Self-determined learning

Self-determined learning (heutagogy)
Stewart Hase and Chris Kenyon
stewart.hase@gmail.com
Summary
This paper will do two things. It will, for the uninitiated, summarize the origins of
heutagogy and the theories from which it was derived. At the same time we will
have a look at more recent work and thinking from authors around the globe and
see what they have discovered through using or thinking about heutagogical
principles. The main theme of the chapter is that people are naturally very efficient
learners and that we can more effectively make use of this fact in our current
education and training systems.
Origins and influences
The power to learn
Heutagogy has come a long way since its initial inception over a bottle of wine
and notes written on a napkin in a restaurant in 2000 (Hase, 2002, 2009; Hase and
Kenyon, 2000, 2003, 2007, 2010; Kenyon and Hase, 2010). Don’t most good ideas
happen this way? The discussion came about as a result of a general dissatisfaction
with the way in which education was being conducted in universities. We thought
that, despite the role of higher education to foster our brightest minds and to
expand the frontiers of knowledge, teaching was primarily a pedagogic, teacher-
centric, activity. To our way of thinking, teaching in our universities needed to be
more aspirational.
Like other humanists such as Carl Rogers (1969) we believe that the power to
learn is firmly in the hands of the learner and not the teacher. We also recognize,
as have Russell Ackoff and Daniel Greenberg (2008), that humans are from early
childhood really adept learners and that much of the education system confuses
learning with teaching. In fact, there is sometimes so much confusion that it can
interfere with people’s natural ability to explore, ask questions, make connections
and to learn. This humanistic view of how people learn has been coined as
student-centred learning (Rogers, 1969) or, more recently, learner- centred
learning (Armstrong, 2012; Graves, 1993; Long 1990) as opposed to teacher-
centric approaches.
Recently I was asked to talk to a group of trainers working for the NSW Rural Fire
Service in Australia. It was their annual conference and they were interested in

finding more exciting ways to train their 70,000 or so volunteers in the various
competencies required to fight fires. I showed a picture of an ancient fire engine
from the end of the nineteenth century but suggested that they think of it as a new
piece of fire equipment. A teacher-centric approach to learning about this new
equipment would be to show some pictures to the group, go through the manual,
demonstrate the required skills and then have the group practice until the required
competency might be attained. A more learner-centric approach and rather more
naturalistic, would be to let the group go play with the machinery and leave the
manual on the seat. The facilitator can play an important role by watching and
making sure that all is safe and intervening if someone is going to initiate a
catastrophic event. Everyone agreed that, indeed, the group would work it out for
themselves.
Unfortunately, as Ackoff and Greenberg (2008) describe so elegantly, humans are
hijacked very early in life by an educational system that was designed in the
industrial revolution to educate workers to make the industrial wheel go around.
Thus, education has become a commodity and the curriculum, chiselled in stone,
is delivered by ‘experts’ from on high. Assessment becomes the key for opening
doors and teaching is geared to providing the key. The needs and motivations of
the learner and, more importantly, what is happening in their brain is of secondary
importance, if it is of any importance at all.
The late Fred Emery was a little more scathing in his assessment of the education
system (1974, p. 1) when he said that, ‘School pokes your eyes out. University
teaches you braille and postgraduate education is speed-reading in braille.’ Less
controversially, a number of educationalists have questioned the assumptions that
underpin common educational practice and the need for approaches that recognize
the complexity of the relationship between the learner, the curriculum and learning
(e.g. Davis et al., 2000; Doll, 1989; Doolittle, 2000; Sumara and Davis, 1997).
Current education practice places the process and outcomes of learning in the
hands of the teacher who determines what is to be taught and how it is to be taught
when, in fact, it needs to be in the hands of the learner (Coughlan, 2004).
Given these beliefs about people’s ability to learn and an education and training
system that disempowers rather than empowers, we decided on the term self-
determined learning to describe this innate power of people to learn as an alternate
view. Chris, the linguist that he is, then manipulated the Greek word for self,
ηαυτος, and came up with the word heutagogy: the study of self- determined
learning.

