INFLUENCES ON STUDENT LEARNING
John Hattie
Inaugural Lecture: Professor of Education
University of Auckland
August 2, 1999
I welcome the opportunity to speak to my colleagues and friends on the
research I wish to undertake during my next years here at the University of
Auckland. This is my third Inaugural lecture since I became a Professor 15
years ago, hence I have learnt to take this opportunity seriously and cast a
vision, as there are so few opportunities to talk to colleagues one’s own
esoterica and passions. Maybe it is that I just need to do the same thing three
times to at least say something, and I know my family has therefore renamed
these my ‘Ignorable Lectures’. I do know that the fact most remembered from
my first was that it was the first time that the chair Michael Scriven and the
presenter presented an Inaugural and both did not wear ties. The fact from
the second in North Carolina was that it was scheduled at the same time as
the Simpson jury read its verdict.
We know that students in lectures learn most in the first 8 minutes, only recall
three things at most after one hour, and that if the content does not shake
their prior beliefs they file away the fascinating facts in the deepest recesses
of their brain, if at all.
Hence, my aim tonight is to wax lyrical about my research projects, to build a
theme around my measurement issues that have impact on students, to
explain that about which I have much passion, and to give you three
fascinating facts.
Too much is known
There is so much known about what makes a difference in the classroom. A
glance at the journals on the shelves of most libraries, my colleagues’
shelves, and on web pages would indicate that the state of knowledge in the
discipline of education is healthy. The worldwide picture certainly is one of
plenty. We now can have a library solely consisting of Handbooks, most of
which can not be held in the hand. Given this bounty, it would seem
remarkable that there is much left to say. That never stopped an academic.
There are at least three things to say:
• We constantly bemoan the lack of integrative reviews and typically
blame methodology;
• The methodological war hinders us seeing the stories in each others
work;
• We have few integrative, bold and verifiable models of student
learning, preferring to study one variable at a time, occasionally
investigating interactive effects, too often look at classrooms through
unfocused eyes, and rarely combine the texture of the learning
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experience with the rigour of asking whether there is an impact on
student learning.
This lack has not stopped us studying our pet beliefs. I must note that this
love of pet belief is matched in classrooms, and herein are the three truths of
research in classrooms:
Teachers/Researchers have models of learning that are rarely
externally elaborated or asked for
2. Teachers/Researchers seek evidence to buttress their models of
learning and thus rarely seek to refute them or introduce major
changes
3. There are no bad Teachers/Researchers.
1.
We all seek positive evidence in that which we love. Teachers/Researchers,
like lovers, are often blind.
Hence, we have a school community peopled with teachers with self-fulfilling
prophecies, all believing they are doing a good job, and with models of
learning rarely based on any other evidence than "it works for me". As well we
have an educational research community peopled with academics chasing
their pet theory, promoting their own methodology while passing each other in
corridors, rarely asking for negative evidence, and pushing with passion that
"if only the teachers would do this, or know that". Both educational
communities work behind closed doors, coming out to discuss kids, curricula,
accountability, and each other, but rarely discussing the fundamental tenets
about their teaching that leads to positive impacts on student learning.
I believe the first step to resolve this dilemma is basic, simple, and powerful,
and has taken me 10 years to build, and am still going.
My three principles are:
•
•
•
We need to make relative statements about what impacts on student
work
We need estimates of magnitude as well as statistical significance – it
is not good enough to say that this works because lots of people use it
etc., but that this works because of the magnitude of impact
We need to be building a model based on these relative magnitudes of
effects.
A model of effects on school and teaching
A model of teaching and learning is proposed that is based on three
postulates. In this session I wish to outline the model and the kinds of data
that are being used to support it.
•
•
That achievement is enhanced to the degree that students and
teachers set and communicate appropriate, specific and challenging
goals
That achievement is enhanced as a function of feedback.
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•
That increases in student learning involves more than surface and
deep learning but also follows a reconceptualisation of information.
A model of effects on school and teaching
•
•
•
Achievement is enhanced to the degree that students and teachers set
and communicate appropriate, specific and challenging goals
Achievement is enhanced as a function of feedback
Increases in student learning involves not only surface and deep
learning but also a reconceptualisation of information.
Let me defend these simple propositions.
MEASURING THE EFFECTS OF SCHOOLING
A major purpose of this Inaugural is to show how the data from the past 30
years of educational research can be used to assess the effects of
innovations and schooling, to provide insights for future innovation, and
provide reasons why different advocates make apparently contrary claims
about the effectiveness of schooling (even using the same data) by
demonstrating how different points of comparison are used by each group.
The beginning of the answer to the question as to the effects of schooling is
to ask, "What are the 'typical' effects of schooling?" and then to use this
typical effect as a benchmark. The problem is how to ascertain "typical
effects" given the myriad of effects on schools, different teachers, subjects,
school administration systems, ages of students, and other moderators such
as gender, prior ability, quality of instruction and teaching styles.
The first requirement is a continuum on which the effects of schooling,
including the typical effect, can be summarised where 0 means that there is
no effect from introducing some teaching package, innovation, or effect on
schooling. A negative effect indicates that the innovation has a decreased
effect on achievement, and a positive effect indicates that the innovation has
as increased effect on achievement. For the present, the model is
constrained to achievement outcomes, but the continuum can be generalised
to other outcomes of schooling, and I have also undertaken a similar
continuum for special education students.
