The APOSDLE project aims to improve knowledge worker productivity by supporting work-integrated learning. Our Work@Learn approach is based on re-using a wide variety of knowledge artefacts within an organization (such as project reports and meeting notes) for learning. Typically these artefacts have been built without any teaching objectives in mind. Within this contribution we present the way competencies are handled within the first APOSDLE prototype and how competency gaps are automatically identified. We then show how the APOSDLE Learning Tool automatically generates learning events relevant to the competency gap by utilizing organizational knowledge artefacts. Early evaluation results of the prototype are provided and future improvements are discussed.
The challenge of the Learn@Work approach is to compile new learning material,
using existing organizational content that was not necessarily created with teaching in
mind [
Within another contribution to this conference we explore the technological aspects
which have to be addressed in order to meet this challenge. These include specifically
searching for context-relevant resources, automatically splitting up these resources
into meaningful pieces and enhancing them with metadata to create rich “learning
artefacts”. Within this contribution we will focus on how such learning artefacts can
be dynamically assembled into Learning Events (see below for detailed explanation)
2
which support a learner in the development, maintenance or advancement of a
specific competence. These Learning Events go beyond simply presenting
contextrelevant resources but in addition provide learning guidance by automatically
applying instructional design rules. In the following, we will first present our
understanding of competencies and the underlying knowledge space theory which
allows for effective competency gap analysis. Based on this understanding we will
then show how the idea of Learning Templates [
The work and ideas presented here are the outcome of the APOSDLE project (Advanced Process-Oriented Self-Directed Learning Environment) that offers individual learning support to people working with information and contributing new content to an organisation’s knowledge pool. These “knowledge workers” include engineers, researchers, software developers, consultants, and designers. APOSDLE follows a “Learn@Work” approach, meaning that learning takes place in the user’s immediate work environment and context. It offers integrated support for all three roles a knowledge worker interchangeably fills at the workplace: the role of the worker, the role of the learner, and the role of the expert (for more details please refer to www.aposdle.org). APOSDLE is funded within the European Commission’s 6th Framework Program under the IST work program. It is an Integrated Project jointly coordinated by the Know-Center, Austria’s Competence Centre for Knowledge Management, and Joanneum Research. APOSDLE brings together 12 partners from 7 European Countries. 2
The use of competencies has often been advocated as a way to deal with the
challenges in workplace learning [
Because the concept of competency is of research interest in a huge number of
different scientific disciplines (e.g., psychology, educational sciences, economics), the
term competency lacks a standardized scientific definition. Nonetheless, in all of these
disciplines, competency is interpreted as a roughly specialized system of individual
and/or collective abilities, proficiencies, or skills that are necessary or sufficient to
reach a specific goal [
In the Learn@Work approach, we define competencies as personal characteristics
of job holders which they bring to bear in different situations. Competencies are
hypothetical constructs which determine performance in a job. The term performance
is understood to encompass all behaviours relevant for the accomplishment of a
certain task in a specific situation [
Competency Advancement with Learning Templates 3
This function-based view on competencies has a number of advantages for
workintegrated learning as intended for APOSDLE. First, it allows for deriving a worker’s
learning needs by comparing task demands with the competencies the worker has
available. Within the APOSDLE prototype, the worker’s competencies are stored in
the user profile. That way, competency gap analysis is performed based on individual
existing and desired levels of skills and knowledge [
In order to perform both, task-based competency assessment, and competency gap analysis, a formal model is needed that allows for inferences on what competencies are required for a certain task. Given such a model, conclusions could be drawn from a worker’s task performance on her minimum competency state. Given the competency state of a worker, and the competency requirements of a task at hand, a discrepancy could be identified and educational interventions could be initialised.
Ley, Lindstaedt and Albert [
In an attempt to develop Knowledge Space Theory further, Korossy suggested that in addition to the set of problems, one should look at the set of competencies that is knowledge, skills and abilities needed to solve the problems. This would generate information on the reasons for different levels of performance, and thereby help to suggest learning measures. Similar to the set of questions, competencies are also structured in a competence space which results from a surmise relation on the set of competencies. 4 The relationship between the two sets (questions and competencies) is formalized by an interpretation function which maps each problem to a subset of competence states which are elements of the competence space. This subset of competence states contains all those competence states in each of which the problem is solvable. The interpretation function induces a representation function which assigns to each of the competence states all problems which are solvable in that competence state. Which problems are solvable is determined by the interpretation function.
