The Impact of Link Suggestions on User Navigation and User Perception

The study reported in this paper explores the effects of providing web users with link suggestions that are relevant to their tasks. Results indicate that link suggestions were positively received. Furthermore, users perceived sites with link suggestions as more usable and themselves as less disoriented. The average task execution time was significantly lower than in the control condition and users appeared to navigate in a more structured manner. Unexpectedly, men took more advantage from link suggestions than women

Disengagement detection in online learning: validation studies and perspectives

Learning environments aim to deliver efficacious instruction, but rarely take into consideration the motivational factors involved in the learning process. However, motivational aspects like engagement play an important role in effective learning-engaged learners gain more. E-Learning systems could be improved by tracking students' disengagement that, in turn, would allow personalized interventions at appropriate times in order to reengage students. This idea has been exploited several times for Intelligent Tutoring Systems, but not yet in other types of learning environments that are less structured. To address this gap, our research looks at online learning-content-delivery systems using educational data mining techniques. Previously, several attributes relevant for disengagement prediction were identified by means of log-file analysis on HTML-Tutor, a web-based learning environment. In this paper, we investigate the extendibility of our approach to other systems by studying the relevance of these attributes for predicting disengagement in a different e-learning system. To this end, two validation studies were conducted indicating that the previously identified attributes are pertinent for disengagement prediction, and two new meta-attributes derived from log-data observations improve prediction and may potentially be used for automatic log-file annotation

Towards an adaptive improvement management framework (Position Paper)

Software process improvement (SPI) knowledge is often brought into organizations from outside, for example, by external experts. The idea of this work is to build up an improvement management framework for supporting managers in their work; finding improvement potentials and making strategic decisions about the implementation of improvement measures. The adaptation of the information delivery to the manager's needs and skills is one aspect of the framework and is solved by employing case-based reasoning. Additionally, we use an organizational model that is put forward as the basis for choosing the improvement action that fits most appropriately within the context and is most promising with respect to the organizational goals

Eliciting requirements for a adaptive decision support system through structured user interviews

Eliciting user requirements at an early stage of software development can safe development time and effort. However, identify requirements for adaptivity, such as inter-individual differences in needs or preferences is not trivial. In this paper we revisit results reported in a previous paper from a methodological point of view. Using an example, we argue that scenarios in combination with structured interviews are not able to adequately identify adaptivity requirements due to reasons inherent to the method, such as the users' trust and their ability to anticipate system funtionality. We suggest that more implicit methods must be used at early development phases to obtain unbiased results