Factors affecting teacher preactive content decision making
by Sharon Strobel Patton
A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Education
Montana State University
© Copyright by Sharon Strobel Patton (1989)
Abstract:
The problem of this study was to determine which factors were most important in influencing teacher
preactive content decisions. The influencing factors used in this study were District Policy, , Teacher
Belief, Student Achievement, Professional Opinion, and Community Pressure.
The study was conducted during the 1987-88 school year. The population consisted of middle school
classroom teachers in the State of Montana.
To collect data, a simulation instrument was utilized. The instrument consisted of a series of fifty
simulations each of which represented a possible context in which a preactive content decision might
be made. The information used to make each preactive content decision in each simulation was a
numerical rating given to each of the five influencing factors. The statistical method used to analyze the
data was Judgment Analysis (JAN) which yielded policy groupings of participants and standard beta
weights for each of the five influencing factors for each participant. Participants were also divided into
demographic categories of size of district, years of experience, years of education, and subject area
taught on the basis of a short demographic survey.
The JAN analysis indicated that there were three policy groupings of participants. These three policy
groupings showed up in every demographic category. Policy group one used a multi-factor approach.
In other words, participants in Policy 1 based their content change decisions on the influencing factors
of Student Achievement, Teacher Belief, and District Policy. Policy group two used a single-factor
approach. In other words, they based their decisions on Student Achievement. Policy group three used
a dual-factor approach basing their decisions on Student Achievement and Teacher Belief. The most
important factor in this study was Student Achievement followed by Teacher Belief and District Policy.
Professional Opinion and Community Pressure were not important influencing factors. FACTORS AFFECTING TEACHER PREACTIVE
CONTENT DECISION MAKING
by
Sharon Strobel Patton
A thesis submitted in partial fulfillment
of the requirements for the degree
of
Doctor of Education
/
MONTANA STATE UNIVERSITY
Bozeman, Montana
September 1989
ii
APPROVAL
of a thesis submitted by
Sharon Strobe I Patton
This thesis has been read by each member of the thesis
committee and has been found to be satisfactory regarding
content, English usage, format, citations, bibliographic
style, and consistency, and is ready for submission to the
College of Graduate Studies.
Date
Chairperson, Graduate Committee
Approved for the Major Department
Date
H e a d , Major Department
Approved for the College of Graduate Studies
Date
iii
STATEMENT OF PERMISSION TO USE
In presenting this thesis in partial fulfillment of the
requirements
University,
for
a
doctoral
degree
at
Montana
State
I agree that the Library shall make it available
to borrowers under rules of the Library.
I further agree that
copying
only
of
this
thesis
is
allowable
for
scholarly
purposes, consistent with fair u s e , as prescribed in the U .S .
Copyright Law.
of this thesis
Requests for extensive copying or reproduction
should be referred to University Microfilms
International, 300 North Zeeb Road, Ann Arbor, Michigan 48106,
to whom I have granted "the exclusive right to reproduce and
distribute copies of the dissertation
in and from microfilm
and the right to reproduce and distribute by abstract in any
format."
Signature
Date
y & S'
iv
ACKNOWLEDGEMENTS I express gratitude to my children, Jerome and Jesse, for
their patience with M o m ’s "project" and for their expressions
of love.
I wish to thank my parents for their support despite
their skepticism.
A very special
thanks goes to my David;
without his encouragement and support I would have never begun
or completed this particular journey.
my committee
Ardys
Clarke
chairman,
and
Dr.
Dr.
Gratitude is also due
Donald Robson;
Douglas
my
Herbster; and
readers,
my
Dr.
committee
members, Dr. Duane Melling, Dr. Robert Thibeault, and Dr. Jack
Olson.
Finally,
Harvey,
and
assistance.
Irma
I would
Tiffany
like
for
to
thank Dan
their
Chandler,
priceless,
Meg
technical
TABLE OF CONTENTS
Page
APPROVAL ........................ . . _____ ____ ..... ... . . .
STATEMENT OF PERMISSION TO USE ..... .
Tii
ACKNOWLEDGEMENTS ,___ _____ ______________....... . . . ... .
iv
LIST OF TABLES ........... . ....... . ..... ......___ _ ...
•.vii
A B S T R A C T ...... .................. .
...
Tx
CHAPTER:
1.
I
Problem Statement ....................
Contribution to Educational Literature
General Questions .......... .
... ......
General Procedure ..... .
...... ...........
.
Limitations and Delimitations ; . .... . ... ... . . .
Definitions ....... ................... . ... ...
Tl
11
16
17
REVIEW OF RELATED LITERATURE .....
.
* VD
2.
INTRODUCTION ...... . ..... .... . . ... . . . . ... . . . .;. .
18
• -r-:,
■■
Introduction ............
......... . . . ......
Teacher T h i n k i n g .... .
Teacher Decision M a k i n g .... . ..........
Teacher Preactive Decision Making. . ..... ......
Teacher Preactive, Content Decision Making .. .
3.
PROCEDURES ........
.....
18
19
21
. 24
28
34
Introduction .................
34
Population Description and Sampling
Procedure ........................... .......
34
Influencing Factors ...........
.
35
Method of Analysis . ................................. 35
Method of Collecting Data .....
.
39
Method of Organizing Data ....... . ..d. . . . . . . .
41
Research Questions ....................
42
Analysis of Data . . . . . . .......... .
... . . * .;.
42
TABLE OF CONTENTS— Continued
Page
4.
ANALYSIS OF DATA .............
Introduction ........... . . .................. .
Populations and Samples ...................
Research Questions ......................... . .
Research Question One ....................
Research Question Two ....................
Research Question Three ......
5.
CONCLUSIONS ....................................
43
43
43
45
45
49
51
69
Introduction ..................
Conclusions ..............
Recommendations for Action ...................
Recommendations forFurther Action ............
69
69
85
88
REFERENCES CITED .......................... ............
94
APPENDICES .............................................
102
Appendix A— JAN Tables .........
Appendix B— Letters .................................
Appendix C— Simulative Instrument ..................
103
113
121
vii
LIST OF TABLES
.
Table
Page
1.
A Sample Simulation .............
15
2.
Influencing Factors ........ .............. ...
39
3.
IntercorreIations of theFactors ...........
40
4.
Means and Standard Deviations of
Simulation Factor ............ . ;.... .
5.
Sample Simulation ............. .
6.
Stages for Judgment Analysis Procedure
. 7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
.
40
41
.....
46
Rankings of Influencing Factors Chosen
as Most Important by Policy ......
Policies Grouped According to Size of
School District ..... .
50
..
52
Percentage of Participants by Policy
and District Size ..........................
53
Policies Grouped According to Years
of Experience .............
56
Percentage of. Participants by Policy
and Years of Experience ..................
57
Policies Grouped According.to Level of
Education ........... . . ....................
60
Percentage of Participants by Policy and .
Years of E d u c a t i o n ..... ........ ...... . ..
61
Policies According to Subject Area
Taught ............ ..................... . . .
64
Percentage of Participants by Policy
and Subject Taught .......... .
65
Profile Ratings and the Mean and Standard
Deviation of Each Rater ............. .
104
viii
LIST OF TABLES— Continued
Table
,
Page.
17.
Correlations Between the Profile Ratings
and the Change Factors for Participating
....
Teachers ..................... .
107
Stages of the JAN Analysis Procedure ...... ;
HO
18.
ix
ABSTRACT
The problem of this study was to determine which factors
were most important in influencing teacher preactive content
decisions.
The influencing factors used in this study were
District
Policy,
Teacher
Belief,
Student
Achievement,
Professional Opinion, and Community Pressure.
The study was conducted during the 1987-88 school y e a r .
The population consisted of middle school classroom teachers
in the State of Montana.
To collect data, a simulation instrument was utilized.
The instrument consisted of a series of fifty simulations each
of which represented a possible context in which a preactive
content decision might be made. The information used to make
each preactive content decision in each simulation was a
numerical rating given to each of the five influencing
factors. The statistical method used to analyze the data was
Judgment Analysis (JAN) which yielded policy groupings of
participants and standard beta weights for each of the five
influencing factors for each participant.
Participants were
also divided into demographic categories of size of district,
years of experience, years of education, and subject area
taught on the basis of a short demographic survey.
The JAN analysis indicated that there were three policy
groupings of participants.
These three policy groupings
showed up in every demographic category.
Policy group one
used a multi-factor approach.
In other words, participants
in Policy I based their content change decisions on the
influencing factors of Student Achievement, Teacher Belief,
and District Policy.
Policy group two used a single-factor
approach.
In other words, they based their decisions on
Student Achievement.
Policy group three used a dual-factor
approach basing their decisions on Student Achievement and
Teacher Belief.
The most important factor in this study was
Student Achievement followed by Teacher Belief and District
Policy. Professional Opinion and Community Pressure were not
important influencing factors.
I
CHAPTER I
INTRODUCTION
Since
the
early
1900s,
the
problem
of
identifying
effective teachers has puzzled educational researchers.
their
search
various
for
an
answer, researchers
teacher variables.
have
In
investigated
They have also employed various
measures of teacher effectiveness.
Their quest has led them
from early investigations of teacher traits as they relate to
teacher effectiveness ratings to present-day investigations
of
teacher
decision
making
as
it
relates
to
student
achievement (Cruickshank,' 1985).
Initially, from the early 1900s to the 1950s, educational
researchers
traits.
Base
friendliness,
rating forms
investigated
teacher
and
teacher
variables
called
traits— characteristics
punctuality— were
(Rupley, Wise,
effectiveness
from
1986).
Researchers
teacher
ratings.
If a supervisor rated a teacher as effective, that
(Rupley, Wise, and Logan).
employing
teacher
measured
teacher was measured as effective
by
like honesty,
gleaned
and Logan,
teacher
for purposes
supervisor
of research
Educational researchers tried to
establish correlations between teacher traits and teacher
2
effectiveness ratings hoping to predict teacher effectiveness
from teacher traits (Cruickshank,
1985).
By the early 1960s, educational
researchers had agreed
upon the following conclusions:
(I) Supervisors did not agree
when
Subjectively
they
were
asked
effectiveness; (2)
to
Traits
by
themselves
rate
did
teacher
not
predict
teacher effectiveness nor could they be combined into one list
or index which could be used to predict teacher effectiveness;
(3)
Few
facts,
regarding
if
teacher
contexts.
any,
could
effectiveness
be
said
for
to
all
be
established
children
in
all
Researchers recognized that their investigations
of teacher traits as they related to teacher effectiveness had
not succeeded in identifying effective teachers (Cruickshankj
1985).
Researchers
successful
from the
(Rupley,
Wise,
1960s
to the
and Logan,
1970s were no more
1986).
B u t , they did
begin to experiment with teacher variables other than teacher
traits and
with a measure of teacher effectiveness other than
supervisor
ratings,
They
began
to
investigate
teacher
behavior as it related to student achievement (Rupley, Wise,
■
and Logan, 1986).
During
the
1970s,
educational
researchers
continued
investigations of teacher behavior as it related to student
achievement.
Researchers marched into teachers’ classrooms
armed with objective observation instruments for the purpose
of
correlating
teacher
behavior
with
student
achievement.
3
This
research
became
known
(Rupley, Wi s e , and Logan,
as
process-product
research
1986).
Process-product research led educational researchers to
some promising conclusions
effective teachers.
recent
research.
researchers
decision
It also
As
became
making
regarding the
they
aware
played
of
led researchers to their most
investigated
of
in
identification
the
that
teacher
important
behavior
behavior,
part
(Duffy
teacher
and
Ball,
1986).
Since
1976,
many
-educational
researchers
have
been
investigating teacher decision making as it relates.to student
achievement
(Clark
and
Peterson,
1984).
They
have
investigated the ways in which teachers make decisions and the.
kinds
of
decisions
researchers
teacher
use
which
student
they
make.
achievement
effectiveness.
This
as
research
Many
present-day
their
measure
relating
of
teacher
decision making to student achievement became known as teacher
decision-making research (Clark and Peterson,
Researchers
decision
have
making,
the
(Shavelson and Stern,
making
included
interaction.
identified
preactive
1981).
decisions
two
and
made
phases . of
the
Teacher
1984).
teacher
interactive
phases
interactive decision
during
actual
classroom
Teacher preactive decision making included those
decisions made before and after actual classroom interaction.
This decision making guided future classroom interactions.
'
For example, teacher preactive decision making included those
.
4
decisions made at the end of a classroom interaction which
determined what would become the classroom interaction for the
following d a y .
decisions
Teacher preactive decision making included
regarding
interactions .
daily,
term',,
■_and
■yearly-
It also includes decisions made, for units and
lessons (Clark and Peterson,
Shulman
.weekly,
1984).
(1986)
stated that educational researchers who
•
:
:
wished to contribute to answering the question, "Effective
.
teachers— who are they?" must
decision making.
preactive
.
investigate, teacher preactive
He urged researchers to investigate teacher
decision
content decisions.
making
particularly
(4)
in what
order,
and
achievement (Clark and Peterson,
This
study
it
related
to
Content decisions were decisions regarding
(I) what will be taught, (2) to whom,
of time,
as.
followed
(3) during what period
(5)
to what
standards
of
1984).
ShuIm a n ’s
urgings.
It
examined,
effective teaching by investigating teacher proactive content
decisions.
Problem Statement
The problem of this study was to determine which factors
were most important in influencing teacher preactive content
decisions.
The
dependent
variables
for
this
study
were,
decisions which teachers made in response to 50 simulations.
In the simulations, teachers were asked to decide whether or
not
they
would
make
content
changes
on
the
bqsis
of
5
descriptions of five influencing factors. These five factors,
the independent variables of this study, were district policy,
teacher belief, student achievement, professional opinion, and
community pressure.
The
five
influencing
factors
were
described
in
the
following manner for the purpose of this study:
1.
District
preactive
content
written policy
policy
-
decisions
statements,
The
extent
were
to
which
influenced
district
curriculum
by
teacher
district
guides,
and
district testing policy.
2.
Teacher
belief
-
The
extent
to
which
teacher
preactive content decisions were influenced by knowledge of
the subject area,
interest
in and enjoyment of the subject
area, convictions about the importance of the subject area and
the
topics
within
the
subject
ar e a , and
expectations
for
student achievement within that area.
3.
preactive
Student achievement - The extent to which teacher
content
decisions
were
influenced by
information
regarding student skill levels provided by diagnostic tests,
formative tests, summative tests, anecdotal reports, comments
from parents, classroom assignments, student verbal responses ,
and teacher observations.
4.
Professional opinion - The extent to which teacher
preactive content decisions were influenced by recommendations
from building principals,
curriculum coordinators, teachers
6
in higher grade levels, teachers at the same grade level and
subject area, and educational research.
5.
Community pressure
- The
extent
to which teacher
preactive content decisions were influenced by the desires of
a single parent or community member, a pressure
group,
the
P T A 1 or the local newspaper.
Contribution to Educational Literature
Will
making
research
contribute
into teacher preactive
to
identifying
content
effective
decision
teachers?
The
researchers cited below think so.
Research into teacher preactive content decision making
is research into teacher thinking.
that
research
into
teacher
And,
thinking
is
researchers agree
necessary.
For
example, Clark and Peterson (1984) stated that research into
teacher thinking was essential in understanding, predicting,
and influencing teacher behavior.
asserted that the way teachers
Allan A. Glatthorn (1987)
thought about their subject
profoundly affected the way in which they taught that subject.
Michael
McKibbon
(1978-79)
concurred.
He
contended
that
teacher thinking influenced and was influenced by the nature
of the content taught.
He asserted that if teacher trainers
were to have an effect on teacher thinking and, consequently,
on student achievement, those trainers would have to teach
teachers
agreed.
to think differently.
They
cited
two
Shavelson and Stern
justifications
for
(1981)
research
into
7
teacher thinking.
First, they stated that a solely behavioral
model of teaching process was incomplete.
for
differences
in
teacher
behavior
It did not account
which
variations in goals, judgments, and decisions.
stated
that
thinking
research
provided
a
linking
basis
teacher
for
arose
Secondly, they
behavior
teacher
from
to
education
teacher
and
for
instructional innovations.
More specifically, researchers called for investigations
into teacher decision making.
In fact,
as has been noted,
this research has become the most recent research trying to
identify effective teachers.
McKibbon (1978-79) highlighted
the teacher decision-making component of teacher thinking when
he proposed that teacher trainers direct their energies toward
those critical incidents in teaching when specific decisions
were
made.
Bush
acknowledged
the
importance
of
teacher
decision making when he declared that awareness of the sources
of teacher decisions could provide insight into the process
of teacher training.
Duffy and Ball
(1986)
asserted that
making decisions is of paramount importance in teaching.
They
believed that teachers must be trained to make decisions as
professionals rather than as technicians.
(1981)
insisted
that
training
training in decision making.
of
Shavelson and Stern
teachers
must
emphasize
Teachers must be made aware of
those decision-making strategies which they used and must be
encouraged to substitute effective ones for ineffective ones.
Finally,
Rupley,
Wise,
and
Logan
(1986)
indicated
that
8
research into this important component of teacher thinking had
only recently been recognized as legitimate.
Researchers,
as
has
been
noted,
broke,
down
the
decision-making component of teacher thinking into two phases.
Those
two
phases.
phases
were
the
preactive
and
the
interactive
Putnam and Duffy (1984), in describing the decisions
of one effective reading teacher, explained that his preactive
decisions accounted for his effectiveness,
in
producing
students
reading tests.
who
achieved
well
i.e. his success
on
standardized
They contended that he made virtually all of
his critical decisions during the preactive decision-making
phase of his teaching.
Yinger (1980) noted that there have
been few studies done on this phase of teacher decision making
even though research has pointed to its importance.
Within
researchers
the
phase
have
investigations.
of
found
preactive
it
necessary
As has been noted,
decision
to
making,
limit
Shulman (1986)
their,
suggests
that researchers should investigate teacher preactive content
decision making.
decisions?
content
Why should researchers investigate content
Rosenshine
(1978)
emphasized the
in determining student
teacher effectiveness,
importance of
achievement— the measure
of
He declared that content was one of
two variables most highly correlated with student achievement.
Frederick J . McDonald
(1976)
agreed.
He
insisted that the
amount of content covered was a.critical variable in student
achievement.
