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Academic risk factors and deficits of
learned hopelessness: a longitudinal
study of Hong Kong secondary school
students
a
a
Raymond C.P. Au , David A. Watkins & John A.C. Hattie
a
b
Faculty of Education, University of Hong Kong, Hong Kong
b
University of Auckland, TLD, Epsom, Auckland, New Zealand
Published online: 22 Jan 2010.
To cite this article: Raymond C.P. Au , David A. Watkins & John A.C. Hattie (2010) Academic risk
factors and deficits of learned hopelessness: a longitudinal study of Hong Kong secondary school
students, Educational Psychology: An International Journal of Experimental Educational Psychology,
30:2, 125-138, DOI: 10.1080/01443410903476400
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Educational Psychology
Vol. 30, No. 2, March 2010, 125–138
Academic risk factors and deficits of learned hopelessness: a
longitudinal study of Hong Kong secondary school students
Raymond C.P. Aua, David A. Watkinsa and John A.C. Hattieb*
Downloaded by [Hong Kong Institute of Education] at 19:30 08 September 2013
a
Faculty of Education, University of Hong Kong, Hong Kong; bUniversity of Auckland, TLD,
Epsom, Auckland, New Zealand
(Received 26 April 2009; final version received 9 November 2009)
Taylor and Francis
CEDP_A_448015.sgm
Educational
10.1080/01443410903476400
0144-3410
Original
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Prof.
j.hattie@auckland.ac.nz
000002009
JohnHattie
&Article
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(print)/1469-5820
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(online)
The aim of the present study is to explore a causal model of academic
achievement and learning-related personal variables by testing the nature of
relationships between learned hopelessness, its risk factors and hopelessness
deficits as proposed in major theories in this area. The model investigates
affective–motivational characteristics of students such as prior academic failures,
academic attributional style, self-efficacy, thoughts about intelligence, school
values, learned hopelessness, self-esteem, learning strategy effectiveness and
academic achievement, and the relationships among them. A sample of 741
Hong Kong secondary students completed a series of scales over a school year.
As expected, prior achievement was the best predictor of subsequent
achievement. The next best predictors were perceived learning difficulties and
learned hopelessness. This in turn leads to disengagement from schooling and
students taking on most responsibility for their failing. Recommendations for
teachers and schools to ameliorate these beliefs may redress the move towards
hopelessness.
Keywords: learned hopelessness; attributions; motivation;
expectancy of success; learning strategies; academic achievement
self-efficacy;
Introduction
The terms ‘learned helplessness’ and ‘learned hopelessness’ are often used by
educators and counsellors to explain the school behaviour of students who seem to
have given up trying academically after a history of failures. These terms came from
the hopelessness model of depression developed by Abramson, Metalsky, and Alloy
(1989). Their theory has proven fruitful for both researchers and clinicians in their
attempts to understand the aetiology and consequences of this psychological condition. There have been many educational parallels and much research and theorising
that has focused on trying to explain the consequences of continuing academic failure using hopelessness-related constructs. As yet, however, the research in the
academic setting has been piecemeal focusing typically on a particular theory and its
related variable(s). No research has attempted to test competing theories, let alone
with longitudinal data suitable for the analysis of causality. The current research
examines these themes in a non-western context, that of Hong Kong secondary
schools.
*Corresponding author. Email: j.hattie@auckland.ac.nz
ISSN 0144-3410 print/ISSN 1469-5820 online
© 2010 Taylor & Francis
DOI: 10.1080/01443410903476400
http://www.informaworld.com
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126
R.C.P. Au et al.
The primary aim of the present study is to explore a causal model of
academic achievement and learning-related personal variables by testing the nature
of relationships between learned hopelessness, its risk factors and hopelessness
deficits as proposed in major theories in this area. The model investigates such
affective–motivational characteristics of students as prior academic failures,
academic attributional style, self-efficacy, thoughts about intelligence, school values,
learned hopelessness, self-esteem, learning strategy effectiveness and academic
achievement, and the relationships among them.
