Learning about elearning, m-learning, eportfolios. Also my meanders into research, in particular research into workplace learning, apprenticeships and apprentice learning, trades tutors and vocational identity formation. Plus meanderings into philosophy and neuroscience as I learn more about how we learn.
Usual disclaimers apply. This blog records my personal learning journey, experiences and thoughts and may not always be similar to the opinions of my employer.
The book is available as an ebook via the Ara library.
Timely book to inform on e-assessments project and the learning design work which makes up a large part of my present work. The book provides direction for the future of learning design as traditional models, based on constructivist / or even behavourist/instructivist models, are no longer pertinent as the education is challenged to assist learners to be sufficiently prepared for the future of work.
The book has 14 chapters organised into 3 parts.
Part 1 – foundations of emerging technologies had 5 chapters
An introductory chapter ‘the dialogue between emerging
pedagogies and emerging technologies’ is by B. Gros and sets the scene for the
book and provides overviews of each chapter. Some of the changes:
learner-centred, individual and social learning; personalised and tailor-made
learning; innovative pedagogical concepts – experiential and immersive learning
and social and cognitive process; formal institutions will need to be flexible
and dynamic; and education and training made available and accessible to all
citizens. Introduces the emerging theories of learning: theories focused on the
network (networked learning, connectivism, actor-network theory); theories
focused on social-personal interaction (heutagogy, peerology); and theories
focused on the design of network (Learning as a Network – LaaN). ). LaaN
combines aspects of connectivism, complexity theory and double-loop learning.
Learning is envisaged to be a personal network of knowledge attained through
interactions with the ‘ecological’ spheres of learning. Hence ‘emerging
pedagogies are held to: support lifelong learning and ecologies of learning;
use different forms of knowledge; integrate the use of technology as
‘mindtools’; change the nature of the traditional roles of teacher and learner;
integrate self-regulation, co-regulation and social share regulation; promote
deep learning tasks; are transparent; based on socio-constructivists
pedagogies; and require new forms of assessment.
Chapter 2 overviews principles of “heutagogy: a holistic
framework for creating 21st century self-determined learners’ by L
M. Blashke and S. Haase. Introduces, defines heutagogy as a form of
self-determined learning and rationalises it as a holistic, learning-centred
approach. Characteristics are learner-centred and determined; based on
capability, self-reflection and metacognition; allows for double-loop learning
along with nonlinear learning and teaching. Presents the affordances for
heutagogy as availed by digital technologies. The heutagogy learning ‘loop’
cycles through / touches base with activities to explore, create, collaborate,
connect, share and reflect.
P. B. Sloep contributes the next chapter on ‘design fornetworked learning’. Networked learning is defined as learning using computer
networks for educational activity. Uses the distinctions between epistemic,
social and set design to guide the design of networked learning. Critiques the
process and suggests improvements. Epistemic design involves ensuring learning
activities are aligned to the achievement of learning outcomes. Uses
Laurillard’s work – design patterns for learning – as a frame complete the
epistemic design. Social design is based on socio-cultural learning theories
including the work of Brown and Duiguid – the social life of information and
Lave and Wenger’s communities of practice. Set design includes the selection of
appropriate tools to support epistemic and social design. It is essential these
tools are used in a holistic manner, so the various ‘elements’ of learning are
connected and assist self-directed (heutological) learning.
Chapter 4 is on ‘why do we want data for learning? Learninganalytics and the laws of media’ by E.D. Gazulla and T. Leinonen. Provides
theoretical and analytical understanding and discusses pros and cons. Of note
is the connection between LA and the types of pedagogies that can be supported.
Examples include analytics to support learning through the use of social
networking, discourse, content learning, dispositional learning and student
centred approaches. The proviso is to ensure the correct type of LA is used to support
the appropriate learning approach. Mis-match leads to invalid data being used
to support decision making!