Humanism and constructivism
Heutagogy is underpinned by the assumptions of two key philosophies: humanism
and constructivism. As mentioned above, the idea of the learner being central to
the educational process is a humanistic concept. Carl Rogers later adapted his
client-centred approach to psychotherapy (1951) to education (1969) in what was
termed student-centred learning. Similarly, constructivism places the learner at the
heart of the educational experience (e.g. Bruner, 1960; Dewey, 1938; Freire, 1972,
1995; Piaget, 1973; Vygotsky, 1978). Constructivism is based on the notion that
people construct their own version of reality using past experience and knowledge,
and their current experience. Thus, the learner is creative, actively involved in
their learning and there is a dynamic rather than passive relationship between the
teacher and the learner.
Constructivism challenged educators to let go of some of the structure in what
they did and allow greater dynamism into the curriculum. Constructivism led to a
rise in the popularity of designing experiential learning as a means for loosening
this control. However, in our view, it did not have the impact on lessening the
control of the learning experience by the teacher and hence education at all levels
has remained teacher-centric. While many constructivist approaches cleverly
engage the learner in experience and active learning, the teacher is still actively
designing the learning task and process. In learner- centred learning tasks become
less specific as control of learning is taken over by the learner (Coomey and
Stephenson, 2001).
Andragogy (Knowles, 1980, 1986) is also based on humanism and constructivism
and was central to the original paper we wrote in 2000. Andragogy was important
because it provided an alternate to pedagogical approaches to teaching towards
those more suitable for adults. Knowles was interested in the motivational aspects
of adult learning and emphasized the previous experience of the learner, relevance,
problems versus content and involvement of the learner in the learning process.
The idea of the self-directed learner can be sheeted back to Andragogy. However,
while context might be in the hands of the learner, the teacher is still largely in
control of process and task. Unfortunately, some students of heutagogy refer to it
as self-directed rather than self-determined learning: the two are perhaps related
but quite different.
Finally, Argyris and Schon’s (1978) notion of double-loop learning influenced our
thinking about heutagogy and others have since associated the two concepts (e.g.
Blaschke, 2012; Canning, 2010; Canning and Callan, 2010). Double-loop learning
often occurs spontaneously and involves internally challenging our deepest values,
beliefs and ways of knowing. While it is difficult to change any of these schema
that drive human behaviour, it is at this level that the deepest learning occurs.

Reconceptualizing learning
The science of learning, discovering how people learn, as apposed to the
philosophy of learning and education that goes back to Egyptian times, can be
sheeted back to around the tenth-century. However, it is only recently that
advances in neuroscience and the capacity to investigate the functioning of the
brain have really enabled us to see what happens when we learn. In the past ten
years our understanding has risen exponentially.
Commonly used definitions of learning have failed to keep pace with these
advances in neuroscience and appear to be rather outmoded (Hase, 2010).
Learning is often referred to as knowledge being gained through study, instruction
or scholarship or the act of gaining knowledge. Many accepted psychological
definitions refer to learning as being the result of any change in behaviour that
results from experience. Discussions about learning mostly concern the education
process rather than what happens in the brain of the learner – where learning really
takes place.
It’s important to establish at this point that we are not attempting a neurological
reductionist explanation of learning. Clearly learning is a complex interaction of
myriad influences including genes, neurophysiology, physical state, social
experience and psychological factors. However, we suggest that understanding
what is happening in the brain when we learn might provide important new
insights into what is happening to the learner in the education or training
experience.
When we learn something, networks of neurons are established that can later be
accessed, what we call memory (e.g. Benfenati, 2007). Laying down larger and
larger numbers of pathways creates an increasingly complex matrix (Willis, 2006).
Thus, old and new pathways influence each other in potentially quite dramatic
ways through a process of activation and association (Khaneman, 2011). It appears
that humans seek to make patterns from their experience. Furthermore, it is hard to
predict just what the effect of this pattern making from the mix of new and old
learning might be. We might be aiming for a simple change in behaviour, a new
competency perhaps. But the learner may end up making a whole bunch of
cognitive leaps and end up seeing the world in completely different ways: ways
not necessarily defined by the curriculum, which now becomes a constraint.
Thus, every brain is different. Our experiences mean that each person will
selectively focus on different issues, concerns and applications of the things they
are learning. They will be asking different questions in their minds, testing their
own hypotheses, making their own conclusions as a result. John Medina in ‘Brain

