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Within this chapter, we are looking back at
this history of personalized, adaptive learning to
formulate a critique on the contemporary models
and theories, while at the same time proposing a
new approach that puts learners centre stage again.
We will argue that this approach is more apt to
explain adaptive personalization in technology-
enhanced learning and is more helpful in guiding
(even end-user driven) engineering and mainte-
nance of personalized learning environments. The
approach we propose has been developed within
the scope of the European IST project 'iCamp'
(Kieslinger et al., 2006) and is currently extended
in the European IST project 'ROLE'.
The rest of this chapter is organized as follows.
First, we characterize background assumptions and
two important research movements that influenced
our own proposal, namely personal learning en-
vironments and end-user development. Then we
elaborate our critique on the contemporary models
for personalized adaptive learning. Subsequently,
we are going to show that learning environment
design is the missing link, able to avoid the flaws of
prior adaptation theories in technology-enhanced
learning. Therefore, we propose our alternative,
i.e. the concept of a mash-up personal learning
environment that provides adaptation mecha-
nisms for learning environment construction and
maintenance. We demonstrate this approach with
a prototypical implementation and a - we think
- comprehensible example. Finally, we round up
this chapter with possible extensions of this new
model and (still) unresolved problems.
of social, self, and methodological competence
(i.e. transcompetences, also known as rich pro-
fessional competences) prior to or in addition to
content competence is superior to only acquiring
content competence (i.e. domain-specific skills,
facts, rules, and the like). This is not only justified
through the added value of transcompetences, but
additionally by the decreasing half-life of domain-
specific knowledge and through the challenges
imposed by lifelong learning (see also Wild et
al., 2009). The competence to adapt both flexibly
and quickly to changing context becomes vital
especially at the transition between education,
training, and work - and in between different
work places or job roles. Monitoring ones own
competence portfolio, identifying knowledge
gaps, and remediating shortcomings planfully
with learning are key competences in our modern
society. We deliberately say 'constructing' as in
constructivist theory a 'transfer' of knowledge
does not exist: knowledge can only be created
from within the minds of the learners, though of
course influenced on sensory experiences provided
by their environment.
Second and consequently, we presuppose that
establishing a learning environment, not in the
usual sense of a technology-based environment
but a network of people, artefacts, and tools (con-
sciously or unconsciously) involved in learning
activities, is part of the learning outcomes, not
an instructional condition. This is even more
important in lifelong learning, where technol-
ogy constantly innovates and where changes in
location, career, or even profession can easily
disrupt an existing environment and cause a need
for learning and adapting to a new environment.
Adaptation strategies go beyond navigational
adaptation through content artefacts along a
predefined path: for example, some learners may
prefer to email an expert instead of reading an
online paper; and managing a professional social
network may hence become equally important
the skills of using a digital library. Adaptation
has to take place along individualized activities
BACKGROUND
The mash-up personal learning environment ap-
proach is strongly based on three assumptions on
which the subsequent approach builds. First, we
assume that learning to learn while at the same
time learning content is a better approach than
just (re-)constructing domain-specific knowledge.
In other words, we believe that the acquisition
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