On the Frontiers of Change:
Designing Bespoke Learning Architecture

Learning is one of the defining aspects of being human.

Truly profound learning experiences change who we are — we change through learning. All learning involves thinking and doing, action and reflection. Learning changes what we can do, it is always active — you haven’t learned to walk until you walk. Peter Senge

Shaping Effective Transformational Learning

This paper briefly explores how a rigorous andragogy (the art and science of facilitating adult learning) will be the most useful tool in producing truly transformational learning experiences, even in the midst of rapidly changing and often seductive learning technologies. Mindful of considerations in neuroscience, sensemaking, tacit/explicit knowledge, and adult learning theory, the authors propose that, regardless of the technology used, effective learning will “cut through the noise” with developing leaders. This will occur most effectively when learning experiences are highly flexible, shaped entirely by context, built on learner expectations, grounded in the experiential, powered by curiosity, and driven by the need for improved theory and practice. The authors affirm that while effective learning will always prize critical analysis and academic rigour it will also focus on being holistic (respecting the psychological, social, intellectual, physical and spiritual dimensions of the learner) and deeply transformational (producing deep personal change evident in improved practice).

Smith and Healey (2015) tested a proof of concept for innovation in transformational learning in the context of a tertiary education provider. They highlighted four considerations that, in the context of their practice, they believe are shaping effective transformational learning:

  • Effective learning works with the neuroplasticity of the brain—educators need to appreciate that learning depends on neuroplasticity. Without it, information cannot be processed, infused with meaning, creatively reframed, or retained (Hartman-Stein and La Rue 2011; Keeling, Stevens, and Avery 2011).
  • Effective learning involves individual and group sensemaking—educators are setting up optimum conditions for learners to better understand and make sense of the world in which they live. The human brain seeks to align ambiguous, uncertain and complex concepts with what is already known to avoid cognitive dissonance.
  • Effective learning makes tacit knowledge explicit, and explicit knowledge tacit— educators have the opportunity to ensure learners wrestle with understanding concepts and skills required to put theory into practice, using both explicit and tacit knowledge. The craftsperson, the maestro, the chef and the artist all use deep knowledge that cannot always be shared as a list of procedures or supporting documents. Technology favours the sharing of explicit knowledge; our andragogy needs to ensure we also creatively develop tacit knowledge.
  • Effective learning cuts through the noise of modern life—educators are taking into consideration advances in adult learning theory and finding old teacher-centred behaviourist approaches less effective than participatory, constructivist approaches that empower the learner regardless of delivery technologies employed.

The authors propose that effective learning will not be enamoured by technology, but rather will pursue a deeper andragogy (of which technology is merely one tool) designed to connect to the real-world needs of developing leaders.

Effective Learning Works with the Neuroplasticity of the Brain

Learning is inherently a human rather than a technical process. It requires humans to be curious, to communicate, to interact, to test, to argue, to define, to hope and to reject. Technology cannot do that. Therefore, technological solutions to learning challenges will be soulless solutions to the great challenges we face in the world today. Problems that are complex require the cutting edge of our collective thinking. Unless technology is used as an effective tool, it will not provide the creative, socially balanced, and rigorously intellectual new ground that is required for humankind to survive and thrive into the 22nd century. In today’s complex world, we cannot teach everything that a student will need to know. Rather, we must help students learn how to learn, educating not merely for competence (skills, knowledge and attitudes), but also for capability— the ability to adapt to change, generate new knowledge, and continuously improve performance at both individual and collective levels.