Rules’ (2008a) gives a great example of the neuroscience underpinning the above
assertion. The part of the cerebral cortex for the use of the fingers of the left hand
in a right-handed violinist is extremely dense with cells. Presumably this is the
result of practice. People who do not play the violin do not have this density in the
same place but presumably have denser areas elsewhere depending on what their
areas of interest might be. So, the response of the individual to new information, to
new experiences will vary a great deal due to this unconscious selection. In fact, it
may take years before a person has that ‘ah, ah’, moment. This all questions the
fixed curriculum, didactic teaching, teacher-directed learning and many of the
methods we currently use.
The notion of brain plasticity recently popularized by Doidge (2007) also provides
some fascinating insights into how people learn. More importantly these insights
have led to the development of highly focused techniques being used to target very
specific areas of the brain. Neuroscience research shows that the more we actually
‘do’ with a new piece of learning the greater the number of neuronal pathways that
are established and cemented in place through the development of matrices of
dendrites mediated by the release of neurotrophins (Willis, 2006). This supports
previous well-known evidence that an enriched environment leads to increased
development of the brain (Rosenzweig et al., 1962) and this finding is used in a
number of educational contexts.
Exploration is far more effective for learning than using rote methods or passive
processes. It is also interesting that the more satisfying, engaging and perhaps
exciting the education process, the more internally reinforcing it is to the learner
through the release of dopamine (Willis, 2006). There are parts of the brain that
are responsible for watching others, forming hypopheses, testing assumptions and
generally exploring (Gopnik et al., 2000). These skills and the relevant brain
activity is seen in children – they are great learners.
Repetition using different senses, application and providing context or at least
finding out what the learner’s context might be are critical to learning. In fact the
more elaborately we experience something more likely we are to learn it (Craik
and Tulving, 1975; Gabrielli et al., 1996; Grant et al., 1998; Hasher and Zacks,
1984; LeDoux, 2002; Medina, 2008b). The converse is also true. The human
attention span has been shown to be limited to about ten minutes when stimulation
is low and there is an absence of activity (Johnstone and Percival, 1976;
Middendorf and Kalish, 1996). Humans are built to be active, to do things, to
apply, to explore and to be curious. They are not designed to sit still and pay
attention to the same stimuli for long periods – this induces a state of trance, as
most hypnotists know.
Our understanding of learning can best be summarized by Sumara and Davis
(1997, p. 107) as: ‘. . . a process of organizing and reorganizing one’s own

subjective world of experience, involving the simultaneous revision,
reorganization and reinterpretation of past, present and projected actions and
conceptions’. Learning results in a whole new set of questions to ask, based on
their new understanding, not only different from their colleagues but also outside
the curriculum, if not well beyond it. These new questions provide a motivation to
learn. Perhaps the example below will illustrate what is meant by this.
Until 1697 all known swans were white. Nobody had seen a black swan, so in
English poetry the idea of a black swan represented the impossible. In that fateful
year Willem de Vlamingh, a Dutch explorer, discovered black swans in what was
later to become Western Australia. Suddenly, the whole idea of swans changed, as
did the metaphor for impossibility. The change eventually led Nassim Taleb in
2004 to write about black swan events. These are unpredictable things that happen,
good and bad, that have profound effects on the world. They are things we often
fail to plan for and, in fact, we cannot prepare for, except by building resilience in
people and in organizations. Taleb’s novel conceptualization of the black swan
leads to a complete rethinking of what we mean by strategic planning by focusing
on building capacity for dealing with uncertainty.
Heutagogy also draws on the notion of capability (e.g. Stephenson, 1996;
Stephenson and Weil, 1992) by distinguishing between the acquisition of
knowledge and skills or competencies and the deeper cognitive processes
described above. Capability involves using competencies in new contexts and
challenging situations. It is about the unknown and the future, rather than the
routine. In demonstrating capability the person is making a host of new neuronal
connections, creating new hypotheses and testing them mentally and physically, in
understanding the best way to proceed. At the same time, capability requires the
learner to have a high degree of self-efficacy in their ability to learn and access
appropriate resources. Capable people also recognize the need to work with others
to deal with new and changing circumstances. Competencies are the building
blocks of learning but our life experiences, serendipity, challenges, the unknown
future, things outside our control, make us do more with these building blocks.
Thus, we propose that there are perhaps two levels of learning: the acquisition of
knowledge and skills on the one hand and, on the other, this more complex
neuronal activity. Pedagogy and andragogy describe the educational activities used
in the development of competence, the acquisition of knowledge and skills (Tay
and Hase, 2004) as learners struggle with new concepts and ideas. Andragogical
techniques are used as the learner makes connections with their previous
experience. Tay and Hase (2004) studied engineers and business managers
undertaking a PhD using an action research approach. With backgrounds based in
technical and scientific research, action research was a completely new concept.
Tay and Hase found that the students moved from pedagogy, with a high reliance

