Teacher Perceptions, Learned Helplessness and Mathematics Achievement:
A Longitudinal Study
Shirley M Yates
The Flinders University of South Australia
As part of a longitudinal study of mathematics achievement, 58 teachers
in 31 schools rated the classroom behaviour and mathematics achievement
of 258 primary and lower secondary South Australian students. The
Student Behavior Checklist, used by the teachers had been designed to
measure learned helplessness and mastery behaviours in the classroom,
but confirmatory factor analysis indicated a single scale of academic
behaviour. This Academic Behaviour scale was analysed with the Rasch
model and the results of the teachers' ratings compared with the
students' scores on the Progressive Achievement Test in Mathematics one
year later. In addition, students' task involvement, ego orientation,
explanatory style and depression were assessed via self-report
instruments. It was found that teachers' ratings of achievement in
mathematics were predictive of subsequent achievement in mathematics,
but their ratings of academic behaviour failed to predict significantly
the students' responses on the self-report scales. However, the
relationship between the Academic Behaviour scale and students'
self-reported depression was of a small but marginally significant
order of magnitude.
Paper presented at the Australian Association for Research in Education
Conference, Brisbane, 3 December, 1997.
Introduction
To what extent can teachers identify students with the disposition to
exhibit learned helplessness? Helplessness is often defined by the use
of student self report indices such as the Intellectual Achievement
Responsibility Scale (IAR; Crandall, Katovsky & Crandall, 1965), by
various attributional-type line scales or by the Children's
Attributional Style Questionnaire (CASQ; Seligman, Peterson, Kaslow,
Tannenbaum, Alloy, & Abramson, 1984). Although the concept of learned
helplessness now has a long history in psychology, there appears to be
no recognized measure of this trait in terms of teachers' perceptions
and judgements. In the current project, the use of a teacher-rating
instrument that emerged from the work of Fincham, Hokoda and Sanders
(1989) was investigated.
As part of a longitudinal investigation into motivational variables
likely to influence primary and lower secondary students' mathematics
achievement, teachers rated the behavioural characteristics of students
in the classroom as well as their achievement in mathematics. These
measures of academic helplessness and achievement, as perceived by
teachers, were compared with student achievement data and motivational
indices one year later. The area of mathematics was chosen in part
because it is an area of the curriculum where students hold strong
attitudes and where success and failure are more obvious (McLeod,
1993).
Learned Helplessness
Helplessness is described by Peterson, Maier and Seligman (1992) in
terms of three criteria: (1) loss of motivation, (2) changes in
cognition and emotion, and (3) a reduction in behavioural agency (such
as passivity). Among the changes in cognition is the perception of
non-contingency; that is, the belief that important outcomes are
uncontrollable. As helplessness in children has been predominantly
measured by pencil and paper self report, the available research has
largely used students in the fifth grade or higher. It has been widely
assumed that the Children's Attributional Style Questionnaire is
predictive of learned helplessness (Nolen-Hoeksema, Girgus & Seligman,
1986; 1992).
In classroom contexts it is likely that helplessness is observed
through the way students respond to situations of actual or conceivable
failure. It may be thus assumed that teachers are in a position to
assess at least some of the recognized dimensions of helplessness as
they surface in classroom life.
The Student Behavior Checklist
In developing the Student Behavior Checklist that was used in this
study, Fincham et al. (1989) generated items that reflected the range
of behaviours associated with learned helplessness and mastery
orientation in the research literature. Thus, by their very nature the
items reflect student characteristics that are directly observable by
teachers, rather than being inferred from an internal state as measured
in student self reports. Fincham et al. (1989) reported that although
the learned helplessness and mastery orientation subscales were highly
correlated (r = -0.81) the psychometric robustness of the instrument
had yet to be established. Furthermore they raised the issue as to
whether the scales specifically measured learned helplessness and
mastery orientation or whether they reflected academic competence.
Lastly, they considered that as the scale was strongly related to
concurrent and future achievement scores in their own study and that of
Nolen-Hoeksema, Girgus and Seligman (1986), perhaps a shorter version
of the scale might "provide a cost-effective measure of helplessness"
(Fincham et al., 1989, p 143).
Teacher Judgement
Classroom behaviour
In a critical review of teacher-administered rating scales of the
classroom behaviour of children Spivack and Swift (1973) noted the
importance of ascertaining student behavioural adjustment in the
classroom not only from a behavioural management point of view but also
because it reflected "the extent to which the child may be benefiting
from participation in the educational enterprise itself" (Spivack &
Swift, 1973, p55). In reviewing the literature of the time they found
19 studies in which teachers had rated overt behaviours, and in most of
these there was both a paucity of classroom behaviours covered and a
marked lack of psychometric rigour in the scales themselves. With
respect to teachers as judges, they reported that teacher ratings
discriminated between a variety of criteria, had some stability over
time, and that teachers' ratings of girls' overt behaviour were more
consistent with their actual performance than was the case for boys. It
was considered that the study of overt student behaviour by teachers
supplied a new dimension to the understanding of classroom behaviour
and school achievement.
