Skip to end of metadata
Go to start of metadata

This is a space for discussion and preparations for a draft of a new CEN CWA on learning outcomes

According to the European Qualification Framework (EQF) "Learning Outcomes are the statements of what a learner knows, understands and is able to do on completion of a learning process". This covers Knowledge, Skill and Competence

There are two issues to be discussed here:

Data Model for Describing Learning Outcome Definitions

A data model for Learning Outcome Definitions (LOD)defines a conceptual base schema for describing and sharing learning outcome definitions in the context of online and technology enhanced learning. The data model provides a way to capture the key characteristics of a learning outcome, independently of its use in any particular context or target group (persons). Thes model should enable the storage, findability and exchange of learning outcomes across learning systems that deal with learning outcomes data, like university administration systems and learning management systems.

In ICOPER Project, an application profile of IEEE RCD was used

This also covers the description of intended learning outcomes..

Is this something we want to discuss at CEN WSLT? Or we just rely on existing standards like IEEE RCD work?

Data Model for Describing Personal Achieved Learning Outcomes

One of the main challenges that face communities and systems that deal with learning outcome information is the interoperability issue. Different communities and systems may use different data models to represent information on skills, knowledge or competence obtained by a person or that is required for a job or a task.

The Personal Achieved Learning Outcomes (PALO) data model is a data model proposed to capture information on knowledge, skills and competences achieved by a person (a learner) and relations between those outcomes. Furthermore, information on the context where the learning outcomes are obtained or applied, evidence records and levels (e.g. proficiency level) associated to the outcomes are also part of this schema.

The PALO specification is a step towards a common model supporting the exchange of such data, to enhance interoperability of personal learning outcome information between, for example, learning management systems, e-portfolios, social applications and recruitment systems.

This data model should enable describing relations between learning outcomes of learners, in addition to contextual and evidence related information:
• Relations between achieved learning outcomes, regardless of the taxonomies or ontologies they belong to;
• Contextual information on where the achieved learning outcome is obtained or applied;
• Information about all types of evidence and assessment that prove the achievement of a learning outcome;
• Information about levels and ranking of an achieved learning outcome, like proficiency level.

The PALO data model covers (with some customization) data elements and concepts related to learning outcomes from other specifications like:
• IEEE RCD: describe the characteristics of learning outcomes;
• HR-XML: describe evidence records of learning outcomes.

More Info. on PALO

Potential Contributors

  • Jad Najjar, Vienna University of Economics and Business (WU Vienna), Austria
  • Bernd Simon, Vienna University of Economics and Business (WU Vienna), Austria
  • Simon Grant, JISC CETIS, UK
  • Michael Derntl, University of Vienna, Austria
  • Tomaž Klobučar, Jožef Stefan Institute, Slovenia
  • Cleo Sgouropoulou, Technological Educational Institute of Athens, Greece
  • Michael Totschnig,Vienna University of Economics and Business (WU Vienna)
  • Petra Oberhuemer, University of Vienna, Austria
  • Susanne Neumann, University of Vienna, Austria
  • Jan Pawlowski, University of Jyväskylä, Finland
  • Daniel Müller, IMC, Germany
  • Joris Klerkx, K.U.Leuven, Belgium
  • Christian Stracke, University of Duisburg-Essen, Gemany
  • Erlend Øverby, Hypatia as, Norway
Enter labels to add to this page:
Please wait 
Looking for a label? Just start typing.