on the supervisors, to andragogy as they started to make sense of how to apply
action research to their life experience.
They then found that reliance on the supervisor diminished and the process
became more learner-centric or heutagogic. There is less predictability about the
task and process. Here the needs of the learner and their motivation may change
rapidly as new connections are made, novel applications are tested and concepts
are redesigned to suit individual needs. This higher-level learning may not be, ‘. . .
necessarily in concert with the aims of the teacher or the curriculum’ (Hase, 2009,
p. 46).
While this study clearly showed a shift from dependent learner to self- determined
learner we do not completely agree with some writers (Anderson, 2006; Luckin et
al., 2011) who suggest that pedagogy, andragogy and heutagogy (PAH)
necessarily lie on a continuum – the PAH Continuum (Luckin et al., 2011). This
continuum assumes that the learner moves from pedagogy to heutagogy depending
on their level of sophistication. This may be the case (as described by Tay and
Hase (2004)) but is not always so. For example, children are very   competent
learners until process and content are pulled from their grasp by schooling, no
matter their level of sophistication.
Emotion and motivation
Studies of the human brain also demonstrate the important role of emotions in
learning, memory and decision-making (e.g. Damasio, 2003; Dolcos et al., 2004;
Medina, 2008a). The driver of emotions, the amygdala, is connected to areas of
the cortex responsible for higher-order cognitive functions and learning. Thus,
emotions affect learning, as they do analysis, decision-making and action. As Hase
(2009, p. 46) states:
It is also clear that there are complex interactions between learning and emotions
in that the latter may make learning more indelible (Ingleton, 1999). Learning,
then, is probably enhanced by excitement and enjoyment, and when there is a gap
in understanding that creates curiosity, confusion or a gentle unease. Thus, it is the
questions that the learning experience raises rather than the provision of answers
that are the primary concern of heutagogy.
It is our contention that it is the role of the learning facilitator to create or at least
enable these kinds of positive emotions.
Closely linked to positive emotions, and perhaps even indistinguishable from it is
motivation. Given the vast literature on motivation and learning, it can probably
safely be said that the two are indelibly intertwined, so we won’t go into much
detail here about the importance of motivation except where it relates to

heutagogy. Motivation to learn has survival value and that is why we are naturally
good at it. The organism’s capacity to attend to relevant stimuli in the environment
is the critical initial element in a process of analysis, decision-making and action.
The human brain seeks to make patterns out of stimuli, to make sense of the
environment, to find associations (e.g. Caine et al., 1999; Sousa, 2011). Moreover,
the learner seeks to make even grander patterns with each new experience.
Associations are made by the learner, not by the teacher, no matter how hard
teachers might try to make them on the learner’s behalf. I like to ask groups to
think of something that they learned once that really made a difference to their
lives, either positively or negatively. My bet that the significant learning
experience did not happen in the classroom is always won.
Motivation to learn is enhanced by: greater involvement in and control by the
learner in the learning process; self-initiated learning; the opportunity to develop
and share patterns; and relevance.
Ackoff and Greenberg (2008) provide a great example of the role of motivation in
learning. This involved a group of students in a poor city neighbourhood with a
high level of illiteracy and no interest in education (over 65% of households had
no books). Knowing that these young people were incredibly street smart and not
dumb a local university professor came up with a novel idea. He started to show
old silent movies, which became very popular in a neighbourhood where
entertainment was scarce. The interesting side-effect, however, was that the young
people started teaching themselves how to read so that they could understand the
captions.
Our environments
Finally, the other influence that has strongly affected the conceptualization of
heutagogy has to do with how we understand context, the environment.
Humans have an apparently innate tendency to want to find simple explanations
for phenomena and the essential reductionism that occurs in science supports this
drive. Complexity theory (e.g. Lissack, 1999; Stacey et al., 2000; Waldrop, 1992)
and systems thinking (Emery and Trist, 1965; Emery, 1993), however, claim that
this can be counterproductive because the world in which we live is far more
complex than can be explained by linear associations, or by simple cause and
effect relationships. This is particularly true of social phenomena, which involve
the interplay of rapidly changing, multiple variables that create a high level of
unpredictability. The importance of complexity theory and systems thinking in
relation to how we learn has been clearly described in a paper by Phelps et al.
(2005). The key factors involved in these two theories can be summarized as
(Hase, 2009, p. 46):

 systems are open and non-linear  l systems are affected by their
environment (and vice-versa) in complex ways;
 systems are not in equilibrium but are constantly adapting to changes; 
 these changes are unpredictable and non-linear but are self-generating and
self-maintaining (autopoiesis); 
 the system is greater than the sum of its parts, and hence, we cannot
understand a system by only considering its parts  ;
 outcomes are dependent on initial conditions that may be unknowable and,
therefore, attempts at prediction are often futile (the butterfly effect);
 adaptation and then stability (bifurcation) occur as a result of stress on the
system; and
 big events may have small consequences and small events may have large
consequences  change is natural and evolutionary.
Thus, learning is an emergent process, unpredictable and involving the interplay of
learner and context, both of which are in a state of constant flux (Doolittle, 2000).
Learning outcomes are similarly unpredictable (Phelps et al., 2005) since learning
is constructed by the learner in a process of purposeful, self-organized adaptation.
In summary, these lines of evidence suggest that we need to rethink how we
engage people in so-called learning experiences. That is, we need to:
 involve the learner in designing their own learning content and process as a
partner;
 make the curriculum flexible so that new questions and understanding can
be explored as new neuronal pathways are developed;
 individualize learning as much as possible; 
 provide flexible or negotiated assessment; 
 enable the learner to contextualize concepts, knowledge and new
understanding;
 provide lots of resources and let the learner explore;  l differentiate between
knowledge and skill acquisition (competencies) and deep learning; 
 recognize the importance of informal learning and that we only need to
enable it rather than control it; 
 have confidence in the learner;
 and  recognize that teaching can become a block to learning.
We need to facilitate rather than teach, step back and guide, and provide a
compass rather than a map.
Advances and applications
Since 2000, the study and use of heutagogical principles has steadily increased.
For reasons that are not quite clear, a good deal of the discussion about heutagogy