For much of the 20th century it was thought the brain was fixed in terms of neurological construction and function (Doidge 2007). There is now more evidence that the human level of intelligence is not fixed at birth, but rather the brain continues to change and develop at a cellular level throughout the entire life span (Carr 2010, 44). New, nonspecific neurons are produced by our brains each day and are then added to neural networks supporting areas of high brain activity or focus. Neuroscientists refer to this as “plasticity” and this change in understanding is evidenced by advances in functional magnetic resonance imaging that give scientists a glimpse of what is happening inside the brain due to changes in blood flow, an indicator of increased activity and resource use. Using the brain in uniform ways strengthens the neurological pathways, resulting in predictable patterns of thinking and action. Our modes of thought build up associated areas of the brain, and this is summed up in Hebb’s rule (1949): “brain cells that fire together, wire together”. This encapsulates the foundational tenet of neuroplasticity (Carr 2010, 27): the brain’s capacity to modify its chemical and physical architecture according to environmental demands and conditions (Cozolino 2006, 11). Neuroplasticity recognises that mental dysfunction can result from the way we have trained our brains to operate. However, it means that we can also have the in-built capacity to expand our minds. Plasticity is not biased. It simply responds to the way it is used (Doidge 2007).

The view that the brain is fixed in function and composition after childhood (with the consequent irreversible neuronal decay) has had a negative influence on the way educators view learning, particularly for the elderly (Boulton-Lewis and Tam 2012). The premise that the elderly cannot learn new things has prejudiced the fields of health science, education and community development (Tyler 1988). Neuroscience now reveals that the right sets of activities and conditions can stimulate new neural connections regardless of age. These reorganised cortical maps provide evidence that learning is an ageless skill. We might do it differently as we age, but the ability remains regardless.

An understanding of how the brain functions seems highly relevant to how adults learn throughout the course of their lives. What we are learning about neuroplasticity in the elderly is useful to knowing how developing leaders can learn in a variety of contexts. Simple classroom “brain dumps” of information are not enough to rewire the student’s brain sustainably (Lovat et al. 2011). However, engaging with the learner on multiple levels has the capability of bringing about transformational change (Greenwood and Parasurama 2012; Willis 2010). As Goswami (2008) recommends, “biological, sensory and neurological influences on learning must become equal partners with social, emotional and cultural influences if we are to have a truly effective discipline of education”.

What we are learning about the internet is that its usage is not only changing the way we access information but it is also changing the way our brains function. This introduces a fundamental change in how technologically savvy learners conduct research, test claims, draw conclusions, make and apply theory, and undertake practical application.

The internet has disrupted the status quo of print and television media, with which the academy had nestled comfortably for more than half a century. While the internet has given many more people access to searchable information, it has not necessarily taught those users how to think and learn effectively.

Reading information (books, journals, magazines, encyclopaedias) on the internet provides a constant opportunity to hyperlink somewhere else for more focused information. Even our social connections (such as Facebook, Twitter, Instagram, Pinterest, blogs and LinkedIn) are intertwined with hyperlinks to more and more people and more and more information about them. This is now accessible from computers, smart phones, tablets and readers, through which we are continually interconnected. This immersion means we can be in the know, and in the now, as more and more of our life is accessed online (Carr 2010, 86).

Greenfield (2009, 71) found that the way people tend to use the internet is disruptive to the kind of cognitive processing that enhances “mindful knowledge acquisition, inductive analysis, critical thinking, imagination, and reflection” because people tend to jump quickly from site to site while multi-tasking with other activities (such as watching television, driving, using social media or talking on the phone), with the result that there is more stimuli than the brain is capable of processing effectively (DeStefano and LeFevre 2007).

Tapscott (2009) believes there is growing evidence that multi-tasking is not a strength of the human brain. The constant hopping from one idea to another means students tend to read less of an article and skim through information quickly, shallowly and with superficial interest (Ziming 2005). Tapscott (2009) also found that internet multi-tasking results in people who are more likely to accept the validity of conventional information presented on the web without questioning the quality of the source or alternative theories.