The fifth chapter is on ‘articulating personal pedagogies
through learning ecologies’ with M. F. Maina and I.G. Gonzalez. Proposes
learning ecologies as one way to explore ‘frontier’ pedagogies to connect the
formal, non-formal and informal learning contexts of individuals. The chapter
provides background on the evolution of learning ecologies including personal
learning ecologies. Presently, attempts to match the needs of individual’s
learning to the offerings of ‘mass education’ have been disappointing. Moving
to personal learning environments (PLEs) requires large shifts in how education
is valued, measured, accreditated etc. PLEs implies learners use their
self-direction to learning through all spheres of their lives, through formal,
‘informal, networked, socially-connected means. Having to ‘measure’ these, and
whether this is the way to go, requires investigation and rationalisation.
Chapter 6 provides some ideas.
Part 2 covers learning design for emerging technologies with
N. S. Selander contributes with chapter 6 on
‘conceptualization of multimodal and distributed design for learning’. The
chapter describes the shifting from SYSTEM 1 (stable structures, national
curricula, classroom teaching, printed school textbooks and assessment
standards) to SYSTEM2 (dynamic (global change), development of digitized media,
cognitive systems, mobile learning and individual learning from 2000 onwards. SYSTEM
2 requires the development of a new paradigm for the future curriculum,
including new ways to recognise learning and need for new assessment practices
(and standards); need to account for and understand learning in relation to
multimodal design; and the role of digital media in organisation of school work
Current theories of learning founded on SYSTEM 1. Proposes
the use of ‘learning design sequences’ as a basic unit of learning. LDL model –
Learning design sequences – see this article for further details.
Chapter 7 by A. Littlejohn and L. McGill covers ‘ecologies
of open resources and pedagogies of abundance’. Presents analysis of diverse
pedagogies enabling learners to capitalise on digital, open resources. The
emphasis is not on the content but on helping learners to create and navigate
their own pathways. This is a modern take on ‘constructivism’ with good
examples of how to leverage off the ease of access to open resources and how
learning can be designed to make the most of the affordances availed.
The next chapter discusses ‘educational design and
construction: processes and technologies’ by S. McKenney and T. C. Reeves.
Comprehensive chapter which provides a range of learning design approaches to
deal with the present and future challenging learning environment. Design
through exploring and mapping and construction of solutions is covered. This
chapter provides the ‘how do we get from design’ to actually implementing the
solution. Strategies for idea generation (synectics, SCAMPER, Slip writing,
picture taking) followed by how to consider the idea (Dr Bono’s hats, courtroom
challenges, SWOT analysis, weighted ranking) and idea checking using logic
modelling. The solution mapping involves refining design, using skeleton design
and constructing the detailed design specifications. Initial solution building
includes management of the prototyping process using assistance form project
management tools – critical path, gannt charts, milestone map, Rasci matrix
followed by evaluation of iterations and consideration of revisions. Outputs of
the entire exercise include the need to record and synthesise frameworks.
‘User-centred design: supporting learning designs’
versioning in a community platform’ is by J. Chacon-Perez, D. Hernandez-Leo, Y.
Mor and J. I. Asensio-Perez. Reports on a project whereby a community platform
called Integrated Learning Design Environment (ILDE) is used to share and
assist with co-editing of resources and activities for implementation into
learning programmes. Represents a ‘worked-example’ case study genre. Many of
the ideas presented in the preceding chapters are used in the ILDE.
Chapter 10 by F. Pozzi, J. I. Asensio-Perez and D. Persico
is on ‘the case for multiple representations in the learning design life cycle’.
As per chapter 9, chapter 10 reports on a project. The project uses
visualisation to assist with learning design across time. Principles of
multimodality are applied and used across both the approaches deployed in the
learning design and in how the overall learning design process is recorded for
later evaluation and analysis. Of importance is the assertion that ‘one size
does not fit all’ and the use of the ‘life cycle’ as a guide, not a framework
set in concrete.
The last part is on adaptive and personalised learning with
Chapter 11 covers ‘measurement of quality of a course:
analysis of analytics’ by J. Seanosky et al. Recommends not just the evaluation
of courses at the end through learner feedback, but continually, formatively
and summatively, using factors across learner motivation, learner capacity,
learners’ increasing competency and instructor competency.