since its inception has concerned online learning (e.g. McNickle, 2003). Blaschke
(2012) and Chapnick and Meloy (2005) conclude that web-based learning, new
technologies and distance education methods lend themselves very well to a
heutagogical approach.
Not everyone, however, has been enthusiastic about heutagogy (McAuliffe et al.
2008; McLoughlin and Lee, 2007). Critics suggest that organizations, like
universities, that credential students would find flexible curricula and negotiated
assessment, in particular, impractical. This is certainly true in the teacher-centred
framework that currently exists in many educational institutions, particularly
universities, where pedagogy is the dominant educational paradigm. Another, and
more relevant concern (in our view) is the preparedness of the learner (Blaschke,
2012) to adopt what would be a completely different educational process.
However, this need can be accommodated as Msilav and Setihako (2012) from the
University of South Africa showed in using a heutagogical approach in an online
teacher education module. They accommodated this important role of the teacher
to nurture students until they can confidently take over their own learning.
Heutagogy, as described at the beginning of this chapter, deliberately challenges
the prevailing educational paradigm. Despite some resistance, and having to
negotiate learner preparedness, heutagogy has been applied, in a number of
settings, including credentialing institutions with success.
The exciting notion of learner-generated contexts (LGC) (Luckin et al, 2005,
2011) fits neatly with the premises of heutagogy and, according to Whitworth
(2008), the two have close ties. Mostly applied to web-based learning, LGC
involves the learner actively finding learning resources rather than having them
supplied by the teacher. Hence, the learner provides the context for the area being
studied. This activity is undertaken with a goal in mind but changes the role of the
learner from consumer to active participant in their own learning.
Ashton and Newman (2006) and Ashton and Elliott (2007) have applied a
heutagogical approach to the design and delivery of a teacher education
programme. The approach involved enabling learner-managed learning through
flexible blended delivery. They found a number of positive effects that included:
better teacher outcomes; increased capability among the student teachers;
increased confidence; increased collaborative learning and peer learning
processes; increased investigative capacity; and increased ability to question.
Canning and Callan (2010) in an observational study helped students in an early
years education programme to ‘discover their own strategies for learning, develop
confidence through active participation and begin to share their knowledge and
understanding of key concepts’ (p. 74). They used reflective processes as a vehicle
to achieve these outcomes. They found that the students increased control of their

own learning, engaged in critical thinking in relation to theory and their own
practice, improved their self-perception, became effective reflective practitioners
both individually and collaboratively, and increased in confidence. Eberle and
Childress (2009) using heutagogical principles have also found collaborative
learning to lead to greater confidence among learners.
Similarly, Bhoyrub et al. (2010) believe that heutagogy provides a useful
framework for creating confidence among nursing students for them to take
advantage of learning opportunities in sometimes chaotic and highly complex
clinical settings. It is up to the learners to make sense of their experience and to
use their competencies in new and challenging situations that the workplace
presents.
Albon (2006), within a heutaogical framework, had postgraduate education
students develop assessment online and collaboratively. She found that the process
drove learning further, increased students’ autonomy and improved active
learning. Albon also noted that the line between facilitator/guide and student
became blurred as they learned together. Eberle and Childress (2009) also
recommend the collaborative approach to designing assessment using double-loop
learning.
The idea of flexible and negotiated assessment is not new and has existed for a
number of years as a component of learning contracts (e.g. Anderson et al., 1998;
Knowles, 1986). The learning contract provides an excellent vehicle for the
negotiation of all aspects of the learning process, as long as it is in itself open to
change as the learner’s learning takes different turns.
Collaboration through teams or communities of practice is an important feature of
heutagogy (Blaschke, 2012; Kenyon and Hase, 2010; Hase, 2009). Collaboration,
however, is concerned with the learning process and learning to learn, as much as
it is about finding content.
Conclusion
Deconstructing heutagogy reveals that there is nothing novel about its
underpinnings, particularly the need to challenge prevailing dogma about the
circumstances under which learners learn best. However, applying principles that
can be sheeted back to heutagogy requires a major shift in the way in which we
think about learning and education. Certainly heutagogy is a challenge to our
credentialing institutions and the inflexibility that characterizes educational
practice and teacher-centric learning. However, applications of heutagogy over the
past 12 years or so have demonstrated that this challenge is one that can be taken
up, and is resulting in some exciting innovation, particularly for learners.