Cromwell (2004) found that information being so constantly and easily available prevents people from putting in the focused work necessary to remember important pieces of information because “I can always look it up”. This was consistent with DeStefano and LeFevre (2007, 1636), who found that the “many features of hypertext resulted in increased cognitive load and thus may have required working memory capacity that exceeded readers’ capabilities”. These social patterns of learning trends are contrary to established learning practice in which the act of remembering enhances the acquisition, application and retention of new knowledge and skills (Kandel 2006) and with sustained attention less likely, short-term memories will dissipate without much chance of the long-term retention of key facts. This is contrary to the quality learning experience defined by Sweller (1999), who found both concentration and contemplation are crucial to building the rich mental models of complex knowledge necessary to develop expertise in any given field.

Changes to the way humans think occurs very quickly. Small and Vorgan (2008) found that even short periods of internet exposure activated new neural pathways in the brain. Within five days of brief (one hour) internet usage, there was a significant increase in activity in the prefrontal cortex of people without a history of previous internet usage. Over time, daily use of the internet “stimulates brain cell alteration and neurotransmitter release, gradually strengthening new neural pathways in our brains while weakening old ones” (Small and Vorgan 2008, 1). Meanwhile, Van Nimwegen (2008) found the use of software-based learning tools can have the opposite effect than their stated desire—they can result in diminishing the ability to learn and retain knowledge.

Effective Learning Involves Individual and Group Sensemaking

Ultimately, useful learning will help students make sense of their world. Sensemaking is a well-established theoretical framework (Gioia and Chittipeddi 1991; Patriotta 2003; Taylor and Van Every 2000; Weick 1995; Weick and Sutcliffe 2001) whereby people give meaning to experience. It is a way that we deal with ambiguity and uncertainty. In our personal lives, we all do it intuitively every day. To become an effective method for formal learning, it must be intentional and explicit. As Weick and Sutcliffe (2005, 419) found, “to deal with ambiguity interdependent people search for meaning, settle for plausibility, and move on. These are moments of sensemaking”. Sensemaking occurs individually and in groups. Conversation is a powerful way of creating shared understanding because “sensemaking is a way station on the road to a consensually constructed, coordinated system of action” (Taylor and Van Every 2000, 275). In sensemaking, we talk mutual understanding into existence by:

Seeking plausibility

Sensemaking seeks plausibility more than accuracy—a workable, useful level of understanding to guide action rather than a search for an empirical universal truth. As Weick (1995, 61) wrote, “in an equivocal, postmodern world, infused with the politics of interpretation and conflicting interests and inhabited by people with multiple shifting identities, an obsession with accuracy seems fruitless, and not of much practical help, either”.

Grounding in self-identity and world view

Who people think they are (self-awareness) in their context shapes how they interpret events and choose to act. Their general orientation projects self into their environment. People notice and extract cues from the environment and interpret those cues in light of values, beliefs, experiences, narratives and mental models. My thoughts follow familiar patterns that shape what I notice to comply with my wider framework for understanding my world. Who I am is revealed in what and how I think—and what I think is revealed in who I am.

Building on past assumptions.

Individuals simultaneously shape, and are shaped by, the relational forces around them: My dialogue is ongoing, emerges over time, competes for attention, is reflected upon in hindsight and is subject to change. How we view the present is shaped by our past thoughts, feelings and experiences: To learn what we think, we look back on the patterns of thinking, feeling and acting in the past.

Acquiring knowledge for action.

The role of conversation, stories and social processes are vital to the process of discovery. Shared meaning is created through shared narrative based on shared experience. People weigh up, assess and give weight to their construction of reality through the use of recalled stories in dialogue. I select my narrative to reveal perceived reality as I construct it.

Educators who ignore the human need to “make sense” of their world lose an opportunity to take into account the learner’s motivation priorities, previous knowledge, work/life situation, professional needs, and desired areas of development. All are powerful internal drivers for learning.