The next chapter by T. Zarraonandia, P. Diaz and I. Aedo is
on ‘modeling games for adaptive and personalised learning’. Of interest to
those incorporating elements of gamification into learning design. The chapter
provides a good overview and discusses ways to ensure games are developed to
allow for personalised learning to flourish.
Chapter 13 is by I. A. Zualkernan who discusses
‘personalised learning for the developing world’. Introduces various models
supporting the development of PLE type educational programmes for developing
countries. Acknowledges the difference in resource and access between the
developed and developing contexts and provides some ideas to assist with
Last chapter is by A. Alun on ‘understanding cognitive
profiles in designing personalised learning environments. Describes the use of
neuropsychological tests’ potential to determine learners’ cognitive profiles
and how these can be applied to better understanding and designing programmes
based on personalised learning environments. Perhaps a chapter that could have
gone earlier into the book. This chapter uses neurological / cognitive
characteristics to assist with the design of PLEs. Takes on the view of ‘know
the learner’ and matched to better way to present learning so learner is able
to access. Various neuropsychological tests detailed. Discusses how we all deal
with attention, memory, navigate through information etc. differently. Proposes
future work on harnessing the individual’s ‘ways of doing’ to help enhance /
mediate / support their learning.
All in, the book rewards for time put into reading the many chapters. Each chapter brings with it an approach to learning design that is supported and informed by previous scholarly works and supplemented by projects in the field. My challenge is to tease out the items which are relevant to our work at Ara. Given the diversity of discipline areas and levels of learning within Ara, there will be congruence between some of the theories described in the various chapters, and the graduate profiles / learning outcomes required. Will need to read through the salient chapters to identify the approaches which we can use or adapt.
‘Super artificial intelligences
(AI)’ are currently able to churn through vast amounts of data to create
solutions. Used in tandem with other digital tools including embedded chips in
other machines, humans and appliances (i.e. the internet of things), AI has and
is set to replace blue and white collar workers. AI will be installed in
machines, turning them into automated ‘robots’, self-drive vehicles, automatic
stock control ‘containers’ and self-repairing appliances.
One perspective is dire. 46% of the current jobs in NZ are
predicted to disappear or be significantly changed due to effects of
technology. (see NZ Labour party website set up to discuss future of work as an
other, and in my humble opinion, more realistic scenario, is that new jobs will
be created and current jobs will be transformed. History supports this
perspective. When work in certain sectors become scarce, people move on into
other types of work. These new types of work would have become necessary to support
the technology that removed the original work itself! (see this article from Forbes for more detailed discussion)
A recent bbc article also supports the above. There are some things, currently still uniquely human, that cannot yet be replicated by machines.
We are now back to the challenges presented to education by the rapidly shifting demands of the world's workforce and economies. Change in education moves ever so slowly. Debates have swung backs and forths as to whether 'Learning Transfer' occurs easily, whereby individuals trained in specialists vocations are able to switch into another (preferably) related job, if their current work disappears. There is the spectre of 'near' and 'far' transfer and for some educationalists', the argument is for very little transfer!
So where does that leave the individual? Continual life-long learning is a given but what of continually retraining to on and on to try to fit into continually changing work? Who bears the costs? the individual? the organisation? the country's educational system? A shared responsibility is the key. It will be interesting to see the final iteration of the 'productivity commission report on tertiary education'. The final report is due out late February but it looks like it is going to be slightly late. The draft sent out for submissions raised more questions than recommended solutions :)
All above important for educational developers to be cognisant on. The 'new' programmes of study we are now working on need to reflect the challenges presented for development of the 'future workforce'.
The overall premise of Grant's work, as summarised in the Ted Talks is how to recognise the difference between innovators and followers.
- innovators may be slow to get off the ground. They are the ultimate procrastinators.Procrastination may be used to mull over ideas and come to better solutions.
- innovators may not be the first or the best. They make mistakes and learn from them.
- There may have to be many bad ideas before good ones come along!
- therefore resilience and ability to learn are also important.
Perhaps deep pockets, ability to garner funds, high social / economic capital to start with which translates to access to 'angel' funding are also important!