Three interrelated sets of constructs are postulated: academic risk factors, expectations and academic deficits. The hypothesised causal chain begins with prior
academic failures, academic attributional style, self-efficacy, school values and an
entity concept of intelligence as academic risk factors, and ends with self-esteem,
learning strategy effectiveness and academic achievement as academic outcomes. The
proposed model reflects the idea that when students, who are entity theorists with
a particular attributional pattern, face prolonged academic failures, have low selfefficacy and low school values, then they are likely to develop hopelessness and are
vulnerable to a cluster of academic deficits such as lowered self-esteem, ineffective
use of learning strategies and deteriorated performance.
It is predicted that the combined contributions of prior academic failures, academic
attributional style, self-efficacy, school values and entity conceptions of intelligence
increase the likelihood of enhanced academic achievement. It is likely, however, that
only a subset of these precursors are predictive of enhanced achievement, hence
structural modelling will be used to determine this best subset. It is planned that a twowave structural model would help the study to test a causal model of learned hopelessness that best explains the aetiology of learning hopelessness for Hong Kong students
in the academic setting based on the framework that integrate Dweck’s (1986) conceptions of intelligence, Bandura’s (1986) conception of self-efficacy, Eccles et al.’s
(1983) expectancy-value theory of achievement performance and Abramson et al.’s
(1989) model of learned hopelessness. The underlying rationale of these theories is
described below.
Hopelessness theory and the academic context
The term ‘learned helplessness’ was introduced by Seligman (1974) to explain the
behaviour of dogs after receiving electric shocks which were both painful and
prolonged and from which they could not escape. The animals became passive and
less motivated to respond in an effective way in other situations. Seligman proposed
that an expectation of non-contingency between response and desired outcome was
generalised to new situations to produce such helplessness deficits. Seligman (1975)
noted the similarities between these deficits and the motivational, cognitive and
emotional deficits of depression in humans.
Abramson, Seligman, and Teasdale (1978) distinguished between learned helplessness and learned hopelessness. They specified the former term as referring to
the expectation that one is helpless to change a situation, whereas the latter refers
both to the expectation that a highly aversive event will occur and that one is helpless to change this situation. In their theory of depression, Abramson et al. (1989)
argued that it is hopelessness not helplessness that is a sufficient cause of hopelessness deficits; it is the perception that a negative event is uncontrollable rather than
an uncontrollable event itself which produces learned hopelessness; and that it is
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127
inferences about causes, negative consequences and negative self-characteristics
when confronted with a negative event that are critical. Like depression, academic
achievement seems to satisfy the criteria for learned hopelessness. Lowered
academic achievement follows academic failures, particularly if a high degree of
importance is attached to these failures, and academic achievement can be mediated
by cognitions of hopelessness. Lowered academic achievement involves maladaptive passivity, lowered persistence and deteriorated academic performance as hopelessness behaviours. Schools (particularly those in Hong Kong) can be places
where academic failures often occur and a student’s effort indeed matters. Thus,
the school is a setting in which learned hopelessness may develop in students at
risk.
Au, Watkins, Hattie, and Alexander (2009) adapted the Abramson et al.’s (1989)
model of depression for the academic context. They included three components in
their model: academic risk factors which if perceived in terms of hopelessness cognitive expectations are likely to lead to academic deficits. From their review of the literature, they integrated the theories of Dweck (1986), Bandura (1986), Eccles (Eccles
& Midgley, 1989), Weiner (1992) and others to postulate the elements of these three
components (see Figure 1). The proposal was that the hypothesised causal chain
begins with the risk factors of prior academic failures, certain academic attributional
style, low self-efficacy, low school values and entity conceptions of intelligence, and
ends with deficits in learning strategies, self-esteem and academic achievement. The
model proposed that students who not only have a history of academic failures but
also have a personal entity theory of intelligence, tend to attribute their academic problems to global, stable and internal causes, have low self-efficacy and assign little value
to school are likely to develop feelings of hopelessness which leave them liable to
academic deficits such as the use of ineffective learning strategies, lower self-esteem
and worsening academic achievement.
