Kirsten A. Smith

Towards Effective Emotional Support for Community First Responders Experiencing Stress

Community First Responders are often the first on the scene in rural medical emergencies, and experience situations where stress is inherent. One way of reducing this stress is through the use of an Empathic Conversational Agent which can provide Emotional Support, and be applied to systems designed for the pre-hospital care domain. This paper outlines the groundwork for this goal by describing the development of stories which describe a particular stressor, and validated Emotional Support categories and statements. These will be used when developing an algorithm for adapting Emotional Support to different stressful situations. We identified 5 categories of Emotional Support, and a set of 52 statements which were validated as belonging to these categories. We then present a preliminary analysis of the patterns of usage of Emotional Support categories for each of the stressors.

The development and evaluation of an emotional support algorithm for carers

Carers - people who provide regular support for a friend or relative who could not manage without them - frequently report high levels of stress. Good emotional support could help relieve this stress. This study uses seven scenarios that depict different types of stress and acquires emotional support messages for them. We then categorize and evaluate the emotional support for different types of stress. We found that telling the carer they are appreciated and offering support are the best types of emotional support. Additionally, we found that how well a supporter sympathises with a situation affects the type of support they consider suitable. We describe and evaluate an algorithm that selects different categories of support to be used by an intelligent virtual agent to provide emotional support to carers experiencing different types of stress.

Adapting exercise selection to learner self-esteem and performance

The past years have witnessed an increased use of applied games for developing and evaluating communication skills. These skills benefit from in-terpersonal interactions. Providing feedback to students practicing communica-tion skills is difficult in a traditional class setting with one teacher and many students. This logistic challenge may be partly overcome by providing training using a simulation in which a student practices with communication scenarios. A scenario is a description of a series of interactions, where at each step the player is faced with a choice. We have developed a scenario editor that enables teachers to develop scenarios for practicing communication skills. A teacher can develop a scenario without knowledge of the implementation. This paper presents the implementation architecture for such a scenario-based simulation.This paper presents an initial evaluation of different forms of adaptation based on learning style and knowledge level, which were implemented in an adaptive e-learning system. An experiment conducted in a learning context with 174 participants produced significant results in terms of learning gain. They indicate that adaptation based on both learning style and knowledge level yields significantly better learning gain than adaptation based on learning style only, and better than adaptation based on knowledge level only.Technology Enhanced Learning (TEL) largely focuses on the retrieval and reuse of educational resources from Web platforms like Coursera. Unfortunately, Coursera does not provide educational metadata of its content. To overcome this limitation, this study proposes a data mining approach for discovering Teaching Contexts (TC) where resources have been delivered in. Such TCs can facilitate the retrieval of resources for the teaching preferences and requirements of teachers.Gamification is the use of game design elements in non-game contexts, and it has reported potential benefits for students. However, the proposals supporting teachers to create gamified ubiquitous learning situations are tied to specific activities and enactment technologies. To start addressing this issue, we propose a system to help teachers design and deploy these situations involving a variety of technologies frequently used in education.Adapting tasks to learner characteristics is essential when selecting appropriate tasks for learners [5]. This paper investigates how humans adapt exercise selection to learner self-esteem (SE) and performance, to allow a future Intelligent Tutoring System (ITS) to use these adaptations. Self esteem is an important factor in learning as it is a significant predictor of academic performance [4]. Previous research adapts task selection to other characteristics e.g. past performance [1], but little work focuses on task selection based on learner personality.

Assessing the Supportiveness of Gift Emoticons in Care Scenarios

There is potential for an Intelligent Virtual Agent to provide good emotional support for carers; however, its text-based messages lack context and may be misconstrued. One possible solution is to use gift emoticons to convey support. I investigate how supportive an emotional support statement is when paired with a digital gift of flowers, varying the modality (text/graphics) and explicitness of the gift (implicit/explicit). Adding a graphical emoticon improved support, measured on four scales of appropriateness, helpfulness, effectiveness and sensitivity. Images of flowers were rated higher than text; additionally, appropriate and sensitive ratings were consistently higher than effective and helpful ratings. There was no difference between explicit and implicit gifts. Participants reported that adding flowers to the support message was sympathetic and represented an effort to cheer the carer up.

Supporting carers through intelligent technology

Informal carers lack adequate practical and emotional support. This PhD investigates how a software agent could be used to help maintain a carers personal social network by mediating communication and facilitating the provision of emotional and practical support. The agent should use features of the carer and their social network to provide a personalized support interface.