Shavelson and Stern (1981) stated that one of
9
the most critical decisions affecting student achievement was
the decision about what content should be covered.
asserted that mere
content knowledge was not
make
teacher;
an
effective
researchers
Shulman
sufficient to
must
pay
as
much
attention to the content aspects of teaching as they pay to
the process aspects of teaching.
that
researchers
must
look
for
Duffy and Ball pointed out
decision
making
that
went
beyond process concerns and must investigate teacher content
decisions.
Zoharik (1975) proposed that the place of content
in preactive decisions be more fully researched.
Floden et al.
preactive
content
(1986)
indicated future uses for teacher
decision, research.
As. a result
of. such
research, publishers of instructional materials could become
more aware of the need to monitor content variables.
Teacher
educators
address
could
become
content decision making.
more
aware
Finally,
of
the
need
to
as a result, of research
into teacher preactive content decision making,
researchers
could become more aware of the importance o f .differences in
teachers in terms of their decision-making abilities and their
■
■
content decisions.
Research into teacher preactive content decision making
could contribute to identifying effective teachers in several
:
' .
.
•’
'■ /• .■ ' V ■
ways.
Such research can eventually indicate differences in
the
decisions
of
effective ,and
ineffective
measured, for example, by student achievement.
the
potential
for
indicating
the
ways
teachers
as
It could have
in which
effective
10
teachers
interact
with
instructional
supervision, and teacher in-service.
materials,
teacher
It could direict future
researchers toward investigations which would contribute to
a more complete identification of effective teachers.
This study contributed to an identification of effective
teachers
proactive
by
contributing
content
to
decision
researchers'
making.
descriptions
It
contributed
of
to
a
description of the factors which influenced teacher preactive
content decisions for Montana public school teachers during
the
1987-88 school y e a r .
It complemented research already
completed at Michigan State University which described factors
which
influenced
the
preactive
content
decisions
of
sixty
fourth grade mathematics teachers in Michigan during the years
from 1978 to 1987 (Porter et a l ., 1986).
Although the contribution of the research conducted for
this
study
was
contribution
provided
a
small
of
when
future
necessary
compared
research,
building
with
it
was
block
the
potential
essential.
with
which
It
future
researchers could construct a complete description of teacher
preactive
content decision making.
That description could
contribute to the completion of the descriptions of teacher
preactive
teacher
decision
thinking.
researchers
effectiveness
achievement.
could
as
As
making,
With
then
teacher
those
begin
measured
researchers
to
by,
decision
descriptions
relate
for
them
making,
completed,
to
example,
investigated the
and
teacher
student
relationship
11
between these
descriptions
and teacher
effectiveness,
they
could contribute to the identification of effective teachers.
General Questions
1.
Was there more than one ranking of the five influencing
factors used by the teachers in this study when they made
their decision to change or not to change their content?
2.
Which of the five influencing factors used in this study
was most important in influencing teachers’ decisions to
change or not to change their content?
3.
How did the ranking of the five influencing factors used
by teachers in this study to decide whether dr not to
change their content
grouped
into
compare
categories
when those teachers were
according to the. size
district in which they teach,
of the
the subject area taught,
their number of years of experience, and their level of
education?
General Procedure
Following is a description of the procedures which were
used for the research described in this study.
During the
1987-88 school year, an instrument which presented simulated .
preactive
content
certified
middle
decision
school
situations
teachers
was
sent
from. Montana
to
who
192
were
randomly selected by school. Middle school was defined as any
school which was comprised of grades 5-9.
12
The
instrument
indicate whether
required
or not,
that
the
selected
on the basis
of
five
factors, they would change their content.
teachers
influencing
The interactions
of the influencing factors were presented as numerical ratings
using a scale,from 0 to 100.
A factor rating of 100 indicated
a strong impetus; a rating of 0 indicated no impetus.
District
change
on
policy
teacher
which
provided
preactive
a
content
strong
impetus
for
decision
making
was
district policy which mandated that teachers adhere to the
curriculum
guides
prepared by the
district
as part
of the
district’s written policy, which mandated that teachers teach
from designated textbooks and be on specific pages on specific
days
as part
district-wide
of
its
curriculum guides,
testing
and
comparison
and which mandated
of
test
scores
by
classroom and school at the end of each semester as part of
its
written
rating
of
impetus
policy.
70-99.
for
A
strong
District
change
on
district
policy
teacher
policy
which
preactive
received
provided
content
a
a weak
decision
making was a district policy which suggested goals and texts
for
teachers
as
part
of
its
written
policy.
It
had
no
curriculum guide and did not mandate district-wide testing.
It received a rating of from 30-1.
Teacher
belief
which
provided
a
strong
impetus
was
teacher belief which was founded on a complete knowledge of
the subject area,
area was
an unshakable conviction that the subject
important
to
students
and that
each topic
taught
13
within that subject area was important to students, and the
expectation that every student could succeed.in the subject
area
if given appropriate
instruction and sufficient time.
Such a policy received a rating of from 70-99.
Teacher belief
which provided a weak, impetus was teacher belief which was
founded on a shakey knowledge of the subject ar e a , a concern
about the importance of the subject area to students -and a
concern about
within
that
the
importance
subject
area,
of many of the
and
the
topics
expectation
students could not succeed in the subject area.
taught
that
many
It received
a rating of 30-1.
Student achievement which provided a strong impetus for
change
on teacher
proactive
achievement which was
beginning
of
each
content
measured
topic
decisions
by diagnostic
within
the
subject
was
student
tests
at the
area.
It was
student achievement which was regularly measured by formative
tests as well as summative tests.
It was also measured by
anecdotal
reports, student
responses, homework
classroom
assignments, comments
observations.
teacher.
verbal
from parents, and
and
teacher
Once it was measured, it was acted upon by the
For example,
the teacher adjusted what was taught
to whom during what time period
in what order and to what
standard of achievement on the basis of student achievement»
This
type
of
achievement
teacher
policy
received
which
provided
preactive
content
a
a rating
weak
of. 70-99.
impetus
decision
making
for
Student,
change
was
on
student
14
achievement which was only measured by summative tests.
measured, it was not acted upon by the teacher.
Once
Instead, the
teacher moved on to new topics according to a predetermined
plan.
That plan could be a district curriculum gpide, for
example.
This policy received a 30-1 rating.
Professional opinion which provided a strong impetus for
change
on
teacher
professional
curriculum
preactive
opinion
which
coordinator,
prescriptive
(stated
content
was
in
teachers,
clearly
and
taught), and carried rewards
decision
making
agreement
and
(principal,
research
concisely what
and sanctions
was
agreed),
should
be
for compliance.
This type of policy received a 70-99 rating.
Professional
opinion which provided a weak impetus for change on teacher
preactive
content
decision making was professional
Opinion
which was conflicting, was.vaguely stated, and carried with
it no rewards
or
sanctions
for
compliance.
This
type
of
policy received a 30-1 rating.
Community pressure which provided a strong impetus for
change on teacher, preactive content decisions, was community
pressure which was unified, i.e. all segments of the community
concur; specific,
i.e. told teachers exactly what needed to
be taught; and powerful, i.e. threatened to punish,
perhaps
through law suit or dismissal, teachers who failed to conform.
This type of policy was rated from 70-99.
Community pressure
which provided a weak impetus for change on teacher preactive
15
content decisions was community pressure which was fragmented,
generalized, and powerless.
It received a rating of 30-1.
Each teacher was presented with 50 simulations consisting
of five numerical ratings— one for each influencing factor.
Teachers were asked to decide whether or not they would change
their content for each one of the simulations. They expressed
their decision
in the
form of a percentage
indicating the
percentage of chance that they would change their content.
Table I presents an example of a simulation.
Table I
A Sample Simulation
I. District Policy
50
100
2 . Teacher Belief
90
75
High likelihood that
you would change
your content.
3. Student Achievement
80
50
Your rating:
4. Professional Opinion
40
25
5
0
Low likelihood that
you would change
content. .
5. Community Pressure
The rankings of influencing factors, or policies, of the
participating
teachers
were
Judgment Analysis Technique
were
similar were
grouped
identified
(JAN).
into
by
the
of
the
Teachers whose policies
clusters.
Each
teachers was described as having one policy.
than one cluster of teachers occurred,
clusters were
use
cluster of
Because more
the policies of the
compared through.narrative
description.
The
16
clusters
factors
were
were
compared
most
on
the
important
basis
for
of
the
which
influencing
teachers
within
the
clusters when making preactive content decisions.
Teachers were also grouped into categories on the basis
of the size of the district in which they taught, the subject
area they taught, the number of years of experience which they
had,
and
the
level
of
education
which
they
had
attained.
Within each category, teachers were separated into divisions.
The policies of teachers within those divisions were compared
on the basis of their rankings of influencing factors to see
if
any
similarities
similarities
teachers,
or
differences
and differences
did
existed.
Since
exist within divisions
of
the policies for the divisions were compared in a
narrative.
Limitations and Delimitations
1.
Since ,it was impossible to include all of the factors
influencing
teachers
when
they
make
their
preactive
content decisions, only five were included.
2.
Those
If
five influencing factors were general
any
of
influencing
those
five
teacher
were
found
preactive
to
content
be
in nature.
important
decisions,
in
they
would require further investigation in future research.
That research would need to attempt to determine which
aspects of the influencing factors were most
important
in influencing teacher preactive content decisions.
3.
Although inferences could be made, this research did not
17
3.
Although inferences could be m a d e , this research did not
investigate what teachers actually decide in preactive
content decision-making situations.
It only indicated
what they did in simulated situations.
1.
The research was
limited to data collected during the
1987-88 school year.
2.
The
population
for
this
study
was
limited
to
middle
school classroom teachers certified.to teach in Montana
public schools.
Definitions
Decision making: Making decisions meant choosing, alternative.
courses of action among alternative
either
before
inferences
or
during
resulting
from
actual
cues
courses
of action
teaching
present
in
based
a
on
learning
environment.
Preactive
decision making:
Decision making which occurred
outside of an actual teaching situation (Duffy and Ball,
1984).
Preactive content decision making: Preactive content decision
making occurred prior to actual teaching situations and
as concerned with choosing among alternative courses of
action with regard to what to teach to which students
during what period of time, in what order, and to what
standards of achievement (Porter et a l ., 1986).
18
CHAPTER 2
REVIEW OF RELATED LITERATURE
Introduction
Identifying
and
investigating
the
variables,
which
contribute to teacher effectiveness has occupied educational
researchers since the early 1900s (Cruickshank, 1985; Rupley,
Wise, and Logan, 1986).
One of these variables— an important
one according to recent research— was teacher thinking (Joyce,
1980;
they
ShaveIson,
have
1983;
and Shavelson and Stern,
investigated
identified
several
of
teacher
its
thinking,
components.
1981).
researchers
The
As
have
components
of
teacher thinking which were examined in this review of the
literature were
decision
making.
teacher decision making,
making,
and
teacher
teacher preactive
preactive
content
decision
The examination of these components proceeded from
an examination of the most inclusive, teacher thinking, to the
most specific, teacher preactive content decision making.
The research reviewed in this chapter was based on three
assumptions.
rational
The
first
professionals
environments.
The
assumption was
who
second
must
assumption
that
plan
was
teachers
about
that
were
complex
there
were
19
certain aspects
time.
of
teacher behavior that were
stable
over
The third was that there are teacher behaviors which
were related to student achievement (Joyce, 1978-79).
Teacher Thinking
As a result of a year-long, descriptive study conducted
during
the
1976-77
Elementary School
(1980)
drew
the
school
year
in South Bay,
following
on
teachers
at
Massachusetts,
conclusion:
The
South
Bay
Bruce Joyce
first
task
in
analyzing teacher decision making, preactive decision making,
and preactive content decision making was to.analyze teacher
thinking.
four
Joyce described teacher thinking as consisting of
parts:
(I)
the
flow
of
cues,
(2)
the
teachers'
perception of those cues which transformed them into stimuli,
(3) the teachers’ interpretation of those stimuli, and (4) the
teachers’ response behaviors to the interpretations of those
stimuli.
According to Joyce
(1980),
teacher thinking commenced
with a flow of cues. The cues within a flow could be numerous
and diverse. Theoretically, a teacher could perceive from zero
to 100% of the cues presented within the flow from a given
environment.
Realistically, a teacher rarely perceived 100%
of the available cues.
Instead, only a few of the cues in a
given environment were perceived.
to the teacher.
These cues become stimuli
20
Not only did teachers fail to perceive 100% of the cues
available
in a given
environment, but
those
teachers
failed to process all of the available stimuli.
could
"mask"
certain
stimuli
by
covering
almost immediately— those stimuli.
also
A teacher
over--forgetting
The choice of whether or
not to "mask" stimuli was made on the basis of a determination
of the potential relevance of those stimuli to the teacher.
Joyce (1980) described relevant stimuli as those stimuli which
had enough meaning to the teacher to require further thought.
This
differentiation
possible
relevance
among
was
complex environments
stimuli
called
on
the
"selective
like the ones
basis
of
the im­
attention."
In
in which teachers often
found themselves, teachers could facilitate this process of
"selective attention" by developing structures which helped
to focus their attention toward relevant stimuli.
Joyce
(1980)
suggested
that
the
attention-focuping
structures of teachers must have considerable impact on the
types of stimuli they choose as relevant.
Because there was
considerable variety in the attention-focusing structures used
by various
teachers, there
was
significant
types of stimuli chosen as relevant.
used
by
teachers
qualified
considerable
as
when
making
impact
on
the
teachers chose as relevant.
types
content
structures
of
in the
Certainly, the policies
preactive
attention-focusing
variety
stimuli
decisions
and
which
had
those
21
Once perceived, stimuli were interpreted (Joyce, 1980).
Inferences were
drawn
from the
stimuli.
These
inferences
could be in the form of judgments, expectations, or hypotheses
(Shave Ison and Stern, 1981).
Forming judgments, for example,
was the process of evaluation or categorization.
called
classification,
selection,
or
It has been
estimation.
Forming
judgments was.more than the simple process of applying rules;
it went beyond available stimuli by integrating new stimuli
as
the
process
continued
(Shavelson,
1983).
Judgment,
insisted Joyce, permeated the interpretation phase of teacher
thinking.
In phase four of teacher thinking, asserted Joyce (1980),
stimuli were acted upon.
The action which resulted from the
process of cue flow, perception, and interpretation was in the
form
of
covert,
teacher
behavior.
immediate,
or
That
delayed.
behavior
might
But
demonstrative of teacher decision making.
it
be
was
overt,
always
In other words, the
cue flow, perception, and interpretation resulted in teacher
decision making.
Teacher Decision Making
Are teachers decision makers?
Shavelson and Stern (1981)
contended that it seemed reasonable to assume that teachers
were decision makers and that their decisions were one of the
factors that influence student achievement.
(1987)
affirmed
that
teaching
was
decision
Madeline Hunter
making.
Bush
22
(1986), in a study conducted at the University of Houston on
the sources of teaching decisions of five preservice teachers,
concluded that teachers could be viewed as rational, thinking
individuals who reached instructional goals through decisions.
Y e t , Shavelson
teachers might
be
decision makers.
and
Stern
(1981)
suggested
decision makers, they were
that
not
while
rational
The rational, prescribed model of decision
making should, for example, follow this pattern:
(I) Specify
objectives, (2) Specify student entry level skills, (3) Select
and organize learning activities to move students from entry
level
skills
to
objectives,
and
(4)
Evaluate
improve planning (ShaveIson and Stern,
1981).
outcomes
to
This was not
the model generally used in teacher decision making.
There
was, Shavelson and Stern (1981) concluded, a mismatch between
the unpredictable and complex environment in which teachers
found
themselves
and
the
prescriptive
instructional
decision-making model.
Besides not following the rational decision-making mod e l ,
teachers
did
not
use
actual
cues
for
making
decisions.
Instead, according to Shavelson (1983), teachers based their
decisions on their perceptions and interpretations of those
cues.
Those perceptions and interpretations,
as have been
noted, resulted from the use of attention-focusing structures
like policies.
Shavelson further contended that teachers were
unaware of their policies.
Teachers also tended to use their
beliefs about education as the basis for their interpretations
23
and
perceptions
in
the
absence
of
relevant
cues.
In
conclusion, Shavelson asserted that the depiction of teachers
as rational
intentions
decision makers
for
their
was
more
descriptive
decision making than
of
of
their
their
actual
behavior.
He
making
suggested that the
was
d u e , at
least
lack of rationality in decision
in p a r t , to
decision making situations.
teacher’s
capacity
uripredictable,
for
demands
of
the
He continued by stating that a
making
complex
the
rational
environment
decisions
like
the
in
an
teaching
environment was probably small compared to the enormous power
of a model like the rational decision-making mod e l .
Finally,
he concluded that teachers behave rationally with respect to
the simplified models of reality which they constructed with
the help of their attention-focusing structures.
He described
teacher decision-making behavior as reasonable
rather than
rational.
Duffy and Ball
(1986) went even further than Shavelson
by declaring that reading teachers make very few decisions.
Furthermore, they proposed that research did. not provide any
evidence of a direct link between teacher decision making and
teacher
effectiveness.
Yet,
teachers did make decisions.
research
resulted
linking
from
decision
incomplete
they
asserted
that
effective
They submitted that the lack of
making
to
teacher
descriptions
of
involved rather than from the lack of a link.
effectiveness
the
processes
They presented
three examples of incomplete descriptions which they found in
teacher decision-making research.
have
incorrectly
described
First,
teacher
researchers might
thinking.
Following
Shavelson's example (1983), they concurred that the rational
model
of decision making might
inappropriate.
very well
be
idealized and
Second, researchers might not have accurately
described, the complexity of the decisions which teachers must
make
and
might
have,
in
decisions
which
teachers
fact,
must
missed
make.
important
For
kinds
example,
of
little
research had been done on content decisions according to Duffy,
and Ball.
occurred
They suggested that this omission might well have
because
instruction.
described
Third,
the
decisions.
of
the
example,
under
if
precise
definition
of
might not have
accurately
which
must
teachers
teachers
must
Ih conclusion, Duffy and Ball quoted Shavelson's
behaved
to
mandated
decisions.
teachers
opportunity
use
make
they
that
little
a
textbooks,
judgment
had
of
researchers
constraints
For
lack
reasonably
make
content
rather
than
rationally.
Teacher Preactive Decision Making
Obviously,
decision
making
a
was
more
complete
necessary.
description
Several
proposed more precise descriptions.
Bush
of
teacher
researchers
have
(1986)
offered a
three-way differentiation among types of decisions.