Academic performance
Hoge and Coladarci (1989) located 16 studies in which teachers'
judgements of their students' academic performance were compared
against actual scores on objective test measures. Across the studies
the median correlation was 0.66 suggesting a strong correspondence
between teacher judgements and student achievement. The data from
several studies suggested that teachers achieved a 'hit-rate' of around
70 per cent accuracy when asked to assess whether individual students
were able to succeed on specific test items. In a review of 42 studies,
Follman (1990) found the best estimate of the correlation between
teachers' estimates of students' achievement and their actual scores on
standardized achievement tests to be 0.50, although the correlations
ranged from about 0.10 to 0.90.
When the judgements of teachers were compared, Hoge and Coladarci
(1989) noted that a number of studies indicated large variations
amongst individual teachers. Moreover, they reported that the accuracy
of teacher judgements appeared to be relatively higher in the case of
judgements made on average to above average ability students. Teacher
ratings of academic brightness have been found to be significantly
correlated with examination success five years later (Kenealy, Frude &
Shaw, 1991).
Teachers' perceptions might be influenced by a variety of student
characteristics and these expectations might in turn affect classroom
interactions. High achievers in the third grade were rated as having
better meta-cognition, higher self concept and stronger effort and
ability attributions about success (Carr & Kurtz, 1991; Carr &
Kurtz-Coates, 1994). Interestingly, in the latter study teachers were
moderately accurate in their perceptions of students' metacognitive
abilities, but not of their attributional beliefs or self concepts
(Carr & Kurtz-Coates, 1994). Physically attractive students were judged
more favorably by teachers (Ritts, Patterson & Tubbs, 1992), while
students for whom the teachers held high performance expectations in
physical education received significantly higher academic learning time
(Cousineau & Luke, 1990). When average achieving students were assigned
to advanced mathematics classes in an urban American junior high
school, they not only received higher level mathematical content and
active teaching, but they also achieved at a higher than expected level
(Mason, Schroeter, Combs & Washington, 1992).
The effect of teacher expectations on student performance has been
termed a self-fulfilling prophecy (Rosenthal & Jacobsen, 1968), a term
originally employed by Merton (1948) to refer to situations in which
initially false beliefs became true. While this phenomenon was believed
to be powerful and pervasive through the 1980s, neither meta-analyses
of the experimental research (such as Raudenbush, 1984; Rosenthal &
Rubin, 1978) nor naturalistic studies (see Brophy, 1983; Jussim &
Eccles, 1995a, for reviews) supported this conclusion although, under
some conditions, self- fulfilling prophecies were more powerful. In a
longitudinal study of the effect of this phenomenon in mathematics,
teachers' expectations predicted changes in student achievement beyond
effects accounted for by previous achievement and motivation (Jussim &
Eccles, 1992), although their perceptions predicted achievement more
strongly for low achievers than high achievers (Madon, Jussim & Eccles,
1997).
The overall conclusion of the Hoge and Coladarci (1989) review was
that, with regard to the achievement domain, teacher judgements did
concur with more objective measures. However, some teachers tended to
be more accurate than others and there was a tendency for teachers to
err in over-estimating the capabilities of low-achieving students.
Teacher grading
In a review of 19 studies of teacher grading over the last ten years,
Brookhart (1994) also noted variability in teacher practices. Different
teachers not only perceived the meaning and purposes of grades
differently, but considered achievement and nonachievement factors
differently (Brookhart, 1993; Frary, Cross & Weber, 1993; Nava & Lloyd,
1992; Pilcher-Carlton & Oosterhof, 1993). Primary teachers relied more
on observation and informal evidence while secondary teachers depended
more on written evidence when grading (Brookhart, 1994).
With respect to achievement and nonachievement factors, Brookhart noted
the confounding effect of effort and achievement on teachers' grading.
When grading students' work, teachers see effort as a separate issue
from considering students' gender or personality (Frary et al., 1993;
Griswold & Griswold, 1992; Nava & Lloyd, 1992; Pilcher-Carlton &
Oosterhof, 1993; Stiggins, Frisbie & Griswold, 1989; Wood, Bennett,
Wood & Bennett, 1990). These comments are important as the
characteristics of learned helplessness include passivity, loss of
motivation and lack of effort, behaviours which in turn impact on
academic achievement. If students do not participate in the activities
and lessons provided by the teachers, then their achievement is
jeopardised (Brookhart, 1994).
The Present Study
The extent to which teachers' judgements of student emotional and
motivational traits reflect the high level of accuracy that is apparent
within the achievement domain is of course open to question. Knowledge
of this area has been hampered by lack of suitable measurement
instruments. Thus the present study sought to investigate properties of
the Student Behavior Checklist (Fincham, Hokoda & Sanders, 1989), and
the extent to which this scale taps into teachers' perceptions of
learned helplessness in the classroom, and the relationship between
their ratings and subsequent student motivation and achievement. This
scale was chosen for investigation because of its importance in the
literature in investigations of student achievement and explanatory
style (Nolen-Hoeksema, Girgus & Seligman, 1986).
