Stern Hermann, Kaiser Rene_DB, Hofmair P., Lindstaedt Stefanie , Scheir Peter, Kraker Peter
2010
One of the success factors of Work Integrated Learning (WIL) is to provide theappropriate content to the users, both suitable for the topics they are currently working on, andtheir experience level in these topics. Our main contributions in this paper are (i) overcomingthe problem of sparse content annotation by using a network based recommendation approachcalled Associative Network, which exploits the user context as input; (ii) using snippets for notonly highlighting relevant parts of documents, but also serving as a basic concept enabling theWIL system to handle text-based and audiovisual content the same way; and (iii) using the WebTool for Ontology Evaluation (WTE) toolkit for finding the best default semantic similaritymeasure of the Associative Network for new domains. The approach presented is employed inthe software platform APOSDLE, which is designed to enable knowledge workers to learn atwork.
Ley Tobias, Ulbrich Armin, Lindstaedt Stefanie , Scheir Peter, Kump Barbara, Albert Dietrich
2008
Purpose – The purpose of this paper is to suggest a way to support work-integrated learning forknowledge work, which poses a great challenge for current research and practice.Design/methodology/approach – The authors first suggest a workplace learning context model, whichhas been derived by analyzing knowledge work and the knowledge sources used by knowledgeworkers. The authors then focus on the part of the context that specifies competencies by applying thecompetence performance approach, a formal framework developed in cognitive psychology. From theformal framework, a methodology is then derived of how to model competence and performance in theworkplace. The methodology is tested in a case study for the learning domain of requirementsengineering.Findings – The Workplace Learning Context Model specifies an integrative view on knowledge workers’work environment by connecting learning, work and knowledge spaces. The competence performanceapproach suggests that human competencies be formalized with a strong connection to workplaceperformance (i.e. the tasks performed by the knowledge worker). As a result, competency diagnosisand competency gap analysis can be embedded into the normal working tasks and learninginterventions can be offered accordingly. The results of the case study indicate that experts weregenerally in moderate to high agreement when assigning competencies to tasks.Research limitations/implications – The model needs to be evaluated with regard to the learningoutcomes in order to test whether the learning interventions offered benefit the user. Also, the validityand efficiency of competency diagnosis need to be compared to other standard practices incompetency management.Practical implications – Use of competence performance structures within organizational settings hasthe potential to more closely relate the diagnosis of competency needs to actual work tasks, and toembed it into work processes.Originality/value – The paper connects the latest research in cognitive psychology and in thebehavioural sciences with a formal approach that makes it appropriate for integration intotechnology-enhanced learning environments.Keywords Competences, Learning, Workplace learning, Knowledge managementPaper type Research paper
Lindstaedt Stefanie , Ley Tobias, Scheir Peter, Ulbrich Armin
2008
This contribution introduces the concept of work-integrated learning which distinguishes itself from traditional e-Learning in that it provides learning support (i) during work task execution and tightly contextualized to the work context,(ii) within the work environment, and (iii) utilizes knowledge artefacts available within the organizational memory for learning. We argue that in order to achieve this highly flexible learning support we need to turn to" scruffy" methods (such as associative retrieval, genetic algorithms, Bayesian and other probabilistic methods) which can provide good results in the presence of uncertainty and the absence of fine-granular models. Hybrid approaches to user context determination, user profile management, and learning material identification are discussed and first results are reported.
Lindstaedt Stefanie , Scheir Peter, Sarka W.
2002