 5 to 33 years with an
average of 10.6.
A three-part data collection strategy was used. First, observers visited the
classrooms of participating secondary teachers and rated their use of CT
activities (“observed CT use”). Second, we asked the participating teachers
to identify the observed classesas low or high with respect to each of the three
advantage characteristics (ability, prior knowledge, and motivation). Third,
we asked teachers to complete the CTBA. The scale’s predictive validity was
then evaluated by calculating the correlation between observed CT use and
the classroom-matched items on the CTBA (i.e., the items that correspond to
the configuration of advantage characteristics that teachers identified as
describing the observed class).
Teachers’ observed CT use was assessed by two raters using a procedure
developed in prior research (Torff, 2003). Raters were enrolled in a graduate-
level program in secondary education and had earned highest grades in a CT-
in-education course. They received additional instruction in measurement of
classroom CT use (i.e., how to identify high-CT and low-CT activities) but
had no specific knowledge of the research design or hypothesis.
To tune the rating process and evaluate interrater reliability prior to data
collection, raters met for 2 hours twice weekly for 4 weeks (a total of eight
meetings). Initially they reviewed lessons on videotape and discussed with
the experimenter how to rate teachers’ use of CT. Then, to test the level of
interrater reliability, raters scored a second set of videotapes separately with-
out discussion. Raters produced suitable levels of interrater reliability after
three iterations of the training process (88% agreement). In data collection
for Study 5, interrater reliability of 85% was sufficient to allow further
analysis of the data.
When scheduling classroom observations, we asked participating teach-
ers to host the raters in periods featuring teacher-led activities and not a spe-
cial event (e.g., a guest presentation) or a lesson in which the teacher’s role
was minimized (e.g., an examination). The two raters visited classrooms
together but made separate assessments without access to each other’s rat-
ings. During each instructional period (40 to 45 minutes in length), raters
made assessments of CT use once per minute using a 5-point Likert-type
scale (5 = a great deal, 4 = a lot, 3 = some, 2 = a little, 1 = not much—or a rat-
ing of “no teaching” had instruction not been attempted in the previous min-
ute). Ratings were entered on specially prepared score sheets as summaries
of the previous minute of classroom activity. Ratings were made simulta-
neously with the use of a clock visible to both raters.

As examples of the scoring procedure, consider three instances of class-
room instruction in social studies classes. In one instance, a teacher described
the events of the Vietnam War. With learners simply watching and listening,
the raters agreed that CT use was very low (1). In a second instance, the
teacher asked learners to participate in a debate about whether the United
States should have refused the sign a treaty banning land mines. Because
learners were charged to reason and argue as political scientists do, raters
agreed that CT use was very high (rated a 5). In a third instance, classroom
activity was temporarily delayed when the teacher reviewed medical docu-
ments provided by a student; in this case, raters concurred that “no teaching”
was appropriate. As measures of teachers’classroom behavior, rating proce-
dures as such are far from ideal (Medley & Coker, 1987; Wilkerson, Manatt,
Rogers, & Maughm, 2000). However, measurement of teachers’use of CTon
a minute-by-minute basis provided ongoing assessment that was sensitive to
changes in classroom activities (Fischer & Bidell, 1998; Granott & Parziale,
2002).
Following the classroom observations, participating teachers were asked
to rate the observed class as high or low in each of the three advantage charac-
teristics. Teachers were not asked to complete the CTBA until 4 weeks later
to reduce response bias based on their recall of the activities employed during
the observed class and the advantage-characteristic identification they pro-
duced following the class.
The 72 teachers were sorted into six groups according to teachers’identi-
fication of the observed classroom as high or low in specific advantage char-
acteristics (for example, high ability, high prior knowledge, and low motiva-
tion). Teachers’ average scores on the classroom-matched items on the
CTBA were then compared to the observed CT-use ratings.
Overall, a strong degree of association (r = .72) was found between
observed CT use and the classroom-matched items. High correlations were
found between observed CT use and classroom-matched CTBA scores
among teachers who identified learners as follows: (a) high ability, high prior
knowledge, and low motivation (n = 12, r = .79), (b) high ability, high prior
knowledge, and high motivation (n = 20, r = .68), (c) low ability, low prior
knowledge, and low motivation (n = 16, r = .70), and (d) high ability, low
prior knowledge, and high motivation (n = 15, r = .71). Despite the small
sample size in two of the six groups, the correlations between observed CT
use and classroom-matched CTBA scores in all groups (ranging from r = .64
to r = .80) suggest that the CTBA produced scores with satisfactory predictive
validity.

General Discussion
Scale Construction and Reliability
The CTBA was developed in Study 1, in which a pool of items with strong
face validity for measuring beliefs about classroom CT use was generated
and revised to meet the criteria of ambiguity, irrelevance, and internal consis-
tency. Study 2 was conducted to explore the factor structure of scores on the
36 selected items, with results supporting a four-factor model (high-CT
activities for high-advantage learners, high-CT activities for low-advantage
learners, low-CT activities for high-advantage learners, and low-CT activi-
ties for low-advantage learners). This factor structure was replicated in Study
3. Strong dominance of the four-factor set, stable pattern/structure coeffi-
cients, and high internal consistency reliabilities indicated that the shared
variation of the items reliably assessed a common set of factors. Moreover,
this result was unlikely to be an artifact of response biases, because instruc-
tions and item wording were designed to minimize acquiescence and self-
presentation, and correlations between CT-use scores and social desirability
were weak.
Validity
In the series of studies reported in this article, the CTBA produced scores
with favorable construct, content, discriminant, and predictive validity. The
empirical method of deriving the scale used in Study 1 enhances the confi-
dence that can be placed in the construct and content validity of obtained
scores. In Study 4, the scale produced scores with acceptable discriminant
validity. Study 5 provided evidence for the predictive validity of the scores
produced by the scale. Taken together, the results of the five studies support
the theoretical utility of the CTBA for assessing teachers’ CT-use beliefs.
Practical Utility
The CTBA has practical utility as a research tool. Research on CT-use
beliefs using interview protocols (e.g., Zohar et al., 2001) or questionnaires
in which respondents self-report their classroom practices (e.g., Raudenbush
et al., 1993) employ methodologies effective only with practicing teachers.
The CTBA seemingly can be used with preservice populations, allowing
researchers to investigate the origin and development of CT-use beliefs.
Issues that remain unexplored include (a) the extent to which prospective
teachers hold similar beliefs relative to individuals who do not become teach-
ers; (b) the extent to which CT-use beliefs change during preservice training;
(c) the extent to which CT-use beliefs change as teachers gain classroom

experience, in-service training, and teaching expertise; and (d) what kinds of
preservice and in-service interventions are maximally effective in inducing
favorable teacher change. Finally, future research should examine the stabil-
ity of the obtained factor structure in other samples (perhaps of varying
diversity) using confirmatory factor analytic methods.
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