This model of academic hopelessness attempts to explain the general processes by
which academic deficits are produced. These academic deficits include lowered
persistence, ineffective learning strategies and deteriorating academic performance as
motivational deficits and lowered academic self-esteem as affective deficits. In the
model, learned hopelessness is the central construct that refers to the expectation that
academic success will not occur or academic failure will occur (outcome expectancy),
and that the student is helpless to change this academic situation (helplessness expectancy). Whenever this expectation occurs, the academic deficits will develop. The
model also suggests that the risk factors that conspire to bring about learned hopelessness are prior academic failure, situational cues, learning styles and inferences that the
students make about causes, negative consequences of the failure and negative selfcharacteristics given the failure.
Many of these beliefs about ability already have a prominent place in current
theoretical models of achievement motivation, including Dweck’s theories of intelligences (Dweck, 1986; Dweck & Leggett, 1988; Nicholls, 1984, 1990), Bandura’s
theory of self-efficacy (Bandura, 1977, 1986), Covington’s self-worth theory
(Covington, 1984), Weiner’s attibutional theory (Weiner, 1979, 1986) and the selfconcept models of Harter, Marsh et al. (Harter, 1982, 1985a, 1985b; Marsh, 1990;
Marsh & Shavelson, 1985). School values are also included in the research model as
the student’s valuing of schooling is postulated to influence achievement behaviour
via learned hopelessness in the general expectancy-value theory of achievement motivation (Eccles et al., 1983; Ethington, 1991; Feather, 1987, 1988; Wigfield, 1994).
Figure 1. Paths between the learning, attributional, affective and achievement latent variables over time.
R.C.P. Au et al.
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128
Figure 1. Paths between the learning, attributional, affective and achievement latent variables over time.
Finally, learning strategy effectiveness is included as one of the academic deficits
because it may result from the development of learned hopelessness via the influences
of entity conceptions of intelligence, self-efficacy, school values, prior academic
failures and dimensions of academic attributional style (Borkowski, Weyhing, &
Carr, 1988; Brown, Bransford, Campione, & Ferrara, 1983; Nolen, 1988; Pokay &
Blumenfeld, 1990).
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Educational Psychology
129
The learning context of Hong Kong
Studies have demonstrated that the contextual factors of learning such as harsh
achievement expectations, examination-oriented curriculum and classroom teaching
characterised by highly structured and authoritarian classroom climate and expository
teaching methods have important impacts on achievement motivation (Anderman &
Maehr, 1994; Pintrich, 2000). These negative contextual factors were found to be
correlated with underachievement and surface learning (Biggs, 1993) and linked to
learned hopelessness (Au, 1995a, 1995b). Students in Hong Kong are often encouraged to put effort into memorising learning materials in textbooks and learn them by
repeated practice. They are assigned tremendous amounts of assignments in various
subjects and, very often, have to stay up late at night to complete homework and revise
for endless tests and examinations. Teaching and learning activities are examinationoriented emphasising recall of details (Biggs, 1993). Teachers seldom use interactive
and student-centred learning activities such as library research, projects, class presentations and group discussions (Watkins, 1996).
Parents in Hong Kong can be very harsh and punitive in shaping their children’s
behaviour. They can use punishment and shaming rather than persuasion with reasons
in disciplining their children. This strict discipline is further reinforced in school
through harsh school regulations and teachers’ punitive attitudes (Ho, 1981). Moreover,
most Hong Kong Chinese parents and teachers tend to set high expectations of achievement for the young in Hong Kong as they believe that success in education leads to a
good job and economic prosperity (Llewellyn, Hancock, Kirst, & Roeloffs, 1982).
Hence, academic excellence in education is strongly emphasised, often at the expense
of personal development.
Most school curricula in Hong Kong are dominated by the highly competitive
public examination system. This examination-oriented curriculum has led students to
spend an inordinate amount of time on their studies – attending regular classes and
after-school cram schools and doing schoolwork at home. The school curriculum
works for the minority of elite academic students but can be deeply injurious for the
majority of students, particularly low achievers (Education Commission of Hong
Kong, 2000).
Aims of research
The main purpose of this research was to investigate how the above constructs in our
model, its risk factors and deficits, developed over time in school and how they could
predict later academic achievement above the influences of prior achievement. The
context of this research was Hong Kong secondary schools. These schools have been
characterised as fiercely competitive and dominated by authoritarian teachers who
seldom praise and often punish their students (see Watkins & Biggs, 1996, 2002).