Effective Learning Makes Tacit Knowledge Explicit, and Explicit knowledge Tacit

Sensemaking creates knowledge for action (Smith 2003). Knowledge that involves tactile experiences, intuition, values, emotions, rules of thumb or unarticulated mental models is described as tacit. Tacit knowledge is not usually consciously accessible; it can be highly personalised and experience based. Therefore, it is difficult to communicate to others. Tacit knowledge is the art, insight and craft that is perhaps captured best in the term “know-how”. Tacit knowledge has an important cognitive dimension. It consists of mental models, beliefs and perspectives so ingrained that we take them for granted, and therefore cannot easily articulate them” (Nonaka 1991, 4). Polanyi (1966) was first to use the term tacit with the assertion “we can know more than we can tell”.

Then there is explicit knowledge. It can be spoken, structured in sentences and captured in writing or drawings. It can be easily communicated and shared in the form of a database, scientific formula, recipe, manual or product specification. It is accessible, transferable and systematic. An example of the difference between explicit and tacit knowledge is cooking a meal. The explicit knowledge is the recipe, the instructions that can be written down or captured in a video. The tacit knowledge is the intuitive understanding of the master chef— the look, taste, smells, touch, timing and techniques that only come with years of hands-on experience. Effective individual and group learning requires a continuous interplay between tacit and explicit knowledge (Nonaka and Takeuchi 1995), as seen in these four dimensions of knowledge creation and sharing:

Learning: from tacit to explicit

The process of developing images, models, frameworks, recipes and examples to articulate tacit knowledge in a form that can be captured and shared.

Learning: from explicit to explicit

The process of organising and integrating knowledge to fit with other parcels of captured knowledge, recognising patterns and building new systems of knowledge, in modes that can be published and easily shared.

Learning: from tacit to tacit

The process of face-to-face interaction (for example, conversations, meetings, brainstorming, sharing experience, living together, apprenticeship and hands-on experience) in sharing deeply known, difficult to express, personal knowledge.

Learning: from explicit to tacit

The process of individuals receiving captured knowledge and, through action and reflection, internalising the experience to be deeply personal, subconscious understanding or expertise that cannot always be articulated.

The challenge for educators is recognising the importance of emphasising both the tacit and explicit in providing opportunities for effective learning. A significant challenge faced by teaching institutions is that technological advances to date have favoured the streamlined delivery of explicit knowledge rather than deep learning that comes with emphasising tacit knowledge (Nonaka and von Krogh 2009).

Effective Learning Cuts through the Noise of Life

In the past 50 years, considerable research has been conducted into the most effective ways adults learn. However, the basic principles of effective learning are much older, expressed in well-known phrases such as “I hear and I forget, I see and I remember, I do and I understand”, attributed to Confucius in 500 BC. Many years later, this old adage is reconfirmed as a valid foundational principle of learning in the concepts of experiential learning (Kolb 1984), action learning (Lewin 1951), reflective practice (Schon 1983), adult learning (Knowles 1984) and transformational learning (Mezirow 1991).

Broadly speaking, there are two dominant theories of learning. A teacher-centred approach grounded in the behaviourist theory of Skinner (Sagal 1981) sees the learner as a passive empty vessel waiting to be filled by the expert with prescribed knowledge. In contrast is a learner-centred approach based on the constructivist theory of Piaget (2001) in which learners actively direct the development of their own knowledge creation through curious inquiry, drawing from personal experience and with input from a broad range of sources.

While the behaviourist “classroom focused” approach has been dominant for centuries, in recent decades, constructivist approaches have gained popularity. This has been particularly driven by industry’s growing need to solve complex problems quickly and ensure learning is useful to real-world business needs (Revans 1980). Constructivism is essentially “a view of learning in which learners use their own experiences to construct understandings that make sense to them, rather than having understanding delivered to them in an already organized form” (Kauchak and Eggen 1998, 184). Constructivist approaches usually start with a problem to be solved or a current practice to be improved. These approaches all attempt to reverse traditional teaching methods, moving from shifting learners from a passive to an active posture that is constructivist, emphasising self-directed and collaborative learning, while the role of the instructor is to facilitate the learning process rather than download content.