The next requirement is to formulate an appropriate scale and it is
recommended that the scale is expressed in effect-sizes. An effect-size
provides a common expression of the magnitude of study outcomes for all
types of outcome variables, such as school achievement. An effect-size of 1.0
indicates an increase of one standard deviation, typically associated with
advancing children's achievement by one year, improving the rate of learning
by 50%, or a correlation between some variable (e.g., amount of homework)
and achievement of approximately .50. When implementing a new program,
an effect-size of 1.0 would mean that approximately 95% of outcomes
positively enhance achievement, or average students receiving that treatment
would exceed 84% of students not receiving that treatment. Cohen (1977)
argued that an effect-size of 1.0 would be regarded as large, blatantly
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obvious, grossly perceptible, and he provided examples such as the
difference between mean IQ of PhD graduates and high school students (we
hope). The use of effect-sizes highlights the importance of the magnitude of
differences, which is contrary to the usual emphasis on statistical significance.
Cohen (1990) has commented that "under the sway of the Fisherian scheme
(or dependence on statistical significance), there has been little
consciousness of how big things are. ... science is inevitably about
magnitudes" and the use of effect-sizes makes a welcome force towards the
cumulation of knowledge" (p. 1310).
For example, it was possible to locate 31 meta-analyses, 17952 studies, and
352 effect-sizes studies that investigated the effects of introducing computers
on students' achievement (see Hattie, 1986). Using meta-analysis, these
effects can be statistically synthesised to ascertain an overall effect as well as
assessing the influence of differing groups of students (e.g., males versus
females), different uses of computers, subject areas, and so on. The average
effect-size across these 557 studies was .31.
Thus, compared to classes without computers, the use of computers was
associated with advancing children's achievement by approximately three
months, improving the rate of learning by 15%, about 65% of the effects were
positive (that is, improved achievement), thus 35% of the effects were zero or
negative, and the average student achievement level after using computers
exceeded 62% of the achievement levels of the students not using
computers. An effect-size of .31 would not, according to Cohen (1977), be
perceptible to the naked observational eye, and would be approximately
equivalent to the difference between the height of a 5'11" and a 6'0" person.
Of course, this is only an overall effect-size from introducing computers,
although contrary to many beliefs the variability around these effects is quite
small. There are many important moderators. For example, the effects
decrease with age: primary students gain most (effect-size = .48), secondary
students have medium gains (effect-size = .32), and college and university
students gain least (effect-size = .25); there are differences in effect-sizes on
achievement between males and females in secondary but not elementary
classes (see Fitzgerald, Hattie, & Hughes, 1985; Hattie & Fitzgerald, 1987).
Compared to not having computers in schools (effect=0) computing can help.
Herein lie three major themes:
•
•
•
we can synthesis seemingly disparate studies to make an overall
conclusion;
diverse studies can be systematically integrated to address the
question of the magnitude of effect;
we can then determine those variables that may moderate this overall
effect.
There is a critical step missing here to build a defensible model of student
learning. It will turn out that there are very few influences in education that are
overall negative; hence it seems there is evidence for every teachers’ pet
theme – and this is too close to reality. So to the missing step.
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The missing step is that the comparison should NOT be to zero point; we
must not compare having computers to not having computers, we must not
compare ourselves as teachers to not having us, but we must compare
innovations to other innovations.
I suggest to you that the synthesis of many studies can provide the normative
effect to which other can be compared.
Over the past 10 years I have been accumulating studies, and now have 337
meta-analyses, 200,000 effect-sizes from 180,000 studies, representing
approximately 50+ million students, and covering almost all methods of
innovation.
The key question is "What is the typical effect of schooling"? The answer is
derived from averaging the effects across the 357 meta-analyses and is .40
(with a se= .05).
Most innovations that are introduced in schools improve achievement by
about .4 of a standard deviation. This is the benchmark figure and provides a
"standard" from which to judge effects. A comparison based on typical, realworld effects rather than based on the strongest cause possible, or with the
weakest cause imaginable. At minimum, this continuum provides a method
for measuring the effects of schooling.
The typical effect does not mean that merely placing a teacher in front of a
class would lead to an improvement of .4 standard deviations. Some
deliberate attempt to change, improve, plan, modify, or innovate is involved.
The best available estimate as to the effects of schooling not based on
innovations is from the National Assessment of Educational Progress (NAEP)
data bank (Johnson & Zwick, 1990). NAEP surveyed what students in
American schools knew and could do in the subject areas of reading, writing,
civics, US history, mathematics and science. The students were sampled at
ages 9, 13 and 17, and the testing has been repeated every two years. The
average effect-size across the six subject areas was .24 per year, which
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indicates that the effects of innovations is (.40-.24 =) .16 standard deviations
above and beyond the teacher effects. A further contention of many
researchers is that maturation alone can account for much of the
enhancement of learning. The effect of maturation is probably about one-third
of the achievement effect (.10; see Cahen & Davis, 1987). Schooling does
enhance learning above the influences of maturation.
