this panel presentation, we were asked to respond to the challenge
of translating research findings in the science of learning into
educational applications. To do this, we were asked to provide you
with an overview of the current state of research on learning, to
consider how the effective application of relevant principles can
improve faculty teaching and student learning, and to examine challenges
of application within the research university context. As preamble
to my talk, I will provide my disciplinary context: although I had
a solid liberal arts and science undergraduate education, I grew
up as a psychologist, and I became an educational researcher, in
fact was the first PhD graduated from the Ontario Institute for
Studies in Education at the University of Toronto. I am thus a hybrid,
and although I honor my roots in philosophy and psychological theory,
I also have the need to test the principles derived from these disciplines
in the field. I embody the skepticism of the engineer, asking, “Will
this work?” My field is teaching and learning in higher education,
and I have spent the last thirty years examining how professors
in different disciplines teach, how students learn, and how we might
optimize student learning. In this presentation two questions guide
my search: What do we know about student learning? What instructional
strategies will help students learn to think?
do we know about student learning?
Helping students learn
would appear to be a straightforward goal, but there are many ways
of perceiving postsecondary teaching and learning. From the perspective
of faculty, learning is a matter of disciplinary knowledge and methods
of inquiry, but the expectations of students differ across disciplines.
Most physics professors expect students to enter their programs
with a high degree of logical ability, while English professors
expect students to learn to argue logically in their courses (Donald,
1988). Law professors expect students to learn to think like a lawyer,
to acquire the skills and methods of analysis and procedure (Donald,
2002). Since scholars learn and think within disciplines, an important
source for what is to be learned is what our disciplines tell us,
particularly the methods of inquiry used and the learning tasks
prescribed by these methods. Learning theories have a more general
effect, influencing what happens in the classroom and how learning
is assessed. The experience of adapting to university may lead students
to view learning from a very different perspective, “What
do I need to do to survive and succeed?” Recognizing this
range of perspectives is a first step in responding to the challenge
of translating research on postsecondary learning into educational
The primary source of
what is to be learned is the discipline. But disciplines are moving
targets, uncertain constructs we can only hope to place within certain
parameters. Disciplines are classically defined as domains of knowledge
that include specialized vocabularies and accepted theories, systematic
research strategies with techniques for replication and validation
(Dressel & Mayhew, 1974). Among disciplines, the most prototypical
are the physical sciences, which have been described as hard, well
structured, or paradigmatic (Frederiksen, 1984; Kuhn, 1970). A paradigm
consists of a logical structure and governing truth criteria that
provide maximum direction to scholars in the field (Kuhn, 1970).
In physics, for example, Newton’s laws of classical mechanics
form part of the curriculum around the world. The theories that
describe physical phenomena, however, are often incongruent with
experience, and to be able to problem solve, the main task in the
physical sciences, students must frequently make a radical change
in their conceptual framework from Aristotelian to Newtonian.
In the social sciences,
phenomena are examined at a broader or more general level than in
the physical sciences, and one of the learning tasks is to choose
among various theoretical frameworks that could describe the phenomena
(Donald, 2002). For example, in psychology, there are several models
of learning and of human development. In comparison with the physical
sciences, where abstract concepts are proven by concrete experiments,
in the social sciences multiple variables and their interaction
render theories more difficult to test. Methods of analysis therefore
assume greater importance in the curriculum, and the student’s
task is to locate, recognize and attempt to relate the varied conceptual
frameworks within a discipline.
specify different tasks again. Often they are described as a training
in sensibility, and an aesthetic criterion is applied to learning
(Donald, 2002). Humanistic truth involves authenticity or genuineness
rather than logical or scientific validity (Broudy, 1977). There
is a technical language to be learned, however; for example, trope
or genre in English literature. The student’s task
is to learn how to interpret text using the specified terminology,
and how to present an argument. The learning tasks for students
in physical and social sciences and the humanities thus differ considerably,
and students must adopt a different approach in order to be successful
in each of them. In physics, for example, the student must analyze
a problem by breaking it down into its elements, then reconstitute
or represent the problem. The student in psychology must wrestle
with contrasting perspectives or theoretical frameworks in order
to approach intellectual closure, but at the same time, needs to
be skeptical and to continually search for consistency to validate
findings. In English literature, the processes of argument and judgment
provide the structure for learning.
of inquiry espoused by disciplines may be part of their heraldry,
but they often cross disciplinary boundaries. The earliest method,
hermeneutics, or interpretation, was developed in order
to analyze biblical text (Table 1). It is the construction of textual
meaning which elucidates the connotations that text explicitly or
implicitly represents (Hirsch, 1967). The interpreter of the text
begins by assuming that the text is coherent, then develops a framework
of explanation which is tested by the facts it generates. The method
is thus a process of hypothesizing and then searching for corroborating
evidence in the text. Although the hermeneutic approach is espoused
most frequently in the humanities, discourse analysis as currently
utilized in the social sciences owes much to hermeneutics.