Decisions
could be preactive, made prior to teaching; interactive, made
25
during teaching;
or postactive, made after teaching.
Duffy
and Ball (1986) followed their own suggestion by proposing the
following differentiation among types of decisions.
might be procedural or substantive.
concerned
with
maintaining
an
Decisions
Procedural decisions were
activity
flow
by
managing
student behavior, time distribution, procedures, instructional
pace,
student responses,
occurred
during
the
and task completion.
interactive
phase
They usually
of. decision, making.
'
Substantive decisions were concerned with content.
Content
decisions usually occurred in the preactive decision-making
phase
and
emphasized
what
would
be
taught,
the
desired
outcomes of the teaching, the materials which would be used,
the
illustrations,
and
the
models
or demonstrations
which
would be employed.
Duffy
(1984)
study which was
Teaching
During
at
this
described his role as a participant
reported by the
Michigan
study,
State
Institute
University
which had
as
one
for Research on
in August
of
in a
its
of
1984.
objectives
to
determine whether or not. ShaveIso n ’s and Stern’s models of
preactive and interactive decision making could actually be
used
to
researcher
describe
a
teacher’s
Joyce
Putnam
behavior,
describes
Duffy
Duf f y ’s
as
he
fellow
taught
two
reading groups in a third/fourth grade reading classroom in
a
low-to-middle
city.
study.
class
neighborhood
school
in a midwestern
He and Joyce Putnam reported the findings from this
Their
report
further
clarified
the
definition
of
26
teacher decision making.
They confirmed that, indeed,
the
distinction between preactive and interactive decision making
I
'
was an accurate one.
.
They agreed with Shayelson and Stern
(1981) that postactive decision making actually cycled into
preactive
decision
making
and
that
there
was
no
real
distinction between those two types of decision making.
They described four phases of preactive decision making.
In the first phase, Duffy decided how to assess his students
individually
in order
to
determine
each
one's
(I)
general
interests and interest in reading, (2) fluency, (3) sight word
recognition,
(4) ability to predict
or generalize based on
personal experience and on what has been read, and (5) ability
to employ reading strategies for comprehension.
The preactive
decisions made by Duffy in phase one provided him with the
stimuli used as the basis for his preactive decisions in phase
two.
Phase
two preactive
decisions
involved procedural
and
substantive decisions like (I) what would be taught to whom,
(2) what materials would be used by whom,
(3) what type of
instruction would be used initially, and (4) what management
I
'
"'
and organization routines would be established.
In phase
three, Duffy’s preactive decisions dealt with (I) management
of one group in particular, (2) explicit explanations for each
individual
lesson,
and (3) correct practice an<f application
of the content being taught.
Finally,
in phase four, Duffy
focused his preactive decisions on the coherence of individual
27
lessons as they were integrated into his long-term plans.
Duffy and Ball (1984) further delineated the description
of
preactive
decision
concerned with
making
by
identifying
it
as
being
content, what would be taught; instruction,
how it would be taught; management, organization; and student
behavior, completing assignments.
relationship
phases
of
They proposed that a strong
existed between these preactive
decision
making
and
the
decisions
subsequent
and
interactive
decisions and phases of interactive decision making.
Robert Yinger
(1980) from the University of Cincinnati
described a study which he conducted which was similar to that
of Duffy and Ball.
In reviewing the observations he made
during his year-long study of a teacher in a combined first
.
and second
Yinger
drew
grade
classroom
several
decision making.
in a Michigan
conclusions
about
school
district,
teachers' preactive
One of them, which he reported in an 1980
article in The Elementary School Journal, was confirmed by the
Duffy
and
decisions.
Ball
study.
Teachers
did
make
instructional
Those decisions w e r e , as Duffy and Ball contended,
made during the preactive and interactive phases of teaching.
B u t , the most important ones were made during the preactive
phase.
nature.
The decisions were both procedural and substantive in
28
Teacher Preactive Content Decision M aking
Zahorik
(1974)
explained
that
content
decisions—
decisions regarding the nature of the subject matter to be
taught— were one of the most
that teachers could ma k e .
important preactive decisions
He described content decisions as
having been made by almost three-fourths of the teachers in
a
study
of
district
194
which
preactive
teachers
he
decisions
from
a
conducted
large
to
teachers
metropolitan
determine
made.
what
school
types
Preactive
of
content
decisions were described as having been made first by more
teachers than any other decision.
Most of the teachers
in
this study were described as asking this question first, "What
is
the
range
and particulars
of
the
subject
matter
to be
taught?"
Porter et al. (1986) , as a result of a project on teacher
decision
making
completed
by
them
for
a
Michigan
State
research project, concluded that teachers determined what was
taught
in
school.
Preactive
content
teachers were a major influence
decisions
on school
made
by
effectiveness
as
measured by student achievement because those decisions, in
effect, determined what it is that students would learn.
These
researchers
proposed
that
preactive
content
decisions could be divided into these five categories:
what
to teach,
students,
(4)
(2)
when
for what
and
in
length of time,
what
order, and
(3)
(5)
(I)
to which
to
what
29
standards of achievement.
content
decisions
Collectively, these five preactive
determined
student
opportunity
to
learn
which w a s , according to these researchers, a major influence
on student achievement.
These
authors
insisted that there
was a direct link between teacher decision making— at least
at the preactive content level— and teacher effectiveness as
measured by student achievement.
Who are effective teachers?
They are teachers who make
effective decisions at the preactive content level of decision
making.
Researchers
are
in the process
of describing how
those effective decisions are m a d e , which of them are more or
less
effective,
and
in
what
ways
those
decisions
affect
student achievement.
The research conducted for this study contributed to that
description by investigating how preactive content decisions
were
influenced
by
the
five
factors
of
district
policy,
teacher belief, student achievement, professional opinion, and
community pressure.
These factors have been recommended as
factors which need to be investigated by Floden et a l . (1986),
:
I
researchers at Michigan State University who have been
investigating teacher preactive content decision making for
the
Institute
for
Research
on
Teaching
sponsored
by
the
National Institute of Education.
The
important
(1986).
influencing
factor
one
research
in the
They discovered
of
district
conducted
tha t , while
by
most
policy
Floden
district
was
an
et
al.
policy
30
regarding
content
is
relatively
weak,
it
has
a
strong
influence on teacher preactive content decision making.
Policies
criteria:
varied
in
their
prescriptiveness,
power.
Prescriptiveness
specificity of a policy.
strength
according
consistency,
referred
to
to
authority,
the
extent
four
and
and
The more extensive the policy and
the more specifically it described what teachers were to do,
the more
strength
example,
a
that policy was
policy
mandating
a
said
to have
textbook
for
had.
use
in
For
each
classroom is weaker than a policy mandating a textbook and
instructing teachers to closely follow that textbook starting
at the beginning and teaching everything in the text to its
completion.
Consistency referred to the degree
to which different
content policies within a district support or contradict each
other.
to
For example, a mandated English textbook might be tied
English
objectives
which
specified
pages
within
the
textbook on which material for each objective was presented.
Authority referred to the degree to which a policy was
tied to
law,
individuals.
social norms, expert knowledge,
Policies
advocated in teaching
within the
teachers
arbitrary,
district
have
more
untested,
which
were
supported
or well-known
by
research,
journals, and designed by individuals
who were
strength
respected by
than
that
policies
district's
which
were
and designed by individuals within the
district who were not known or respected.
31
A final criterion for judging the strength of a policy,
according to Floden et a l . (1986), was power.
Power referred
to the degree to which the policy was tied to rewards
sanctions.
progress
A policy which mandated that
in
a
mandated
textbook
to
a
and
a teacher report
department
head
or
principal had more power than a policy which merely mandated
the textbook.
Floden et a l . (1986) also found that teacher belief was
a
strong
factor
decisions.
SchwiH e ,
influencing
teacher
preactive
content
In fact, in their first study (Floden, Porter, and.
1980), they found teacher belief to be the strongest
influence on teacher preactive content decisions.
Floden et
a l . attributed differences in the strength of teacher belief
as
it
affects
teacher
preactive
content
decisions
to
differences in subject area knowledge, interest and enjoyment
in the subject area, convictions about the importance of the
area and topics within the area, and expectations
students
can accomplish within the
importance of teacher belief
found
in articles
Cruickshank
Support
for the
in teacher decision making was
by George M.
(1985),
area.
for what
Christopher
Schuncke
M.
(1981),
Clark
and
Donald R.
Penelope
L.
Peterson (1984), Richard Shavelson and Paula Stern (1981), and
Gerald G, Duffy (1982).
Many
researchers
have
commented
on
the
importance
of
using student achievement data when making teaching decisions
(Schuncke, 1981i Meisels, 1986;
Salzer, 1986;
Rosenshine,
32
1978; Hartley,
Joyce,
1976; Duffy and McIntyre, 1980; Bloom,
1978-79;
1978-79).
Tindal
et a l . , 1981;
Floden et a l . (1986)
achievement
data
influenced
1984;
and Morine-Dershimer,
likewise agreed that student
teacher
preactive
content
decisions although they found the influence to be minimal.
Floden et al. (1986) found community pressure, especially
parent
pressure,
achievement.
to
be
more
influential
than
The strength of parental pressure seemed to be
linked to the socioeconomic status of the parents.
of higher
than
in
student
socioeconomic
schools
of
status,
lower
In schools
parents had more
socioeconomic
status.
influence
Community
pressure in the form of newspapers which printed local test
results by grade
level
and building did not seem to have a
strong effect on teacher preactive content decision making.
The following authors have also emphasized the importance of
community in influencing teacher decision making:
Yinger
Robert J .
(1980), Richard J . Shavelson and Paula Stern (1981),
Christopher M.
Clark
and Penelope
L.
Peterson
(1984),
and
Allan A. Glatthorn (1987).
Finally,
Floden
especially principals,
et
al.
(1986)
the
that
peers,
had very little influence on teacher
preactive content decision making.
emphasized
found
importance
of
Despite literature which
principals
as
instructional
leaders, they did not find principals to be a major influence
on teachers’ decisions about what to teach.
They found that
principals tended to leave content decisions to teachers and
33
to policymakers at higher levels, have little knowledge about
district
content
policies,
carrying out those policies.
that
peers
McIntyre,
did
influence
1980; Bush,
and Bush, 1986).
and
show
little
interest
Other authors have
teacher
decisions
1986; Glatthorn,
in
suggested
(Duffy
1987; GoodIad,
and
1987;
34
.
CHAPTER 3
PROCEDURES
Introduction
The problem of this study was to determine which factors
were most important in influencing teacher preactive content
decisions.
This chapter described the procedures which were
followed in this study.
Population
Description
It was divided into these sections:
and
Sampling Procedure,
Influencing
Factors, Method of Analysis, Method of Data Collection, Method
of Data Organization, Research Questions, Analysis of Data and
Precautions taken for Accuracy.
I Population Description and Sampling Procedures
The
population
for
this
study
consisted
of
certified
public school teachers in the State of Montana who taught in
middle schools during the 1987-88 school year.
Middle schools
were those schools consisting of any combination of grades 59.
A sample of 192 teachers was randomly selected from their
buildings to participate in this study.
by their building principals.
They were selected
Each of Montana’s 64 middle
35
school principals was contacted.
select
3
teachers
from
their
They were asked to randomly
schools
and
ask
that
those
teachers complete the simulation instrument.
Influencing Factors
From this study's review of literature, five factors were
selected as being important in influencing teacher preactive
content decisions.
teacher beliefs,
These five factors were district policy,
student achievement,
and community pressure.
teachers were
also
professional
opinion,
Four demographic factors relative to
selected
for
study.
They were
area of
teaching, education, size of district,, and number of years of
experience.
Method o f Analysis
JAN
used
in
(Judgment Analysis), was
this
study
to
the
determine
statistical
which
technique
factors
were
most
important in influencing teacher preactive content decisions.
This
technique
has
been
effectively
used
cluster the policies of raters (Dudycha,
to
1970).
capture
and
"Capturing"
the policies of a rater resulted in a researcher being able
to
predict
the
characteristics
(Dudycha, 1970).
decisions
of
the
of
factors
a
he
rater
was
from
the
required
to
known
rate
"Clustering" the policies of raters resulted
in a researcher being able to group raters on the basis on
the
homogeneity
of
the
policies
which
they
use
(Dudycha,
36
1970).
The
"policy"
of
a rater
referred
to
that
rater’s
regression equation which identified the importance placed on
the influencing factors by the rater.
A policy resulted in
a decision made by a rater when faced with a complex situation
consisting of several
factors
(Dudycha,
1970).
for purposes of this study, was a teacher.
A "rater,"
A "situation," for
purposes of this study, was a simulation,
JAN
was
researchers
an
effective
statistical
technique
for
to use when trying to determine policies which
might be present in decisions which were made collectively or
individual Iy (Houston and Stock, 1969).
According to Anderson
(1977),
factors
JAN
decisions
rating.
had
in
distinguished
simulations
between
more
clearly than
influencing
did
ranking
or
This technique had been applied in many studies and
been
found
to
provide
valid
and
reliable
information
technique
lay in the
(Christal, 1968).
The validity of this
validity
of
the
statistical
influencing
factors
chosen
for
study.
A
review of the literature established those factors which were
most
likely
reliability
to
of
be
important
this
influencing
statistical
factors.
technique
consistency of a rater’s policies.
The more
lay
in
The
the
consistent
a
rater’s policies were across all of the simulations contained
within
an
instrument,
the
more
provided by the JAN technique.
reliable
was
information
37
In
this
simulations
study,
contained
teachers
in
a
weipe
presented
survey-type
with
instrument.
50
The
simulations consisted of variations on the five influencing
factors selected for use in this study.
Teachers responded
with a percentage rating for each simulation.
rated
the
chance, given
a
variation
of
The percentage
the
five
factors
presented for a particular simulation, that a teacher would
change a preactive content decision.
After making their ratings, teachers were asked to return
the simulation instruments to the researcher for analysis by
JAN.
The JAN procedure consisted of two stages.
In the first
stage, the JAN technique acted on the assumption that each
teacher
had
an
individual
Houston, 1977) .
policy
(Keelan,
Houston,
and
A multiple regression equation was developed
for each teacher which ordered the five factors according to
their
importance
in accounting for the variability in that
teacher’s ratings.
JAN also determined a correlation (R^) for
each teacher which expressed the consistency of a teacher’s
ratings across all of the simulations (Dudycha, 1970),
In
the
second
stage
of
analysis,
JAN
determined
how
teachers clustered together in terms of the similarities of
their ratings.
First of all, the over-all
was computed for
all of the teachers’ ratings. The policy of the teacher whose
R^ was closest to the over-all R^ was identified.
then
computed
for
the
identified
policy
plus
An R^ was
each
of
the
remaining N-I (total number of teachers minus one) teachers’
38
policies.
The combined policy which resulted in the smallest
drop in
when compared with the policy of the teacher whose
was
closest
combined
to
policy
the
then
over-all
became
R^
the
was
identified.
policy
with
remaining N-2 individual policies were combined.
That
which
the
Again, the
combination of three policies which resulted in the smallest
drop in R^ when compared to the preceding combination of two
policies became the policy with which all of the remaining N-3
policies were combined.
This process continued until the drop
in R^ between a combined policy and that combined policy plus
a remaining
policy
exceeded
.05.
Al I the
teachers
whose
policies had been included in the combined policy prior to the
combination
which
resulted
in
the
unacceptable
drop
were
considered, for the purposes of this study, to have similar
policies
which
decisions.
teachers’
they
used
when
making
preactive
content
The process was then repeated with the remaining
policies
until
all
of
the
teachers
had
been
clustered into policy groups.
Once teachers had been clustered together according to
policy
groups,
they
demographic groups;
were.
people
schools
of 49,999-20,000,
different
were
categorized
together.
divisions
into
different
for example, teachers from districts of
50,000+
categorized
categorized
of
together.
19,999-5,000
Policy
groups
teachers.
The
divisions were compared in a narrative.
Teachers
from
and 4,999 were
also
were
formed
policies
for
of
the
those
39
M ethod of Collecting Data
A packet including a cover letter briefly describing the
study,
was
sent
principals.
to
each
of
The packet also
Montana’s
64
middle
school
contained explanations
of the
process to be followed, examples of simulations, explanations
of
influencing
gathering
factors, short
demographic
data,
surveys
for
simulation
the
purpose
instruments,
of
and
stamped, self-addressed envelopes to be given to the selected
teachers.
Each of 50 simulations consisted of a numerical rating
from I to 100 for each of the five influencing factors.
The
five influencing factors were the independent variables for
this
study.
These
five
factors had been determined to be
important in teacher preactive content decision making from
a review of the literature.
They are the following:
Table 2
Influencing Factors
Number
Factor
Abbreviation
I
District Policy
DP
2
Teacher Beliefs
TB
Student Achievement
SA
Professional Opinion
PO
Community Pressure
CP
. 3
;
: 4
5
40
The
numerical
rating
for
each
factor
simulation was determined by computer.
3,
the
intercorrelations
of
in a particular
As was shown in Table
simulation
factor
ratings
was
close enough to zero to be acceptable for the JAN statistical
technique (Dudycha, 1970).
Table 3
Intercorrelations of the Factors
Factor
DP
I
2
3
4
5
1.0000
TB
.09
SA
— .05
.00
PO
.00
-.03
.07
CP
.16
.02
-.25
The
means
1.0000
and
standard
1.0000
deviations
1.0000
for
.05
1.0000
the
simulation
factor ratings was shown in Table 4.
Table 4
Means and Standard Deviations of Simulation Factor
Factor
Mean
Standard Deviation
DP
51.04
29.81
TB
51.30
28.19
SA
49.70
28.76
PO
49.48
26.46
CP
49.50
28.35
41
Table 5 presented a sample simulation.
Table 5
Sample Simulation
SIMULATION FACTOR RATINGS
RATING SCALE
District Policy
20
100
Teacher Beliefs
60
75
High likelihood that
you would change
your content
Student Achievement
40
50
Your rating:
Professional Opinion
10
25
Community Pressure
10
0
Low likelihood that
you would change
The survey instrument was short.
packet which was
study.
It was included in the
mailed to each teacher
selected
for this
It asked teachers for their names, school district,
size of school district, subject taught, level of education,
and number of years of experience.
Method of Organizing Data
The
tables•
for
data
teachers’ ratings,
simulation
ratings
teacher, the
ratings
from
this
study
was
organized
in
The tables described the mean and standard deviation
each
teachers'
obtained
stages
the
correlations
and
the
influencing
of
the
JAN
and
the
influencing
factors
procedure
ratings, and correlations
between
factors
by
between
for
the
each
for
clustering
the
simulation
policy
for
each
42
teacher.