Hence my three normative comparison points:
Normative comparison points
•
•
•
student maturation
a teacher in front of a classroom
innovations in schooling
.10
.24
.40
The obvious – schooling makes a difference – contrary to the Coleman study,
and possible contrary to the Harris argument about the power of peers over
parents and teachers – although I keenly await the results of my colleagues
Ian W, Mike T, Judy P, Charlotte and Irene and others who are working on
the peer influences literature review as part of a grant, at present.
COMPUTERS. Let me return to computers and now compare their effects
with other influences — then they are just in there. So, out with the computer
salespeople who push computers as the magic answer — yes, compared to
not having them they have an influence, but compared to other influences a
different conclusion can be made — there are not so influential.
Let me show you an example of the innovations that are below the typical
effect.
OVERALL EFFECTS
No. of
Effects
165,258
Peers
Advance organizers
Simulation & games
Computer-assisted instruction
Instructional media
Testing
Aims & policy of the school
Affective attributes of students
Calculators
Physical attributes of students
Learning hierarchies
Ability grouping
Programmed instruction
Audio-visual aids
Individualisation
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122
387
111
566
4421
1817
542
355
231
905
24
3385
220
6060
630
August 2, 1999
Effect-Size
.40
.38
.37
.34
.31
.30
.30
.24
.24
.24
.21
.19
.18
.18
.16
.14
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Finances/money
Behavioural objectives
Team teaching
Physical attributes of the school
Mass media
Retention
No. of
Effects
658
111
41
1850
274
861
Effect-Size
.12
.12
.06
-.05
-.12
-.15
RETENTION
The effect is among the very lowest of many possible innovations and it can
be vividly noted that retention is overwhelmingly disastrous across many
educational interventions at enhancing academic achievement. This topic is
fascinating to me. Last year I was an expert witness for the NAACP in a
Federal Court Case arguing that retention had a particularly invidious impact
on African American children, I have been awe-stuck at the number of
teachers who fundamentally believe retention is justified ("if you could only
give me more time"), and reiterate to you that these defenders compare the
potential impact of holding the student back a year because of a belief that
the difference between the start of the grade and end of the grade could
increase not appreciating that the comparison is the start of the grade with
the performance of similar students who are now tested at a higher grade.
The groups of non-promoted/retained students scored .15 to .26 standard
deviation units lower than the promoted comparison groups on the various
outcome measures:
•
•
•
•
After one year the retained groups were scoring .45 standard deviation
unit lower than the comparison groups who had gone on to the next
grade and in many cases were being tested on more advanced
material. Each subsequent year this difference became larger with the
difference reaching .83 standard deviation unit for measures taken four
or more years after the time of retention.
Being retained one year almost doubled a student’s likelihood of
dropping out, while failing twice almost guaranteed it.
The negative effects are pervasive over all academic and personal
educational outcomes, and at all ages (including kindergarten)
There is a consistently negative picture of the association between
retention and race, gender, SES, and school outcomes.
Those who continue to retain pupils at grade level do so despite cumulative
research evidence showing that the potential for negative effects consistently
outweighs positive outcomes.
It would be difficult to find another educational practice on which the
evidence is so unequivocally negative (House, 1989).
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CLASS SIZE
The research on the effects of class size has been among the more
voluminous in educational research with very systematic findings:
•
•
•
Achievement, attitude, teacher morale, student satisfaction gains are
appreciable in smaller classes, so long as we recognise that small
classes mean 10-15, as there are negligible gains between 40 to 20
students per class.
This effect was the same for primary and secondary schools, across all
subjects, and across various ability levels.
There is little evidence that instruction methods change when class
size is reduced, although a large part of improvement can be explained
by improvements in student task engagement.
Reducing class sizes from the 30’s to the 20’s is in the right direction, but
there is little support for the claim that there are increases in student
achievement or satisfaction, or teacher attitude or morale. Only when the class
size reduces to 15 or below are there appreciable positive benefits.
TELEVISION
This is one of the few non-linear effects. Less than 10 hours per week is
associated with increases in achievement, more than 10 hours with
decreases – but show me a New Zealand child who watches less than 10
hours per week.
And this table provides examples of influences above the average.
OVERALL EFFECTS
No. of
Effects
165,258
Reinforcement
Students prior cognitive ability
Instructional quality
Instructional quantity
Direct instruction
Acceleration
Home factors
Remediation/feedback
Students disposition to learn
Class environment
Challenge of Goals
Bilingual programs
Peer tutoring
Mastery learning
Teacher in-service education
Parent involvement
Homework
Questioning
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139
896
22
80
253
162
728
146
93
921
2703
285
125
104
3912
339
110
134
August 2, 1999
Effect-Size
.40
1.13
1.04
1.00
.84
.82
.72
.67
.65
.61
.56
.52
.51
.50
.50
.49
.46
.43
.41
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Five overall findings from these positive effects:
•
•
•
•
•
critical innovations
feedback
setting of appropriate, specific and challenging goals
It is what some teachers do that makes the difference; and
The introduction of most teaching and school influences merely
impacts on the probability of the presence of feedback and challenging
goals.