Subjects
In November, 1994, 58 teachers in 31 schools in an Australian city
rated 258 students from Years 4 to 8 with the Student Behavior
Checklist. Of these students, the 243 in the final sample were located
in 26 primary and 24 lower secondary schools in Term 4, 1995, where
they were administered a test of mathematics achievement, and
questionnaires of explanatory style, depression and attitudes towards
mathematics. The distribution of these students by year level and
gender in 1995 is presented in Table 1.
Table 1
Numbers of students by year level and gender in 1995
Gender Year 5 Year 6 Year 7 Year 8 Year 9 Total N
Male 8 28 21 28 24 109
Female 10 34 22 38 30 134
Combined 18 62 43 66 54 243
Instruments
1. Student Behavior Checklist
The Student Behavior Checklist (Fincham, Hokoda & Sanders, 1989)
designed as a rating scale for teachers is comprised of 24 items, 12 of
which had been selected from the research literature to measure the
construct of learned helplessness, while the other 12 were designed to
measure mastery orientation. An example of an item measuring learned
helplessness is "Prefers to do easy problems rather than hard". An
example of an item measuring mastery orientation is "Tries to finish
assignments even when they are difficult". The teachers were asked to
rate student behaviour over the past two to three months on a five
point scale ranging from 1 (not true) to 5 (very true). They also
provided a single estimate of student achievement in mathematics on a
five point scale which ranged from 1 (excellent) through 3 (average) to
5 (poor).
2. Progressive Achievement Tests in Mathematics
The Progressive Achievement Tests in Mathematics (ACER, 1984), which
utilises a multiple choice format, consists of three tests (Tests 1, 2,
and 3) at different grade levels and different levels of difficulty,
with each covering a range of general mathematics topics. Form A of
each test was used. Within each test, the items are arranged in order
of increasing difficulty in content groups. The item difficulty order
was determined by the Rasch analysis of the responses from the
Australian standardization sample tested in November, 1983.
Test 1 designated for Years 3, 4, and 5 contains 47 items, encompassing
number, computation, fractions, measurement and money, statistics and
graphs and spatial relations. Test 2 with 57 items covers the areas of
number, computation, fractions, measurement and money, statistics and
graphs, spatial relations and logic and sets and is designed for use in
Grades 5, 6, 7, and 8. Test 3, intended for Grades 6, 7, and 8,
contains 55 items measuring the same areas except fractions. Initial
concerns that there might have been a ceiling effect for some students
in Year 9 were allayed by consultation with Heads of Mathematics
Departments in some of the participating secondary schools who
considered that curricular changes after 1984 made the items still
relevant for students at this level.
In the Rasch calibration procedure, the items in the tests were
analysed with the Rasch model calibration program BICAL3, with a
common-items equating procedure enabling the preparation of a scale
score equivalence table from the item difficulty estimates (ACER,
1984). It is possible to equate the results from Tests 1, 2 and 3 for
all year levels and place the students' scores on a single scale of
achievement. These Rasch scaled scores locate students' performance on
either of the sets of tests on the same single common scale of
mathematics achievement irrespective of the level of the test and the
time of the school year at which students took the test. Students' raw
scores on the two tests were therefore converted to Rasch scaled scores
by reference to the relevant conversion tables provided in the Teachers
Handbook.
3 Your Feelings in Mathematics: A Questionnaire
Your Feelings in Mathematics: A Questionnaire (Yates, Yates & Lippett,
1995), is designed specifically for this study to measure the task
involvement and ego orientation dimensions of goal orientation beliefs
in mathematics. It is an adaptation of the Motivation Orientation
Scales (Nicholls, Cobb, Wood, Yackel, & Patashnick; Duda and Nicholls,
1992). Fifteen of the 25 items measure task involvement, six items
measure ego orientation, with the remaining four designated as filler
items.
Students are asked to rate their attitudes towards mathematics on a
five point Likert-type scale ranging from a strong yes to a strong no.
Items are coded from 1 to 5 with a 5 being allocated for a strong yes
through to a 1 for a strong no. Each item commences with the stem "Do
you really feel pleased in maths when ... " which is then followed by a
statement that relates to student mathematics behaviour. The students
then circle the rating that most closely approximates their feeling
about the situation presented in the item.
4 The Children's Attributional Style Questionnaire
The Children's Attributional Style Questionnaire (CASQ), (Seligman,
Peterson, Kaslow, Tanenbaum, Alloy, & Abramson, 1984), a forced choice
pencil and paper instrument, consists of 48 items of hypothetically
good or bad events involving the child, followed by two possible
explanations (Seligman et al., 1984). For each event, one of the
permanent, personal or pervasive explanatory dimensions is varied while
the other two are held constant. Sixteen questions pertain to each of
the three dimensions, with half referring to good events and half
referring to bad events. The CASQ is scored by the assignment of 1 to
each internal or stable or global response, and a 0 to each external,
or unstable or specific response.
Scales are commonly formed by summing the three scores across the
appropriate questions for each of the three dimensions, for composite
positive (CASQCP) and composite negative (CASQCN) events separately
(Peterson et al., 1993). In some cases a composite total score (CASQCT)
is derived by reversing the direction of the negatively scaled items
(Nolen-Hoeksema, Girgus, & Seligman, 1986).