1. Methods of inquiry in different disciplines
Interpretation, the construction of textual meaning
through a dialectic between understanding and explanation
text, English literature, social sciences (discourse analysis)
A reasoned or questioning approach in which one examines assumptions
and seeks evidence
Steps for formulating a problem, calculating and verifying the
Well developed representation of knowledge, action schemas
A method more
generally referred to across disciplines, critical thinking,
developed out of the Socratic tradition of disciplined inquiry.
Defined as a reasoned or questioning approach in which one examines
assumptions and seeks evidence (Donald, 1985), researchers suggest
that critical thinking includes components of logic, problem solving
and Piagetian formal operations (Meyers, 1986; Sternberg, 1985).
Different disciplines focus on different aspects of critical thinking
- inferential processes in physics compared with testing assumptions
in English (Donald, 1985; Meyers, 1986).
to critical thinking, problem solving is described more
specifically and procedurally as a set of steps consisting of formulating
or representing a problem, selecting the relations pertinent to
solving the problem, doing the necessary calculations, and verifying
the logic used to see if the final answer makes sense (Reif, Larkin
& Brackett, 1976). Thus problem solving includes critical thinking
processes but, in addition, those of implementation or testing;
the difference between critical thinking and problem solving is
analogous to understanding versus doing. For example, the critical
thinker would examine underlying assumptions and deduce their effects;
the problem solver would continue from this action to create a strategy
for dealing with the problem. Problem solving is most frequently
used to describe inquiry in the physical sciences.
A more recent
approach to understanding methods of thinking is to examine expertise,
because the expert is one who has acquired not only a solid base
of knowledge but the ability to apply it (Ericksen & Smith,
1991). The expert in a given area has well-developed representations
of knowledge or schemas in the subject matter and can relate the
schemas in order to operate intelligently. Research on the development
of expertise provides insight into potential pedagogical practices.
For example, studies on expert and novice differences reveal that
novices use knowledge of surface structures while experts use action
schemas (Chi, Feltovich & Glaser, 1981); novices represent problems
literally while experts use a scientific and mathematical representation
(McDermott & Larkin, 1978). Novices become experts by passing
through a stage of analysis where problem solving time increases
until they develop the representations and strategies characteristic
of the expert. Experts recognize patterns and solve problems efficiently
and effectively. They have a sense of the context or parameters,
select appropriate information, recognize organizing principles,
and verify their inferences. Their action schemas equip them with
representations and thinking strategies for applying these representations
to problems. What is particularly important about this approach
is that it describes the relationship between knowledge and thinking
processes, and contrasts the thinking strategies of novices and
experts, thus opening the way to promoting such strategies.
theories and implications for instruction
the methods of inquiry used in disciplines, the influence of learning
theories on classroom practice and the assessment of learning is
more pervasive though tacit. The history of learning beginning with
the earliest universities provides context for this discussion.
Scholastics in the middle ages assumed a fixed body of knowledge;
they defined that knowledge and were the authorities (Johnston,
1998). The enlightenment and the scientific revolution that followed
it challenged the notion of fixed knowledge; a tenet of the revolution
was that knowledge was an expanding and open system. Validity was
now based in scientific measurement, and dissent was integral to
the process of testing hypotheses. The role of the university changed
to that of creator of new knowledge, a major transformation in epistemology
that led to the increasingly important role of research in the university.
It could be expected that the principle of an expanding universe
of knowledge would guide instructional practice. But we are still
dealing with the quandary of what is foundational or ‘must
be learned first’ in many disciplines versus testing hypotheses
as a way of learning.
of learning have guided practice in postsecondary education?