First, innovation is the theme underlying most of these effects. That is, a
constant and deliberate attempt to improve the quality of learning on behalf of
the system, principal and teacher typically relates to improved achievement.
The implementation of innovations probably captures the enthusiasm of the
teacher implementing the innovation and the excitement of the students
attempting something innovative. Often this has been explained as an
experimental artifact in terms of a Hawthorne effect. No matter the reason, it
appears that innovation per se can have positive effects on students’
achievement. Teachers who constantly question "How are I going", who wish
to verify that their methods are having impacts on student learning are the
prerequisites for excellence.
I highlight this innovation and willingness to try new methods particularly as
too many classes involve listening, mimicking, copying, and learning how to
survive the information overload.
Second, the most powerful single moderator that enhances achievement is
feedback. The simplest prescription for improving education must be "dollops
of feedback" -- providing information how and why the child understands and
misunderstands, and what directions the student must take to improve.
The most fundamental component of teaching is imparting information to
students, assessing and evaluating the students understanding of this
information, and then matching the next teaching act to the present
understandings of the student.
This is not feedback in the behavioural sense of input/output models, but the
understanding of the constructions that student have made from the
information. Feedback is the information component whereas reinforcement
is the evaluative component relating to information and motivation. For
example:
•
•
•
•
•
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reinforcement
corrective feedback
remediation and feedback
diagnosis feedback
mastery learning (which is based on feedback)
August 2, 1999
1.13
.94
.65
.52
.50
Page 9
Although not all forms of feedback are as effective, for example:
•
•
•
extrinsic rewards
immediate vs. delayed
punishment
.37
.28
.20
There is a contrast here in the old fashioned notions of intrinsic and extrinsic
rewards, although the better jargon now is task vs. ego involvement.
a. There are many ways in which teachers can deliver feedback to
students, and for students to receive feedback from teachers, peers
and other sources. The implication is NOT that we should
automatically use many tests and provide over-prescriptive directions.
Rather, it means providing information how and why the child
understands and misunderstands, and what directions the student
must take to improve. Tests can perform this function but too often
they are devoid of much feedback to the students and thus can be an
inefficient method of providing feedback.
b. The incidence of feedback in the typical classroom is very low, usually
in seconds at best per day. Ask yourself how much feedback there is in
the typical lecture – yes, imparting information is there, but how do you
know it is appropriately challenging, that the student shares or even
understands the specific goals, and how do you provide appropriate
information about what directions the student must take to improve
their understanding. Perhaps it is no surprise to note that students who
survive university undergraduate degrees are those with impeccable
surface and not deep strategies, those who learn to be flexible to the
instructors assessment demands which so often value information and
not understanding, and that the students with the more deep, critical,
and passionate learning strategies have the highest probability of not
completing our degrees.
c. It is likely that the information function of feedback for an individual
may be too diluted in a regular classroom to afford much control over
behaviour for special education students.
d. Reducing class size, prescribing more homework, introducing more
computers, etc. merely offers increased opportunities for more
feedback and appropriately challenging goals to occur - it does not
guarantee it occurs.
e. It is predicted that programs that do not capitalise on effective
classroom management practices to optimise feedback will not be
successful. One example is individualised instruction. Individualisation
programs produce an average effect-size of .14, and programmed
instruction yields .18. Too often, individualisation means placing the
child alone to work on a particular task, usually relating to his or her
particular needs, progress, pace, and behaviour. These attempts
usually have little feedback, little attention by a busy teacher catering
to the other 30 or so students, and the student typically has little
knowledge of success or failure at the specifics of the task. Teachers
need excellent management systems with classes greater than 20, and
superb management systems with classes greater than 30. To
introduce individualisation with 30 students means that, at best, a
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single student can only receive seconds of a teachers’ time per day,
minutes of a teachers’ time in preparation, and merely passing
glimpses of time in feedback - no matter how noble the intentions of
the teacher. It is neither efficient nor effective to individualise
instruction for 30 students, expect high competence in the
management of such programs, and provide feedback to all students.
Individualisation in regular classes must fail and does fail. The
negligible effects of individualisation are particularly important when it
is recognised that students spend about 66 percent of their time
working alone (Rosenshine, 1979).
Feedback effects on performance are primarily via cues that direct
attention to the task-motivation processes, particularly when coupled
with information regarding erroneous hypothesis. The fewer the
cognitive resources needed for a task and the more the feedback is
directed at the task demands and not the person then the more
powerful the feedback.
If we, as teachers, are to have an impact on learning, then we must come to
know what our students are thinking so that we can provide more feedback,
task information, encourage trial and error, and develop deep understanding
and transformations.
Third, achievement is enhanced to the degree that students and teachers set
challenging rather than "do your best" goals relative to the students' present
competencies. Goals need to be specific, challenging, and it helps if the
students are committed to these goals -- although it is the challenge that
is most critical (Locke & Latham,1992).
Never allow a student to "do their best" as this is the goal with the least
challenge; everything the student does can be claimed as the best!