5 The Children's Depression Inventory
The Children's Depression Inventory (Kovacs, 1992), suitable for
administration in either individual or group settings, was developed in
1977 as a self-rating symptom orientated scale for school-aged children
and adolescents aged from 7 years to 17 years. It consists of 27 items,
covering a range of depression symptoms which include disturbed mood,
hedonic capacity, vegetative functions, self-evaluation and
interpersonal behaviours presented in contexts which are relevant to
children. Factor analytic studies of these items found that although
the CDI captured one major second-order factor of depression, five
primary factors were also present (Kovacs, 1992). For this study, the
questionnaire comprised 26 items, as Item 9 concerning suicide
ideation, was deemed not to be appropriate for the student sample and
was omitted. The questionnaire was also referred to as an Attitude
Survey, since this was considered to be less anxiety provoking for
students in the sample than the original title.
For each of the 26 items, students are presented with three sentences
for which they are asked to rate the one that describes them best for
the past two weeks by placing a cross in the appropriate box. The
statements within each item present contexts with which students are
likely to be familiar, with the ratings ranging from an absence of the
symptom, through a mild symptom to a definite symptom. About half the
items start with a choice which represents the greatest symptom
severity while in the remainder of the items the sequence of choices is
reversed. The items are scored as a 0 for the absence of symptom, 1 for
a mild symptom, and 2 a definite symptom. While it is designed for
children in the age range of 7 years to 17 years (Kovacs, 1992), some
differences have been reported from the normative study in relation to
the age and gender of the child, with boys and older children having
significantly higher CDI scores (Finch, Saylor & Edwards, 1985).
Procedure
Teacher ratings
The Student Behavior Checklist was posted to 58 teachers in 31
different schools in Term 4, 1994. The teachers were requested to
consider the student over the previous two or three months and for each
of the 24 items, circle the rating from 1 to 5 that indicated how true
that description was of the student. Teachers were asked to read the
items carefully as they were directed towards several different aspects
of the student's behaviour. Teachers also rated the student's
achievement in mathematics on a five point scale. Completed
questionnaires for 258 students were returned by post.
Student data
When 243 of these students were traced in 1995, the mathematics
achievement test and the questionnaires were administered either
individually or to groups of students in Term 4 by a male or female
research assistant during normal school hours within the students' own
school. Students were informed in very general terms as to the purposes
of the study, with the instructions for the administration of each
instrument being described to them verbally. These administrative
instructions were also written on the mathematics tests and each
questionnaire. At the beginning and the end of the administration
session, students were assured of the confidentiality and anonymity of
their responses.
The Progressive Achievement Test in Mathematics was administered first,
followed by the Children's Attributional Style Questionnaire, Your
Feelings in Mathematics: A Questionnaire and the Children's Depression
Inventory. Test 2 or 3 of Form A of the Progressive Achievement Test in
Mathematics was administered in strict accordance with the
standardization procedures on pages 5 to 7 of the Teachers Handbook,
with 45 minutes plus administration time being allowed. The level of
the test that was most appropriate for the year level of the student
was chosen by reference to the guidelines given in the Teachers
Handbook, with all students in Years 5, 6 and 7 being administered Test
2, and all students in Year 9 taking Test 3. Students in Year 8 were
administered either Test 2 or 3, with the majority taking Test 2. All
responses were recorded by the students with an Hb or 2b pencil on the
computer scoring answer sheet.
Responses to the Children's Attributional Style Questionnaire, Your
Feelings in Mathematics: A Questionnaire and the Children's Depression
Inventory were recorded in pen by the students directly on the printed
questionnaire sheets. If students experienced difficulty reading any of
the items these were read aloud by the researcher, but no other
assistance was given. The administration of the three questionnaires
was not timed.
RESULTS
Calibration of the instruments
Each of the instruments and the student data were analysed with the
Rasch scaling procedure. The major advantage of the Rasch model is that
the students' estimated ability or attitude is independent of the
sample of items, while at the same time the difficulty level of the
items is not dependent on the sample of students who take the items
(Wright, 1977, Wright & Stone, 1979, Hambleton, 1989). The performance
of students who take different items from the same test battery can
then be compared, provided that the items or students have been
calibrated on a common scale (Green, 1996). Moreover, the items and the
persons are brought to a common interval scale.
The item response model employs the notion of a single specified
construct (Snyder & Sheehan, 1992) or an inherent latent trait
dimension (Weiss & Yoes, 1991; Hambleton, 1989), which is referred to
as the requirement for unidimensionality (Wolf, 1994). Prior to the use
of the Rasch model, it was first necessary to determine whether each
instrument met the requirement of unidimensionality (Lord, 1980; Weiss
& Yoes, 1991).
The factor structure of the Student Behavior Checklist was explored by
principal components analysis, and subsequently by confirmatory factor
analysis. In the case of the student measures, only the structure of
Your Feelings in Mathematics: A Questionnaire was considered through
factor analysis. The fact that the separate tests for the Progressive
Achievement Tests in Mathematics had been brought to a common scale
during the calibration and equating procedure was taken as evidence of
the unidimensionality of mathematical ability that the test tapped
(ACER, 1984). The items in the Children's Attributional Style
Questionnaire had been designed to measure the construct of a single
trait of explanatory style while unidimensionality had been
specifically examined through the use of oblimin rotation factor
analytic procedures in the construction of the Children's Depression
Inventory.
