Dialogue and the machine: an interactional perspective on computer dialogue models, mediation and artifacts

The topic of this thesis is the notion of dialogue and how machines have not only influenced the development of our understanding of this fundamental human social activity but also the possibilities for engaging in mediated dialogue. In particular, the concern is with its adoption and distortion from a computational point of view. An interactional perspective is developed that provides insight into the problems and limitations of computer dialogue models, motivates the investigation of the achievement of dialogue mediated 'through' machines, and informs the conception and design of computer systems (or artifacts) that support the metaphor of dialogue 'with' machines. To motivate a reconstruction of the notion of dialogue and a different understanding of the status of machines in terms of action, a critical analysis of computer models of dialogue, concerning theory, data and implementation, is given. In general, computer models lack a consideration of interaction as a constitutive domain, assume the interchange model of dialogue, promote a sanitised view of data, and are a poor foundation for the design of machines that are to engage in dialogue-like behaviour with a user. An alternative interactional perspective is derived from hermeneutics and ethnomethodology in which it is argued that the machine is an intelligible - not intelligent - artifact, and communicative activity is circumstantial, situated and interactively constituted. Instead of reifying dialogue as the repeated exchange of discrete messages between isolated cognitive processors (the interchange model), dialogue is understood here to be the collection of practices in which parties are mutually engaged in coordinating communicative actions and achieving shared understanding out of the materials at hand. The empirical methodology of the thesis comes from conversation analysis and forms the basis for the investigation of the achievement of dialogue 'through' machines. A detailed audio-visual study of a particular computer-mediated communication modality is presented. Parties engaged in cooperatively constructing mutual orientation in dialogue (in a virtual dialogue space) were recorded and features of their conduct were rendered for analysis with the aid of a notation system specially developed for this study. The findings are that the computer-mediated dialogue activity is a skilled, interactive accomplishment in which dialogic presence, monitoring and participation are contingently created and maintained. An emergent transformation of the dialogue activity demonstrates the situated work of constructing participation, a process that is shaped by the dynamics of that activity. A brief study of copresent collaboration documents two further features: the embodiment of actions and their complementarity. The consequences of the interactional perspective and the empirical study for computer models and dialogue 'with' machines are discussed. Suggestions are also made about an alternative use of computer modelling for dialogue 'between' machines, and about the future of dialogue mediation and artifacts

Adaptive Cognitive Interaction Systems

Adaptive kognitive Interaktionssysteme beobachten und modellieren den Zustand ihres Benutzers und passen das Systemverhalten entsprechend an. Ein solches System besteht aus drei Komponenten: Dem empirischen kognitiven Modell, dem komputationalen kognitiven Modell und dem adaptiven Interaktionsmanager. Die vorliegende Arbeit enthält zahlreiche Beiträge zur Entwicklung dieser Komponenten sowie zu deren Kombination. Die Ergebnisse werden in zahlreichen Benutzerstudien validiert

Complex Systems in Engineering and Technology Education: A Mixed Methods Study Investigating the Role Computer Simulations Serve in Student Learning

This research was conducted to determine if students receiving complex systems instruction in the form of software simulations recognize patterns and underlying elements of complex systems more effectively than students receiving traditional instruction. Complex systems were investigated with an analytic (reductive) approach in a control group and with a synthesis approach in the treatment group. Exploration of this top-down approach to learning complex systems counters traditional bottom-up methodologies, investigating systems and subsystems at the component level. The hypothesis was that students experiencing complex systems scenarios in a computer-based learning environment would outperform their counterparts by constructing a greater number of explanations with emergent-like responses. A mixed method experimental, pretest posttest, control group triangulation design research study was designed for high school students enrolled in an Introduction to Technology and Engineering course. A pretest consisting of one open-ended near transfer problem and one far transfer problem was administered, investigating the generation of reductive (clockwork) and complex (emergent-like) mental models. A stratified sampling procedure was used to assign students to control or treatment groups. Following treatment, an analysis of covariance failed to reveal statistically significant evidence supporting the hypothesis. However, qualitative data in the form of student transcriptions, daily lab reports, and data entry worksheets revealed evidence of emergent-like response and behaviors

Serious Games in Cultural Heritage

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

New measurement paradigms

This collection of New Measurement Paradigms papers represents a snapshot of the variety of measurement methods in use at the time of writing across several projects funded by the National Science Foundation (US) through its REESE and DR K–12 programs. All of the projects are developing and testing intelligent learning environments that seek to carefully measure and promote student learning, and the purpose of this collection of papers is to describe and illustrate the use of several measurement methods employed to achieve this. The papers are deliberately short because they are designed to introduce the methods in use and not to be a textbook chapter on each method. The New Measurement Paradigms collection is designed to serve as a reference point for researchers who are working in projects that are creating e-learning environments in which there is a need to make judgments about students’ levels of knowledge and skills, or for those interested in this but who have not yet delved into these methods

A New Constructivist AI: From Manual Methods to Self-Constructive Systems

The development of artificial intelligence (AI) systems has to date been largely one of manual labor. This constructionist approach to AI has resulted in systems with limited-domain application and severe performance brittleness. No AI architecture to date incorporates, in a single system, the many features that make natural intelligence general-purpose, including system-wide attention, analogy-making, system-wide learning, and various other complex transversal functions. Going beyond current AI systems will require significantly more complex system architecture than attempted to date. The heavy reliance on direct human specification and intervention in constructionist AI brings severe theoretical and practical limitations to any system built that way. One way to address the challenge of artificial general intelligence (AGI) is replacing a top-down architectural design approach with methods that allow the system to manage its own growth. This calls for a fundamental shift from hand-crafting to self-organizing architectures and self-generated code – what we call a constructivist AI approach, in reference to the self-constructive principles on which it must be based. Methodologies employed for constructivist AI will be very different from today’s software development methods; instead of relying on direct design of mental functions and their implementation in a cog- nitive architecture, they must address the principles – the “seeds” – from which a cognitive architecture can automatically grow. In this paper I describe the argument in detail and examine some of the implications of this impending paradigm shift