Appropriate, challenging, and specific goals inform individuals "as to what
type or level of performance is to be attained so that they can direct and
evaluate their actions and efforts accordingly. Feedback allows them to set
reasonable goals and to track their performance in relation to their goals so
that adjustments in effort, direction, and even strategy can be made as
needed" (Locke & Latham).
•
•
•
•
•
•
They direct attention to relevant tasks or outcomes
They energise task performance
They motivate individuals to persist in their activities through time
They convey normative information by suggesting or specifying what
level of performance the student could be expected to attain
They have dramatic effects on the development of self-efficacy, which
in turn affects the choice of difficulty of goals
Feedback without goal setting is less effective, and goal setting without
feedback is ineffective.
A combination of goal setting plus feedback is most effective = goals
and challenging goals are mutually supportive. The greater the
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challenge the higher the probability of the student seeking, receiving,
and assimilating feedback information.
The scenario is that effective teachers set challenging goals and then
structure situations so that students can reach these goals. If teachers can
encourage students to share commitment to these challenging goals, and if
they provide much feedback, then goals are more likely to be attained.
A good example is the effectiveness of Outward Bound programs to enhance
self-esteem. Of the many self-esteem programs, one of the most effective are
the Outward Bound programs (Hattie, 1992). In these programs, a common
feature is the setting of seemingly very difficult goals (e.g., abseiling), and
then structuring the environment so that students can attain these goals,
while providing much informative feedback. Further, the instructors remove
many of the possibly irrelevant tasks so that students focus on these
challenging goals.
Fourth, it is teachers that make the difference. Let me go back to the big
picture, and re-order the effects into those that are school policy and
structural effects, social, home, what the student brings, teacher methods,
and learning process related. The bold are those effects greater than the
average. It is clear that structural and social influences are minor, what the
student brings in terms of achievement and disposition to learn are powerful,
teaching process are paramount, and the teacher methods are there – this
must lead to the conclusion that, yes teachers make the difference, but only
teachers who teach in certain ways.
Too many teachers compare what they are doing with them not being there;
they compare their methods with not using that method; whereas teachers
need to be more informed evaluators/consumers of teaching methods. Like
their students they must set challenging goals, seek feedback on the
effectiveness of their teaching on students, and constantly be attention to
improvement and innovating the methods which optimise feedback and
meeting challenging goals.
Influence
Teacher process influence
Reinforcement
Instructional quality
Remediation/feedback
Challenge of Goals
Teacher methods
Direct instruction
Class environment
Peer tutoring
Mastery learning
Homework
Teacher Style
Questioning
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August 2, 1999
Effect-Size
1.13
1.00
.65
.52
.82
.56
.50
.50
.43
.42
.41
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Influence
Effect-Size
Advance organisers
Simulation & games
Computer-assisted instruction
Instructional media
Testing
Programmed instruction
Audio-visual aids
Individualisation
Behavioural objectives
Team teaching
Student influences
Students prior cognitive ability
Students disposition to learn
Affective attributes of students
Physical attributes of students
Home influences
Home factors
Parent involvement
Social influences
Peer
Television
School Policy Influences
Aims & policy of the school
Ability grouping
Finances/money
Physical attributes of the school
Retention
.37
.34
.31
.30
.30
.18
.16
.14
.12
.06
1.04
.61
.24
.21
.67
.46
.38
-.12
.24
.18
.12
-.05
-.15
Fifth, the major argument is that most of the structural innovations in
schooling are probabilistic – their introduction merely alter the probabilities of
the core effects occurring: these core effects include feedback, appropriate
and challenging goals, and reconceptualisations as well as surface and deep
knowledge.
Hence the five themes:
1. Innovation is the theme underlying most of these effects;
2. The most powerful single moderator that enhances achievement is
feedback;
3. The setting of appropriate, specific and challenging goals is critical;
4. It is what some teachers do that makes the difference; and
5. The introduction of most teaching and school influences merely
impacts on the probability of the presence of feedback and challenging
goals.
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Teachers must be more informed evaluators as they need to ask how their
methods increase the probability of that which makes the difference –
information, reconceptualisation, feedback, and appropriate goals.
I must note that
•
•
•
•
•
These findings along the continuum have remarkable generality,
across subjects, and ages. Generality is the norm.
Aptitude treatment interactions are noted by their absence. God must
love main effects.
Attempt to individualise instruction are not noted by success.
Individualisation programs produce an average effect-size of .14, and
programmed instruction yields .18. The negligible effects of
individualisation are particularly important when it is recognised that
students spend about 2/3rds of their class time working alone.
These studies have been undertaken primarily on children in western
countries. Academic achievement in low-income countries is affected
more by pupils' social status and less by school and teacher quality,
whereas the converse is the case in high-income countries like New
Zealand.
I have expanded this meta-analysis from achievement to attitudes and
a separate table for special education teachers – with similar
conclusions.
Thus, I hope I have
•
•
•
Demonstrated the power of meta-analysis, and research synthesis to
address the more critical questions in education – I have spent much
research time synthesising these studies, finding major gaps and then
filling it with my own meta-analyses – for example on study skills, outof-school experiences, self-concept, and my current one is on the
effects of ADHD/ADD medication on learning
Demonstrated the power of assessing magnitude rather than statistical
significance – which is one of my fascinations.