In the analysis of each of the instruments, the infit mean square
values of each item were inspected to determine whether they fell
within the predetermined range of 0.83 and 1.20. For each instrument,
items with infit mean square values within this range were considered
to fit the Rasch model and were thus retained, while those outside this
range which did not fit the model were progressively deleted. Items
which misfitted were discarded because they represented a different
construct, were ambiguous, discriminated so well as to be redundant
with other items or did not discriminate well (Green, 1996). The final
scales were composed of those items that met the requirements of the
Rasch model.
With the exception of the Progressive Achievement Tests in Mathematics
(ACER, 1984) which had been Rasch analysed with the BICAL3 program, the
QUEST program (Adams & Khoo, 1993) was used for Rasch scaling of all of
the instruments.
Calibration of the Student Behavior Checklist
1. Confirmatory Factor Analyses
Unidimensionality of the items in the Student Behaviour Checklist was
established with confirmatory factor analysis of a one factor, two
factor, hierarchical and nested model through the use of the LISREL8W
computer program (Joreskog and Sorbom, 1993). Acceptance of the one
factor model indicated that there was no evidence to support the two
separate factors Learned Helplessness and Mastery which were
hypothesised by Fincham, Hokoda and Sanders (1989) in the development
of the instrument (Yates and Afrassa, 1995). As a consequence of these
analyses, it was evident that the items in the Student Behaviour
Checklist measured only one factor Academic Behaviour.
2 Principal components factor analysis
Exploratory principal components factor analysis using the SPSS
computer program was carried out to examine the factor loadings on
Learned Helplessness and Mastery. All the Mastery items had negative
factor loadings while all the Learned Helplessness items were
positively loaded. As the Mastery and Learned Helplessness items loaded
in opposite directions, the results from both the principal components
and confirmatory factor analyses indicated that it was necessary to
reverse the Learned Helplessness items responses from (01234) to
(43210) during the subsequent analysis.
3 Rasch Analyses
The Rasch rating scale procedure was selected, because it involved "a
single underlying dimension for academic behaviour and sought to scale
the data in such a way that interval scale data were obtained for the
variable formed" (Wolf, 1994, 4926). The responses however, also
involved unipolar scales with the same response categories across all
items. Rating scale analysis was the preferred technique for the
analysis of these response categories (Wolf, 1994).
Of the 24 items analysed with the QUEST computer program (Adams & Khoo,
1993), 14 items had infit mean squares outside the acceptable range of
0.83 to 1.20. These misfitting items were progressively deleted from
the scale (Yates and Afrassa, 1995). Of the ten remaining items that
fitted the Rasch scale, six were learned helplessness items (LH) and
four were mastery items (MO) (see Table 2). The items in the final
scale related to effort (items 1 (LH) and 13 (MO)), motivation (items 4
(LH) and 7 (MO)), reaction to failure (items 6 (LH), 9 (LH) and 24
(MO)), persistence (items 20 (LH) and 22(MO)), and response to teacher
inquiry (item 18 (LH)).
Rasch scaled teacher ratings were estimated for each student on the
basis of these ten items of academic behaviour. A separate score for
each student was recorded from the single rating of achievement made by
their teachers. This is referred to as the 1994 teacher rating of maths
achievement.
Table 2
The Academic Behaviour Scale
Characteristics Learned Helplessness items (LH) Mastery Oriented items (MO)
Effort 1. Prefers to do easy problems rather 13. Prefers new and challenging
than hard ones. problems over easy problems.
Motivation 4. Takes little independent initiative; 7. Tries to finish assignments,
you must help him/her to get started even when they are difficult.
and keep going on an assignment.
Failure 6. When s/he fails one part of a task, 24. When s/he receives a poor
s/he looks discouraged-says s/he is grade, says s/he will try harder
certain to fail at the entire task. in that subject the next time.
9. Gives up when you correct him/her
or find a mistake in his/her work.
Persistence 20. Says things like "I can't do it" 22. When experiencing difficulty
when s/he has trouble with his/her s/he persists for a while
work. before asking for help.
Response to 18. Does not respond with enthusiasm
teacher inquiry and pride when asked how s/he is
doing on an academic task.
Calibration of the Progressive Achievement Tests in Mathematics
In the calibration and equating of the Progressive Achievement Tests in
Mathematics in 1983, Rasch procedures were employed for item selection,
item ordering within topic areas and in the provision of scaled scores
that enabled the students' results to be placed on a common scale
irrespective of the test, the year level of the students, the items the
students answered and the difficulty levels of these items.
Students correct responses in this study were therefore added together
and converted to the PATMATH scale scores through the use of Table 11
in the Teachers Handbook (1984, p. 34). Omitted items were considered
as wrong. The students' scores were on the same scale irrespective of
whether the they took Test 2 or Test 3.