There is wide support in the literature for the constructivist approach, where the deepest learning is achieved through (1) exposure to rich experiences, (2) opportunity to practice, (3) conversation and exchanges with others, and (4) reflection on action. Building on the work of Knowles (1984), Healey, Bingham and Smith (2014), in their review of effective corporate learning and development practices, asked, “When do I learn deeply and effectively?” and found:

  • I learn when I am involved in planning my own development
  • I learn through taking action and reflecting on ways to improve my practice
  • I learn when challenged by problems rather than merely hearing about solutions
  • I learn when the subject is relevant and is something I care about

Cutting through the noise of technology requires intentionality. While rigorously grounded in the theoretical fundamentals of each academic discipline, instructional designers can shape learning experiences around relevant themes significantly connected to real life.

The Nexus of Theory and Pratice

This paper expresses the development of theory and practice within tertiary and professional learning and development programs. Making this explicit is important, as E. M. Forster (1927) commented, “How can I know what I think until I see what I say?” While mindful of the four considerations previously mentioned (in neuroscience, sensemaking, tacit/ explicit knowledge and adult learning theory), the authors assert that, regardless of the technology, effective learning will “cut through the noise” with the learners and suggest some areas of experimentation in instructional design:

a) Breaking learning into bite-size “chunks”—using small parcels of learning that require a shorter attention span, are easier to remember, and when integrated with one another, knit together to build a larger, comprehensive picture and increased understanding.

b) Providing learners with opportunities to plan their own development—choosing pathways based on their own curiosity and discovery, and granting ways to shape their own assessments based on what they care about and find relevant.

c) Using action-oriented assessments that cannot be undertaken online—focused mini-research projects that cannot be done through googling and hypertext links (e.g. review this specific journal article, review this book and use the books in the library to…). These activities force the learner to focus on one source and go deeper into one primary source. Metacognition, the process of thinking about thinking, occurs when learners reflect on what they have learned, identify their own gaps in theory and practice, and initiate their own plans to improve their practice. This is an essential element of learning how to learn.

d) Creating wisdom opportunities—Zeleny (1987) differentiates the layers of knowledge as information (know what), knowledge (know how) and wisdom (know why). Wisdom adds human values to knowledge, requiring soul, discernment and judgement. Whereas knowledge involves understanding and communicating patterns––wisdom involves understanding principles (Rowley 2007). Wisdom contextualises “know how” to include the deeper understandings of culture, history, social interaction and spirituality. This happens through communication and relationship: the connection between various types and sources of information; comparison: contrasting information with other situations; implications: the consequences of this knowledge for decisions and actions; and feedback: the involvement of others in evaluating the quality and usefulness of the information.

e) Creating “disorienting dilemmas” for deep transformational change (Mezirow and Taylor 2009, 19) requires safe emotional engagement enabling the learner to unattach from the known and face the discomfort of the unknown. This safe or held tension creates a climate for learners to examine self, test taken-for-granted assumptions, create an awareness of a gap in knowledge and/or behaviour, and integrate new knowledge (cognitive, behavioural and affective) into their whole-of-life. Immersive simulations, real-life on-the-job situations and interactive case studies are useful tools that can utilise disorienting dilemmas.

f) Using peer learning—in peer learning, learners are required to self-organise in processes that enhance collaborative learning. This could take on a variety of forms: perhaps learners write their own questions and then, in discussion, select the best one for their individual assessment; or perhaps an experienced student coaches an inexperienced cohort of learners through a series of group gatherings as a catalyst, helping them engage with new ideas, challenge case problems, ask provocative questions, and support successful completion of group assessments.

g) Getting specific about reflective learning—educators should specify what sort of reflection they are looking for in an assessment task. The type of reflection should be chosen based on the student learning outcomes desired. Donald Schon (1983), in describing the value of reflective practice, drew a distinction between reflection-on-action (focused in the past) and reflection-in-action (focused in the present). Later, Killion and Todnem (1991) added the future focus with the concept of reflection-for-action. Mezirow (1991) took a different approach, seeing useful approaches to reflection being focused on content, process or premise.