And identified that which makes the difference on student learning.
So far the prescriptions for influencing student learning are clear:
dollops of feedback, specific and challenging goals, and a constant
attention to asking, "How am I going".
There is at least one major complicating factor.
The inherent nature of learning is that there is a gap between the feedback
and the attainment of goals. There are four possible ways for students to
reduce this gap:
•
•
Students can increase their effort, although the evidence we find of a
"just-world" that more time in the class or more time studying increases
learning is not convincing.
Students can abandon the standards, and they are doing this in
droves. We are successfully alienating so many students from our
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•
schools, particularly high schools as we promulgate the merits of our
subject cramming and chauvinism, while the students look to their
older peers who are successful in their eyes without that cramming.
We say students must have this knowledge about English when most
of the adult population does not need it; we say students must have
this advanced math when their fellow teachers do not have it and are
successful. Students become not engaged, and do not wish to have
their reputations based on attaining our social conformists goals of
high school-based achievement;
Students can change the standard by setting lower goals in
achievement at school, accepting far below their capabilities as
satisfactory.
More often these drop out effects occur because students reject or reinterpret the feedback information. It is this latter reaction that has so driven
my recent research program.
Students too often have conceptions of learning inbred by years of shallow,
fact-pushing, routine-ised teachers who pride themselves on presenting the
very best content, teaching from the front, sitting tests, prodding students by
external cues such as exams, and valuing themselves in terms of successful
imparting knowledge usually via teaching models akin to drips into empty
vessels.
Students, however, are not inert recipients and build strategies to deal with
this daily grind of the knowledge dump.
Achievement is enhanced to the degree that students develop selfstrategies: to seek and receive feedback to verify rather than enhance
their sense of achievement efficacy.
Although I have spent many years exploring self-concept, this is NOT what I
am talking about. We have demonstrated there is a very low relationship
between self-concept and achievement (less then 4% of the variance), hence
asking causal questions is misplaced. We know much about the
multidimensionality of self-concept, and the age and gender effects etc. but
this has rarely helped us in our understanding of learning. More recently I
have moved towards asking about the relation between learning processes
and self-strategies and conceptions of learning. I do wish to emphasise that
the self-strategies that students have directly leads to enhanced or decreased
performance AND their conceptions of learning they have can lead them to
(mis-) interpret the often excellent teaching they receive – although I do not
intend to purse the conceptions of learning tonight.
There are two major self-strategies that students used when learning:
Self status quo strategies
• the wish to be viewed as one believes one is;
• to do whatever it takes to preserve this concept of self
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by adopting strategies that maximise positive or minimise negative selfevaluations
Self testing strategies
• the seeking of confirmation and/or disconfirmation about conceptions
of self
•
by adopting hypothesis-confirming strategies that allow for the best
opportunities for self-expression.
It is not so simple that we can match the use of these strategies with high and
low self-esteem, as all individuals prefer self-verification but low self-esteem
students have a greater tendency to use self-enhancing strategies:
•
•
•
When students are using self-verification strategies, initial success
signifies a talent or potential ability, whereas for self-enhancement
initial success confirms a deficiency needed to be remedied.
Students using self-verification strategies cope better with
disconfirmation as they can relate to positive and negative verifications
of self. As a consequence of disconfirmation, those who use selfverification make more optimistic predictions about their performance
after initial failure than after initial success, they seek specifically
unfavourable feedback so as to excel at the tasks.
Students using self-enhancement show moderately high persistence at
the task after failure, consistent with the view that they are interested in
remedying their deficiencies in order to reach a passable level of
performance, which would afford them protection against humiliating
failure. Further, they tend to avoid tasks following initial success as
such success signifies that they have already reached an adequate
level of performance, and further tests merely run the risk of
disconfirming the favourable outcome. This can lead to rejection of
success, not because they prefer failure but because success is
disconfirming, may require alterations to expectations, or maybe be
threatening because "they may lack confidence that they can repeat
that success".
Yes, feedback is powerful, but the self-strategies that students develop can
alter the interpretation and consequences of this feedback. Students selfenhance by biasing information and by selecting information that provides
affirmation of their prior beliefs. Providing feedback to students is not enough
- as the ways and manner in which individuals interpret your information is the
key to developing positive and valuable concepts of self.
As has been demonstrated by many researchers, including my own, this is
where cultural factors have a major mediating effect in the teaching-learning
process. We have undertaken these studies in Australia, Hong Kong, Japan,
the USA, and with tertiary, secondary, primary students, and more recently
with groups of males and groups of female juvenile delinquents and teenage
prisoners. Understanding their conceptions of learning and the self-strategies
they have, and how they use these to enhance their reputations is most
powerful. I would conject that there would be powerful self-strategies by many
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Maori and Pacifica students that mediate the reception and assimilating of
feedback offered by Pakeha teachers.
We have been working with nine major strategies.
Nine major strategies
1.
2.
3.
4.
5.
6.
7.
8.
9.
Self-handicapping
Discounting
Social comparison
Disconfirmation
Setting less challenging goals
Setting performance rather than task goals
Self-monitoring
Confirming negative cultural stereotypes
Seeking negative information
Self-handicapping providing a handicap that can be used as an explanation
for maintaining beliefs, and accounting for success or failure that is
inconsistent with prior beliefs.
