and Kühn in (Karagiannis & Kühn, Metamodelling
Platforms, 2002), (Kühn, 2004) has been used to
develop the Learn PAd meta-modelling method.
As depicted in Figure 1 the building blocks of a
modelling method include: (1) the modelling
language introducing modelling concepts pre-
defined according their semantic, their syntax and
their graphical notation, (2) the modelling procedure
which defines the stepwise usage of the modelling
language and may not be always available and (3)
generic and domain specific mechanisms and
algorithms enabling the computer-based processing
of models.
3.1 Modelling Language
The modelling language has been developed
following the meta model based approach and is
described in detail in D3.2 (Learn PAd D3.2, 2015).
The core domain is the business process model
(using BPMN (OMG, OMG BPMN, 2015)) and the
flexible case management (using CMMN (OMG,
OMG CMMN, 2015)), which is linked to the
business processes. Both are performed by workers,
who are described in the organizational (structure)
model. In order to perform skill-management, there
is also a competence models, which details the
traditional work place description of the
organizational model.
Document and knowledge models provide the
organizational knowledge in order to perform and
execute the business processes and the cases.
In order to enable continues improvement, the
business motivation model describes goals,
intensions and rules, whereas the KPI (Key
Performance Indicator) model, collects and
aggregates measures and construct measurable
indicators to assess the evolution of the learning
organization.
Some other model types like the process map or
the knowledge system model are introduced. Those
model types do not carry own domain information
but mainly act as a navigation support to navigate
between the different aforementioned models.
BPMN 2.0 has been realized in Learn PAd
focusing on those aspects which are relevant for
human – learning – interaction, and leave out –
technical – aspects, which are not relevant.
Although all concepts are specified in the BPMN
2.0 standard, its realization including abstract classes
as well as references to other model types (– so
called model type weaving.
More information on the BPMN realization is
provide on the Learn PAd development space at
ADOxx.org (ADOxx.org DS, 2015), as well as in
D3.2 (Learn PAd D3.2, 2015).
The use of flexible case management, hence the
description and collection of different cases
introduces not only a flexibility into the business
processes but also enables collaboration in form of
discussions, recommendations and lessons learned in
exceptional cases.
Due to the absence of appropriate standards that
describe the organizational structure, Learn PAd
used the meta model from the first and most
successful community business process management
tool ADONIS
®
Community Edition.
Organizational units describe the different
departments, sections or the enterprises, hence
define organizational boundaries. The roles describe
the ideal representation of competences, whereas the
performer describes the current workplace holder
and hence describes the actual competences.
The Document and Knowledge Model type
specification, that is interesting for learning and / or
knowledge management models, traditionally, is a
document pool, that lists all documents that are
needed – either as input, as a resulting output, as a
guidance or as a support document – when executing
a business process. This traditional view is highly
important in quality management scenarios or in
keeping the business process documentation clear
and simple.
In the context of learning, we enriched this
model type with elements from the PROMOTE
®
modelling language (Robert, Process-Oriented
Knowledge Management: A Service-Based
Approach, 2004). A language that was first
implemented in 2000 in a research project (Rainer,
Dimitris, & RobertWoitsch, 2001) and now founds
its way into teaching and industrial projects.
Knowledge resources are described in three
forms: (a) the document as an atomic knowledge
carrier with a unique identifier, (b) the knowledge
source that is – often a very large – container of
documents, which collects, manages and
encapsulates the big amount of documents like
databases, document management systems or file
directories, as well as (c) the knowledge resource,
which represents not only complicated but also
complex knowledge carries such as humans, or
communities.
The difference between knowledge source and
knowledge resource is that a knowledge source
provided predictable results, hence a formal correct
query into a database or file repository, will result in