The discipline of psychology has assumed primary responsibility
for the topic of learning, and asks the question, ‘How does
learning occur?’ The generally accepted definition of learning
- a relatively permanent change in behavior that occurs as a
result of practice - renders learning scientifically testable,
that is, measurable, but it has certain limitations. The primary
limitation is that in order to be measured, the learning task may
be construed in an oversimplified manner. This definition of learning
is most frequently interpreted reductively as association, that
is, a connection between a stimulus and a response. The focus is
on specific connections, and practice or repetition explains the
process, consistent with experimental findings.
theories promoted this atomistic approach. In experimental studies
of learning, Ebbinghaus in 1885 conceptualized human learning as
a process of memorization, especially by repetition, so that one
can repeat or reproduce. The emphasis on scientific measurement
led him to reason that because words have many previous associations,
to control the learning and recall of material, he would use nonsense
syllables like glet or roit to study human learning
(Woodworth & Schlosberg, 1954). Absent in his reasoning was
comprehension that he was thus rendering learning nonsensical. Ebbinghaus’
conception of learning as memorization was accompanied by a model
of measurement that still guides much assessment practice. He postulated
that there were four stages of memory: impression, retention (persistence
of changed performance), recall (reproduction of once learned items)
and recognition (awareness of previous experience). We set examinations
to measure our students’ recall and recognition. The limitation
of this model is that it does not explain the more complex task
of testing our students’ understanding of pattern and relationship
and their methods of inquiry.
A second early
theory of learning focused on the effect of practice. Thorndike
in 1914 applied the law of effect, originally developed to explain
animal training, to human learning. The law of effect stated
that satisfaction following from an act strengthens the bond and
leads to its repetition, while annoyance weakens the bond. Satisfaction
and annoyance were conceived in terms of synaptic functions, and
were thus coherent with biological theory. His law of exercise,
that the use of a given connection between a stimulus and a response
strengthens the bond, is consistent with the associationist model,
and with the saying that practice makes perfect. It is reflected
in more recent biological approaches to pedagogy in which learning
is described as a process of burning in mental circuitry (Leamnson,
1999). It too, however, neglects the effects of complexity and higher
The first breakthrough
in terms of paying attention to higher order processing was Shannon
and Weaver’s (1949) information theory, which drew on communications
theory to explain how messages or signals are sent and received.
The prototype of an information channel is a perfect telephone line
in which information transmission is complete, but information theory
took into account the fact that channels do not deliver total output
and the receiver is left with some uncertainty (Berlyne, 1965).
The receiver may also select information to reduce the uncertainty,
and complexity of form influences information transmission. Thus
information theory, in which information is encoded and in the process
transformed and actively retrieved, is closer to a model of active
or directed learning. Information theory also updated theories of
memory: the concepts of immediate or short term memory and long
term memory were introduced to discriminate between the limited
capacity of an individual to attend to data – the magical
number seven plus or minus two (Miller, 1956), and semantic or mediated
A more molar
approach, based in gestalt psychology which looks for principles
of synthesis or organization, pays attention to a wider array of
variables influencing learning. One is the tendency or need to categorize
or group information, and another is the tendency to encode new
information in terms of extant categories. The articulation of new
knowledge with already existing knowledge requires attention to
what the learner brings to the classroom. Learning therefore depends
upon discovering relationships between the concepts or ideas presented
and the learner’s extant experience. Patterns of knowledge
exist in schemas or cognitive structures, coherent plans
displaying the essential or important relations between concepts
which learners actively create. This model is coherent with the
notion of expertise. The question of why an individual
learns led Tolman (1932, 1949) to postulate that the organism responds
purposefully and selectively to its environment. Learning is goal
oriented. These more molar approaches to learning were the basis
for cognitive theory (Woodworth & Schlosberg, 1954) and, more
specifically, constructivism, in which individual learners
construct their own understanding of organized public knowledge.
Models of learning
provide us with insights into our instructional habits in higher
education. Association theory supports the custom of professors
repeating important concepts in their lectures and courses of study
and giving students a series of problem sets to solve – practice
makes perfect (Table 2). Association theory also explains the tendency
to give frequent tests, based on the laws of effect and exercise,
and why students are asked to recall facts or, in the case of multiple
choice tests, recognize the best of several alternative answers.
The limitation of associationist models lies in their tendency to
promote rote rather than conceptual learning, that is, knowledge
is construed as bits of information not necessarily related or contributing
to a pattern or theory. The learner therefore adds to a storehouse
of knowledge without necessarily linking it to other knowledge.