Combined with parental pressure to succeed and failure blamed by students, teachers
and parents on lack of effort, there are all the seeds for learned hopelessness.
Method
Participants
At Time 1, there were 827 students who completed the scales, but 10% of the students
left the schools, such that there were 741 junior secondary students (14–15 years old)
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who completed the scales on both occasions. The majority of students were living in
public housing estates and came from families of lower socioeconomic class, although
the schools were selected to be representative of the range of abilities of Hong Kong
students. The sample came from 10 Hong Kong secondary schools. Schools in Hong
Kong are strictly streamed, and the students came from Bands 1, 3 and 5, thus representing a cross-section in achievement. The second occasion was 11 months after the
first administration (at the beginning and end of the academic year). This two-wave
design allows the examination of how academic hopelessness and its cognitive correlates change over an academic year, and whether learned hopelessness was a mediating variable influencing such changes.
Measures
Chinese versions of the following nine instruments, which were either constructed
by the first author or adapted from the research literature, were employed to
measure the risk factors and deficits of learned hopelessness described above. The
questionnaires were written in Chinese, the mother tongue of the subjects under
study. The measures were translated into Chinese when necessary using the usual
translation-back translation method. All measures were found to have very adequate
estimates of reliability (coefficient alpha), and confirmatory factor analysis
supported the structure of each measure (see Au, 1998, for details). The scales
covered five major domains: prior academic failure, learned hopelessness, attribution style (internality, stability, globality, entity conceptions of intelligence), affective attributes (self-efficacy, school values, self-esteem) and learning (learning
strategy effectiveness and academic achievement).
Prior Academic Failure Scale
This 14-item instrument, constructed by the first author, was used to assess participants’ experience of academic failures. The items of the measure were constructed
with reference to junior secondary students’ responses elicited in open-ended questions. Students were asked to rate the frequency of the occurrence of these events in
the last six months on a five-point Likert scale assessing students’ learning difficulties encountered in learning and negative performance feedback received from
teachers in the subscales, namely Learning Difficulties Scale and Negative Feedback
Scale.
Learned Hopelessness Scale
The eight-item Learned Hopelessness Scale was designed after Beck’s Hopelessness
Scale (Beck, Weissman, Lester, & Trexler, 1974), which was originally developed to
measure an individual’s negative expectations about the future. Beck’s scale was
adapted with local modifications to make it appropriate for the present study to assess
the students’ level of learned hopelessness in the academic context. The modifications
included specifying students’ negative expectations about performance outcomes only
in the academic context and using a five-point Likert scale so that the response format
was consistent across the instruments and the students’ individual level of academic
hopelessness could be distinctively assessed.
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131
Academic Attributional Style Scale (AASS)
This instrument was used to measure students’ academic attributional style for
academic failures in terms of causal dimensions of internality, stability and globality.
Academic attributional style refers to one’s general tendency to attribute academic failures to causes that are stable in time, global in effect and internal to oneself. The
measure was designed after the Attributional Style Scale (Peterson & Barrett, 1987)
except that it presents hypothetical scenarios depicting only academic failure situations
modified locally to ensure sufficient coverage and relevance to the Hong Kong culture
for Chinese junior secondary students. Academic Attributional Style Scale (AASS)
consisted of three subscales, Causal Internality Scale, Causal Stability Scale and Causal
Globality Scale, respectively, representing internality, stability and globality dimensions of academic attributional style. In the AASS measure, students were asked to read
hypothetical scenarios of five different academic failure situations. For each hypothetical scenario of academic failure, students were asked to imagine it happening and circle
the best possible one of the causes given for each failure. Then, they were asked to
rate their attributional choice on a seven-point Likert scale assessing the causal dimensions of internality, stability and globality as postulated by Abramson et al. (1989).