Tables were
also presented
describing the
information for each of these divisions of teachers:
from districts with 50,000+, 49,999-20,000,
4,999 students;
above
teachers
19 >000-5,000 and
teachers who teach English,
Social Studies,
Mathematics, Art, Home Economics, Physical Education, Special
Education,
have
taught
Industrial
15+,
14
Ar t s , Music
to
4,
or
or Science;
3-;
and
teachers who
teachers
who
have
BAs/BSs, MEds/MAs/MSs, Masters plus 45, or Ed.D.
Research Questions
Question I:
Was
there
teachers
more
in
than
one
determining
policy
their
used
by
preactive
content decisions?
Question 2:
What was the importance placed on each of the
five factors by teachers in making preactive
content decisions?
Question 3:
How did the policies of teachers compare when
teachers were categorized by size of district,
area
of
teaching,
level
of
education,
or
number of years of experience?
Analysis_of_Data
The computer services at Montana State University Testing
Service were used to perform the JAN analysis,
An a priori
minimum drop of .05 in R2 from one stage to another indicated
a significant change in policy.
43
CHAPTER 4
ANALYSIS OF DATA
:
Introduction
The data reported
following
in this chapter are arranged in the
categories:
populations
and
samples, research
questions, hypotheses, and summary.
Populations and Samples
The
population
for this
study
consisted
of
certified
public school teachers in the State of Montana who taught in
middle
schools
during
the
1987-1988
school
year.
Middle
schools were defined as those schools consisting of grades 5-9
or any combination of grades
total
of
64
schools
falling within grades 5-9.
in Montana
consequently
qualified
A
as
middle schools.
Each
middle
school
principal
was
asked
to
randomly
select,
for participation in this study, three teachers from
his/her
school
teacher on the
by
identifying
the
school’s roster.
first, middle,
last
then
asked to
distribute study packets, to those three teachers.
From the
64 qualifying middle
schools
He/she was
and
a total
of
192
became potential participants in this study.
teachers
thus
44
Out
of the
64 middle
school
principals
survey packets, 44 principals responded.
principals
who were
Forty-two of those
agreed to distribute packets
to their teachers.
Out of the 126 possible teacher participants
HO
responded.
Of those H O
in this study,
participants’ packets,
valid and, consequently, usable for this study.
considered
to
be
invalid
incompletely filled out.
if
they
sent
were
107 were
Packets were
improperly
or
These 107 valid packets resulted in
a 55.7 rate of return out of 192 possible packets.
The demographic surveys contained in the valid packets
yielded the following description of the participants in this
study.
50.000
Eleven of the participants came from communities of
or
more;
20.000 people;
5.000 people;
or fewer.
teaching
seven
came
from
communities
49,999
to
seventeen came from communities of 19,999 to
and sixty-four came from communities of 4,999
Fifty—one participants had
experience;
experience;
of
twenty-eight
15 or more years
had
thirteen had 9 to 4 years;
fewer years of teaching experience.
14
to
10
of
years
and eleven had 3 or
Three participants had
earned their Ed.D. degrees; nineteen had their M.A.+ degrees;
twenty-two had their M.A.
degrees;
of
the
degrees;
two had their B.A./B.S.+
and sixty-one had their B.A./B.S.
participants
eleven taught
taught
science;
English;
degrees.
fourteen
three taught music;
taught
Thirty
math;
fourteen taught
social studies; three taught art; two taught home economics;
three taught industrial arts; three taught physical education;
45
five taught special
education;
and nineteen taught multiple
subjects.
Research Questions
The research questions
in this study were
using the Judgment Analysis
beta weights, in the
indicated
the
expressed
by
indicated the
equation.
prediction
importance
the
(JAN)
of
equation
each
participating
consistency
of
technique.
for
The standard
each policy,
influencing
teachers.
the
investigated
raters
The
in the
factor
R2
as
value
prediction
The data are presented in tables.
Research Question One
Was there more than one ordering of the five influencing
factors used .by the
teachers
in this
study when
they made
their decision to change or not to change their content?
The purpose
of this
question was
to determine
if all
teachers used the same policy when deciding whether or not to
change
the
content
which
they
taught
to
their
students.
Policy referred to the relative importance participants placed
on each of the five influencing factors used in this study.
If the results from this study indicated that there was only
one policy used by the participants, then it would indicate
that the teachers
agreed on the relative importance of the
influencing factors when making decisions to change or not to
change content.
If this study indicated that there was more
than one policy, then it would indicate that teachers did not
46
agree
on
factors.
the
relative
importance
of
the
five
influencing
This disagreement would be expressed as individual
or group policies.
Table 6
Stages for Judgment Analysis Procedure
Stage
107
3
Number of
Policies
107
3
Participant
(Identified by Number)
Single member policies
Policy Number I
R2
R2
Drop
.6794
.3914
as
(67, 90, 56, 66, 83, 92,
40, 107, 96, 41, 46, 88,
89, 31, 63, 47, 98, 93,
54, 72, 4, 52, 99, 100,
13, 33, 21, 79, 35, 57,
76, 105, 6, 15, 91, 49,
103, 81 ,
r 34, 78, 14, 18,
73, 59, 19, 32, 95, 7,
71, 61, 80, 74, 8, 85,
16, 106, 10, 38, 101, 58,
82, 9, 29, 77, 12, 60,
69, 97, 20, 53, 22, 94)
Policy Number 2
(43, 45, 28, 44, 84, 36,
3, 37, 17, 11, 68, 51, 24,
26, 55, 23, 50, 86, 87)
Policy Number 3
(65, 102, 25, 27, 48, 42,
30, 62, 64, 70, 75, 104)
2
2
Policy Number I
(67, 90, 56, 66, 83, 92,
40, 107, 96, 41, 46, 88,
89, 31, 63, 47, 98, 93,
54, 72, 4, 52, 99, 39,
100, 13, 33, 21, 79, 35,
57, 76, 105, 6, 15, 91,
49, 103, BI, 34, 78, 14,
.3146
.0769
47
Table 6 (continued)
18, 73, 59, 19, 32, 95,
7, 71, 61, 80, 74, 8, 85,
16, 106, 10, 38, 101, 58,
82, 9, 29, 77, 12, 60,
69, 97, 20, 53, 22, 94,
2, 43, 45, 28, 44, 84,
36, 3, 37, 17, 11, 68,
51, 24, 26, 55, 23, 50,
86, 87)
Policy Number 2
(65, 102, 25, 27, 48, 42,
30, 62, 64, 70, 75, 104)
I
I
Policy Number I
(67, 90, 56, 66, 83, 92,
40, 107, 96, 41, 46, 88,
89, 31, 63, 47, 98, 93,
54, 72, 4, 52, 99, 39,
100, 13, 33, 21, 79, 35,
57, 76, 105, 6, 15, 91,
49, 103, 81, 34, 78, 14,
18, 73, 59, 19, 32, 95,
7, 71, 61, 80, 74, 8, 85,
16, 106, 10, 38, 101, 58,
82, 9, 29, 77, 12, 60,
69, 97, 20, 53, 22, 94,
2, 43, 45, 28, 44, 84,
36, 3, 37, 17, 11, 68,
51, 24, 26, 55, 23, 50,
86, 87, 65, 102, 25, 27,
48, 42, 30, 62, 64, 70,
75, 104)
.2009
.1137
The data from Table 6 provided the answer to research
question one.
It indicated that there were three policies
used by teachers when making the decision to change or not to
change content.
JAN analysis
This was indicated because at stage 2 in the
there
was
significant R^ drop was
mo r e .
a significant
determined to be
drop
of
.0796.
a drop of
A
.05 or
48
Three
policies
were
present
in stage
3 consisting
of
seventy-six (71%), nineteen (17.8%), and twelve participants
(11.2%),
respectively.
Policy
number
I,
called
Policy
I
because it contained the most participants, was expressed by
the seventy-six participant cluster; Policy number 2, called
Policy 2 because
participants,
cluster; and
contained
twelve
it contained the second
was
expressed
Policy
the
number
fewest
by
3,
the
called
nineteen
Policy
participants, was
participant
cluster.
This
largest number of
participant
3 because
expressed
data
by
showed
it
the
that,
considering all participants in this study, there were three
orderings of influencing factors used when making the decision
to:
change or not to change content.
The data from Table 16 in Appendix A indicated that at
stage
107
of
the
JAN
analysis
where
each
participant
was
considered as an individual unit the R2 values were very high.
This indicated that they were consistent in their policies.
At stage three of the JAN analysis,
R2 value
indicated
that
39
the R2 was
percent
accounted for by using three policies.
of
the
.3914.
This
variance
was
At stage two there
was a significant drop in R2 of .0769 which occurred when two
large
groups
of
participants
predictability— demonstrated
R2— showed
that
two
separate
were
by
united.
the
policies
This
significant
regarding
influencing factors existed in those two groups.
loss
of
drop
in
the
five
When trying
to combine all three groups present at stage three into one
49
group as was done in stage o n e , an even larger drop in
.1137 occurred.
by
the
of
This loss of predictability— as demonstrated
significant
drop
in R2— showed
that
three
separate
policies regarding the five influencing factors existed in the
total group of participants.
Research Question Two
Which of the five influencing factors used in this study
was
most
important
in
influencing
teachers'
decisions
to
change or not to change their content?
The purpose of this question was to determine if all of
the five influencing factors used in this study were of equal
importance in helping teachers to make decisions to change or
not to change their content.
A multiple regression analysis
was used to make this determination.
Table
7
showed
the
three
policies
used
by
the
participants in this study to decide whether or not to change
their content.
participants
The percentages indicated the percentage of
who
chose
each
of
the
factors
as
the
most
important factor influencing their decision to change or not
to change
their content within each policy.
The value
in
parentheses was the relative ranking of each change factor
within each policy.
value of Beta.
Rankings were determined by the absolute
50
Table
7
Rankings of Influencing Factors
Chosen as Most Important by Policy
Policy Number
Influencing Factor
2
3
4
TB
SA
PO
I
DP
I
(3)
20.5%
(2)
26%
2
(2)
0%
(2)
0%
3
(3)
8.3%
(I)
50%
CD
47.9%
(I)
100%
(2)
25.0%
5
CP
(5)
2.7%
(4)
5.4%
(2)
0%
(2)
0%
(3)
8.3%
(3)
8.3%
The percentages indicated that the participants in Policy
I used a multi-factored approach to determining whether or not
to
change
their
influencing
Achievement,
content.
factor
They
ranked
accordingly:
factor
#2
was
the
factor
Teacher
most
#1
Belief,
important
was
Student
factor
#3
was
District Policy, factor #4 was Community Pressure, and factor
#5
was
Professional
Achievement,
Teacher
Opinion.
Belief,
The
factors
and District
considered important by the participants
factors of Professional
of
Policy
in Policy
Student
all
were
I.
The
Opinion and Community Pressure were
considered to be of lesser importance.
Participants in Policy 2 used a single-factor approach
to determining whether or not to change their content.
They
all ranked as their most important influencing factor Student
>■
51
Achievement.
There was no other most important influencing
factor chosen by participants who fell into Policy 2.
Participants in Policy 3 used a dual-factor approach to
determining whether
or not
to
change
their
content.
They
ranked the most important influencing factor in the following
order:
factor #1 was Teacher Belief and factor #2 was Student
Achievement.
Participants in policy 3 did not differentiate
between District Policy,
Pressure.
Professional Opinion and Community
These three factors were of lesser importance.
Research Question Three
What
effect did the demographic
categories of
size of
district, years of experience, years of education, and subject
taught have on the rankings of the five influencing factors?
The purpose of this question was to determine if all of
the five influencing factors used in this study were of equal
importance in helping teachers to make decisions to change or
not to change
their
content regardless
of the
size of the
district in which the teacher taught, the number of years of
experience
which
the
teacher
had,
the
number
education which the teacher had accumulated,
which
the
teacher
participant
fell
taught.
was
used
The
as
policy
the
of
years
of
or the subject
group
into which
indication
of
a
that
participant’s rankings of influencing factors.
Table
8 showed the policy
into which each participant
fell as well as the division of the demographic category of
District Size into which each participant fell.
52
Table 8
Policies Grouped According to Size
of School District
District
Size
Policy I
Policy 2
Policy- 3
-
11, 28, 50, 51
30
49,00020,000
13, 14, 15, 71,
80, 83
84
0
19,9995,000
21, 31, 32, 33
61, 63, 69, 72,
79, 90, 100 *
107
68
42,
104
4,999-
4, 6, 7, 8, 9,
16, 18, 19, 20,
22, 34, 35, 38,
39, 40, 41, 46,
47, 52, 53, 54,
57, 58, 59, 60,
67, 73, 74, 76,
77, 78, 81, 82,
85 , 88, 89, 91,
92, 93, 95, 96,
101 , 103 , 105,
106
3, 17, 23, 24,
26, 36, 37, 43,
37, 43, 44, 45,
55, 87
25, 27, 65,
70, 75, 102
!
Table
9
showed
the
number
and
percentage
O
to
10, 12, 29, 49,
97, 99
CO
50,000+
of
participants who fell into each division of the demographic
category of District
Size.
It then showed the number
and
percentage of participants per policy within each demographic
division.
53
T able 9
Percentage of Participants by Policy
and District Size
District
Size
% of Participants
Compared to Total
Policy
% by
Policy
50,000+
10.2% (11)
I
2
3
54.5% ( 6)
36.4% ( 4)
9.1% ( I)
49,99920,000
6.5% ( 7)
I
2
3
85.7% ( 6)
14.3% ( I)
0.0% ( 0)
19,9995,000
15.9% (17)
I
2
3
70.6% (12)
17.6% ( 3)
22.8% ( 2)
4,999
59.8% (64)
I
2
3
71.9% (46)
18.8% (12)
9.4% ( 6)
Table
9
indicated
that
the
50,000+
district
size
demographic division was the third largest division in this
demographic
category.
In
it,
there
were
11
participants
equaling 10.2% of the total sample size of 107 participants.
Out of those 11 participants, 6 fell into Policy I. These 6
i
participants equaled 54.5% of the number of participants in
the
50,000+
district
participants
fell
participants
in
division.
size
demographic
division.
Four
into Policy 2 for 36.4% of the number of
the
50,000+*
district
size
demographic
One participant fell into Policy 3 for 9.1% of the
participants in that division.
54
The 49,999-20,000 district size demographic division was
the smallest division in this demographic category.
In it,
there were 7 participants equaling 6.5% of the total sample
size of 107 participants.
into Policy
number
I.
These
6 participants
of participants
demographic
Out of those 7 participants, 6 fell
in the
division.
One
equaled 85.7% of the
49,999^20,000
participant
district
(14.3%)
fell
size
into
Policy 2 and no participants (0.0%) fell into Policy 3.
The 19,999-5,000 district size demographic division was '
the second largest division in this demographic category.
it,
there were
sample
size
17 participants
of
participants,
107
equaling 15.9% of the total
participants.
12 (70.6%)
In
Out
of
those
fell into Policy I, 3 (17.6%)
17
fell
into Policy 2, and 2 (22.8%) fell into Policy 3.
The 4,999- division was the
largest division.
In it,
there were 64 participants equaling 59.8% of the total sample
size.
Out
Policy I,
of those
12 (18.8%)
64 participants,
fell
46
(71.9%)
fell
into
into Policy 2, and 6 (9.4%)
fell
into Policy 3.
Participants in the 50,000+ district size division were
least likely of the participants in any of this demographic
category
to
use
Policy
I,
a
multi-factored
approach,
determine whether or not to change their content.
words,
they were
least
Student Achievement,
to
In other
likely to consider District Policy,
and Teacher Belief in conjunction with
each other when making their decision.
They were more likely
55
to
use
Policy
2,
a
single-factor
approach,
than
participants in the other district size divisions.
the
This means
they were more likely to rely on Student Achievement as the
singIe-most-important basis for making their content-change
decision.
Participants in the 49,999-20,000 district size division
were
most
category
likely
to
use
of
the
Policy
participants
I,
a
in
this
multi-factored
demographic
approach,
determine whether or not to change their content.
to
In other
words, they were most likely to consider Student Achievement,
Teacher Belief,
and District Policy together as a basis for
making content-change decisions.
They were the least likely
of the participants in these demographic divisions to use the
dual-factor
approach
(Policy
3)
emphasizing
Student
Achievement and Teacher Belief to the exclusion of the other
factors.
Likewise, participants in this demographic division
were least likely to use the single-factor approach (Policy
2) which emphasizes Student Achievement.
For participants in
this division, district policy was an essential ingredient in
their content-change decisions.
I
■
Participants
.
in the 19,999 district size division were
most likely of the participants in this demographic category
to use Policy 3, a dual-factor approach, to determine whether
or not to change their content.
In other words,
they were
most likely to consider Student Achievement and Teacher Belief
together as a basis for making content-change decisions.
56
Table 10 showed the policy as well as the division of. the
demographic category of Years of Experience into which each
participant fell.
Table 10
Policies Grouped According to Years
of Experience
Years of
Experience
Policy 2
Policy 3
4, 7, 9 , 10,
12, 14, 19, 21,
22, 38, 39, 41,
46, 47, 53, 56,
57, 63, 71, 72,
74, 78, 79, 80,
85, 88, 91, 93,
94, 95, 97, 99,
100 , 106
11, 17, 23, 37,
44, 50, 51, 84,
87
25, 27, 30, 42
48, 62, 70, 104
8, 13, 16, 20,
29, 31, 32, 33,
35, 40, 52, 54,
61, 67, 69, 73,
77, 81, 83, 89,
96, 98, 105
24, 28, 36, 55
64
I
O'
15+
Policy I
6, 15, 34, 49,
76, 82, 101,
107
3, 26, 68, 86
65
3- .
18, 58, 59, 60,
90, 92, 103
43, 45
75, 102
:
O
I
Hje
r-H
Table 11 showed the number and percentage of participants
who fell
into each division of the demographic
Years of Experience.
category of
It then showed the number and percentage
of participants per policy within each demographic division.