Information theory introduces the processes of encoding, transforming
and retrieving, and situates the student as an active participant.
Constructivist theory suggests that students need to identify themselves
as explorers or inventors who select and organize their own knowledge.
This theory is more consistent with the methods of inquiry that
different disciplines espouse. How do these theories translate into
optimizing student learning?
2. Models of learning and implications for students
matter is impressed, retained, and recalled:
Student as storehouse of knowledge
as information processing
is encoded, transformed and retrieved:
Student as active knowledge processor
discovery of relationships between new and extant knowledge:
Student as explorer and inventor, selecting and organizing
do our students know about learning?
We know that student
preparation for learning and student goals have changed over the
past 30 years. More entering students report experiencing stress;
over the last decade, the percentage of students ‘overwhelmed
by everything they have to do’ has risen from 16% to 29% (Astin,
1998). Astin also reports that financial well-being is a more important
goal for American postsecondary students than developing a meaningful
philosophy of life. Students thus tend to not be oriented to a scholarly
life. Their orientations are reflected in the priority they assign
to different activities – the way they spend their time. In
a sample of over 500 students at my university, they told us that
they spent an average of 13 hours per week on studying and homework,
but almost as much time socializing with friends and partying (9
+ 3 hours) (Donald & Dubuc, 1999). Other extra curricular activities
took up less time (four hours in exercising or sports; three-to-four
hours watching TV and hobbies). They spent less than one half hour
a week talking with teachers outside of class, a pattern that is
widespread in North America. Students may complain that they have
little chance of encountering their professors, but they do not
appear to take advantage of opportunities when they arise. We can
infer from these findings that students’ priorities are peer
oriented rather than academic.
At the same
time, our students tell us that they expect to progress on several
fronts during their undergraduate years: In their ability to analyze,
synthesize and think critically, in their basic communication skills;
in independence in learning; in the ability to interact with others;
and in clarity of educational and career goals (Donald & Denison,
2001). Table 3 shows significant increases (*) in the importance
of these criteria from entry to graduation. Students consider a
commitment to learning quite important at entry, and this does not
change. Counterintuitively, they rate academic preparedness equally
important on graduation and at entry to university. What is perhaps
most encouraging is that they attach extreme importance to the ability
to analyze, synthesize and think critically on graduation, although
their rating is more modest at entry. They are clearly telling us
that they expect to learn to think, and that it is highly important
they graduate being able to do so.
3. Students' ratings of the importance of criteria for student quality
to analyze, synthesize, think critically
to interact with others
of educational & career goals
to get a job
(2.50 - 3.49), quite important (3.50 - 4.49), extremely important
findings, how can we help students learn? Attention at three levels
is needed: the institution, students, and faculty. At the level
of the institution, policies must be reconsidered to establish a
supportive learning climate. These may include greater access to
professors, a statement of the university’s commitment to
learning, and clear expectations of student responsibilities. Students
need to become aware of their role and responsibilities as learners,
but this must be explained and supported by university policies
and practices. As faculty, we first need to consider what our conception
of learning is and what consensus there is within our field as to
the nature of learning. To do this, we need to discuss with our
colleagues what learning should be about in our programs. Then we
need to make clear to our students what our conception of learning,
and particularly higher order learning or thinking, is in our discipline,
and instruct and assess our students according to this conception.
instructional strategies will help students learn to think?
student learning, the role of the instructor must evolve from a
limited but frequently prescribed model of transmission or presentation
of information to that of a facilitator of learning. The general
question we pose in the courses and workshops we provide for our
faculty and graduate students is: How can we help students to
become responsible learners? Our primary goal is for participants
to understand useful models of higher order learning that are consistent
with the framework of a course they are designing or redesigning,
and the kinds of instructional and learning strategies needed to
achieve this kind of learning.
a variety of models, one of the most comprehensive being the working
model of thinking processes developed at McGill University from
the postsecondary literature and tested in different disciplines
at research universities such as Stanford, Harvard, Cambridge and
Monash (Donald, 2002). This model is a detailed set of examples
consisting of 30 thinking processes that apply directly to courses
at the postsecondary level. It also delineates inquiry models used
in particular disciplines, for example, ‘expertise’
(identify the context, select relevant information, evaluate
results), so that references can be made in the terms used
by a specific discipline. Table 4 shows those thinking processes
most frequently used across domains.