Entity Conception of Intelligence Scale
The Entity Conception of Intelligence Scale, adapted from Hau (1992), was used to
measure students’ implicit beliefs of intelligence. Items of the scale are designed to
elicit students’ beliefs in source of intelligence (inborn or effort), globality of intelligence and effects of effort on intelligence. Students were asked to rate their opinions
on entity conception of intelligence on a five-point Likert scale. For example, ‘intelligence is inborn, and is not obtained by effort.’
There were three affective scales:
(1) School Values Scale. To assess school values, the measure of Eccles et al.
(1983) was adapted to refer to school learning in general. Students reported
their beliefs about school values in terms of the utility of school learning, the
importance of school success and their interest in schoolwork. For example,
students answered the question, ‘school success is very important to me.’
Students responded to each item on a five-point Likert scale, with higher
scores indicating greater school value.
(2) Self-efficacy Scale. The Self-efficacy Scale developed by Pintrich and De
Groot (1990) was adapted to assess students’ perceived academic competence.
Nine statements of the form, ‘I am certain I can understand the ideas taught in
the class,’ were used. Students responded to each item on a five-point Likert
scale, with high scores indicating higher self-efficacy.
(3) Self-esteem Scale. Rosenberg’s (1965, 1979) Self-Esteem Scale was adapted
to measure students’ global self-concept. Typical items include ‘I feel that
I have a number of good qualities,’ ‘I am able to do things as well as most
people’ and ‘I take a positive attitude toward myself.’ The scale was slightly
modified by expanding the four-point format to a five-point Likert scale to
keep the consistency of the response format across the instruments.
There were two learning scales, one related to cognitive strategy use and the other
to academic achievement:
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R.C.P. Au et al.
(1) Learning Strategy Effectiveness Scale. This scale consists of five items,
adapted from the cognitive strategy use of Pintrich and De Groot (1990), to
measure students’ use of cognitive strategies which include rehearsal strategies, elaboration strategies and organisational strategies.
(2) Academic Achievement. Academic achievement was measured by collecting
data from school records on student performance in Chinese, English and
Mathematics in actual examinations. These three academic subjects were
chosen because they represented students’ academic achievement in secondary
school, most used to make decisions about student future schooling placements, and were often assessed by the Education Department of Hong Kong.
Of course, there are many other subjects in school of import, but these three
tend to dominant the curricula in Hong Kong.
Procedure
All the questionnaires were administered by the teachers to all students twice, at the
beginning and at the end of a full academic year. The questionnaires were answered
anonymously to encourage truthful responses. A unique number assigned to each
student in a class was used to identify students’ responses for the second wave. For all
scales, the administrators emphasised that students should read and respond to each
item solely on the basis of how that item applied to his or her opinions and feelings
about school learning. Students completed the questionnaires in 40 minutes under
normal test and classroom conditions.
Structural equation modelling (SEM) was used in this longitudinal study, as it
can account for the causal influence of a variable on itself over time (i.e. an autoregression effect), while testing models about latent variables. Two SEM models were
estimated. As the focus of this study is learned hopelessness and achievement, then
Model 1 relates all the dimensions to hopelessness and achievement at Time 2 and
Model 2 only includes those dimensions that were found to be statistically significant.
This two-step process allows a test of all measures and then whether the reduced
model is appreciably more parsimonious in predicting hopelessness and achievement.
These models can be assessed using a range of goodness-of-fit measures (e.g. RMSEA
< .05, GFI > .90). It is important to note that the aim of this study was more about
prediction than tight explanation, and lesser goodness-of-fit is acceptable provided
that the paths are statistically significant and that the second model explains more of
the variance than the first stability model. LISREL was used for these analyses
(LISREL 8.3; Joreskog & Sorbom, 1998).
Results
The means and standard deviations, estimates of reliability (alpha) and stability
(test–retest) fit the expected measurement models for all instruments (N = 741 on
both occasions). The prior academic failures measurement model specified two
factors, and the academic attribution styles specified three factors. For both sets of
scales, a restricted model was estimated with each item only expected to load on its
own factor. In all other cases, a single factor was specified. In all cases, there is
evidence to assume that each factor is unifactorial. The estimates of reliability and
stability are also sufficiently convincing to provide confidence when using these
scales. Similarly, the size of the item factor loadings on each factor (not shown here
Educational Psychology
Table 1.