57
Table 11
Percentage of Participants by Policy
and Years of Experience
Years of
Experience
% of Participants
Compared to Total
15+
47.7% (51)
I
2
3
66.7% (34)
17.6% ( 9)
15.7% ( 8)
14%
(28)
I
2
3
82.1% (23)
14.2% ( 4)
3.6% ( I)
9-4
12.1% (13)
I
2
3
61.5% ( 8)
30.8% ( 4)
7.7% ( I)
3-
10.3% (11)
I
2
3
63.6% ( 7)
18.1% ( 2)
18.1% ( 2)
14-10
Table
11
indicated
demographic
division
demographic
category.
that
was
In
the
the
15+ years
largest
it,
% by
Policy
Policy
there
of
experience
division
were
51
in
this
participants
equaling 47.7% of the total sample size of 107 participants.
Out of those 51 participants,
34 fell into Policy I.
These
34 participants equaled 66.7% of the number of participants
in the
15+ years of experience demographic division.
participants
fell
participants
in
division.
Eight
Nine
into Policy 2 for 17.6% of the number of
the
15+
fell
years
into
participants in that division.
of
Policy
experience
3
for
demographic
15.7%
of
the
58
' The 14-10 years of experience demographic division was
the second largest division in this demographic category.
it,
there
were
sample size.
28 participants
equaling
14%
of
the
In
total
Out of those 28 participants, 23 (82.1%) fell
into Policy I, 4 (14.2%) fell into Policy 2, and I (3.6%) fell
into Policy 3.
The 9-4 years of experience demographic division was the
third largest division in this demographic category.
In it,
there were 13 participants equaling 12.1% of the total sample
size.
Out
of
those
:
13 participants,
8
(61.5%)
fell
into
'
Policy I, 4 (30.8%) fell into Policy 2, and I (7.7%) fell into
Policy 3.
The 3- years of experience demographic division was the
smallest division in this demographic category.
In it, there
were 11 participants equaling 10.3% of the total sample size.
Out of those 11 participants,
7 (63.6%)
fell into Policy I,
2 (18.1%) fell into Policy 2, and 2 (18.1%) fell into Policy
3.
Participants in the 14-10 years of experience demographic,
division were most likely of participants in any of the years
of experience demographic divisions to use Policy I, a multifactored approach to content-change decisions.
they were most
Belief,
and
likely to consider District Policy,
Student
Achievement
their content-change decisions.
Policy
2,
a
This means
single
factor
together
as
Teacher
the basis
for
They were least likely to use
approach,
and Policy
3,
a dual
59
factor approach.
an essential
For these participants, District Policy was
ingredient in making content-change decisions.
They were not willing to exclude both District Policy and
Teacher Belief as were participants in Policy 2 or District
Policy as were participants in Policy 2 or District Policy as
were
participants
in
Policy
3
from
their
decision-making
process.
Participants in the 9-4 years of experience demographic
division were most likely of the participants in any of the
years of experience demographic divisions to use Policy 2, a
single—factor approach to content—change decisions.
participants,
the
single most
important
factor
For these
in content-
change decisions was Student Achievement.
Participants
division
were
in the 3- years of experience demographic
most
likely
to
use
Policy
approach to content-change decisions.
2,
a dual-factor
For them, the factors
of Student Achievement and Teacher Belief together formed the
basis of their content-change decisions.
Table
demographic
12 showed policy as well as the division of the
category of Years of Education into which each
participant fell.
60
Table
12
Policies Grouped According to Level
of Education
Policy I
Policy 2
Policy 3
M.A.+30
7, 12, 15, 18,
46, 71, 72, 73,
78, 92, 93
11, 23, 50
25, 30,
104
M. A.
9, 10, 20, 21,
29, 33, 35, 38,
56 , 57, 63, 74,
80, 85, 91, 100,
106
24, 37, 87
B.A.
4,
, 13 , 14,
16, 19, 22, 31,
32, 34, 40, 41,
47, 49, 52, 53,
54, 58, 59, 60,
61, 67, 69, 77,
79, 81, 82, 83,
88, 89, 90, 94,
95, 96, 97, 98,
99, 101, 103,
105, 107
3, 17, 26, 28,
36, 43, 45, 51,
27, 42, 64, 65,
102
Table
13
showed
participants who fell
the
number
to
0
and
CO
84
CO
39, 76
VO
Ed.D.
Ch
Level of
Education
70,
75
percentages
of
into each division of the demographic
»
'
category of Years of Education. It then showed the number and
percentage of participants
division.
per policy within each demographic
61
Table 13
Percentage of Participants by Policy
and Years of Education
Years of
Experience
% of Participants
Compared to Total
Ed.D.
% by
Policy
Policy
2.8% ( 3)
I
2
3
66.7% ( 2)
33.3% ( I)
00.0% ( 0)
M.A.+30
17.8% (19)
I
2
3
57.8% (11)
15.8% ( 3)
26.3% ( 5)
M.A.
20.6% (22)
I
2
3
77.2% (17)
13.6% ( 3)
9.1% ( 2)
B.A.
54.2% (58)
I
2
3
72.4% (42)
19.0% (11)
8.6% ( 5)
Table
13
showed
demographic
division
demographic
category.
that
was
the
the
In
equaling 2.8% of the total
it,
Ed.D.
years
smallest
there
of
division
were
3
education
in
this
participants
sample size of 107 participants.
Out of those 3 participants,
2 fell into Policy I.
These 2
participants equaled 66.7% of the number of participants
the
Ed.D.
participant
years
fell
of
education
demographic
division.
into Policy 2 for 33.3% of the number
participants in the Ed.D. division.
in
One
of
No participants fell into
Policy 3.
The M.A.+30 years of education demographic division was
the third largest division in this demographic category.
In
62
it, there were
sample
size
participants,
19 participants
of
107
11 fell
equaling 17.8% of the total
participants.
into Policy I.
Out
Three
(15.8%)
those
19
These 11 participants
equaled 57.8% of the number of participants
demographic division.
of
in the M.A.+30
fell into Policy 2 and
5 (26.3%) fell into Policy 3.
The M.A. years of education demographic division was the
second largest division in this demographic category.
In it,
there were 22 participants equaling 20.6% of the total sample
size.
Out of those
22 participants,
17
(77.2%)
fell
into
Policy I, 3 (13.6%) fell into Policy 2, and 2 (9.1%) fell into
Policy 3.
The B.A. years of education demographic division was the
largest division.
In it, there were 58 participants equaling
54.2% of the total sample size.
Out of those 58 participants,
42 (72.5%) fell into Policy I, 11 (19.0%) fell into Policy 2,
and 5 (8.6%) fell into Policy 3.
Participants in the M.A. years of education demographic
division were most likely to use Policy I, a multi-factored
approach,
when making content-change decisions.
This means
that they were most likely to include District Policy in their
decision-making process
Teacher Belief.
along with Student
Achievement
and
They were least likely to rely on Policy 2,
a single-factor approach emphasizing Student Achievement.
Ed.D.
participants
were
most
likely
of
the
four
demographic divisions to use Policy 2 when making content-
63
change decisions.
In other words, they emphasized the single
factor of Student Achievement above all
making such decisions.
other
factors when
They were least likely to use Policy
3, a dual factor approach emphasizing both Student Achievement
and Teacher Belief.
M.A.+30
participants
were
most
likely
of
the
four
demographic divisions to use Policy 3, a dual-factor approach,
when making content-change decisions.
This means they were
basing their
decisions
on both Teacher Belief
and Student
Achievement.
They were least likely to use Policy I, a multi­
factor approach emphasizing District Policy along with Teacher
Belief and Student Achievement.
Table 14 showed the policy as well as the divisions of
the demographic
participant fell.
category of Subject Taught
into which each
64
T able
14
Policies According to Subject
Area Taught
Level of
Education
Policy I
English
6,
35,
54,
73,
95
Math
10,
40,
67,
74,
13,
46,
69,
83,
Policy 2
14,
49,
72,
90,
Policy 3
23, 26, 28, 44,
45, 50, 55, 86
48, 62, 75, 102
8, 18, 21, 29,
53, 63, 78, 79,
92, 93
24, 68, 84
25
Science
16, 20, 41, 52,
57, 60, 71
11, 87
30, 64
Music
7, 76, 100
0
0
Social
Studies
12, 15, 32, 33,
56, 59, 61, 91,
98, 99
3, 17
42
Art
85, 88
51
0
Home Ec
22, 80
0
0
Shop
9, 101
0
70
P .E .
31, 58, 77
0
0
Spec Ed
47, 89, 107
43
70
Table 15 showed the number and percentage of participants
who fell
into each division of the demographic
Subject Taught.
category of
It then showed the number and percentage of
participants per policy within each demographic division.
65
Table 15
Percentage of Participants by Policy
and Subject Taught
Subject
Taught
% of Participants
Compared to Total
English
27.1% (29)
I
2
3
58.6% (17)
27.6% ( 8)
13.8% ( 4)
Math
13.1% (14)
I
2
3
71.4% (10)
21.4% ( 3)
7.1% ( D
Science
10.3% (11)
I
2
3
70.0% ( 7)
20.0% ( 2)
10,0% ( D
2.8% ( 3)
I
2
3
100% ( 3)
0% ( 0)
0% ( 0)
12.1% (13)
I
2
3
76.9% (10)
15.4% ( 2)
7.7% ( D
Art
2.8% ( 3)
I
2
3
66.6% ( 2)
33.3% ( D
00.0% ( 0)
Home Ec
2.8% ( 3)
I
2
3
100% ( 2)
0% ( 0)
0% ( 0)
Shop
2.8% ( 3)
I
2
3
66.6% ( 2)
0% ( 0)
33.3% ( D
P.E.
2.8% ( 3)
I
2
3
100% ( 3)
0% ( 0)
0% ( 0)
Special Ed
4.7% ( 5)
I
2
3
60.0% ( 3)
20.0% ( D
20.0% ( D
Music
Social
Studies
Policy
% by
Policy
66
Table
15
indicated
demographic
division
demographic
category.
that
was
the
the
In
it,
English
largest
there
subject
division,
were
29
taught
in
this
participants
equaling 27.1% of the total sample size of 107 participants.
Out of those 29 participants, 17 fell into Policy I.
These
17 participants equaled 58.6% of the number of participants
in the English
subject taught demographic division.
participants
fell
participants
in the English subject taught division.
Eight
into Policy 2 for 27.6% of the number of
Four
participants fell into Policy 3 for 13.8% of the participants
in that division.
The
math
subject
taught
demographic
division was
second largest division in this demographic category.
the
In it,
there were 14 participants equaling 13.1% of the total sample
size of 107 participants.
fell into Policy I.
the
number
of
Out of those 13 participants,
These 10 participants equaled 71.4% of
participants
demographic division.
10
in
the
Three (21.4%)
math
subject
taught
fell into Policy 2 and
one (7.1%) fell into Policy 3.
The science subject taught demographic division was the
fourth largest division in this demographic category.
In it,
there were 11 participants equaling 10.3% of the total sample
size.
Out
of
those
Policy I, 2 (21.4%)
11 participants,
fell
7
(70.0%)
fell
into
into Policy 2, and I (10.0%)
fell
into Policy 3.
\
67
The music subject taught demographic division was one of
five smallest divisions in that category.
In it, there were
3 participants equaling 2.8% of the total sample size.
All
three of those participants fell into Policy I.
The social studies subject taught demographic division
was the third largest division in that category.
In it, there
were 13 participants equaling 12.1% total sample size.
of those 13 participants,
10
(76.9%)
fell
Out
into Policy I,
2
(15.4%) fell into Policy 2, and I (7.7%) fell into Policy 3.
The art subject taught demographic division was one of
the five smallest divisions in that category.
In it, there
were 3 participants equaling 2.8% of the total
sample size.
Out of those 3 participants,
2 (66.6%) fell into Policy I, I
(33.3%) fell into Policy 2, and 0 fell into Policy 3.
The home economics subject taught demographic division
was one of the five smallest divisions in that category.
it,
there
were
sample size.
3 participants
equaling
2.8%
of
the
In
total
Al I 3 of those participants fell into Policy I.
The shop subject taught demographic division was one of
the five smallest divisions in that category.
In it, there
were 3 participants equaling 2.8% of the total
sample size.
Out of those 3 participants, 2 (66.6%) fell into Policy I, 0
fell into Policy 2, and I (33.3%) fell into Policy 3.
The P.E. subject taught demographic division was one of
the five smallest divisions in that category.
In it, there
68
were 3 participants equaling 2.8% of the total sample size.
All 3 of those participants fell into Policy I.
The special education subject taught demographic division
was the fifth largest division in that category.
In it, there
were 5 participants equaling 4.7% of the total sample size.
Out of those 5 participants, 3 (60.0%) fell into Policy I, I
(20.0%) fell into Policy 2, and I (20.0%) fell into Policy 3.
Participants
in
the
music,
home
economics,
and
P.E.
subject taught divisions were most likely of all participants
in this
category to base their content-change
Policy I, a multi-factored approach.
decisions on
They were least likely
to emphasize Policy 2, a single-factor approach, or Policy 3,
a dual-factor
decisions
approach.
on all
This
means
three factors
that
they based their
of District Policy,
Teacher
Belief, and Student Achievement.
Participants
divisions
were
in
most
the
art
likely
and
of
all
English
subject
participants
taught
in
this
category to base their decisions on a single-factor approach.
They emphasized Policy 2 which uses Student Achievement as the
basis for content-change decisions.
Participants in shop and special education subject taught
divisions
were
category to base
most
likely
of
all
participants
in
this
their decision on a dual-factor approach.
They were most likely to base their content-change decisions
on the combined
Belief.
factors of Student Achievement
and Teacher
69
CHAPTER 5
CONCLUSIONS
Introduction
In
this
chapter,
conclusions
study’s data are discussed,
presented,
and
reached
recommendations
recommendations
for
based
on
this
for action are
further
research
are
suggested.
Conclusions
The
school
purpose
teachers
influencing
of this
used one
factors
change or not to
when
study was
to determine
if middle
or more than one ranking of five
making
the
preactive
change their content.
decision
to
In regard to this
purpose, it has been found that the middle school teachers in
this study used more than one ranking of influencing factors
when making their content-change decisions.
Within each of
the
policies
demographic
present.
categories
Participants
in
studied,
each
of
three
the
categories
were
chose
a
policy which represented a dual-factor approach (Policy 3).
Those participants in each of the demographic categories who
chose the multi-factor approach emphasized District Policy,
Teacher Belief,
and Student Achievement in their decisions.
70
Those who
chose
the
single-factor approach emphasized only
Student Achievement.
Those who chose the dual-factor approach
chose both Student Achievement and Teacher Belief.
It can be concluded from this finding that the topic of
teacher preactive content decision making is a topic worthy
of
study.
Because
there
is
more
than
one
ranking
of
influencing factors used by teachers to make preactive content
decisions, there
is
the
possibility
that
the
ranking
of
influencing factors is correlated with teacher effectiveness
as measured by
effectiveness
student
studies
achievement.
might
find
For
that
multir-factor approach to preactive
example, teacher
teachers
who
use
a
content decision making
produce students who achieve higher on a designated measure
of student achievement than teachers who use a single-factor
approach.
Joyce (1980) explained how this correlation might occur.
He suggested that
which
teachers
facilitate
attention
in complex environments
make
their
structures.
are
structures
by
Teachers’
examples
of
helped
in
decisions, teachers
process
structures.
factors
These
content
decision-making
focusing
influencing
preactive
like the ones
developing
rankings
of
attention-focusing
teachers
focus
their
attention on stimuli which they considered to be relevant and
"mask" stimuli which they considered to be irrelevant.
The
factors
existence
indicated
of
that
different
rankings
of
influencing
different
teachers
used
different
71
attention-focusing structures when making preactive content
decisions.
suggested,
These
different
rankings
could h a v e , as Joyce
considerable impact on the types of stimuli they
chose as relevant. For example, teachers employing the multi;
.
.
.
factor approach would attend to stimuli from their district’s
curriculum policy along with stimuli
from their own belief
system as it has been formed by their experience and stimuli
concerning
student
single-factor
achievement.
Teachers
approach would attend to
employing
student
the
achievement
stimuli and "mask" stimuli from district policy and their own
belief
system
student
approach
except
as
achievement.
system
Teachers
would
attend
teacher belief
stimuli
AlI
that
to
and
teachers would tend to
is
affected
employing
student
"mask"
the
achievement
by
past
dual-factor
stimuli
and
district policy stimuli.
"mask" professional
opinion and
community pressure stimuli.
The
choice
of
different preactive
different
relevant
content decisions.
stimuli
In this
resulted
in
study, the
percentage each participant chose for each simulation was the
overt indication of teacher preactive content decision making
which Joyce
described
in his
study.
participants’ attention-focusing
In
other
words, the
structures— their rankings
of influencing factors— narrowed the flow of stimuli to the
point that they could make consistent decisions— consistent
percentage choices.
were consistent was
That the decisions of the participants
indicated by the high
(.6794) at the
72
107 stage of the JAN analysis.
three
consistent
but
It is the effect of these
different
decision-making
approaches
(Policies I, 2 and 3) on student achievement that could be of
concern to teacher effectiveness studies.
This finding that teachers do use more than one ranking
of influencing factors when making preactive content decisions
also substantiated the conclusions of McKibbon (1978-79), Bush
(1986),
and
researchers
Shavelson
contended
and
that
Stern
because
(1981).
of
Each
such
of
these
consistent
but
different decisions, teacher preactive decision making needed
to be addressed by research, teacher training, and teacher inservice.
Certainly,
correlate
teacher
as has been noted above,
rankings
of
subsequent content decisions,
influencing
studies which
factors, their
and student achievement could
result in important information about who effective teachers
are
and how
effective
teachers
can be trained by teacher­
training institutions and encouraged by school districts.
A
second purpose
of
this
study was
to
determine
the
relative importance of each of the five influencing factors:
District
Policy,
Student
Professional Opinion,
Achievement,
Teacher
and Community Pressure.
Belief,
The findings
of this study indicated that Student Achievement was the most
important influencing factor being the first choice for policy
groups
I and
2 and
the
second
choice
for policy
group
3.
Teacher Belief was the second most important factor being the
first
choice
for policy
group
3 and the
second
choice
for
73
policy group I.
District Policy was the third most important
factor being the third choice for policy group I.
These findings led to several conclusions.
First of all,
the majority of the teachers in this study did not employ a
rational, prescribed model of decision making.
Shavelson and
Stern (1981) described the rational model as
(I) specifying
objectives, (2) specifying student entry levels, (3) selecting
and organizing activities to move students from entry level
skills to objectives, and (4) evaluating outcomes to improve
planning.