Education, in particular summative assessments whereby students attain a final grade are therefore not a good measure of entrepreneurship or innovation as the learner is penalised (marked down) for mistakes! We perhaps need to make overt to students, the subjects or topics which are important towards attainment of foundational knowledge and skills, the canon of the discipline. Then the courses whereby project work, portfolios etc. are the mechanisms for assist 'learning by making mistakes', allowing for reflection and review to inform the next stages of learning.
Despite TV series like Human and movies – 2001 Space
Odyssey, Matrix, Terminator etc. the actual performance of AI is still emergent. However, we perhaps have an
innate fear of non-human intelligence. Especially if we are unable to totally control
all aspects of the intelligence.
Here are two videos, providing a more nuanced view on how AI may or may not impact on our lives, in particular, the work that humans do.
First up, a TED talk video from Grady Booch in a 10 minute presentation, delivered late last year. The title, Don't fear super intelligence, is apt. The presentation provides a good overview of
the possibilities and challenges. Optimistic slant similar to book by- – teaching AI to value human characteristics –
ethics, emotion and judgment.
In short, humans are still the directors (we can still unplug the
computer at the moment!).
Second video, another TED talk by David Autor on the topic, of why jobs will not be lost despite advances in technology and AI. This talk also from late last year and is 18 minutes long. Another optimistic viewpoint, creating machines to do work
for us, has actually not led to human labour becoming obsolete. The %age of working
adults actually increased.
Two aspects support Autor's argument. One 'the O-ring principle' – determines the type of work with do
General principle of work means all work requires a range of
skills. Automating some aspect of the work means need for worker to upskill and
a different aspect of work becoming the focus. Example bank tellers who now do
not have to do the mundane tasks but have become ‘sales’ people and problem
solvers. Improvement of tools increases importance of human expertise
Secondly the 'never get enough principle' – certain industries did not
exist before, but now take up large sectors. Argues less work equates to more
leisure. Leisure generates new sectors.
Automation creates wealth by creating more time for us
think, create and re-create.
The challenge is not that we will run of work, the challenge
is skill mis-match. High skill jobs and low skills jobs increase, but the
middle skill jobs are the ones most treathened. Examples used of agreicultural
revolution in the US whereby young people were encouraged to complete high
skill, increasing skills for manufacturing. Key still through education.
Technology actually magnifies human’s strengths –
creativity, innovation and problem solving. We never have enough, so new
industries will create new types of work. 40% of Americans in agriculture, now
2% but producing sufficient food for now. 95% decrease in workforce but
increase in productivity.
Again, the importance of education, continual need for workers to up-skill, is reiterated. For education to keep up, the learning of occupational specific skills require distillation into salient 're-configurable' skills as technology shifts job types and needs.
Many of the items we read in the news about the future of work, tend to focus on the ways in which technology will impact on humans in a negative manner. In all endeavours, there are good and bad sides to the story.
For example, this article from Forbes, argues that the future is not that scary. The article does a good job of summarising the salient impacts and approaches the future of work by distilling the personal, organisational and societal impacts. Of importance is the need for individuals to shift from a pathway of education, work and retirement into a cycle of where education, work and leisure are continually 're-invented'. The 're-design' of organisations also includes a need to continually 're-skill' with the 'middle management' layer the ones to most likely be wiped out as jobs which are more 'mundane' disappear and AI replaces 'company wisdom'. Jobs may disappear, but many other jobs well be changed and created as well. There is a call at the end of the article for education and public policy to keep up. These two megaliths have always been slow to change. For education, the recommendation is to ensure vital 'basic skills' including thinking, writing, analysing and maths and science are pre-requisites to completion of formalised schooling. The is then space for 'new education companies' liked Pluralsight, General Assembly, EdX and Coursera - offering small / just-in-time training / educational packages.
On a related note, an article on 'crafting the employee experience' from Deloitte University Press, advocates for the use of 'design thinking' to help employees and employers (i.e. HR). HR becomes 'experience architects' and are tasked with reimagining all aspects of work in their organisations. Aspects include the physical environment; how people meet and interact; the focus of management; and the processes of selecting, training and evaluating workers. Therefore, a focus on individuals and their experience, not just the process of HR.