Calibration of Your Feelings in Mathematics: A Questionnaire
1 Factor analysis of Your Feelings in Mathematics: A Questionnaire
Principal components analysis and the oblimin rotation procedure were
chosen for the establishment of unidimensionality of this 25 item
questionnaire as they simplified factors by minimizing cross products
of loadings and allowed for a wide range of factor intercorrelations to
occur (Tabachnick and Fidell, 1996). Items 2, 7, 11 and 25, designated
as filler items, were deleted prior to the factor analysis. Factor one
with an eigen value of 7.47 was composed of 15 items which measured
Task Involvement. Factor 2, with a eigen value of 2.36 was comprised of
six items that measured Ego Orientation. There was a moderate
correlation of 0.40 between the two factors. On the basis of these
results the questionnaire was then divided into two separate scales of
Task Involvement and Ego Orientation, each of which independently met
the criteria of unidimensionality for the application of the Rasch
procedure.
2 Rasch Analyses of the Task Involvement and Ego Orientation scales
Each scale was then analysed separately with the QUEST program (Adams &
Khoo, 1993). Of the 15 items which comprised the Task Involvement
Scale, 12 items met the requirements of the Rasch model, while five of
the 6 items from the Ego Orientation Scale had infit mean squares
within the preset limits of 0.83 and 1.20 (Yates & Yates, 1996; Yates,
1997). The items for both scales are presented in Table 3. Rasch scaled
student scores were estimated separately for the Task Involvement Scale
and for the Ego Orientation Scale.
Table 3
Items in the Task Involvement and Ego Orientation Scales
Calibration of the Children's Attributional Style Questionnaire
The 24 positive items (CASQCP), the 24 negative items (CASQCN) and the
composite measure (CASQCT) were analysed separately (Yates and Afrassa,
1994). The CASQCT was formed from the CASQCP and reversed CASQCN items.
The results of the separate Rasch analyses of the CASQCP, CASQCN and
CASQCT scales indicated that as the items on each of these scales
fitted the Rasch model, the scales could be considered independently
(Yates, Keeves & Afrassa, 1996). Student scores were estimated
separately for the CASQCP, CASQCN and CASQCT scales.
Calibration of The Children's Depression Inventory
Of the 26 items that were administered to students, 20 met the
requirements of the Rasch model. These items were used for the
estimation of student scores.
Table 4
Correlations with students' achievement in mathematics
Variable
2 3 4 5 6
1. 1995 Mathematics achievement -0.40** 0.33**
0.13* -0.08 -0.07
2. 1994 Teacher rating of maths achievement - -0.68**
-0.14* 0.05 -0.11
3. 1994 Teacher rating of academic behaviour -
0.08 -0.04 0.07
4. 1995 Student Task involvement
- 0.26** 0.34**
5. 1995 Student Ego orientation
- 0.09
6. 1995 Student Explanatory style (CASQCT)
-
N = 243, ** p< 0.001, * p < 0.05
Relationships between Teacher Ratings and Student Variables
The relationships between the teacher ratings of academic behaviour and
mathematics achievement obtained in 1994 were examined in relation to
the students' achievement in mathematics, as well as the students' task
involvement in and ego orientation towards mathematics, explanatory
style and self-reported depression measured one year later. Teachers'
ratings of both academic behaviour and achievement were analysed with
correlations and multiple regressions separately in relation to student
achievement in mathematics and to depression.
The Relationship between Teachers' Ratings and Student Achievement in
Mathematics
Table 4 presents the correlation between the teachers' prior ratings of
mathematics achievement, ratings of academic behaviour, students'
achievement in mathematics, task involvement, ego orientation and
explanatory style. Significant correlations were evident between the
teacher ratings of achievement and classroom behaviour and between both
of these variables and student achievement one year later. Teacher
ratings of achievement were also significantly correlated with
subsequent student task involvement.
However, as shown in Table 5, when the predictive relationship between
the teachers' ratings and achievement in mathematics were examined with
direct entry multiple regression, the teachers' ratings of achievement
in the previous year were found to be significant but this effect did
not hold for their rating of academic behaviour within the classroom.
In these analyses, students' task involvement and explanatory style was
also significantly related to students' achievement in mathematics in
1995.
Table 5
Regression analysis: predicting mathematics achievement by teacher
ratings, motivational orientation, and explanatory style.
Variable r Beta t Sig t
1994 Teacher rating of maths achievement -0.40 -0.32 -3.97 0.00
1994 Teacher rating of academic behaviour 0.35 0.11 1.34 0.18
1995 Student Task involvement 0.13 0.16 2.43 0.02
1995 Student Ego orientation 0.08 -0.08 -1.40 0.16
1995 Student explanatory style (CASQCT) -0.07 -0.16 -2.57 0.01
N = 243 R = 0.45 R2 = 0.20
Table 6
Regression analysis: Predicting mathematics achievement by teacher
ratings, motivational orientation, and positive and negative
explanatory style.