According to this model, teachers would make their
preactive
content
decisions
based,
first
of
all,
on
the
factors of District Policy and/or Teacher Belief (specifying
objectives)
student
policy
and
entry
then
on
levels).
Student
Only policy
group, prioritized
order:
Teacher
Achievement
Achievement
Belief
the
group
influencing
(objectives)
(specifying
3,
the
smallest
factors
in that
followed
by
Student
(student entry levels).
Secondly, the majority of teachers in this study did not
employ the decision-making policy described by Zahorik (1974) .
He
found
preactive
that
most
content
of
the
decisions
range and particulars
teachers
on
the
in
his
question,
study
"What
based
is the
of the subject matter to be taught?"
This question was one of the ingredients of the influencing
factor of Teacher Belief.
in this
factor,
Although none of the participants
study used Teacher Belief
participants
as the only
influencing
in policy group 3 did use
it as their
74
most
important
influencing
factor
supported
by
Student
teacher preactive
content
Achievement.
Instead,
the
description
of
decision making provided by this study might very well supply
substantiation for the more accurate description of teacher
making requested by Duffy and Ball
(1986).
Duffy contended
that teachers began their preactive content decision making
with an assessment of student achievement.
findings
of
this
study,
a
third
According to thq
conclusion
was
that
the
majority of teachers do make their preactive content decisions
by beginning with an assessment of student achievement rather
than
with
school
an
assessment
district
policy groups
of
those
of
objectives
or a teacher’s belief
as
provided by
system.
Two
of the
(groups I and 2) followed this pattern.
groups
chose
Student
Achievement
as
the
Each
its
most
influential factor.
A fourth conclusion which might be construed from these
findings
service
is
and
positively
stemmed
that
teachers
district
affect
from
will
policy
student
the
be
which
most
responsive
can be
This
influence
inr-
demonstrated
achievement.
prominent
to
of
to
conclusion
the
Student
Achievement factor in all three policy groups.
Teachers were
willing
changes
to
make
content
changes
when
thcjse
were
perceived to positively affect student achievement.
In this researcher's opinion, a fifth conclusion related
to the Student
Achievement
factor was
that
the qualify of
75
student achievement information upon which teachers base their
content decisions becomes very important.
teachers ’ individual
their
school’s
student
and
school-wide
The
accuracy of
classroom assessments,
assessments,
district’s district-wide assessments
and
of
is crucial.
of
their
Likewise,
the thoroughness of assessment reporting is essential on the
school and district level.
achievement
across
and
Also, the consistency of student
among
curriculum
areas
becomes, of
interest.
The
finding
influential
that
factor
Teacher
led to the
.
Belief
was
the
second
most
conclusion that teachers are
•
willing to suspend their own preferences for topics within e
subject
area
in
favor
of
student
achievement
information.
Nevertheless, beliefs about the subject area such as whether
or not teachers enjoy various topics within a subject area,
whether or not they view topics as important, and whether or
not
they
believe
students
in
general
or
students
grouped
according to specified criteria can succeed within a subject
area or a topic within a subject area did influence teachers’
preactive content decisions.
of Shavelson’s
(1983)
This finding substantiated one
conclusions— that
teachers
use their
beliefs about education as an attention-focusing structure.
The
finding
that
District
Policy
was
the
third
most
influential factor led to the conclusion, supported by Floden,
et
al.
(1986) ,
that
district
policy
is
of
notable
but
relatively minimal importance in influencing teacher content
76
decision
making.
Three
possible
causes
for
influence might be suggested by this study.
this
lack
of
(I) The policy
is not articulated clearly enough to be of value.
.(2) The
policy was not sufficiently linked to student achievement to
be
of
perceived
worth.
(3)
The
policy
was
not
enforced
strongly enough to be of consequence.
The
findings
that
Professional
Opinion
and
Community
Pressure were not important influencing factors led to several
conclusions.
First of all, this research has concluded that
middle school teachers
in Montana are not subjected to the
influence of Community Pressure
parts
of
the
Community
country.
Pressure
For
in
like some teachers in other
example, Floden,
Michigan,
et
especially
a l . found
pressure
from
parents of high socioeconomic status, to be of more influence
than Student
Achievement.
It
is possible
to
several possible reasons for this difference.
speculate
on.
One reason for
this variation in results might be that teachers and community
members in Montana agree on the content to be taught— -perhaps
because Montanans tend to be a more homogeneous group than is
found in other locations.
Or, because of the small size of
most Montanan communities, teachers might exercise more of an
influence on community opinion about subject area content than
in
larger
communities
where
the
teaching
staff makes
smaller percentage of the total population.
up
a
Another reason
for lack of pressure might be that even though factions of a
Montana
community might
not
agree
with
content
decisions,
77
there is not a tradition of or organization for challenging
those decisions.
of
this
factor
A fourth reason for the lack of influence
might
be
that
school
boards
and
district
administrations view— as part of their job— the support and
protection of their teachers’ content decisions and do a good
job of supporting and protecting their staffs.
A fifth reason
for this lack might be that the voting population in Montana
districts
does
a
good
job
of
electing
board
members
who
represent their content views, the board does a good job of
hiring
administrators
administrators
do
who
represent
those
vie w s , and
a good job of hiring teachers
who
the
enact
those views.
Secondly,
making
content
these
findings
teachers
follow a
decisions.
that
This
teachers
"closed door"
researcher
are
not
policy when
concluded
influenced
professional opinion when making content decisions.
do not communicate about their content decisions.
share the responsibility with their peers
decisions.
from
by
Teachers
They do not
for making those
They make their own individual decisions based on
their own individual experiences.
Peer coaching has not made
in-roads into Montana as far as content decision making goes.
Thirdly,
literature
leaders,
decisions.
despite
the
stresses
the
principals
do
The
principal
fact
that
principal
not
as
influence
either
as
effective
the
schools
instructional
teacher
representative
content
of
the
district and its policy or as instructional expert is not an
78
important
influence.
conclusion
in their
Floden,
study:
effective instructional
et
al.
principals
reached
were
this
not
same
providing
leadership in the content area.
As
in this study, Floden, et a l . found Professional Opinion to
be of little influence.
Fourthly, the relative unimportance, of district policy,
community pressure, and professional
opinion
indicate
that
teachers use a- "bottom up" rather than, a "top down" approach
to decision making.
They rely on their own
evaluation of
student achievement and their own internal experience of the
subject area to make their content decisions.
rely
on
"higher"
authority
either
in
the
They do not
form
of
expert
knowledge or bureaucratiye pow e r .
Finally,
this
researcher
concluded that
teachers will
respond to change initiatives and in-service which are based
on a "bottom up" teacher originated and organized approach
more positively than a "top down" authority—based approach.
Teachers
do
not
respond
to
district
policy,
professional
opinion, or community pressure.
A third purpose of this
study was to begin to explore
what effect, if any, certain demographic characteristics had
on the
participants'
rankings
of
the
influencing
factors.
This study suggested some tentative conclusions.
For example, teachers in medium large districts (49,99920,000)
were most
likely to use a multi-factor approach to
preactive content decision making and least likely to use a
79
single-factor or dual-factor approach when compared to other
district-size demographic divisions.
The factor of District
Policy was an important factor to participants from districts
in
the
49,999-20,000
explanation
for
demographic
these
division.
participants'
One
possible
on
District
emphasis
Policy could be that teachers in districts of this size were
more
susceptible
teachers
to
the
influence
in larger districts.
of District
Policy
Because there were
than
fewer of
them, these teachers might fee I themselves to be more easily
monitored
by
administration
than
teachers
from
larger
districts.
Al s o , participants in districts of this size might
have been more susceptible to the influence of District Policy
than
teachers
districts
in
smaller
of this
size,
districts.
It
could
be
that
in
there was a strong district policy
while in smaller districts the policy was weaker.
On the other hand, teachers in large districts (50,000+)
were most likely to use a single-factor approach to preactive
content decision making and least likely to use a multi-factor
approach
when
divisions.
compared
to
other
district
demographic
Teachers in the largest district size demographic
division were more willing than teachers
size
size
divisions
to
determining factor.
rely
on
Student
in other district
Achievement
as
their
Perhaps, in this size district, the size
of the teaching staff modified the impact of district policy
on individual teachers.
Teachers in this size district might
be able to avoid close scrutiny regarding content decisions
80
and, therefore, might be able to make those decisions based
on other factors.
Teachers
in medium small districts
(19,999-5,000) were
most likely to use a dual-factor approach to content decision
making.
In other words, teachers in districts of 19,999-5,000
were most likely to rely on Student Achievement and Teacher
Belief
together
in making their
content
decisions.
It
is
possible that in this size district, district policy was not
an influence because it was not articulated strongly enough
or sufficiently related to student achievement to influence
teachers.
Perhaps administrators in this size district left
content decisions to their staffs either because of lack of
time or interest or expertise.
In
the
demographic
category
of
years
of
experience,
teachers with the medium largest number of years of experience
(14-10 years) were most likely to base their content decision
making on a multi-factor approach including District Policy.
They were least likely to use a single-factor or dual-factor
approach
when
compared
to
teachers
experience demographic divisions.
number
of years
other
years
of
There were several possible
explanations for this conclusion.
this
in the
Perhaps more teachers of
of experience
taught
in medium
large
districts where the impact of District Policy seemed to have
been
the
solidified
greatest.
their
More
own beliefs
likely,
about
these
their
teachers
subject
area
have,
and
their own knowledge of student achievement within that area.
81
They were more willing to expand the factors which influenced
them to consider another factor like District Policy.
On the
other hand, teachers with the most experience (15+ years) had
perhaps? included District Policy in their content decisions
for a time (during their tenth through fourteenth years) and
then excluded it because they found it to be of minimal value.
Teachers
experience
smallest number
of years
of
(9-4 years) were most likely to use only Student
Achievement
compared
with the medium
and
to
least
likely
participants
to
in
use
the
divisions of years of experience.
District
remaining
Policy
when
demographic
Teachers with this number
of years of experience might possibly have experimented with
both Teacher Belief
and Student Achievement
as non-tenured
teachers, but decided to focus on Student Achievement as their
primary influence.
implement
the
Learning how to measure, interpret, and
results
of
student
achievement
might
have
sufficiently occupied these teachers.
Teachers with the least experience (3- years) were most
likely to rely on both Student Achievement and Teacher Belief
to make content decision.
Teachers with this number of years
of experience— beginning teachers— might be exploring their
own responses to their subject area and, therefore, might be
more
willing
to
decision approach.
include
Teacher
Belief
in
their
content
On the other hand, it was interesting to
this researcher that as non-tenured teachers they were not
more interested in District Policy.
One might speculate that
82
this
lack of
were
not
service
interest could result
encouraged to
training.
consider
Or,
perhaps
from the fact that they
that
factor
they were
in their pre­
preoccupied
with
trying to incorporate student achievement and teacher belief
information into their decision making and did not have the
energy to also work with district policy information. A third
possible reason might be that
school
districts do not do a
good job of imparting district policy information to teachers.
In the years of education demographic category> teachers
with the second fewest years of education
(M.A.) were most
likely to want to base their content decisions on multiple
factors including District Policy and Teacher Belief as well
as Student Achievement and least likely to want to base their
decisions on one factor, Student Achievement, when compared
to teachers in the other divisions of that category.
teachers
in this
encounter
with
Perhaps
division might be reflecting their recent
institutions
of
teacher
training.
Perhaps
earning their M.A.s influenced them to broaden their content
decision-making b a s e .
Teachers with the largest number of years of education
(Ed.D.) were most likely to use Student Achievement as their
most
influential
factor
and
least
likely
to
rely
on
combination of Student Achievement and Teacher Belief.
they chose
combine all
District
to use
a combination of
It
might
be
If
factors, they chose to
three— Student Achievement, Teacher Belief,
Policy.
a
that
these
teachers
and
were
83
influenced both by
their
experience
and
education
in this
choice of influencing factors.
Teachers
education
with
the
(M.A.+30)
second
were
largest
most
number
likely
of
to
years
use
of
Student
Achievement, Teacher Belief, and District Policy when compared,
with teachers in other years of education divisions. Teachers
in this demographic division might again have been reflecting
their education.
along
with
Their willingness,to include Teacher Belief
Student
Achievement
might
have
reflected
an
awareness of their own autonomy in the decision-making process
and an awareness of the lack of influence of District Policy.
Teachers
in
teachers
with
positions.
up"
this
category
no
are
most
aspirations
to
likely
be
in
to
be
career
administrative
They would be most likely to reflect a "bottom-
approach
to
decision
making.
Their
unwillingness
to
include District Policy in their approach might reflect an
anti-administration bias not uncommon to career teachers.
In the demographic category of subject taught, teachers
in the demographic divisions of Music, Home Be, and P.E. were
most
likely
to
include
District
Policy
in
their
content
decisions when compared to other teachers in this demographic
category.
their
These
subject
departments
teachers
areas.
are
possible
perhaps
In
at
reflected
larger
the
the
schools,
middle
school
nature
where
pf
such
level,
the
departments function with coordinators and a strong districtlevel
content
policy.
Therefore,
teachers
in
such
areas
84
contend
with
teachers
in
stronger
subject
district
areas
policy, influences
with
more
teachers
cohesive district-1eve I influence.
than
and
a
do
less
'
Teachers in the demographic division of Shop were most
likely to
rely
on
Teacher Belief.
P.E.
to
the
factors
of
Student
Achievement
and
They were less likely than A r t , Home .Ec, and
rely on District
Policy. . These
conclusions
might
result from the nature of the Shop teacher— independent— and
from
the
lack
of
district
level
coordinators
and
strong
district level policy.
Teachers
in
the
demographic
division
of
English were
least likely to use District Policy in their content decision
making.
This
researcher
speculated
that
perhaps
this
conclusion resulted from the "liberal arts" orientation of the
English
teacher
which
can
include
an
"anti-establishment"
aspect.
Teachers
in the demographic division of Art were most
likely to rely on Student Achievement as their sole basis for
content
decision
making.
Again,
these
teachers
might
be
reflecting the nature of their subject— one in which student
achievement
is obvious
in each student’s product.
Teacher
response to individual student achievement is much easier in
the smaller, product-oriented class typical of art.
85
Recommendations for Action
In reviewing the data and conclusions relating to this
study, the following recommendations for action evolved.
First of all, from the high correlation (.6794) presept
at stage 107 of the JAN analysis, it is apparent that teachers
do use policies when making preactive content decisions and
that their policies are quite consistent.
Since— as Shavelson
(1983) contended— teachers are not aware of their use of such
policies, it is recommended that individual teachers become
aware of the policies which they use.
Becoming aware of the
policies they use involves becoming aware of the factors which
influence
teachers'
preactive
rankings of those factors.
content
decisions
and
the
Becoming aware of their policies
allows teachers to choose to continue to use those policies,
td modify them, or to discard them.
Teachers can become aware
of their content decision-making policies by discussing their
decisions
and
the
bases
for
their
decisions
with
other
teachers, by taking workshops and classes on content decision
making, and by reading literature on that topic.
It is further recommended that not only should teachers
become
aware
policies,
but
of
their
school
preactive
districts
content
and
decision-making
teacher-training
institutions should encourage them to become aware of those
policies.
Inservice and preservice training should be used
to encourage that awareness.
86
School
which
are
policy was
districts need to become
being
used
not
used as
participants
in
this
school teachers,
by
their
an
aware of the policies
employees.
important
study— and,
Since
influencing
by
inference
district
factor by
many middle
an investigation into the cause(s) of this,
lack of use might be warranted.
Particularly districts of
+50,000 should investigate the influence of their curriculum
policies on the actual teacher going on in the classroom since
teachers in this demographic division seemed inclined not to
use
District
Likewise,
Policy
as
districts
important
might
decisions
of
teachers;
their Ed.Ds
art,
special
and
their
an
most
wish
to
influencing
monitor
experienced
and
and their MAs+15;
education
teachers.
least
the
factor.
content
experienced
and their English,
Teachers
in
these
divisions manifested a more than expected unwillingness to use
District Policy as an influencing factor.
If it is important
to school districts that their curriculum policies be used,
they might want to find out if, in fact, they are and if not,
why not.
The result of such an investigation might be a more
well-thought-out, clearly articulated, and enforceable content
policy.
This
recommendation presupposes
that
school
districts
need to make certain that their content policies are based on
the most current and defensible research and recommendations
of experts
about
in the relevant
content
concerns
fields.
then
becomes
Becoming knowledgeable
imperative
for
such
87
districts.
opinion
It is recommended that districts use professional
in
the
articulated,
formulation
and
of
enforceable
well-thought-out,
policy
clearly
regarding
content
decisions.
Districts
formulating
Community
should
also
curriculum
Pressure
and
was
consider
community
curriculum
not
one
of
desires
policies.
the
in
While
most . important
influencing factors as perceived by the participants of this
study,
districts
should consider the
district-wide content decisions.
community when making
Individual teachers should
be protected by district policy from the weight of community
pressure.
Finally, with regard to the problem of this study, it is
recommended
that
institutions
responsible
for
preparing
teachers for employment acknowledge the existence of policies
used in making preactive content decisions and help potential
teachers to become aware of their own policies.
Furthermore,
in accordance with research and expert opinion,
encourage
potential
inappropriate
teachers
policies
and
to
to
change
they should
or
formulate
and
discard
act
upon
appropriate ones.
The
among
fact
the
that
Professional
influencing
participants
should
be
factors
of
Opinion
for
concern
is
a distant
most
of
to
all
this
last
study’s
involved
in
education. Despite a wealth of research available for teacfter
u s e , participants in this study seemed unwilling to rely oh
districts, and
.
teacher
,
;
training
-
•
*
•
institutions
.
■■■■■"
;
need
.
■
to
"
;
take
• "
..
responsibility for encouraging knowledge of hnd reliance oh
applicable
research
and
professional.
recommendations.
Teachers can do this by reading professional
attending
workshops
and
classes
in
literature arid
appropriate
areas.
Districts can do this by in-service training, providing money
and time for workshops, classes, and degrees, and providing
teachers
with
appropriate
literature.
Teacher
training
institutions can do this by providing teachers with sources
of
professional
opinion
and
research,
directing
potential
teachers to use the literature, and teaching them how to use
the literature.
t ‘
Recommendations for Further Action
Recommendations for further research growing out of this
study
fall
policies
into
used
decisions,
by
areas:
teachers
when
further
making
research
preactive
into
the
content
further research into the factors which influence
such decisions,
between
three
and further research
preactive
content
decision
into the. relationship
making
and
teacher
effectiveness.