Example: a student could claim he or she scored 100% on an examination
because the items were too easy rather than because of ability or effort in
learning; or scored lower because of the excellent television program they
watched instead of studying.
Self-handicapping occurs when:
• students have high uncertainty about their competencies
• there is high salience of an evaluative task
• in public rather than private performance situations
• there is an abnormal investment in the question of self-worth
• when the students believe that the handicap will be viewed by others
as a legitimate reason for potential failure
It is used by both high and low self-esteem individuals: high self-esteem
people to enhance success, low self-esteem people to protect themselves
against the threat of failure.
Discounting whereby feedback is "dismissed" as being information that is
not valuable, accurate, or worthwhile for the individual.
Example: when a teacher tells a student that he or she is doing a great job,
and the student’s reaction is to discount this by claiming "she always says
that," "she’s only trying to make me feel good," or "it’s only because it is neat,
not correct".
Social comparison whereby low self-esteem individuals constantly monitor
other peers’ behavior for cues and attributions to explain/enhance their
conceptions of self. They compare themselves with others, and social
comparison sets standards or frames of reference.
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Example: Students often compare themselves to those less fortunate than
themselves, and often attempt to present themselves as more confident to
impress others and maybe even themselves.
Disconfirmation whereby students ignore or reject information that
disconfirms their self beliefs.
Less challenging goals whereby students set less challenging goals and
thus ensure more success and confirmation about their learning.
Setting performance rather than task goals.
Example, students who set performance goals are more concerned with
gaining favourable judgements of their competence, whereas task goals are
more concerned with increasing their competence on the task.
Self-monitoring whereby students actively plan, enact and guide their
behavioural choices in social situations through the process of selfmonitoring. High self-monitors are more dictated to by the external
environment and by social comparison.
Confirming negative cultural stereotypes whereby students absorb
negative societal stereotype about their group’s intellectual ability and
competence.
Steele (1992; Steele & Aronson, 1995), for example, has argued that
whenever African American students (particularly males) perform an explicitly
scholastic or intellectual task, they face the threat of confirming or being
judged by a negative societal stereotype about their group’s intellectual ability
and competence. Such a reputation influences the academic functioning of
these students, particularly during standardised testing. He claimed that this
reputation "may have the further effect of pressuring these students to
protectively disidentify with achievement in school" (p. 797), such that school
achievement is neither a basis of self-evaluation nor a personal identity.
There are various effects of this cultural reputation (such as spending more
time answering fewer test items) that can undermine motivation, effort, and
self-efficacy.
Seeking on negative information. Although all students prefer favourable
feedback some have adverse stress reactions to negative feedback – hence
try to avoid seeking negative information altogether and seek only positive
information.
The effects of the strategies
These self learning strategies explain how individuals can bias, select and
retain information that affect their self-concepts and they have major
influences on how students learn, how they set challenging goals, how they
accept feedback, and their subsequent learning outcomes.
The point is that a teacher may be providing a remarkable amount of
feedback but this does not mean that this student is receiving this feedback.
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Excellent teaching requires teachers setting challenging goals and providing
feedback, and students setting challenging goals, and seeking, biasing and
interpreting information and accepting feedback. Oh, not so easy, eh! If only it
was one-way.
Teacher Education
The implications of the above have much to say to teacher education.
Teachers need to be well prepared in their content to know WHAT
information is to be taught, and WHAT information can be used as feedback
– clearly if they have deeper understandings of their content they increase the
probability they can set challenging goals and provide feedback.
More important teachers need to understand that the variations in individual
students manner of receiving, transforming and being disposed to this
information is considered in the act of teaching. This, I believe, requires that
teachers care about their students, know where they are coming from, and
overly attend to the issue of whether their students are learning.
For example, we have been researching the Paideia teaching method, which
was forcibly introduced into every class in 91 schools. Yes, it was innovation,
yes it was a teacher method and not a structural change, and yes, it involved
setting challenging goals and dramatic amounts of feedback – all the
hallmarks for success; but forcibly introduced.
The Paideia program promotes three modes of teaching: a didactic mode, a
seminar component, and a coaching aspect. The seminar component is the
most distinctive and involves much training in active listening by the teacher,
constructing peer group tutoring for the whole class that uses rich and
challenging texts (across all the curricula), and structures ways for the
students to question the text and each others understandings. I used Paideia
in my classes in measurement and statistics and it opened up to me, as
teacher, the ways in which the students were constructing knowledge, and the
ways they had already constructed it – very sobering – despite my having
taught the material using the drip filter model perfectly.
In the forced implementation there was remarkable success in the
standardised test scores across all ages, subjects, and most critically in this
particular county for all racial backgrounds, primarily by reducing the negative
effects of social comparison that African American students had been using.
There was also powerful evidence that Paideia influenced students’
perceptions of the quality of schooling. The students claimed that teachers
who implemented Paideia were better at explaining information, more able in
ensuring that students had a good understanding, put more effort into
teaching, taught in interesting ways, and showed by example that learning is
fun. There was less friction in classes, less fooling around, students were
considered more calm and not mean, and they felt safe. Students see more
flexibility in the classroom when Paideia is implemented.