References
Ackoff, R. L. and Greenberg, D. (2008), Turning Learning Right Side Up: Putting
Education Back on Track. New Jersey: Pearson.
Albon, R. (2006), ‘Motivation, dialogue, and heutagogy: driving collaborative assessment
online’, in J. R. Parker (ed.), Proceedings of the Second IASTED International
Conference on Education and Technology. Calgary, AB: ACTA, 63–71.
Anderson, J. (2006), The E-mature Learner. Retrieved 29 November 2008 from:
http://tre. ngfl.gov.uk/uploads/materials/24875/The_ema-
ture_learner_John_Anderson.doc.
Anderson, G., Boud, D. and Sampson, J. (1998), ‘Qualities of learning contracts’, in J.
Stephenson and M. Yorke (eds), Capability and Quality in Higher Education. London:
Kogan Page, 162–73.
Argyris, C. and Schon, D. (1978), Organizational Learning: A Theory of Action
Perspective. Reading, MA: Addison-Wesley.
Armstrong, J. S. (2012), Natural Learning in Education. Encyclopedia of the Sciences of
Learning. Heidelberg: Springer.
Ashton, J. and Elliott, R. (2007), ‘Juggling the balls – study, work, family and play:
student perspectives on flexible and blended heutagogy. European Early Childhood
Education Research Journal, 15(2), 167–81.
Ashton, J. and Newman, L. (2006), ‘An unfinished symphony: 21st century teacher
education using knowledge creating heutagogies’, British Journal of Educational
Technology, 37(6), 825–40.
Benfenati, F. (2007), ‘Synaptic plasticity and the neurobiology of learning and memory’,
Acta Biomed, 78, 58–66.
Bhoyrub, J., Hurely, J., Neilson, G. R., Ramsay, M. and Smith, M. (2010), ‘Heutagogy:
an alternative practice based learning approach’, Nursing Education in Practice, 10, 322–
6.
Blaschke, L. M. (2012), ‘Heutagogy and lifelong learning: a review of heutagogical
practice and self-determined learning’, The International Review of Research in Open
and Distance Learning, 13(1). Retrieved 17 October 2012 from: www.irrodl.org/
index.php/irrodl/article/view/1076/2087.
Bruner, J. (1960), The Process of Education. Cambridge, MA: Harvard University Press.
Caine, G., Nummela-Caine, R. and Crowell, S. (1999), Mindshifts: A Brain-based
Process for Restructuring Schools and Renewing Education (2nd edn). Tucson, AZ:
Zephyr Press.

Canning, N. (2010), ‘Playing with heutagogy. Exploring strategies to empower
maturelearners in higher education’, Journal of Further and Higher Education, 34(1),
59–71.
Canning, N. and Callan, S. (2010), ‘Heutagogy: spirals of reflection to empower learners
in higher education’, Reflective Practice, 11(1), 71–82.
Chapnick, S. and Meloy, J. (2005), Renaissance E-learning: Creating Dramatic and
Unconventional Learning Experiences. San Francisco, CA: Pfeiffer.
Coomey, M. and Stephenson, J. (2001), ‘Online learning: it is all about dialogue,
involvement, support and control – according to the research’, in J. Stephenson (ed.),
Teaching and Learning Online: Pedagogies for New Technologies. London: Kogan Page,
37–52.
Coughlan, R. (2004), ‘From the challenge to the response’, Proceedings of the BiTE
Project Conference. Adastral Park, December.
Craik, F. I. M. and Tulving, E. (1975), ‘Depth of processing and the retention of words in
episodic memory’, Journal of Experimental Psychology General, 104, 268–94.
Damasio, A. (2003), Looking for Spinoza: Joy, Sorrow, and the Feeling Brain. London:
William Heinemann.
Davis, B., Sumara, D. and Luce-Kapler, R. (2000), Engaging Minds: Learning and
Teaching in a Complex World. Mahwah: Lawrence Erlbaum.
Dewey, J. (1938), Experience and Education. New York: Macmillan.  Doidge, N.
(2007), The Brain that Changes Itself: Stories of Personal Triumph from the
Frontiers of Brain Science. New York: Viking.  Dolcos, F., Labar, K. S. and Cabeza, R.
(2004), ‘Interaction between the amygdala and the medial temporal lobe memory system
predicts better memory for emotional events’, Neuron, 42, 855–63. 
Doll, W. E. (1989), A Post-modern Perspective on Curriculum. New York: New
YorkTeachers College. 
Doolittle, P. E. (2000), Complex Constructivism: A Theoretical Model of Complexity and
Cognition. Retrieved 28 August 2012 from:
www.tandl.vt.edu/doolittle/research/complex1.html.
Eberle, J. and Childress, M. (2009), ‘Using heutagogy to address the needs of
onlinelearners’, in P. Rogers, G. A. Berg, J. V. Boettecher and L. Justice (eds),
Encyclopedia of Distance Learning (2nd edn). New York: Idea Group Inc, 181–7. 
Emery, M. (1993), Participative Design for Participative Democracy (2nd edn).
Canberra, Australia: Centre for Continuing Education, The Australian National