Means, standard deviations, estimates of reliability (alpha) and stability (test–retest).
Time 1
Mean
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133
SD
Time 2
Mean
SD
Learned hopelessness
1.71
.70 2.11
.87
Prior academic failures
Learning difficulties
3.31
.74 3.39
.71
Negative feedback
3.31
.74 3.39 3.39
Academic attributional styles
Causal internality
4.85 1.02 4.70 1.05
Causal stability
4.70 1.05 3.85 1.35
Causal globality
3.48 1.37 3.85 1.35
Entity conception of intelligence 1.99
.77 2.28
.83
School values
3.42
.79 3.45
.62
Self-efficacy
1.89
.66 2.09
.76
Self-esteem
2.68
.68 2.74
.74
Learning strategy effectiveness
3.45
.88 3.41
.86
Academic achievement
92.55 50.63 92.03 50.57
Alpha
T1 T2 Test–retest RMSEA
.87 .89
.54
.77 .77
.77 .89
.62
.71
.028
.034
.038
.79
.83
.73
.71
.80
.89
.74
.81
.93
.82
.81
.77
.75
.81
.90
.77
.78
.93
.52
.50
.44
.55
.54
.58
.61
.63
.97
.046
.060
.019
.026
.039
for space reasons) provides much confidence of the measurement models at each
occasion (see Table 1).
While not the major focus of this article, it is noted that the effect sizes (ES) for
the change over time were negligible (average ES = .02). The greatest increase was
for causal globality (.22) and decreases were for causal stability (−.53) and causal
internality (−.11). All other changes had small effect sizes between −.1 and .1.
The stability model
This first model only specified paths between the respective Time 1 and Time 2 latent
factors. That is, learned hopelessness at Time 1 was only free to relate to hopelessness
at Time 2 and so on (Figure 1). As expected, these stability coefficients closely mirror
the test–retest correlations. The RMSEA was .035, GFI = .738, TLI = .830 (Chisquare = 17,568, df = 9720). The paths over time indicate much stability. These fit
indices are low, but this was expected, as there are no cross-parameters over time
(latent variables at Time 1 only relate to its partner at Time 2), and thus not surprisingly there is much variance–covariance unexplained. The stability of achievement is
much greater than the other affective–motivational variables. Prior achievement, not
surprisingly, is clearly the best predictor of later academic success.
The personality model
In this second model, a series of paths were estimated that allowed for the most
statistically significant paths to be added to the stability model. First, the path from
achievement at Time 1 to Time 2 was omitted so as to evaluate which is the next
most powerful set of predictors. Second, the next highest path between Time 1 and
Time 2 constructs was entered into the model (using modification indices). As the
modification indices are 1 degree of freedom statistics, it is only meaningful to allow
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one path at a time to be estimated and the modification indices re-estimated. This
was continued until no modification index was greater than 10 (a most conservative
cut point).
Figure 2 presents the final solution. The fit indices for this model were RMSEA =
.035, GFI = .737, TLI = .827 (Chi-square = 17,681, df = 9701). Like the fit for the
stability model, there is still much variance–covariance to be explained, and much of
Figure 2. Cross paths between the learning, attributional, affective and achievement latent
variables over time.
Educational Psychology
135
this is because we intentionally did not fit a path between achievement over time (or
allow paths between the constructs at Time 2). The differences in chi-square relative
to differences in their degrees of freedom for these two models show that they are very
similar. It is perhaps not too surprising that these two models are very similar in fit.
The suggestion is that the various paths between the personality variables over time
explain similarly to what achievement can predict from one time to another. Clearly,
prior academic achievement is not only a powerful predictor of later academic
achievement but can also explain as much as the personality variables included in this
study. On the other hand, the paths between these personality variables suggest some
powerful ways by which educators may be able to influence achievement.
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Figure 2. Cross paths between the learning, attributional, affective and achievement latent variables over time.
Discussion
This research aimed to investigate how various risk factors and deficits developed
over time in school and whether they could explain more variance in later achievement than prior achievement. The context of Hong Kong schools was particularly of
interest, given the high press for achievement success, the importance placed on
education by parents, the pressure to succeed and blame failure on lack of effort, and
the very competitive and all pervasive examinations system.