Another way to look at the dimensions of reflection is as follows. Content reflection is focused on what is happening. Process reflection is focused on how things are being done. Premise reflection is focused on critiquing underlying assumptions. Meanwhile, Smith (2013, 38) adopts a four lenses approach to learning through reflective questions:

  • What do I observe happening? (a focus on data)
  • What do I feel about it? (a focus on emotional response)
  • What do I think is going on? (a focus on cognitive analysis)
  • What do I want to be different? (a focus on action for improved practice).

h) Embedding learning into work practice—growing research into how adults learn reveals that effective learning “generally begins with a realisation of current or future need and the motivation to do something about it. This might come from feedback, a mistake, watching other people’s reactions, failing or not being up to a task—in other words, from experience” (Lombardo and Eichinger 1996). This has led to the popularity of the 70:20:10 educative model, which asserts that “about 70% of adult learning comes from on-the-job experiences, working on tasks and problems; about 20% from feedback and working around good and bad examples of the need, and 10% from courses and reading”

(Lombardo and Eichinger 1996). This approach shifts the common “learn then work” paradigm to “work then learn, then work in an improved way”.

The 70:20:10 approach is to be thought of as a simple heuristic model and not a prescriptive recipe (Jennings 2008). It is consistent with other research in the field of adult learning (Cross 2007; McCall 2010; Tough 1968). Yet most of our learning systems in school, work and life still seem formal and classroom focused. Not surprisingly, corporate learning and development tend to mirror what is easiest and least effective—off-site classroom-like information transmission. In comparison, fresh and effective learning architecture can harvest the best of the 70:20:10 approach and focus on learning rather than a focus on instruction by being:

  • relevant and useful (outcomes based)
  • flexible (simple and makes sense)
  • on-the-job (embedded in everyday practice)
  • cost effective (not heavy in expensive face-to-face instruction).

70:20:10 learning is embedded in the workflow yet relevant knowledge is continually extracted from the experience of taking action through observations, peer review and personal reflection. Using this approach, educators are challenged to find opportunities for students to apply new learning in practice immediately and also inform the depth of their theoretical understanding.

i) Using problem-based learning—this approach is now used widely in medical schools around the world to ensure medical practitioners become skilled in both theory and practice. Learners:

a. are presented with a real-world problem;
b. through discussion with their peers, access their existing group knowledge;
c. together develop possible explanations for the problem;
d. curiously ask, “What do we need to know?”, and identify issues to be investigated; and
e. collaborating, construct a shared model to make sense of the problem at hand.

The facilitator guides the process, providing a scaffold (a framework) on which learners can mutually construct useful knowledge (theoretical and practical) to solve the problem. Learners will continue to ask, “What do we need to know?”, until the problem is adequately solved.

j) Learning while taking action—Building on the work of Lewin (1951), Reg Revans (1980) popularised action learning as an industry-focused system to improve business practice, where “the end of learning is action, not knowledge”. Action learning is a form of peer learning with a group of colleagues who work on real, live challenges they are facing. The approach is built on iterative cycles of curious questions, usually in the form of: What did I plan to do? What action did I take? What did I observe? What are my reflections? And then the cycle repeats.


Bateson (1972, xvi) wrote, “an explorer can never know what he is exploring until it has been explored”. While technology is changing rapidly, educators have the opportunity to use new tools to enhance learning. However, the authors assert that a rigorous andragogy will be the most useful tool in producing deep transformational learning. Regardless of the technology used, effective learning will “cut through the noise” with the student by being highly flexible, shaped entirely by context, built on the student’s expectations and previous experience, grounded in the experiential, powered by curiosity, and driven by the need for improved theory and practice. Effective learning will be holistic (respecting the psychological, social, intellectual, physical and spiritual dimensions of the learner) and deeply transformational (producing deep personal change).