Teacher Education programs must produce teachers with a conception of
teaching based on a high and rigorous set of standards of what beginning
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teachers know and are able to do. I have worked with NCATE developing a
new model for teacher accreditation based on this simple notion. Instead of
asking institutions, like ours here at UoA, what courses do your students
experience, and are the staff qualified.
We oversaw:
•
•
•
a major consultative process to determine the high and rigorous
competencies of graduating teachers in terms of what they know, and
are able to do
asked the Institutions to provide evidence that their graduating
teachers know and able to do the competencies to the appropriate
standards of excellence, and
ask the professionals to adjudge this evidence.
We are in trials in many Institutions in the US at the moment and this is
beginning to have a profound and positive effect on what is undertaken in
teacher education institutions. No longer is exposure to wisdom sufficient, no
longer are scores on our student sufficient, no longer are our posturing that
we are quality providers convincing. Instead, the course is evaluated by the
quality of the graduates in terms of knowing, performing and their dispositions
in terms of their impact on their students’ learning outcomes– a hard but
correct ask.
We spent much time in teacher education programs imparting the necessary
knowledge so that students are sufficiently learn to teach, we spent much
time on teaching methods, and we need to spend much time understanding
how students learn, their conceptions of learning, and how the feedback cycle
works. Too often we compared experienced with novice when the better
comparison is experienced and expert. This is my mission.
Identifying Accomplished Teachers
We have a system that spends inordinate energies worrying about initial
teacher training when more attention needs to be placed at the highest ends
of excellence. We have a model of teaching which assumes that experience
is sufficient, we pride well run quiet classrooms, we pride mimicking, listening,
and regurgitating information. I have argued extensively elsewhere that New
Zealand needs a National Board for Professional Teaching Standards.
I propose the development of an Australasian Board for Professional
Education Standards (ABPES) that parallels the USA National Board
(NBPTS) to advance the excellence of the principal and teaching profession.
The mission would be to:
•
•
•
Establish high and rigorous standards for what accomplished teachers
and principals should know and be able to do,
Operate a national voluntary system to assess and certify teachers and
principals who meet these standards, and
To advance related education reforms for the purpose of improving
student learning in Australasian schools.
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This has been done in the USA and I am still involved in projects relating to
the National Board. Currently, I have a $.75m project on how NBCT and nonNBCT teachers manifest their expertise in the classroom, and not surprisingly
given tonight, are finding differences relating to the amount of feedback, the
manner the teacher understands the learner and how he or she is learning,
deals with the connections of learning and strategies of learning, and cares
and respects what the child brings to their classroom. These facets are often
missing in the too-typical over-routines classroom where teaching is
undertaken as knowledge forced into the recalcitrant brains, assembled in
straight rows, silent, listening and waiting to be tested.
A major imperative why we must identify, reward, and promote these
excellent teachers in a fair, credible and dependable manner is that they are
most likely to provide the voting public the confidence in a national system of
public schooling. National testing, braying by parents and politicians about low
quality and more accountability, and the highlighting of the minimally
competent reinforces those 80% of New Zealanders who typically argue that
the quality of public schooling in New Zealand is awful; whereas the
identification of excellence reinforces those 80% of New Zealanders who
believe that the quality of their child’s teacher is great. We must promote
excellence.
Research Program
To conclude I wish to outline a series of research study that I and my
colleagues (and I hope colleagues here in Auckland) have underway:
What influences student learning
• A model of teaching and learning based on a synthesis of metaanalyses
From the student perspective
• Defending the power of feedback, and goals (in classrooms, out-ofclassrooms such as Outward Bound, Adventure Sailing ships, and with
at-risk students)
• Developing models of conceptions of learning of teachers and students
and how these affect how teachers teach and students learn
• Discovering self strategies for learning (particularly cross-culturally)
• Building models of conceptions of self particularly based on reputation
enhancement
• Ascertaining the study skills of students that assist in the learning
process
From the teacher perspective
• Determining the differences between experienced and expert teachers
• Assessing the teaching methods that increase the probability of impact
on student learning
• Devising measurement procedures to address the question as to how
expert and experienced teachers differ in classroom practice and how
to identify highly accomplished teachers
• Developing accreditation processes for teacher education programs
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•
The development of a New Zealand National Board that sets high and
rigorous standards and has excellent performance measures to identify
accomplished teachers
Addressing the desirable outcomes
• Tests and measures of models of achievement, particularly surface
and deep outcomes based on the SOLO model
• Tests and measures of learning self-strategies
• Training teachers in setting standards (e.g., using exemplars, scoring
rubrics)
• Developing models of wellness to add to the achievement outcomes
Using the best statistical modelling
• Conducting meta-analyses to achieve integration, perspective, and
magnitude of effects
• Incorporating measures of magnitude with statistical significance in
research designs
• Building structural modelling to assess explanations and prediction
• Using item response models to assess dimensionality and create
better measurement, particularly in the affective domain
• Developing and conducting evaluation models of successful teaching
and school innovations
I now consider myself inaugurated.
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