http://dl.gi.de/handle/20.500.12116/5010 Thu, 23 Jul 2026 07:54:00 GMT 2026-07-23T07:54:00Z http://dl.gi.de/handle/20.500.12116/5042 State of the Art of Adaptivity in E-Learning Platforms Hauger, David; Köck, Mirjam Brunkhorst, Ingo; Krause, Daniel; Sitou, Wassiou Adaptivity has been an important research topic during the past two decades, especially in the field of e-learning. This paper deals with the question of whether and to what extent adaptivity is actually being used in e-learning systems. It describes the state of the art of adaptivity features and gives an overview on the most frequently used learning management systems (LMSs) as well as on a number of research projects and systems providing adaptivity. Mon, 01 Jan 2007 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/5042 2007-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/5043 Prediction Algorithms for User Actions Hartmann, Melanie; Schreiber, Daniel Brunkhorst, Ingo; Krause, Daniel; Sitou, Wassiou Proactive User Interfaces (PUIs) aim at facilitating the interaction with a user interface, e.g., by highlighting fields or adapting the interface. For that purpose, they need to be able to predict the next user action from the interaction history. In this paper, we give an overview of sequence prediction algorithms (SPAs) that are applied in this domain, and build upon them to develop two new algorithms that base on combining different order Markov models. We identify the special requirements that PUIs pose on these algorithms, and evaluate the performance of the SPAs in this regard. For that purpose, we use three datasets with real usage-data and synthesize further data with specific characteristics. Our relatively simple yet efficient algorithm FxL performs extremely well in the domain of SPAs which make it a prime candidate for integration in a PUI. To facilitate further research in this field, we provide a Perl library that contains all presented algorithms and tools for the evaluation. Mon, 01 Jan 2007 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/5043 2007-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/5044 Taking the Teacher’s Perspective for User Modeling in Complex Domains Janssen, Christian P.; van Rijn, Hedderik Brunkhorst, Ingo; Krause, Daniel; Sitou, Wassiou Mon, 01 Jan 2007 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/5044 2007-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/5041 Context-adaptation based on Ontologies and Spreading Activation Hussein, Tim; Westheide, Daniel; Ziegler, Jürgen Brunkhorst, Ingo; Krause, Daniel; Sitou, Wassiou Ontologies and spreading activation are known terms within the scope of information retrieval. In this paper we introduce SPREADR, an integrated adaptation mechanism for web applications that uses ontologies for representing the application domain as well as context information like location, user history and local time. Those context factors can be modeled in an ontology and be linked to certain domain nodes. In each session a Spreading Activation Network is build based on those ontologies and recognized con- text factors or user actions can trigger an activation flow through this network. A node’s resulting activation value then represents its importance according to the current circumstances. While identically in structure, the Spreading Activation Networks are personalized by automatically modifying link weights and activation levels of nodes. As a result the system learns about the user preferences and can adjust its adaptation mechanism for future runs through implicit feed- back. Mon, 01 Jan 2007 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/5041 2007-01-01T00:00:00Z