This paper is adapted from: Smith, S., and Healey, S. (2015). On the frontiers of change: Designing bespoke learning architecture. In Harrison, J. and Debergue, Y. (eds) Teaching in a Technological Age. Cambridge Scholars Press, Newcastle upon Tyne.


Banks, R. 1999. Reenvisioning Theological Education. Grand Rapids: Eerdmans.

Bateson, G. 1972. Steps to an Ecology of Mind. Chicago: University of Chicago Press.

Boulton-Lewis, G., and M. Tam, eds. 2012. Active Ageing, Active Learning: Issues and Challenges. New York: Springer.

Carr, N. 2010. The Shallows: What the Internet Is Doing to Our Brains. New York: Norton.

Cozolino, L. 2006. “Neuroscience of Adult Learning.” In New Directions for Adult and Continuing Education, No. 110, edited by S. Johnson and K. Taylor. San Francisco: Jossey-Bass.

Cross, J. 2007. Informal Learning: Rediscovering the Natural Pathways that Inspire Innovation and Performance. San Francisco: Wiley & Sons.

Crowell, S. 2004. “The Neurobiology of Declarative Memory.” In The Neurobiology of Learning: Perspectives from Second Language Acquisition, edited by J. Schumann, S. Crowell, N. Jones, N. Lee and A. Schuchert. New York: Taylor & Francis.

DeStefano, D., and J. LeFevre. 2007. “Cognitive Load in Hypertext Reading: A Review.” Computers in Human Behavior 23 (3): 1616–41.

Doidge, N. 2007. The Brain that Changes Itself. New York: Viking Press.

Farmer, K. 1991. “Integrating Academy and Field.” Unpublished paper, Churches of Christ, Sydney.

Forster, E. 1927. Aspects of the Novel. London: Edward Arnold Publishing.

Gioia, D. A., and K. Chittipeddi. 1991. “Sensemaking and Sensegiving in Strategic Change Initiation.” Strategic Management Journal 12 (4): 433–48.

Goswami, U. 2008. “Principles of Learning, Implications for Teaching: A Cognitive Neuroscience Perspective.” Journal of Philosophy of Education 42 (3): 381–99.

Greenfield, P. 2009. “Technology and Informal Education: What Is Taught, What Is Learned.” Science 323 (1): 68–76.

Greenwood, P., and R. Parasuraman. 2012. Nurturing the Older Brain and Mind. Cambridge: MIT.

Hartman-Stein, P., and A. La Rue, eds. 2011. Enhancing Cognitive Fitness in Adults: A Guide to the Use and Development of Community-Based Programs. New York: Springer.

Healey, S., M. Bingham, and S. Smith. 2014. Global Best Practice in People Development. Sydney, Robertson and Chang.

Hebb, D. 1949. The Organization of Behavior. New York: Wiley & Sons.

Jennings, C. 2008. The Point-of-Need: Where Effective Learning Really Matters. London: Advance.

Kandel, E. 2006. In Search of Memory: The Emergence of a New Science of Mind. New York: Norton.

Kauchak, D., and P. Eggen. 1998. Learning and Teaching: Research-Based Methods. Boston: Allyn & Bacon.

Keeling, R., D. Stevens, and T. Avery. 2011. “Biological Bases for Learning and Development across the Lifespan.” In The Oxford Handbook of Lifelong Learning, edited by M. London, 40–51. New York: Oxford University Press.

Killion, J., and G. Todnem. 1991. “A Process of Personal Theory Building.” Educational Leadership 48 (6): 14–17.

Knowles, M. 1984. The Adult Learner: A Neglected Species. 3rd ed. Houston: Gulf Publishing.

Kolb, D. 1984. Experiential Learning. Experience as the Source of Learning and Development. Englewood Cliffs: Prentice-Hall.