Variable r Beta t Sig t
1994 Teacher rating of maths achievement -0.40 -0.31 -3.92 0.00
1994 Teacher rating of academic behaviour 0.33 0.10 1.22 0.23
1995 Student Task involvement 0.13 0.16 2.54 0.01
1995 Student Ego orientation -0.08 -0.08 -1.36 0.17
1995 Positive explanatory style (CASQCP) -0.17 -0.21 -3.44 0.00
1995 Negative explanatory style (CASQCN)-0.06 0.02 0.32 0.75
N = 243 R = 0.47 R2 =0.22
In order to examine the relative effects of students' positive and
negative explanatory style in relation to their mathematics achievement
in 1995, the multiple regression was repeated with the separate
variables for positive and negative explanatory style in place of the
total score. In the results of this analysis, presented in Table 6, it
is evident that the positive explanatory style rather than the negative
explanatory style is significantly predictive of achievement
The Relationship between Teachers' Ratings and Student Depression
Table 7 presents the correlation between the teachers' ratings of
achievement and academic classroom behaviour and the students' task
involvement, ego orientation, explanatory style and self reported
depression. There are significant correlations between the teachers'
rating of both mathematics achievement and academic behaviour and the
subsequent measures of students' depression, task involvement and
explanatory style.
Table 8 gives the results obtained when the predictive relationship
between these variables was examined with multiple regression. The
teachers' prior ratings of classroom behaviour were predictive of
subsequent student self-reported depression at a marginally significant
level. In these results, task involvement and explanatory style were
found to relate significantly to depression.
Table 7
Correlations with students' self reported depression
Variable
2 3 4 5 6
1. 1995 self reported depression 0.16* -0.18**
-0.28** -0.01 0.36**
2. 1994 Teacher rating of maths achievement - -0.68**
-0.14* 0.05 -0.11
3. 1994 Teacher rating of academic behaviour -
0.08 -0.04 0.07
4. 1995 Student Task involvement
- 0.26** 0.34**
5. 1995 Student Ego orientation
- 0.09
6. 1995 Student Explanatory style (CASQCT)
-
N = 243, ** p< 0.001, * p < 0.05
Table 8
Regression analysis: predicting student self reported depression in
1995 by teacher ratings, motivational orientation, and explanatory
style.
Variable r Beta t Sig t
1994 Teacher rating of maths achievement 0.16 -0.00 -0.03 0.97
1994 Teacher rating of academic behaviour -0.18 -0.15 -1.81 0.07
1995 Student Task involvement -0.28 -0.19 -2.86 0.01
1995 Student Ego orientation 0.01 0.06 0.10 0.32
1995 Student explanatory style (CASQCT) -0.36 -0.29 -4.67 0.00
N = 243 R = 0.43 R2 = 0.18
Table 9 presents a correlation matrix in which the relative effects of
teachers' ratings on students' positive and negative explanatory style
scores was calculated. Interestingly, while teachers' ratings
correlated with the negative explanatory style, significant
correlations were also found between both the positive and negative
explanatory style scales and depression.
Table 9
Correlations with students' positive and negative explanatory style and
self reported depression
Variable 2 3
4 5 6 7
1. 1995 self reported depression 0.16* -0.18** -0.28** -0.01
0.21** 0.33**
2. 1994 Tch rat. of maths ach. - -0.68** -0.14*
0.05 -0.01 0.16*
3. 1994 Tch rat. of academic behav. - 0.08
-0.04 -0.03 -0.14*
4. 1995 Student Task involvement -
0.26** 0.26** -0.24**
5. 1995 Student Ego orientation
- 0.09** -0.03
6. 1995 Pos. Expl. style (CASQCP)
- -0.11
7. 1995 Neg. Expl. style (CASQCN)
-
N = 243, ** p< 0.001, * p < 0.05
Key to abbreviations:
Tch rat Teacher ratings
ach. achievement
behav. behaviour
Pos. Positive
Neg. Negative
Expl. Explanatory
The results of self-reported depression regressed on teachers' ratings
are presented in Table 10.Their prior rating of academic behaviour was
found to be a significant predictor of depression at the ten per cent
level, but the rating of achievement was not significant. In it is also
evident that the concurrent measure of student task involvement and
positive and negative explanatory style were also predictive, with the
negative values for the task involvement and positive explanatory style
indicative of the inverse relationship between these variables and
depression. In this regression analysis, negative explanatory style has
the strongest relationship with the concurrent measure of depression.
Table 10
Regression analysis: predicting depression by teacher ratings,
motivational orientation, and positive and negative explanatory style
Variable r Beta t Sig t
1994 Teacher rating of maths achievement 0.16 -0.01 -0.09 0.93
1994 Teacher rating of academic behaviour -0.18 -0.14 -1.72 0.09
1995 Student Task involvement -0.28 -0.18 -2.84 0.01
1995 Student Ego orientation 0.01 0.06 0.93 0.36
1995 Student positive exp style (CASQCP) -0.21 -0.15 -2.38 0.02
1995 Student negative exp style (CASQCN) 0.33 0.26 4.19 0.00
N = 243 R = 0.44 R2 = 0.19
DISCUSSION
Summary of the findings
This study set out to consider teachers' perceptions of students'
learned helpless behaviours in the classroom. The following findings
emerged from the data:
1. The Student Behavior Checklist possessed acceptable psychometric
properties as a short form interval scale of ten items.
2. The Student Behavior Checklist correlated (r = 0.33 p < 0.001) with
achievement in mathematics one year later. However, this relationship
was not predictive when the other concurrent variables were entered
into the regression analysis.
