Tobias Ley

Scaling up Learning for Sustained Impact

MOOCs have been a disruptive educational trend in the last months. Some MOOCs just replicate traditional teaching pedagogies, adding multimedia elements like video lectures. Others go beyond, trying to engage the massive number of participants by promoting discussions and relying on their contributions to the course. MOOC platforms usually provide some built-in social tools for this purpose, although instructors or participants may suggest others to foster discussions and crowdsourcing. This paper analyses the impact of two builtin (Q&A and forum) and three external social tools (Facebook, Twitter and MentorMob) in a MOOC on educational technologies. Most of the participants agreed on the importance of social tools to be in touch with their partners and share information related to the course, the forum being the one preferred. Furthermore, the lessons learned from the enactment of this MOOC employing social tools are summarized so that others may benefit from them.

Recommending tags with a model of human categorization

When interacting with social tagging systems, humans exercise complex processes of categorization that have been the topic of much research in cognitive science. In this paper we present a recommender approach for social tags derived from ALCOVE, a model of human category learning. The basic architecture is a simple three-layers connectionist model. The input layer encodes patterns of semantic features of a user-specific resource, such as latent topics elicited through Latent Dirichlet Allocation (LDA) or available external categories. The hidden layer categorizes the resource by matching the encoded pattern against already learned exemplar patterns. The latter are composed of unique feature patterns and associated tag distributions. Finally, the output layer samples tags from the associated tag distributions to verbalize the preceding categorization process. We have evaluated this approach on a real-world folksonomy gathered from Wikipedia bookmarks in Delicious. In the experiment our approach outperformed LDA, a well-established algorithm. We attribute this to the fact that our approach processes semantic information (either latent topics or external categories) across the three different layers. With this paper, we demonstrate that a theoretically guided design of algorithms not only holds potential for improving existing recommendation mechanisms, but it also allows us to derive more generalizable insights about how human information interaction on the Web is determined by both semantic and verbal processes.

How do people learn at the workplace? investigating four workplace learning assumptions

Any software development project is based on assumptions about the state of the world that probably will hold when it is fielded. Investigating whether they are true can be seen as an important task. This paper describes how an empirical investigation was designed and conducted for the EU funded APOSDLE project. This project aims at supporting informal learning during work. Four basic assumptions are derived from the project plan and subsequently investigated in a two-phase study using several methods, including workplace observations and a survey. The results show that most of the assumptions are valid in the current work context of knowledge workers. In addition more specific suggestions for the design of the prospective APOSDLE application could be derived. Though requiring a substantial effort, carrying out studies like this can be seen as important for longer term software development projects.

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.

Conceptual Foundations for a Service-oriented Knowledge and Learning Architecture: Supporting Content, Process and Ontology Maturing

Effective learning support in organizations requires a flexible and personalized toolset that brings together the individual and the organizational perspective on learning. Such toolsets need a service-oriented infrastructure of reusable knowledge and learning services as an enabler. This contribution focuses on conceptual foundations for such an infrastructure as it is being developed within the MATURE IP and builds on the knowledge maturing process model on the one hand, and the seeding-evolutionary growth-reseeding model on the other hand. These theories are used to derive maturing services, for which initial examples are presented.

Knowledge Maturing in the Semantic MediaWiki: A Design Study in Career Guidance

The evolutionary process in which knowledge objects are transformed from informal and highly contextualized artefacts into explicitly linked and formalized learning objects, together with the corresponding organisational learning processes, have been termed Knowledge Maturing. Whereas wikis and other tools for collaborative building of knowledge have been suggested as useful tools in this context, they lack several features for supporting the knowledge maturing process in organisational settings. To overcome this, we have developed a prototype based on Semantic MediaWiki which enhances the wiki with various maturing functionalities like maturing indicators or mark-up support.

Supporting competency development in informal workplace learning

This paper seeks to suggest ways to support informal, self-directed, work-integrated learning within organizations. We focus on a special type of learning in organizations, namely on competency development, that is a purposeful development of employee capabilities to perform well in a large array of situations. As competency development is inherently a self-directed development activity, we seek to support these activities primarily in an informal learning context. AD-HOC environments which allow employees context specific access to documents in a knowledge repository have been suggested to support learning in the workplace. In this paper, we suggest to use the competence performance framework as a means to enhance the capabilities of AD HOC environments to support competency development. The framework formalizes the tasks employees are working in and the competencies needed to perform the tasks. Relating tasks and competencies results in a competence performance structure, which structures both tasks and competencies in terms of learning prerequisites. We conclude with two scenarios that make use of methods established in informal learning research. The scenarios show how competence performance structures enhance feedback mechanisms in a coaching process between supervisor and employee and provide assistance for self directed learning from a knowledge repository.

Seeing what the system thinks you know: visualizing evidence in an open learner model

User knowledge levels in adaptive learning systems can be assessed based on user interactions that are interpreted as Knowledge Indicating Events (KIE). Such an approach makes complex inferences that may be hard to understand for users, and that are not necessarily accurate. We present MyExperiences, an open learner model designed for showing the users the inferences about them, as well as the underlying data. MyExperiences is one of the first open learner models based on tree maps. It constitutes an example of how research into open learner models and information visualization can be combined in an innovative way.

A methodology for eliciting, modelling, and evaluating expert knowledge for an adaptive work-integrated learning system

We present a methodology for constructing and evaluating models for adaptive informal technology-enhanced workplace learning. It is designed for knowledge-intensive work domains which are not pre structured according to a fixed curriculum. We extend research on Competence-based Knowledge Space Theory which has been mainly applied in educational settings. Our approach employs systematic knowledge elicitation and practically feasible evaluation techniques performed as part of the modelling process for iterative refinement of the models. A case study was performed in the Requirements Engineering domain to apply and test the developed methodology. We discuss lessons learned and several implications for knowledge engineering for adaptive workplace learning.

Modeling Activation Processes in Human Memory to Predict the Use of Tags in Social Bookmarking Systems

Modeling Activation Processes in Human Memory to Predict the Use of Tags in Social Bookmarking Systems