Information Technology Reference
In-Depth Information
Table 3. Scenario for APL
Actor
APL candidate
Pre condition
Assessment policy is available in the system.
Standards for APL are nationally established for formal educational programs in the vocational
domain. On the labour market, standards are available for some professions, like assistant professor
or management assistant, and for some general competences, like presenting or organizational sensi-
tivity. These standards are the basic assumption for an APL procedure (
assessment policy
).
Scenario description
1. APL candidate (
candidate
) assumes having competences in domain of management.
2. APL candidate selects in the system the domain and searches for the standards for management
(trait)
.
3. System delivers standards (
trait
) with lower level standards (
complex trait)
and indicators for
these lower level standards (
elementary trait)
.
4. APL candidate starts self-assessment for these standards (according to
assessment plan
)
5. System delivers e-portfolio template after the self-assessment.
6. APL candidate has to provide evidence with argumentation (
item
;
demonstration item
) in portfo-
lio template.
7. APL candidate uploads portfolio.
Post condition
Portfolio template and self assessment are stored and send to assessors.
of APL. In case of APL, does the model fit the
above-mentioned requirements? Therefore, the
educational model for assessment is validated for
APL. For this purpose, use cases and scenarios are
used. In Table 3 one of the scenarios is given. The
corresponding concepts of the assessment model
are placed in italics between brackets.
Based on this validation, we conclude that the
model fits APL.
meaning of words by statistical computations.
The technologies Kalz developed appear to be
very promising and therefore should be further
developed in future research.
CONCLUSION
In the contemporary information society people
are best seen as lifelong learners. However, if we
want people to act as lifelong learners then we
need to assure that there is an e- infrastructure to
support their learning endeavours. This learning
infrastructure does not only offer more, better
and faster education, but most importantly should
fit people's learning needs. One of the key com-
ponents of this emerging learning infrastructure
consists of people's recognition of their prior
learning, since it will shorten their education tracks
and will motivate them throughout their learning
life-histories. Assessment of Prior Learning (APL)
however is time-consuming and expensive.
In this chapter we have described the work-
flow of APL and the instruments needed in this
procedure. We also explained how re-use of
these instruments can contribute to decreasing
the expensiveness of the development of APL.
Support System for Learners
in Learning Networks
It goes without saying that institutes like to offer
personalized learning arrangements to the candi-
dates that finished their APL procedure. However,
composing personalized learning arrangements is
a time-consuming process for which Kalz (2009)
has proposed a technological solution that reduces
time and costs and even improves the quality of
APL. His technical solution consists of a web-
service for lifelong learning that pre-analyses
documents and consequently assists in deciding
the relevancy of these documents for the further
course of the APL procedure. Katz applied Latent
Semantic Analyses (LSA), which is a method for
extracting and representing the contextual-usage
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