Different types of research— other than JAN studies— nesd
to be
attempted.
preactive
content
Teachers need to be studied making actual
decisions
in actual
teaching
situations.
Policies used in actual preactive teaching situations needed
to be ascertained, described, and compared to results from JAN
89
studies.
Certainly,
effects
of
more
research
demographic
is
needed
categories
on
to
determine
preactive
of district,
level
of
the
content
decision policies.
Size
education,
years of experience,
and subject taught all require further
research.
Further research into the policies used by teachers when
making preactive content decisions should investigate teachers
other
than middle
school
teachers.
Floden,
et
investigated sixth grade teachers in Michigan.
of elementary teachers
and high school
al.
(1986)
Other levels
teachers need to be
investigated.
Likewise, teachers in locations other than Montana need
to be investigated.
limited
to
Since the sample used for this study was
districts
participants
from
in
large
metropolitan areas.
Montana,
districts
it
such
did
as
not
those
contain
found
in
Within Montana, more teachers need to be
investigated in all the divisions of the demographic category
of District Size except 4,999-.
to
More participants from these
divisions
are
needed
validate
Therefore,
the
category of district
this
study's
size
as
results.
it relates
to
content decisions definitely requires further research.
Likewise, the categories of years of experience and level
of
education
do
not
contain
enough
participants
in
all
categories to warrant generalizations beyond the population
of
this
study.
Particularly
the
divisions
of
Years
of
90
Experience 14-10,
Education
9-4, and 3- and the divisions of Years of
Ed.D.,
participants
MA+30,
to warrant
and
MA
do
not
generalizations
fall into these divisions.
contain
about
enough
teachers
who
More research needs to be done on
teachers within each of these divisions.
Finally,
more
the
research.
category of
Again,
subject
because
area taught
of the
requires
few participants
several of the divisions, generalizations are difficult.
in
More
research definitely needs to be done to determine the effect
of subject area taught on content decisions.
There are several recommendations for further research
into
the
factors
decisions.
First
influencing
preactive
content
of all, the factors themselves need to be
more fully investigated.
example,
teacher
contains
The factor of district policy, for
several
criteria:
prescriptiveness,
consistency, authority, and power (Floden et al., 1986).
The
effects of variations of these criteria within the factor of
district policy
further
on preactive
investigated.
Ways
content
to
decisions
increase
the
need
to be
influence
of
district policy on teacher preactive content decision making
should be investigated.
The factor of Teacher Belief needs to be investigated in
order to determine the ranking(s) of the criteria which make
up
Teacher
Belief.
Such
an
investigation
might
also
investigate how it is that teacher belief is formed and how
it can best be changed when change is desired.
91
Because
important
Student
Achievement
influencing
investigated.
factor,
seemed
it
to
be
should
be
such
an
intensely
Actual observations of teachers should occur
in order to determine how they measure student achievement and
how the measurement of that achievement is actually manifested
in content decisions.
Which of the criteria of the Student
Achievement factor are most important in determining content
decision would be an important question to answer.
The
bears
relative
further
within
the
of
investigation.
factor
investigated.
questions
unimportance
of
importance— of
the
each
of
A g a i n , the
Professional
Questions
about
the Professional
that
need
relative
the
various
Opinion
to
Opinion
be
criteria
need
studied
importance— or
criteria, the
to
be
include
lack
of
desirability
of
increasing the importance of each of the criteria, and ways
to increase the importance of those criteria deemed desirable.
For example, although school principals are supposed to be the
instructional
leaders
for
their
schools,
teachers
in this
study did not seem to rely on professional opinion— including
that
of
their
instructional
students.
principals’— for
decision
Although
of
what
teachers
making
material
are being
the
to
most
teach
encouraged
important
to
what
to work
together, especially at the middle school level where teaming
is
recommended,
Professional
opinions
Opinion— seemed
of
to
peers— one
be
viewed
criteria
as
of
unimportant.
Certainly, the apparent lack of use of research and literature
92
needs further investigation.
Different combinations of influencing factors should be
researched.
studies.
Factors
Also,
the
can
be
factors
deleted
could be
or
added
to
future
reduced to essential
criteria, and those criteria could become factors for future
studies.
Further research should be done on relationship between
policies used to make preactive content decisions and teacher
effectiveness.
For example, a follow-up study could be done
on the sample used in this study to determine the correlation
between the policy held by each teacher and the effectiveness
of
that
teacher
as
measured
by
a
standard
of
student
achievement.
In conclusion, the relationship between preactive content
decisions
and teacher effectiveness
achievement
research.
needs
further
as measured by student
clarification
policies
are
used?
teachers’ preactive
How
train
content
potential
decisions?
investigated
further
can
school
decision-making
improve student achievement?
to
further
How are effective decisions, i.e. decisions leading
to acceptable student achievement, reached?
what
through
districts
processes
in
affect
order
to
What are the most effective ways
teachers
These
In other words,
to
make
questions
through more
appropriate
and others
JAN
studies
preactive
need to be
and
through
other types of research.
All of the above suggestions for further research have
93
the
potential
information
teachers.
of
adding
researchers
As
researchers
student achievement
to
are
the
growing
gathering
become
more
and at relating
storehouse
about
adept
student
of
effective
at
measuring
achievement
to
teacher behavior, they will become more able to describe the
practices which lead to high student achievement.
Certainly,
the
thinking—
investigation
particularly
content
teacher
decision
description.
of
the
behavior
thinking
making— will
This
study
has
as
add
it
of
teacher
relates
to
substantially
attempted
to
add
preactive
to
that
to
that
description by adding to the understanding of the factors that
influence teacher preactive content decisions.
94
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102
APPENDICES
103
APPENDIX A
JAN TABLES
104
Table
16
Profile Ratings:
Mean and Standard Deviations of each Rater
Rater
Mean
Standard Deviation
I
2
3
4
5
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
44.40
62.76
65.20
50.70
61.30
41.60
39.70
44.00
39.38
57.62
47.60
48.00
57.06
54.50
40.60
67.30
61.14
70.36
48.00
48.34
42.60
66.40
61.28
48.30
58.44
49.70
55.50
43.50
51.40
32.18
70.16
49.42
57.42
55.54
47.08
61.10
39.10
51.74
36.20
27.20
46.20
28.96
36.45
26.49
15.49
26.27
19.99
24.12
24.72
23.09
26.05
23.58
21.40
24.55
25.91
25.11
27.66
18.34
25.31
27.09
2 3.87
25.14
28.33
30.58
25.68
26.68
20.37
31.27
15.57
17.32
18.95
22.52
20.19
24.06
33.17
32.40
21.82
23.66
17.86
25.91
16.95
20.43
105
Table 16 (continued)
Profile; Ratings:
Mean and Standard Deviations of each Rater
i
Rater
Mean
Standard Deviation
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
60.34
53.88
59.78
25.04
45.68
52.28
53.96
63.20
56.60
51.30
47.64
42.82
53.36
44.60
49.38
40.90
51.50
51.96
41.96
51.24
29.94
58.46
59.06
41.78
48.22
59.16
41.60
55.70
39.90
37.34
59.66
39.20
57.00
54.50
46.40
52.30
50.40
41.80
48.60
40.40
44.30
50.74
32.58
29.09
29.63
13.21
22.35
25.39
21.56
23.93
27.88
25.43
27.25
28.97
32.86
31.11
20.21
27.12
22.90
24.08
21.90
16.38
24.14
24.51
25.99
39.06
22.05
26.59
24.15
18.11
14.78
32.24
15.40
22.48
18.49
22.03
23.17
20.89
19.18
30.75
23.50
19.69
25.57
29.55
106
Table
16
(continued)
Profile Ratings:
Mean and Standard Deviations of each Rater
Rater
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
' Mean
45.86
67.18
75.92
32.76
39.78
43.46
53.50
45.47
43.30
51.68
68.72
29.70
37.50
48.60
53.50
56.70
40.20
42.76
50.56
50.52
56.40
39.52
35.16
Standard Deviation
23.31
30.27
34.40
28.10
21.13
22.11
19.42
30.88
22.37
25.88
21.83
23.68
23.22
20.32
23.55
23.51
23.19
26.38
20.89
27.08
24.10
22.25
25.39
107
Table
17
Co rr el a ti o ns B et we e n the Profile Ratings and the
Change Facto rs for P a r t i c i p a t i n g Te ac her s
Rater
D.P.
I
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
.29
30
31
32
33
34
35
36
37
38
39
-.12
.09
.26
.17
.02
.53
.68
.36
.25
.06
.17
.80
.27
-.14
.26
.16
.28
.22
.42
.25
.14
.38
-.12
.29
.00
.32
-. 11
.02
.50
.25
.42
.59
.25
.25
.15
-. 12
.17
.26
.06
T .B .
— .36
-. 19
.07
.27
.43
-.39
-. 15
— .26
-.09
-.12
-.22
-.20
-.47
-.12
-. 46
-. 11
-.50
-.53
-.01
.16
-.51
-.09
-.30
-.08
.79
-.34
.79
-.16
-.01
.43
— .66
-.27
-.34
-.72
-.57
-.01
— .31
-.57
.18
CO
>
Change Factors
-.69
-.82
-.51
-. 64
.72
-.35
.05
-.55
— .36
-.46
-.80
-.26
-.67
-.22
-.54
-.54
— .62
-.39
-. 38
-.76
-.39
-.73
-.80
— .68
.41
-. 66
.47
-.90
-.42
.15
.09
-.10
-.64
-.31
-.71
-.94
— .64
-.58
— .62
P.0.
-.09
.04
.26
.22
.04
.35
.21
-.04
.40
-.23
.13
.21
.15
.00
.15
.16
.16
.15
.09
.20
.29
-.08
.01
.04
-.05
.02
.03
.01
.28
.12
.20
.09
.23
.11
.09
.12
.46
.11
.41
C.P.
.22
.00
.22
.38
-.15
.05
.30
.34
.11
.44
.11
.16
.18
.51
.26
.40
.18
.23
.58
.26
.00
.12
.33
.14
,00
.21
-.04
.06
.15
.56
.10
.40
.24
.32
.07
.06
.06
.27
.35
108
Table
17
(continued)
Co rr el at ion s B et w e e n the P r ofi le Ratin gs and the
Change Factors for P a r t i c i p a t i n g Teachers
Change Factors
D.P.
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
,64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
.03
.21
.14
-.07
.00
-.03
-. 14
.00
-.10
.48
.05
.10
.12
.41
-.03
.22
-.07
.05
.40
.37
.62
.25
.57
.06
.26
.00
-. 12
— .08
.15
.68
-.01
.48
-.19
.28
.12
.20
.13
.46
.19
T .B .
-.06
-.11
.77
-.14
-.08
-.08
-.17
-.58
.77
-.41
-.07
-.22
-.28
.14
-.76
-.14
'.05
-.77
-. 46
-.46
-.04
.15
.53
-.73
.21
.30
-.15
-.25
-.29
.09
.66
— .25
-.63
— .36
.00
.46
-.71
-.21
— .63
CO
>
Rater
-.76
-.70
.25
-.84
-.93
-.96
-.52
-.34
.35
-.23
-.90
-.79
-.46
-.43
— .44
-.85
— .50
-.53
-.41
.22
-.34
.10
.59
-.43
.10
.88
-.71
-.70
-.81
-.26
'.36
.31
-.25
-.35
-.03
-.20
-.46
-.43
.00
P.0.
-.23
.01
.00
.04
.01
.03
-.34
-.22
-.02
.14
-.03
.04
.07
.20
.02
.10
.06
.06
.08
-.18
-.10
.20
.02
— .05
-.09
.05
-.12
-.31
.10
-.03
.17
.09
.09
.32
-. 13
.50
.09
.26
.15
C.P.
.15
-.05
-.04
-. 11
-.02
.01
.18
-.03
-.02
.23
.03
.17
.27
.21
.10
.26
-.16
.05
.40
-. 11
.48
.2 2
-.01
.09
.01
.04
.07
.11
.11
.24
-.07
.23
.13
.42
.81
.10
.03
-.01
.37
109
Table
17
(continued)
Co r r e la ti o ns B e t w e e n the Profi le R a tin gs and the
Change Facto rs for P a r t i c i p a t i n g Te achers
Change Factors
Rater
D .P .
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
.03
.23
.28
.36
.02
.00
.48
.05
.04
.08
.11
-. 14
.32
.07
-.02
.56
.57
-.28
.52
-. 15
.03
-.29
.17
.24
.46
.02
.05
.27
-. 15
T.B.
-.42
.21
-.64
-.39
-.40
-.17
-.30
-.32
-.12
.17
.28
-.12
-.46
-.53
-.73
.03
.31
— .03
-.02
-.61
-.09
-.11
-.40
.22
— .49
.20
— .64
— .35
-.08
S.A.
-.67
.01
-.27
— .26
-.78
-.91
-.54
— .62
-.83
-.43
-.61
-.69
-.60
-.78
-.11
— .65
.09
-.78
-.41
-.45
-.51
-.51
-.48
.74
-.45
.00
-.68
-.58
-.81
P.0.
.38
.14
.22
.31
.05
.01
.05
-.08
.03
.49
.38
— .20
.21
.01
-.23
-.06
.03
.03
.31
-.09
.02
-.07
.16
-.13
.26
.16
.19
.15
- .28
C.P.
.22
.18
.15
.31
— .02
-.01
.22
.03
-.03
.01
.09
.01
.33
— .03
.01
-.01
.36
-.03
.26
.01
.14
.13
.42
-.13
.28
-.01
.16
-.03
-.04
HO
Table
18
Stages of the JAN An alysis Proc ed ure
Stage
I
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Number of
Policies
R2
107
106
105
104
103
102
101
100
99
98
97
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81
80
79
78
77
76
75
74
73
72
71
70
69
68
67
66
.6794
.6794
.6793
.6792
.6791
.6790
.6789
.6787
.6786
.6784
.6783
.6781
.6779
.6777
.6774
.6772
.6769
.6767
.6764
.6761
.6757
.6753
.6750
.6746
.6742
.6737
.6733
.6729
.6724
.6719
.6714
.6709
.6703.
.6698
.6692
.6686
.6681
.6675
.6669
.6663
.6657
.6650
Successive
Rj Drop
.0000
.0000
.0001
.0001
.0001
.0001
.0001
,0001
.0001
,0002
.0002
.0002
.0002
.0002
.0002
.0002
.0003
.0003
.0003
.0003
.0004
.0004
.0004
.0004
.0004
.0004
.0004
.0004
.0005
.0005
.0005
.0005
.0005
.0005
.0006
.0006
.0006
.0006
.0006
.0006
.0006
.0006
Accumulated
Ri Drop
.0000
.0000
.0001
.0003
.0004 J
.0005
.0006
.0007
.0009
.0010
.0012
.0013
.0015
.0018
.0020
.0022
.0025
.0028
.0031
.0034
.0037
.0041
.0045
.0048
.0052
.0057
.0061
.0065
.0070
.0075
.0080
.0086
.0091
.0096
.0102
.0103
.0113
.0119
.0125
.0131
.0138
.0144
Ill
Table
18
(continued)
Stages of the JAN An alysis P r oc ed ure
Stage
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
Number of
Policies
65
64
63
62
61
60
59 .
58
57
56
55
54
53
52
51 .
50
49
48
47
46
45
44
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
28
27
26
25
24
Successive
R2 Drop
R2
.6644
.6637
.6630
.6623
.6616
.6609
.6601
.6593
.6585
.6577
.6568
.6560
.6551
.6541
.6532
.6523
.6513
.6503
.6492
.6481
'.6470
.6458
.6446
.6433
.6419
.6405
.6390
.6376
.6361
.6346
.6331
.6315
.6298
.6281
.6261
.6241
.6219
.6196
.6173
.6149
.6123
.6096
•
.0007
.0007
.0007
.0007
.0007
.0007
.0008
.0008
.0008
.0008
.0008
.0009
.0009
.0009
.0009
.0009
.0010
.0010
.0010
.0011
.0011
.0011
.0012
.0013
.0014
.0014
.0015
.0015
.0015
.0015
.0015
.0016
.0017
.0017
.0020
.0020
.0022
.0022
.0024
.0024
.0026
.0026
Accumulated
R 2 Drop
.0150
.0157
.0164
.0171
.0178
.0185
.0193
.0201
.0209
.0217
.0226
.0234
.0244
.0253
.0262
.0271
.0281
.0291
.0302
.0313
.0324
.0336
.0348
.0361
.0375
.0389
.0404
.0418
.0433
.0448
.0463
.0479
.0496
.0513
.0533
.0553
.0575
.0598
.0621
.0645
.0672
.0698
112
Table
Stages
Stage
Number of
Policies
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
23
22
21
20
19
18
17
16
15
14.
13
12
11
10
9
8
7
6
5
4
3
2
I
I
18
(continued)
of the JAN An alysis Proc ed ure
R2
.6069
.6039
.6008
.5976
.5939
.5901
.5861
.5810
.5758
.5702
.5646
.5580
.5507
.5432
.5332
.5223
.5109
.4949
.4755
.4410
.3914
.3146
.2009
Successive
Rj Drop
.0028
.0029
.0031
.0032
.0037
.0038
.0039
.0051
.0052
.0056
.0056
.0066
.0073
.0075
.0100
.0109
.0114
.0160
.0194
.0344
.0496
.0769
.1137
Accumulated
Ri Drop
.0726
.0755
.0786
.0819
.0855
.0894
.0933
.0984
.1036
.1092
.1149
.1214
.1287
.1362
.1462
.1571
.1685
.1845
.2040
.2384
.2880
.3648
.4785
113
APPENDIX B
LETTERS
114
Sharon Patton
3425 4th Avenue South
Great Falls, MT 59405
January 18, 1988
Charles Strand
Washington School
210 North 9th
Street Miles City, MT 59301
Dear Mr. Strand:
As a doctoral student at Montana State University, I am
conducting a study to determine what factors influence
teachers when they make pre-instructional content decisions
such as what material to teach to which students. A study of
this sort is important to all educators.
Recent research
indicates that content decisions such as those which will be
investigated in this study are one of two variables most
highly correlated with student achievement.
In order to conduct this study, I need your help. I am hoping
that you will be willing to identify the names of the first,
middle, and last teachers from your school’s roster and
distribute to these teachers the enclosed packets.