For many years, education have had 'personal learning environments (PLEs)' as an approach. There are considerable logistical and funding challenges to implementation. The current models based on 'one size fits all' and 'factory production' of outputs (i.e. learners) are being dismantled but only in small pockets of education. So a challenging but exciting time to be in education.
In an effort to get to grips with the role of technology,
going forward into the future, I worked through two books by Kevin Kelly over
the summer ‘break’. In much of the literature and media collation of ‘the
future of work’, the role of technology is the all present BIG elephant.
Technology is seen to be ‘a good thing’ but also the harbinger of changes to
our way of life and the types of work available in the future. In more dystopic
and pessimistic versions of the future, the cause of social inequalities and
division is how technology changes the availability of 'mundane / unskilled' work. The more able and educated are able to transition rapidly into new work leaving many others behind who are unable to make the shift.
So, firstly, read through Kevin Kelly’s first book,
published in 2010. Kelly was editor of Wired and has an interesting background. In effect, coming from an original 'back to basics' philosophy to becoming an early adopter and 'observer' of technology's eventual pervasive influence on our current lives.
What does technology want provides an interesting comparison
between natural evolution and the development of technology. The overall
approach is optimistic and the main argument is for us humans to understand and
maximise the strengths technology provides to augment human potential. The book has been critiqued for imposing a technological view on to biological evolution. There is a 16 minute TED Talk to summarise the book's premises and the concept of 'the technium'.
The second book published 2015, The Inevitable, is perhaps more readable and applicable to the current
context than the first. In this book, Kelly brings evidence from the recent
past and the present, to support 12 coalescing ‘verbs’ on how technology
impacts on the near future. There is a one hour Youtube video summarising the book's thesis.
These, as recorded in wikipedia are:
1.Becoming: Moving from fixed products to always upgrading
services and subscriptions
2.Cognifying: Making everything much smarter using cheap powerful
AI that we get from the cloud
3.Flowing: Depending on unstoppable streams in real-time for
4.Screening: Turning all surfaces into screens
5.Accessing: Shifting society from one where we own assets, to one
where instead we will have access to services at all times.
6.Sharing: Collaboration at mass-scale. Kelly writes, “On my
imaginary Sharing Meter Index we are still at 2 out of 10.”
7.Filtering: Harnessing intense personalization in order to
anticipate our desires
8.Remixing: Unbundling existing products into their most primitive
parts and then recombine in all possible ways
9.Interacting: Immersing ourselves inside our computers to
maximize their engagement
10.Tracking: Employing total surveillance for the benefit of
citizens and consumers
11.Questioning: Promoting good questions are far more valuable than
12.Beginning: Constructing a planetary system connecting all humans
and machines into a global matrix.
As prefaced in the book, there are overlaps
between the inevitables. So each does not stand alone and there is synergy between several 'inevitables'.
What is the impact on the 12 inevitables with education, especially vocational education?
Unlike the compulsory-school and the higher education (preparation for work) sectors, vocational education has the advantage (or disadvantage) of having a foot in the 'formal / structured' learning environment and the more 'informal' learning accessed by people across their lives. Just-in-time learning, micro-learning etc. via mlearning and summarised for example via Jane Hart's blog, already evidence some of the inevitables.
People can 'subscribe' (belonging as in #1 inevitable) to learning via MOOCs or other methods to 'bespoke' their own personal learning environments. Flowing (#2), Screening (#4) and Accessing (#5) all add to people's learning experiences as they learn collaboratively on a global scale (#6 sharing), interacting (#9) and often have to use tools to filter (#7), remix (#8) to their own requirements. They can, along with others, track (#10) all their activities. Their learning may be supplemented by AIs (cognifying as in #2) and their are opportunities to question (#11) are availed through being part of networks, social media, access to multitudes of 'content' etc.
The Inevitable provides a good overview of where humanity may be headed. There is importance in understanding how the rapid shifts in technology impact on us. We can then make more informed choices as to what initiatives we support and advance. To use technology for betterment of the human condition rather than just let technology overwhelm our humanity.