Search

Shared decision making (SDM) is increasingly considered as the best way to reach a treatment decision in a clinical environment. However, the use of SDM in practice can be obstructed by a number of factors, such as time constraints or lack of applicability due to patient characteristics. Our project, PrepDoc, explores how a Virtual Training Doctor (VTD) can help patients overcome some of these obstacles to experiencing effective SDM during doctor's visits. In this paper, we report on user studies conducted with 19 participants in Scotland aged 65+. The goal of these studies was to identify the reactions of this audience to the PrepDoc system, evaluate its suitability within Scotland, and elicit suggestions to improve it. Our findings revealed that the idea of empowering people to participate in SDM using a virtual agent was positively received by all participants. However, the reactions to how this idea was implemented in the PrepDoc system varied greatly across participants. Based on this, our paper outlines recommendations for enhancing the user experience with VTDs, accommodating individual differences of older adults, and accounting for the national context.

We present BEETLE II, a tutorial dialogue system designed to accept unrestricted language input and support experimentation with different tutorial planning and dialogue strategies. Our first system evaluation used two different tutorial policies and demonstrated that the system can be successfully used to study the impact of different approaches to tutoring. In the future, the system can also be used to experiment with a variety of natural language interpretation and generation techniques., Presented at the Proceedings of the ACL 2010 System Demonstrations held in Uppsala, Sweden on 13 July 2010.

We propose that a set of five dimensions forms a foundation underlying a number of prevalent theoretical perspectives on learning. We show how student contributions to instructional dialogue can be reliably annotated with these dimensions. Finally, we provide preliminary validation evidence for our coding scheme and illustrate the potential value of such an approach to analyzing student behavior in tutorial dialogue., Prepared in cooperation with Human Communication Research Centre, University of Edinburgh.

Research suggests that students who are aware of their own confusions and take steps to resolve those confusions are most likely to benefit from a learning experience. At the same time, there are conversational maxims, such as Leech's politeness maxims, that may inhibit a student from expressing and pursuing confusions within a tutorial dialogue. We investigated students' expressions of confusion while working through a series of learning activities with a tutor. We found that, during the times when students were working independently on an activity, their expressions of confusion were reliable indicators of their (lack of) understanding however, when they were conversing with their tutors, these same students did not express confusion and, in fact, the more often the expressed comprehension, the worse they performed on the post-test. This suggests that student metacognitive statements should not be interpreted without taking into consideration the context in which they were expressed. We briefly consider implications for human tutors and the development of computer tutoring systems., Presented at COGSI Annual Meeting of the Cognitive Science Society held at the VU University Amsterdam, 29 Jul-1 Aug 2009. The original document contains color images.

The need for users to make sense of their growing mass of personal digital data presents a challenge to Design and HCI researchers. There is a growing interest in using narrative techniques to support the interpretation and understanding of such data. In this early study we explore methods of selecting images from personal Instagram accounts in the form of a triptych (a sequence of three images) in order to create a sense of narrative. We present a brief description of the algorithms behind image selection, evaluate how effective they are in creating a sense of narrative, and discuss the wider implications of our work. Results show that semantic tagging, a dynamic programming algorithm, and a simple narrative structure produced triptychs which were significantly more story-like, with a significantly more coherent order, than a random selection, or a neutral sequence of images.

As the quantity and variety of personal digital data shared on social media continues to grow, how can users make sense of it? There is growing interest among HCI researchers in using narrative techniques to support interpretation and understanding. This work describes our prototype application, ReelOut, which uses narrative techniques to allow users to understand their data as more than just a database. The online service extracts data from multiple social media sources and augments it with semantic information such as sentiment, themes, and named entities. The interactive editor automatically constructs a story by using unit selection to fit data units to a simple narrative structure. It allows the user to change the story interactively by rejecting certain units or selecting a new narrative target. Finally, images from the story can be exported as a video clip or a collage.

As the quantity and variety of personal digital data shared on social media continues to grow, how can users make sense of it? There is growing interest among HCI researchers in using narrative techniques to support interpretation and understanding. This work describes our prototype application, ReelOut, which uses narrative techniques to allow users to understand their data as more than just a database. The online service extracts data from multiple social media sources and augments it with semantic information such as sentiment, themes, and named entities. The interactive editor automatically constructs a story by using unit selection to fit data units to a simple narrative structure. It allows the user to change the story interactively by rejecting certain units or selecting a new narrative target. Finally, images from the story can be exported as a video clip or a collage.

The need for users to make sense of their growing mass of personal digital data presents a challenge to Design and HCI researchers. There is a growing interest in using narrative techniques to support the interpretation and understanding of such data. In this early study we explore methods of selecting images from personal Instagram accounts in the form of a triptych (a sequence of three images) in order to create a sense of narrative. We present a brief description of the algorithms behind image selection, evaluate how effective they are in creating a sense of narrative, and discuss the wider implications of our work. Results show that semantic tagging, a dynamic programming algorithm, and a simple narrative structure produced triptychs which were significantly more story-like, with a significantly more coherent order, than a random selection, or a neutral sequence of images.