3. The teachers' single rating of student achievement in mathematics
predicted mathematics achievement data one year later.
4. In general. the Student Behavior Checklist failed to predict
responses to the three measures of self-reported motivation (task
involvement, ego orientation, and explanatory style) used in the study.
However, the relationship between the Student Behavior Checklist and
depression was of a small but marginally significant order of
magnitude, after controlling for other variables.
5. Levels of depression were predicted by the CASQ and by task
involvement data.
Discussion of the variables
The Student Behavior Checklist
In developing the Student Behavior Checklist, Fincham et al. (1989)
highlighted the need both for a shorter version of the scale and to tap
teacher perceptions as a means of either supplementing or replacing
student self report measures. This modified scale of ten items
certainly met the first need. However, while teachers' ratings of overt
academic behaviour in the classroom did not generally predict students'
internal states one year later, they were significantly related to
self-reported depression.
The findings support Fincham et al.'s (1989) suggestion that the scale
measures academic competence. The ten items in the Student Behavior
Checklist can be conceptualised as constituting a scale of academic
behaviour, with six designated learned helplessness items clearly
relating to a lack of academic behaviour and the designated mastery
orientation items relating to the presence of academic behaviour.
Spivak and Swift (1973) noted that when asked to rate overt behaviours
teachers do discriminate between groups, with their ratings being
stable over time.
Learned helplessness
When these ten acceptable items in the Student Behavior Checklist were
examined, with respect to the criteria for learned helplessness
suggested by Peterson et al. (1992), Item 1 clearly related to a
reduction in behavioural agency, with Item 13 as its antithesis, Item 4
related to motivation with Item 7 as its antithesis, and Items 6 and 9
related to changes in cognition and emotion. This reaction to failure
aspect measured in Items 6 and 9 was countered by Item 24 which
measured an increase or renewal of effort in the face of failure. In
addition, Item 10 related to lack of enthusiasm and pride in response
to teacher inquiry. This trait has been reported by Yates et al. (1995)
as being a significant difference between pessimistic and optimistic
children in relation to their reported attitudes towards mathematics.
Teacher judgments
Classroom behaviour
The variability of teacher judgements noted in the reviews of the
literature by Hoge and Coladarci (1989) and Brookhart (1994) was not
apparent in many of the items deleted from the Student Behavior
Checklist, as these items had high discrimination indices and narrow
band widths indicating that the teacher ratings on these items provided
information over a very limited range (Yates & Afrassa, 1995). However,
considerable variation was noted in the manner in which individual
teachers furnished ratings data, with one teacher actually rating the
entire class as "average" on all characteristics. This factor obviously
served to reduce the magnitude of obtained relationships.
Academic performance
The correlation (r = -0.40, p , 0.001) between the teachers' single
subjective rating of achievement in mathematics with the objectively
measured achievement on the Progressive Achievement in Mathematics one
year later is slightly below the median estimates from the reviews of
Hoge and Coladarci (1989) and Follman (1990). However, as it was
unlikely that the teacher who completed the rating taught the student
mathematics in the following year, their single estimate was
surprisingly strongly predictive. This suggests that effort and
achievement may not have been confounded in this estimate (Brookhart,
1994) and furthermore, that teachers' expectations, as indexed by this
rating, predicted achievement over time (Jussim & Eccles, 1997).
Teacher grading
The finding that teacher ratings of achievement predicted achievement
independently of their ratings of classroom behaviour which was related
to students' self-reported depression supports the outcome of the
review of teacher grading by Brookhart (1994). Nevertheless, this
conclusion needs to be tempered by the finding that teacher rating of
achievement correlated with subsequent student task involvement (r =
-0.14, p < 0.05), particularly as task involvement was significantly
related to concurrent achievement in mathematics. It may be that
student behaviour influences academic learning time both in the short
and long term (Cousineau & Luke, 1990). However, the extent to which
teacher ratings were influenced by students' prior achievement and task
involvement has not been considered in these analyses.
CONCLUSION
Although teacher ratings were predictive of subsequent student
achievement and depression, the present study does not support the
notion that teachers' perceptions of student helplessness actually
relate to student self-reported motivational levels. Although the
Student Behavior Checklist possesses acceptable psychometric
properties, there is no way of knowing if the scale actually measures
"helplessness" in a manner independent of actual student achievement.
Perhaps the teachers' ratings on their students' overt behaviours
simply do not reflect whatever internal motivational process is
occurring in students some time later. Perhaps teacher ratings of
"helplessness" are not the same construct as the students' experience.
This paper reports on only a subset of a more complex design. Future
reports will examine the impact of earlier achievement levels, measured
two years prior to the present data set. Towards this work, path
analyses are being carried out, along with the analysis of gender, year
level and school site.
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Acknowledgments
I would like to express my deepfelt thanks to Professor John Keeves for
his expert guidance and assistance with this study, to Tilahun Mengesha
Afrassa for his analysis of the Student Behavior Checklist, to Ron
Thomas for his meticulous data entry and to Milton Yates for his
computing skills.
I would also like to express my appreciation to the participating
schools, teachers and students and indirectly the parents whose valued
co-operation made the study possible.
This research was supported by a Flinders University Research Board
Establishment Grant.