University.
  Emery, F. E. and Trist, E. L. (1965), ‘The causal texture of organizational
environments’, Human Relations, 18(1), 21–32. 
Freire, P. (1972), Pedagogy of the Oppressed. Harmondsworth, UK: Penguin.
  —. (1995), Pedagogy of Hope. Reliving Pedagogy of the Oppressed. New York:
Continuum.
Gabrieli J. D .E, Desmond J. E, Demb J. B, Wagner, A. D, Stone M. V, and Vaidya C.
J.(1996), ‘Functional magnetic resonance imaging of semantic memory processes inthe
frontal lobes’, Psychological Science, 7, 278–83.
  Gopnik, A., Meltzoff, A. N. and Kuhl, P. K. (2000), The Scientist in the Crib. New
York: William Morrow.
Grant, H. M., Bredahl, L. C., Clay, J., Ferrie, J., Groves, J. E., McDorman, T. A. and
Dark, V. J. (1998), ‘Context-dependent memory of meaningful material: information for
students’, Applied Cognitive Psychology, 12, 617–23.
Graves, N. (ed) (1993), Learner Managed Learning: Practice, Theory and Policy. Leeds:
WEF and HEC.
Hase, S. (2002), ‘Simplicity in complexity: capable people and capable organisations
need each other’. Paper presented at the Australian Vocational Education  and Training
Research Association (AVETRA) Conference, Melbourne, 22–24 April. Retrieved 2 July
2012 from: http://epubs.scu.edu.au/cgi/viewcontent.
cgi?article=1145&context=gcm_pubs.
—. (2009), ‘Heutagogy and e-learning in the workplace: some challenges and
opportunities’, Impact: Journal of Applied Research in Workplace E-learning, 1(1), 43–
52.
—. (2010), ‘Learner defined curriculum: Heutagogy and action learning in vocational
training’, Southern Institute of Technology Journal of Applied Research, Special Edition
on Action Research. Retrieved from: http://sitjar.sit.ac.nz
Hase, S. and Kenyon, C. (2000), ‘From andragogy to heutagogy’, ultiBASE, 5(3).
Retrieved 23 October 2012 from: http://ultibase.rmit.edu.au/Articles/dec00/hase1. pdf.
—. (2003), ‘Heutagogy and developing capable people and capable workplaces:
strategies for dealing with complexity’. Proceedings of The Changing Face of Work and
Learning Conference. Edmonton, AB: University of Alberta. Retrieved 23 October 2012
from: www.wln.ualberta.ca/papers/pdf/17.pdf.
—. (2007), ‘Heutagogy: a child of complexity theory’, Complicity, 4(1). Retrieved 23
October 2012 from: www.complexityandeducation.ualberta.ca/COMPLICITY4/

documents/ Complicity_41k_HaseKenyon.pdf.
Hasher, L. and Zacks, R. T. (1984), ‘Automatic and effortful processes in Memory’,
Journal of Experimental Psychology General, 198, 356–88.
Ingleton, J. (1999), ‘Emotion in learning: a neglected dynamic’. Paper presented at  the
Higher Education Research and Development Society of Australasia (HERDSA) Annual
International Conference, Melbourne, Australia, 12–15 July. Retrieved 23 October 2012
from: www.herdsa.org.au/wp-content/uploads/conference/1999/pdf/ Ingleton.PDF.
Johnstone, A. H. and Percival, F. (1976), ‘Attention breaks in lectures’, Education in
Chemistry, 13 (3), 49–50.
Kenyon, C and Hase, S. (2010), ‘Andragogy and heutagogy in postgraduate work’, in T.
Kerry (ed.), Meeting the Challenges of Change in Postgraduate Higher Education.
London: Continuum Press, 165–77.
Khaneman, D. (2011), Thinking Fast and Slow. London: Penguin.
  Knowles, M. S. (1980), Modern Practice of Adult Education: Andragogy versus
Pedagogy. Chicago: Association Press/Follett. 
—. (1986), Using Learning Contracts. San Francisco, CA: Jossey-Bass.
LeDoux, J. (2002), Synaptic Self: How Our Brains Become Who We Are. New York:
Viking Press.
Lissack, M. R. (1999), ‘Complexity: the science, its vocabulary and its relation to
organizations’, Emergence, 1(1), 110–26.
Long, D. (1990), Learner Managed Learning: The Key to Life Long Learning and
Development. New York: Kogan Page.
Luckin, R., du Boulay, B., Smith, H., Underwood, J., Fitzpatrick, G., Holmberg, J.,
Kerawalla, L., Tunley, H., Brewster, D. and Pearce, D. (2005), ‘Using mobile technology
to create flexible learning contexts’, Journal of Interactive Media in Education, 22, 1–21.
Luckin, R., Clark, W., Garnett, F. Whitworth, A., Akass, J., Cook, J., Day, P.,
Ecclesfield, N., Hamilton, T. and Robertson, J. (2011), ‘Learner generated contexts: a
framework to support the effective use of technology for learning’, in M. J. W. Lee and
C. McLoughlin (eds), Web 2.0-based E-learning: Applying Social Informatics in Tertiary
Teaching. Hershey: Information Science Reference, 70–84.
McAuliffe, M. B., Hargreaves, D. J., Winter, A. J. and Chadwick, G. (2008), ‘Does
pedagogy still rule? Paper presented at the 19th Annual Conference of Australasian
Association for Engineer Education, 7–10 December, Central Queensland University,
Yeppoon.