As expected, prior achievement was the best predictor of subsequent achievement,
nothing surprising here. Other learning, attributional and affective variables pale in
significance compared to the effects of prior achievement. When we remove prior
academic achievement, however, then the best predictors are perceived learning difficulties and learning strategies. The greater these learning difficulties, the higher the
entity concept of intelligence which then translates into lower academic achievement.
Students who receive negative feedback at Time 1 were more likely to have lower
self-efficacy and self-esteem, and an entity conception of intelligence at Time 2.
Higher school values lead to greater causal internality at Time 2. That is, the greater
the students perceive the value of school, the more the attributional to the student not
to outside influences, and the converse – the lower the value of schooling, the more
attributions are to others. In terms of attributional style, the greater the students see
their achievement is a function of others and not themselves (e.g. effort), then the
higher the later levels of learned hopelessness, learning difficulties and lower selfesteem. Students who have an entity level of intelligence (i.e. fixed and stable) are
more likely to have a lower causal stability, and lower levels of self-efficacy and selfesteem. This indeed paints a depressing picture.
In terms of direction, learned hopelessness is less of a powerful predictor of subsequent achievement but is the consequence of lower achievement. The effects of
learned hopelessness are causal one way – from lower achievement to greater hopelessness. Hopelessness is more an outcome of lower achievement, but its consequential effects (low hopelessness, low achievement) are a recipe for disengagement from
schooling. This then can lead to other negative attributes such as causal internality
(e.g. ‘Is the cause of failing in understanding something related to you or is it something related to other people or circumstances?’). The statistically significant path
from causal internality to learned hopelessness reinforces this notion that the student
takes on most responsibility for their failing. When students experience declines in
academic achievement, it can feed a belief of ‘hopelessness’. It is likely that such
hopelessness then leads to beliefs as expressed in the ‘learning difficulties’ factor, and
the spiral of lowering achievement and affect to schooling and learning is set.
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R.C.P. Au et al.
It seems important for teachers and parents to devise triggers to intervene into this
self-fulfilling spiral, as it is likely that many of the other more negative attributions
and affective attributes may contribute to the feelings of hopelessness. Certainly, it is
likely that teachers who attend to factors such as engagement in learning and who
deliberately set out to invite students to participate in learning that involves appropriately challenging tasks are more likely to decline in hopelessness. The power of feedback, peer involvement and collaboration, understanding learning intentions and
knowing success criteria, and teaching learning strategies can reverse the disengagement (Hattie, 2009). There is also much research on the effects of teachers’ behaviours
on students (they are to be seen by students as causal agents in success often via
formative feedback) and the power of high and positive teacher expectations on
subsequent performance. It is likely that students who perceive difficulties in their
learning can readily find evidence to support their perceived difficulties, and thus lead
to lower academic performance. If provided with alternatives to these difficulties,
such as more effective teaching, an environment to admit ‘I don’t know’ and thence
receiving assistance, this lack of engagement can be mediated. Certainly, the structural model indicates that these students also build a fixed model of ability – that
achievement is more related to natural ability and not to their effort – a major barrier
to enhancing their learning but one that can readily be supported in high competitive,
external examination oriented and pressure classrooms.
The model of learning hopelessness can be of high value to better understanding
the processes that lead to the disengagement of students from schooling. This should
not mean that these students have lower self-efficacy, failure or lack strategies in other
than school achievement domains. Indeed, many use their skills and intelligence in
other, often non-socially conforming ways (Carroll, Houghton, Durkin, & Hattie, 2009).
It is incumbent on schools to maintain high levels on inviting students to be a part of
school learning, to make the relevance of what is being taught an integral part of students
sense of their own well-being and future, and not set up structures that led to some
‘failing’ via an examination system more oriented to selecting for further schooling or
job employment, that is, not if a society wishes to harness the socially optimal ways
of schooling its citizens. Learning hopelessness is a depressive, serious and alienating
condition, and this study shows that there can be ways for schools (and parents and
peers) to be aware of its existence, effects and create conditions to prevent its existence.
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