The Competence based Knowledge Space Theory has been applied in technology
enhanced learning applications. For example, Hockemeyer et al. [
The first prototype of the APOSLDE system contains a competency model for the
learning domain requirements engineering. 47 tasks in this domain were derived from
expert interviews, and 33 competencies were found to be necessary to perform these
tasks. The competency model also consisted of a mapping of which competencies are
required for which of the tasks. The APOSDLE competency model as well as the
method for its construction and validation is given in [
Currently, the user profile of an APOSDLE user is filled by selecting each task the worker is able to perform, which defines the performance state. The worker’s competence state is inferred from her performance state. When the worker selects a task from a list, the APOSDLE system performs competency gap analysis by comparing the task requirements (interpretation function) with the worker’s competence state. According to the worker’s competency gap, the APOSDLE system provides her with learning resources that are related with the missing competencies. The selection and initialization of learning resources is handled by the learning tool (see next chapter).
Within APOSDLE, the Learning Tool is responsible for managing and supporting the learning process. In this section, we outline the Learning Tool’s conceptual ideas, present an overview of the developed software and we conclude with the results from the early evaluation sessions.
The Learning Tool is based on the principles of self-direction in learning, and on the relationship between types of desired learning outcomes and instructional strategies. We provide a short description of these two principles below.
According to Knowles, self-directed learning is ‘a process in which individuals
take the initiative in designing learning experiences, diagnosing learning needs,
locating resources, and evaluate learning’ [
Competency Advancement with Learning Templates 5
selection and implementation of a learning strategy, and the evaluation of the learning
outcome. This is similar to Stubblefield’s four phases, described by Brockett and
Hiemstra: initiating, planning, managing, and evaluating [
The second principle on which the tool is based is the relationship between types of
learning goals and instructional strategies. This approach is based on Robert Gagné’s
conditions of learning [
intended to actively engage the user in the learning material. For example, users are asked to compare examples and to critique provided definitions.
Our current design supports the first four steps that were identified in Knowles’ five step model. In APOSDLE, the learning need is identified either by users themselves or (in the future) by the system. After a learning need is identified, a learning goal is selected. In APOSDLE the learning goals are represented as competencies. These competencies describe the desired learning outcomes and are classified according to the classification presented before. The selection of a Learning Template is performed by the APOSDLE Learning Tool. This selection is based on the type of the selected competency. Then, appropriate learning material is identified and the material is used to create Learning Events. The user can select the created Learning Events from a list. The final step, the evaluation of the learning outcome, is not performed in the first prototype.
For the formative evaluation of the APOSDLE prototype we performed several
evaluation activities, including expert walkthroughs (with usability and instructional
experts), evaluation sessions at the application partners and evaluation sessions with
students. In terms of Kirkpatrick’s four-level evaluation model [
Currently, APOSDLE presents fragments of documents. The fragments were cut out of the original document and APOSDLE provided no feedback on the location of the original document. The evaluation sessions that were performed at the application partners revealed that the users did not appreciate this approach. Besides, the information provided by the documents was sometimes difficult to link to the competencies to acquire. Obviously, the effectiveness of Learning Templates can only be studied when the provided content is suitable.
The next version of APOSDLE will take into account the differences between
learners to enhance learning. Smith and Ragan [
Competency Advancement with Learning Templates 7
as cognitive styles, Tennant [
In the first APOSDLE prototype, the competency model is mapped onto a domain model (ontology) in order to select appropriate learning resources. Both, the mapping and the annotation of learning resources with domain model elements were done manually. In the second prototype, the competency model will be embedded into the domain ontology in order to avoid the mapping between the two. Moreover, a tool will be developed for performing supervised automated document annotation.
Additionally, the Learning Tool will provide sequences of learning material. Currently, every Learning Event is self-contained and Learning Events do not include references to other Learning Events. However, some subjects and learning goals are harder to master and cannot be learned in one learning session. In the Learning Tool we want to develop the functionality to construct a sort of plan consisting of a series of Learning Events.
For the next versions of the APOSDLE system, the evaluation sessions will gradually shift the focus from Kirkpatrick’s lower evaluation levels, such as reaction, towards the higher levels, such as the learning results and the behavioral changes in the workplace.
APOSDLE is partially funded under the FP6 of the European Commission within the IST work program 2004 (FP6-IST-2004-027023). The Know-Center is funded by the Austrian Competence Center program K plus under the auspices of the Austrian Ministry of Transport, Innovation and Technology (www.ffg.at) and by the State of Styria.