McLoughlin, C. and Lee, M. J. W. (2007), ‘Social software and participatory learning:
pedagogical choices with technology affordances in the Web 2.0 era’. Proceedings of the
Ascilite Conference, Singapore, 2–5 December. Retrieved 23 October 2012 from:
www.ascilite.org.au/conferences/singapore07/procs/mcloughlin.pdf.
McNickle, C. (2003), ‘The impact that ICT has on how we learn – pedagogy, andragogy
or heutagogy?’ Proceedings of the Sustaining Quality Learning Environments: 16th
ODLAA Biennial Forum Conference. Canberra: Canberra Institute of Technology.
Medina, J. (2008a), Brain Rules. Seattle: Pear Press.  —. (2008b), ‘Why emotional
memories are unforgettable’, Psychiatric Times, 14–17. Merriam, S. B., Caffarella, R.
and Baumgartner, L. (2007). Learning in Adulthood: A Comprehensive Guide (3rd edn).
New York: Wiley. 
Middendorf, J. and A. Kalish (1996), ‘The “change-up” in lectures’, National Teaching
and Learning Forum, 2 (5). Retrieved June 4, 2013, from http://www.ntlf.com/html/
pi/9601/article1.htm. 
Msilav, V. and Setihako, A. (2012), ‘Teaching still matters: experiences on developing a
heutagogical online module at UNISA’, Journal of Educational and Social Research,
2(2), 65–71. 
Phelps, R., Hase, S. and Ellis, A. (2005), ‘Competency, capability, complexity and
computers: exploring a new model for conceptualising end-user computereducation’,
British Journal of Educational Technology, 36(1), 67–85. 
Piaget, J. (1973), To Understand is to Invent. New York: Grossman.  Rogers, C. (1969),
Freedom to Learn: A View of What Education Might Become. Columbus, OH: Charles
Merill.
Rosenzweig, M. R., Krech, D., Bennett, E. L. and Diamond, M. C. (1962), ‘Effects  of
environmental complexity and training on brain chemistry and anatomy: a replication and
extension’, Journal of Comparative and Physiological Psychology, 55, 429–37.
Sousa, D. (2011), How the Brain Learns. Thousand Oaks, CA: Corwin Press. Stacey, R.
D., Griffin, D. and Shaw, P. (2000), Complexity and Management: Fad or Radical
Challenge to Systems Thinking? London: Routledge. 
Stephenson, J. (1996), ‘Beyond competence to capability and the learning society’,
Capability, 2(1), 60–2. 
Stephenson, J. and Weil, S. (1992), Quality in Learning: A Capability Approach in
Higher Education. London: Kogan Page. 
Sumara, D. J. and Davis, B. (1997), ‘Enactivist theory and community learning: toward a
complexified understanding of action research. Educational’, Action Research, 5(3),403–
22.

Tay, B. H. and Hase, S. (2004), ‘The role of action research in workplace PhDs’, Action
Learning and Action Research Journal, 9(1), 81–92. 
Vygotsky, L. S. (1978), Mind in Society: The Development of Higher Psychological
Processes. Cambridge, MA: Harvard University Press. 
Waldrop, M. (1992), Complexity: The Emerging Science at the Edge of Order and
Chaos. London: Penguin. 
Whitworth, A. (2008), ‘Learner generated contexts: critical theory and ICT education’.
Paper presented at the 6th Panhellenic Conference on Information andCommunication
Technologies in Education, Limassol, Cyprus, 25–28 September.
Willis, J. (2006), Research-based Strategies to Ignite Student Learning: Insights from a
Neurologist and Classroom Teacher. Alexandria, VA: ASCD.

Self-determined learning

More Related Content

Similar to Self-determined learning (20)

More from Dr Stewart Hase (14)

Recently uploaded (20)

Self-determined learning