Recommending knowledgeable people in a work-integrated learning system

According to studies into learning at work, interpersonal help seeking is the most important strategy of how people acquire knowledge at their workplaces. Finding knowledgeable persons, however, can often be difficult for several reasons. Expert finding systems can support the process of identifying knowledgeable colleagues thus facilitating communication and collaboration within an organization. In order to provide the expert finding functionality, an underlying user model is needed that represents the characteristics of each individual user. In our article we discuss requirements for user models for the workintegrated learning (WIL) situation. Then, we present the APOSDLE People Recommender Service which is based on an underlying domain model, and on the APOSDLE User Model. We describe the APOSDLE People Recommender Service on the basis of the Intuitive Domain Model of expert finding systems, and explain how this service can support interpersonal help seeking at workplaces.

[1]  Stefanie N. Lindstaedt,et al.  A Socio-technical Approach towards Supporting Intra-organizational Collaboration , 2008, EC-TEL.

[2]  Martin Wessner,et al.  Exploiting Context Information for Identification of Relevant Experts in Collaborative Workplace-Embedded E-Learning Environments , 2007, EC-TEL.

[3]  Pierre Dillenbourg,et al.  Times of Convergence. Technologies Across Learning Contexts, Third European Conference on Technology Enhanced Learning, EC-TEL 2008, Maastricht, The Netherlands, September 16-19, 2008. Proceedings , 2008, EC-TEL.

[4]  Henry Lieberman,et al.  Agents to assist in finding help , 2000, CHI.

[5]  Stefanie N. Lindstaedt,et al.  Getting to Know Your User - Unobtrusive User Model Maintenance within Work-Integrated Learning Environments , 2009, EC-TEL.

[6]  Tobias Ley,et al.  How Do People Learn at the Workplace? Investigating Four Workplace Learning Assumptions , 2007, EC-TEL.

[7]  A. Jameson.  Adaptive interfaces and agents , 2002 .

[8]  Peter Brusilovsky,et al.  ELM-ART: An Adaptive Versatile System for Web-based Instruction , 2001 .

[9]  Stefanie N. Lindstaedt,et al.  Knowledge Services for Work-Integrated Learning , 2008, EC-TEL.

[10]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[11]  Josep Lluís de la Rosa i Esteva,et al.  A Taxonomy of Recommender Agents on the Internet , 2003, Artificial Intelligence Review.

[12]  Tobias Ley,et al.  Identifying Employee Competencies in Dynamic Work Domains: Methodological Considerations and a Case Study , 2003, J. Univers. Comput. Sci..

[13]  Stephen Richard Billett.  Guided learning at work: Stephen Billett , 2012 .

[14]  Erik Duval,et al.  Creating New Learning Experiences on a Global Scale, Second European Conference on Technology Enhanced Learning, EC-TEL 2007, Crete, Greece, September 17-20, 2007, Proceedings , 2007, EC-TEL.

[15]  Peter Brusilovsky,et al.  User Models for Adaptive Hypermedia and Adaptive Educational Systems , 2007, The Adaptive Web.

[16]  S. Weibelzahl,et al.  Framework for the Evaluation of Adaptive CBR-Systems , 2001 .

[17]  Stephen Billett.  Authenticity and a culture of practice within modes of skill development , 1993 .

[18]  Andreas S. Rath,et al.  UICO: an ontology-based user interaction context model for automatic task detection on the computer desktop , 2009, CIAO '09.

[19]  Mark T. Maybury,et al.  Expert Finding Systems , 2006 .

[20]  Peter Brusilovsky,et al.  KnowledgeTree: a distributed architecture for adaptive e-learning , 2004, WWW Alt. '04.

[21]  Jimeng Sun,et al.  SmallBlue: Social Network Analysis for Expertise Search and Collective Intelligence , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[22]  Judy Kay,et al.  Student Models that Invite the Learner In: The SMILI: () Open Learner Modelling Framework , 2007, Int. J. Artif. Intell. Educ..

[23]  Alfred Kobsa,et al.  Expert-Finding Systems for Organizations: Problem and Domain Analysis and the DEMOIR Approach , 2003, J. Organ. Comput. Electron. Commer..

[24]  Tobias Ley,et al.  Scaffolding Self-directed Learning with Personalized Learning Goal Recommendations , 2010, UMAP.