In our study
of this model, we found that professors across disciplines considered
certain thinking processes or strategies important; this suggests
that there are thinking processes a student in any discipline will
need to acquire, although the discipline will determine the specific
characteristics of the process. Greatest agreement across disciplines
was found in the importance professors attached to students’
learning to identify the context and state assumptions, in changing
perspective, and in selecting relevant information, recognizing
organizing principles and synthesis (Table 4).
4. Thinking processes used across postsecondary domains
the situation, framework, underlying principles, facts.
suppositions, postulates, or propositions assumed.
relevant information, elements, relations
information, concepts, relationships pertinent to the issue
organize elements & relations
methods, rules that organize knowledge. See how ideas fit together.
compare and contrast evidence. Match evidence to theory.
facts, concepts or procedures, compose, interpret, integrate
to develop an explanation or solution.
viewpoint, perspective of facts or issues.
facts, concepts or procedures to solve an actual problem.
strengths and weaknesses of findings, justify or reject an assumption.
the context may consist of processes as diverse as setting
up a general framework for a problem, recognizing what kind of problem
one is dealing with, finding where a framework fits the processes
being studied, or recognizing the history of the period in which
the text was written. Stating assumptions is critical to
solving a problem, recognizing bias, perspective or the framework
being applied, or considering the steps to be taken or individuals
to be taken into account. The general importance of changing
perspective is consistent with the need for a constructivist
approach to knowledge, where in building one’s own cognitive
structure, students must be aware of alternative frameworks and
their advantages and disadvantages.
acknowledge that because of the abundance of information and phenomena,
students must learn to select. Recognizing organizing principles
is essential to understand the structure of a discipline. Synthesis
results in laws in physics, while engineering professors approach
synthesis as a pedagogical goal for their students, training them
in design skills in team projects. In education, synthesis is important
for bringing together the many components of the classroom situation.
In English literature, despite multiplicity and paradox as hallmarks,
the search for form is central.
processes originate in different conceptualizations of thinking,
for example, identifying the context is the mark of the
expert, while stating assumptions is a defining characteristic
of critical thinking. Selection has been used to define
intelligence (Sternberg, 1998), while analysis and synthesis
are found in the problem solving literature. Changing perspective
and evaluating results are found in several approaches to thinking
– in expertise, problem solving, and critical thinking. The
fact that professors from different disciplines agreed on the importance
of these thinking processes suggests that they are foundational
to postsecondary learning. What if professors across disciplines
advised students that these were strategies they needed to learn
whatever course of study they were pursuing? What if these processes
were deliberately taught and assessed in each course?
To help our students
achieve higher order learning, we need to take a constructivist
approach in which learning is goal-oriented and consists of the
discovery of relationships between new and extant knowledge, where
the student is thought of as an explorer and inventor, selecting
and organizing knowledge. This means that we must help our students
to learn how to judge knowledge on the basis of evidence, think
through problems, and integrate and apply knowledge. In order to
do this, we need to examine the disciplinary inquiry strategies
we are responsible for developing, and how students develop more
general learning strategies. For example, a team of professors may
be needed to develop an explanation of the major principles and
tenets governing the field of study, to describe how knowledge is
validated, and to show the gaps or paradoxes and therefore the areas
requiring further research and discussion (Donald, 2000). We also
need to consider how we will model the processes of inquiry in our
disciplines and explain how theory is developed and tested.
To set the stage, we
need to show students what it takes to succeed in the context of
a course, for example, giving them a sense of the number of hours
of study required and the kind of work required. Small group learning
experiences such as seminars, tutorials or undergraduate research
allow students to develop their exploratory skills. Learning tasks
that improve attitudes to learning, for example, participation in
class discussion, projects, or explaining material to another student
can be included in any course at any level. What these benchmark
practices demand of us as professors is course organization, which
is the instructional dimension that has the highest correlation
with student learning (Feldman, 1989; 1996). When we talk about
prospects for supporting students’ higher order learning,
however, we find that professors become animated by the possibility
of creating learning situations that are exciting and personally
fulfilling. Although much groundwork may be needed to produce a
constructivist curriculum, this innovative process can be enriching
This article is based on research funded by the Social Science and
Humanities Research Council of Canada and by les Fonds pour la formation
des chercheurs et aide à la recherche du Québec.
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