Lewin, K. 1951. Field Theory in Social Science: Selected Theoretical Papers. Edited by D. Cartwright. New York: Harper & Row.

Lombardo, M., and R. Eichinger. 1996. The Career Architect Development Planner. Boston: Center for Creative Leadership.

Lovat, T., K. Dally, N. Clement, and R. Toomey. 2011. Values Pedagogy and Student Achievement: Contemporary Research Evidence. New York: Springer.

McCall, M. 2010. “Peeling the Onion: Getting Inside Experience-Based Leadership Development.” Industrial & Organizational Psychology 3 (1): 61–68.

Mezirow, J. 1991. Transformative Dimensions of Adult Learning. San Francisco: Jossey Bass.

Mezirow, J., and E. Taylor. 2009. Learning as Transformation. San Francisco: Jossey-Bass.

Nonaka, I. 1991. “The Knowledge-Creating Company.” Harvard Business Review (November–December): 45– 54.

Nonaka, I. & H. Takeuchi. 1995. The Knowledge-Creating Company. New York: Oxford University Press.

Nonaka, I. & G. von Krogh. 2009. “Tacit Knowledge and Knowledge Conversion: Controversy and Advancement in Organizational Knowledge Creation Theory.” Organization Science 20 (3): 635–52.

Patriotta, G. 2003. “Sensemaking on the Shop Floor: Narratives of Knowledge in Organizations.” Journal of Management Studies 40 (2): 349–76.

Piaget, J. 2001. Studies in Reflecting Abstraction. Hove: Psychology Press

Polanyi, M. 1966. The Tacit Dimension. Chicago: University of Chicago Press.

Revans, R. 1980. Action Learning: New Techniques for Management. London: Blond & Brigg.

Rowley, J. 2007. “The Wisdom Hierarchy: Representations of the DIKW Hierarchy.” Journal of Information Science 33 (2): 163–80.

Sagal, P. 1981. Skinner’s Philosophy. Washington: University Press of America.

Schon, D. 1983. The Reflective Practitioner. New York: Basic Books.

Small, G., and G. Vorgan. 2008. iBrain: Surviving the Technological Alteration of the Modern Mind. New York: Collins.

Smith, S. 2003. “Connecting People: Improving Knowledge Sharing and Collaboration.” Doctor of Management Thesis, Southern Cross University, Lismore Australia and International Management Centres, Edinburgh.

Smith, S. 2013. “Savouring Life: The Leader’s Journey to Health and Effectiveness.” PhD Thesis, Faculty of Health Sciences, University of Sydney.

Sweller, J. 1999. Instructional Design in Technical Areas. Camberwell: ACER.

Tapscott, D. 2009. Grown Up Digital: How the NET Generation Is Changing Your World. New York: McGraw- Hill.

Taylor, J., and E. Van Every. 2000. The Emergent Organization. New Jersey: Lawrence Erlbaum Associates.

Tough, A. 1968. Why Adults Learn: A Study of the Major Reasons for Beginning and Continuing a Learning Project. Toronto: OISE.

Van Nimwegen, C. 2008. “The Paradox of the Guided User: Assistance Can be Counter-Effective.” PhD dissertation, Utrecht University.

Weick, K. 1995. Sensemaking in Organizations. London: Sage.

Weick, K., and K. Sutcliffe. 2001. Managing the Unexpected. San Francisco: Jossey-Bass.

Willis, J. 2010. “Current Impact of Neuroscience on Teaching and Learning.” In Mind, Brain, Education: Neuroscience Implications for the Classroom, edited by D. Sousa. Bloomington: Solution Tree.

Zeleny, M. 1987. “Management Support Systems: Toward Integrated Knowledge Management.” Human Systems Management 7 (1): 59–70.

Ziming, L. 2005. “Reading Behavior in the Digital Environment.” Journal of Documentation 61 (6): 700–712.