These
three teachers, which you have randomly selected, will be
asked to participate in this study by taking approximately one
hour of their time to fill out the enclosed survey and
simulation instruments. You are asked to return, within three
days of having received this mailing, the enclosed postcard
indicating your name, the names of the three participating
teachers, the name of your school, its address, and its
telephone number.
Ybur participation in this study is essential to its success.
If you have any questions, please call me collect at (406)
727-9779 after 4:00 p.m.
If I have not heard from you either
by postcard or by phone call within the next week, I will call
you to see if I can assist you in any way.
Thank you.
Your time and effort are really appreciated!
Sincerely,
Shar on Pat ton
115
3425 4th Avenue South
Great Falls, MT 59405
January 18, 1988
Dear Fellow Teacher:
As a doctoral student at Montana State University and a
teacher of seventh grade English at East Junior High School
in Great Falls, Montana, I am conducting a study to determine
what factors influence teachers when they make pre-instructional content decisions such as what material to teach to
which students.
A study of this sort is important to us as
educators
since recent research has
identified content
decisions made by teachers as one of two variables most highly
correlated with student achievement.
I have asked your principal to give you this packet because
I need your help.
I am hoping that you will be willing to
give this important study approximately one hour of your time.
During that h o u r , you are asked to fill out the following
short demographic survey and to respond to 50 simulated
situations. You are then asked to return your survey and
simulation responses to me in an enclosed envelope.
Once I have verified that you have returned your responses to
me, you will be identified by number only.
In that way, your
anonymity will be protected.
As a teacher, I realize how valuable an hour's worth of time
is. I am asking you to spend an hour on this study because I
believe that it is worth that expenditure. Your participation
in this study is essential to its success.
The following page in this packet will more fully explain the
survey and simulation procedure.
If you are interested in
receiving a copy of the results of this study, please check
the appropriate box on the survey form.
If you have any questions,
after 4:00 P.M.
If I have
or by phone within the next
if I can assist you in any
Sincerely,
Sha ro n Pa tt o n
please call me at (406) 727-9779
not heard from you either by mail
seven days, I will call you to see
way.
116
Dear Participant:
)
The attached packet contains a demographic survey and a
simulation instrument. Please fill out the survey by filling
in and checking the appropriate blanks.
Please fill out the
simulation instrument by filling in each rating blank with an
appropriate estimate.
Then place both instruments in an
enclosed envelope and return them to me.
When filling out the simulation instrument, each estimate
you place in a rating blank will indicate the likelihood
you would change the content which you would present to
students.
The situation in which you will be making
content decision is as follows:
that
that
your
this
You have taught a subject for five years. At the end of
your fifth year, you move to a different school district.
Your teaching assignment remains the same as it has been
in the past, i.e. the same subject and the same grade.
You need to decide whether or not you will continue to
teach the same content.
The factors which will affect your decision to change or
not to change your content are district policy, your own
beliefs, student achievement, professional opinion, and
community pressure.
Each of these five, influencing
factors has been given a numerical rating for each of the
50 simulations.
That rating indicates the strength of
that factor for that simulation. These numerical ratings
can be interpreted in the following manner:
1.
District Policy - District policy which provides
a strong impetus for changing your content has
been given a rating of 70 to 100 with 100 being
the strongest rating. District policy receiving
a strong rating might contain any or all of
these characteristics.
It might mandate that
teachers adhere to curriculum guides prepared
by the district. It might mandate that teachers
teach from designated texts and be on specific
pages on specific days.
It might mandate
district-wide testing and comparison of test
scores by classroom and by school at the end of
each semester.
District policy which provides
a weak impetus for changing your content has
been given a rating of 30 to I. District policy
receiving a weak rating might contain any or all
of these characteristics:
suggested goals and
tests and an absence of curriculum guides.
2.
Teacher Beliefs - Teacher beliefs are your
beliefs based on your past experience. Beliefs
117
which provide a strong impetus for retaining
your content have been given ratings of 70 to
100.
They might be based on any or all of the
following: a complete knowledge of your subject
area, an unshakable conviction that your subject
area and each topic within that subject area
which you cover are important to students, and
ah expectation that students can succeed with
your content.
Beliefs which provide a weak
impetus for
retaining your content have been
given ratings of 30 to I. They might be based
on any or all of the following:
a shaky
knowledge of your subject area, a concern about
the importance of your subject area and/or the
topics which you cover within that area to your
students, and an expectation that many of your
students might not succeed with your content.
3.
Student Achievement - Student achievement refers
to the achievement of students which you have
taught. Achieve-ment which provides a strong
impetus for retaining your content has been
given a rating of 70 to 100. It might have been
measured by any or all of the following means:
regularly administered formative and summative
tests, anecdotal reports, diagnostic tests,
student verbal responses, homework and classroom
assignments, comments from parents, and teacher
observation. Student achievement which provides
a weak impetus for retaining your content has
been given a rating of 30 to I.
It might have
been measured by any or all of the following
means: summative tests only or formative tests
only.
Once measured, such achievement was not
used as a basis for teacher decision making.
Instead, other bases such as curriculum guides
were used.
4.
Professional Opinion - Professional opinion
which provides a strong impetus for changing
your content has been given a rating of 70 to
100.
Professional opinion receiving a strong
rating might contain any or all of the following
characteristics:
broad-based support from the
teachers and principal at your new school, your
new curriculum director, and experts in your
subject area; a prescriptive statement of what
each teacher’s content should be; and rewards
and sanctions for compliance and non-compliance.
Professional
opinion which provides a weak
impetus for changing your
content has been
given a rating of 30 to I. Such opinion might
118
contain
any
or
all
of
the
following
characteristics : conflicts among teachers, the
principal, the curriculum director, and experts ;
vagueness; and an absence of sanctions and
rewards.
5.
Community Pressure - Community pressure which
provides a strong impetus for changing your
content has been given a rating of 70 to 100.
It might contain any or all of the following
characteristics:
broad-based support from all
elements in your new community, specificity, and
power backed by the threat of dismissal or law
suit for lack of compliance. Community pressure
which provides a weak impetus for changing your
content has been given a rating of 30 to I. It
might be fragmented, generalized, and lacking
in power.
Here are two sample simulations.
Hopefully, after
reading the following samples and, perhaps, re-reading
the above interpreta-tions of the numerical ratings for
each of the five influencing factors, you will be able
to provide your own numerical estimate for each of the
50 simulations in the simulation instrument.
Sample Simulation #1
Influencing Factor
Rating
Rating Scale
District Policy
20
100 High Likelihood that
you would change
75 your content
Teacher Belief
60
Student Achievement
40
50
Professional Opinion
10
25
Community Pressure
10
Your rating:
15
0 Low likelihood that
you would change
your content
Possible Interpretation #1
I would estimate my likelihood of changing my content as
low— perhaps about 15 percent.
My rationale for my
119
unwillingness to change might go as follows: my beliefs
are strong; my past experience with student achievement
indicates that students do well with my content; district
policy, professional opinion, and community pressure are
weak. Therefore, I would have little problem in deciding
to retain my content.
Sample Simulation #2
Influencing Factor
Rating
Rating Scale
District Policy
20
Teacher Belief
76
Student Achievement
66
50
3
25
Professional Opinion
Community Pressure
24
Your rating:
45
100 High likelihood that
you would change
75 your content
0 Low likelihood that
you would change
your content
Possible Interpretation #2
I would estimate my likelihood of changing my content as
average.
My rationale for my indecision might go as
follows:
my beliefs are strong; my past experience
indicates that students do well with my content; district
policy would be a strong factor for changing my content;
professional opinion and community pressure are weak
factors. Therefore, I would have a difficult time making
my decision.
I would lean toward not changing my
content.
Your ratings might very well differ from mine.
In fact,
I hope that they do.
We will not all weight the five
influencing factors in the same manner. For example, in
the second simulation you might not have any problem
making a decision either because you do not consider
district policy as an important factor in your content
decisions or because you believe that district policy
should be the determining factor.
It is this very
difference in the weightings of factors which this study
is attempting to identify.
120
Please continue by filling out the following demographic
survey and the simulation instrument.
When you have
finished, please return the survey and the simulations
to me in the enclosed envelope.
Be sure to give me a
call if you have any questions.
Thank you again for your time and effort.
appreciated!
It is really
121
APPENDIX C
SIMULATIVE INSTRUMENT
122
A SIMULATION OF TEACHER
DECISION MAKING
An Investigation of the Factors Which
Influence Teachers to Try Mastery
Learning in Their Classrooms
Simulative Instrument
123
#_____
Demographic Survey.
Na m e :__________________________________
School:
______________________________
Address:
Size of district:
50,000+
49,000-20,000
19.999- 5,000
4.999Years of experience:
15 +
14-10
9-4
3Education:
Ed.D.
M.A. + 30
M.A.
B. A.
___
Subject Taught:
English
_____
Math
Science
_____
Music
_____
Social Studies
_____
Art
_____
Home Ec
_____
Shop
____
P .E .
Special Ed
_____
Please send me the results of this study.
124
#'
Simulation Instrument
iy.encing_Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating
30
36
__46
__ 32
___ 2
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Rating
.
___I
36
__12
77
___ 1_
R ating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
R ating
79
93
__30
___ 4
__61
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
%D&lBenc^ng_Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
lBf.lM6nclng_Fa.ctor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
Rat ing Rating Scale
20___ 100 High likelihood that you
68___ 75 would change your content
76___ 50
65___ 25
65
0 Low likelihood that you
would change your content
125
#
Simulation Instrument
Influencing Factor
Rating
District Policy
73__
Teacher Belief
12__
Student Achievement __25__
Professional O p i n i o n ___ I__
Community Pressure
__24__
Rating Scale
100 High likelihood that you
75 would change your content
50 .
25
0 Low likelihood that you
would change your content
Your rating:
Rating
Influencing Factor
__74__
District Policy
__49__
Teacher Belief
Student Achievement
0
Professional Opinion
35
Community Pressure
98
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
lsf i^enc j^ng_Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating
37
50
___I^
__71
__1^6
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Rating Scale
lSl.Iuenc j^ng_Factor
Rating
District Policy
82___ 100 High likelihood that you
Teacher Belief
46___ 75 would change your content
50
Student Achievement
55
25
Professional Opinion __43
0 Low likelihood that you
Community Pressure
__59
would change your content
Your rating:
____
126
#
Simulation Instrument
ZsZ lM 61iciLng_Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating
65
30
__51
__74
__93
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Rating
_92__
__99__
21
_60__
__22__
Rating_ScaJe
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Rating
29
87
__86
__37
__JJ.
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
Influencing Factor
Rating
Rating Scale
District Policy
97___ 100 High likelihood that you
Teacher Belief
72_
75 would change your content
Student A c h i e v e m e n t __J7__
50
Professional O p i n i o n __42__
25
Community Pressure
58___
0 Low likelihqod that you
would change your content
Your rating:
127
#
Simulation Instrument
Influencing Factor
Bating
District Policy
__SJl
Teacher Belief
'__25__
Student A c h i e v e m e n t __SJl__
Professional Opinion __49__
Community Pressure
__60
Your rating:
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
______
Influencing Factor
Rating
17
District Policy
Teacher Belief
,
_73__
Student Achievement __80__
55
Professional Opinion
19
Community Pressure
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating Scale
Rating
84___ 100 High likelihood that you
74___ 75 would change your content
60___ 50
57___ 25
0 Low likelihood that you
29___
would change your content
Your rating;
Influencing Factor
Rating
District Policy
_JL00_
Teacher Belief
82;_
Student Achievement
64_
Professional Opinion
76_
Community Pressure
7Jl_
Your rating:
Rating Scale
100. High likelihood that you
75 would,change your content
50 .
25
O Low likelihood that you
would change your content
128
Simulation Instrument
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating
Rating Scale
99___ 100 High likelihood that you
84___ 75 would change your content
90___ 50
34___ 25
48___
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating
1.4__
33__
___9__
___ 6 __
_41__
Your rating:
____ __
Influencing Factor
Rating
District Policy
27_
Teacher Belief
45_
Student Achievement
95_
Professional Opinion
100_
Community Pressure
__99_
Rating Sca le
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
Rating
77_
9 Il_
39_
44_
SIl_
Rating Scale.
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
129
Simulation Instrument .
Inf luenc iLng_Fac tor R ating
District Policy
0__
Teacher Belief
4__
Student Achievement _68__
Professional Opinion __64__
Community Pressure
__38 .
Bating_Scale ,
100 High likelihood that you
'
75 would change your content
50
.
..
25
0
Low likelihood that you
would change your content
Your rating:
lnfiuencing_Factor
Rating
Rating Scale
District Policy
69
100 High likelihood that you
Teacher Belief
100______ 75 would change your content
Student Achievement
59
50 •
25
Professional Opinion
18_
• 0 Low likelihood that you
Community Pressure
42 .
would change your content
Your rating:
■
_
'''
Influencing Factor
Rating Rating_Scale
District Policy
24
100 High likelihood that you
Teacher Belief
. __41
75 would change your content
Student Achievement
53____ 50
Professional Opinion
92
25
/ . .
"
Community Pressure
33_
0 Low likelihood that you
would change your content
Your rating:
______
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
Rating
57__
__IIl__
_52__
__38__
___6__
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
130
Simulation Instrument
Influencing Factor
Rating
Rating Scale
District Policy
64_
100 High likelihood that you
Teacher Belief
44_
75 would change your content
Student A c h i e v e m e n t __8JL__
50
Professional Opinion
75____ 25
Community Pressure
87____ .0 Low likelihood that you
would change your content
Your rating:
II
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating
13__
6_;
__50__
___0__
_69__
I ■■■ ■
I
I
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating Rating Scale
62____100 High likelihood.that you
58_
75 would change your content
73____ 50
58____ 25
25____ 0 Low likelihood that you
would change your content
Your rating:
Influencing_Factor
Rating
Rating Scale
District Policy
89_
100 High likelihood that you
Teacher Belief
34____ _____
75 would change your, content
Student A c h i e v e m e n t __57.__
50
Professional Opinion
62_
25
Community Pressure
21
0 Low likelihood that you
would change your content
Your rating:
______
131
VA_____
Simulation Instrument
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
R ating
40
52
__62
__79
__26
Rating Scale
100 High likelihood that you
75 would change your content
50
25
6 Low likelihood that you
would change your content
Influencing Factor
Bating
District Policy
__44__
Teacher Belief
26
Student Achievement
98
Professional Opinion
46
Community Pressure
8
Bating_Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Rating
90
. 47
__24
__87
__46
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Rating
4__
96__
_42__
__24__
_72__
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
132
#____
Simulation Instrument
Influencing Factor
Rating
District Policy
61
Teacher Belief
__65__
Student Achievement
99
Professional Opinion __73__
Community Pressure
89
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
Rating
District Policy
8
Teacher Belief
__61__
Student Achievement
28
Professional Opinion __13__
Community Pressure
30
Rating Scale
100 High likelihood that yovi
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
lnf%uenci.ng_Factor
Rating
District Policy
; __33__
Teacher Belief
;
24_
Student Achievement; __67__
Professional Opinion __82__
Community Pressure
__43__
Your rating:
______
Influencing Factor 1 Rating
District Policy
75__
Teacher Belief
60
Student Achievement ___2__
Professional O p i n i o n__6JL__
Community Pressure
__18__
j
Your rating:
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
-----------------
; ______
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that yqu
would change your content
133
#
Simulation Instrument
Influencing Factor
Rating
District Policy
3
Teacher Belief
92
Student A c h i e v e m e n t __1.9
Professional Opinion.__48
Community Pressure
__32
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
I
——
I■ I
Your rating:
Influencing_Factor
Rating
District Policy
95
Teacher Belief
IJI
Student A c h i e v e m e n t __45
Professional Opinion __50
Community Pressure
__61
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
Eating
District Policy
__46__
Teacher Belief
67
Student Achievement
4
Professional Opinion __80__
Community Pressure
49
Rating_Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
Your rating:
Rating
47__
8J__
__96__
___7__
__68__
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
134
#
Simulation Instrument
InfluencingFactor
Rating
District Policy
50
Teacher Belief
55
Student Achievement __84
Professional O p i n i o n__1J5
Community Pressure
__74
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
Your rating:
Influencing_Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community. Pressure
Rating Rating Scale
43____100 High likelihood that you
53____ 75 would change your content
97____ 50
25
16
76_
0 Low likelihood that you
would change your content
Your rating:
Influencing Factor
Rating
District Policy
__28 .
Teacher .Belief
'{ .85
Student Achievement , 10
Professional Opinion
.67
Community Pressure
__9__.
Your rating:
____ ;
_
Influencing^Pactor
Rating
District Policy
80__
Teacher Belief
_31__.
Student Achievement
_35__
Professional Opinion
25
Community Pressure
_^_64_
Your rating:
Rating Scale
100 High likelihood that you
75 would change your content
,50
25
0 Low likelihood that you
would change your content
Rating Scale
100 High likelihood that you
75. would change your content
50
25
0 Low likelihood that you
would change your content
135
#_:___
Simulation Instrument
Influencing_Factor
Rating
District Policy
87__
Teacher Belief
5__
Student A c h i e v e m e n t __41.__
Professional Opinion __69__
Community Pressure
__92__
Your rating:
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
______
Influencing Factor
Rating Rating Scale
District Policy
25____100 High likelihood that you
Teacher Belief
48____ 75 would change your content
Student A c h i e v e m e n t __29_
50
25
Professional O p i n i o n__31___
Community Pressure
44____ 0 Low likelihood that you
would change your content
Your rating:
______
Influencing Factor
Rating
District Policy
______
Teacher Belief
______
Student Achievement ______
Professional O p i n i o n____ _
Community Pressure
______
Your rating:
Influencing Factor
District Policy
Teacher Belief
Student Achievement
Professional Opinion
Community Pressure
B
M
M
B
M
M
M
M
M
W
W
W
B
M
M
^
M
M
B
M
^M
B
M
B
^
M
M
W
M
A
lA
M
^
W
M
M
M
M
W
M
M
B
M
W
B
B
P
M
W
W
Your rating:
Rating Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
______
Rating
______
______
^____ _
______
__:___
M
W
W
B
M
W
B
M
M
M
M
B
B
^
M
A
*
Ratin g Scale
100 High likelihood that you
75 would change your content
50
25
0 Low likelihood that you
would change your content
MONTANA STATE UNIVERSITY LIBRARIES
*
#