Improving human computer interaction in intelligent tutoring systems
Wheeldon, Alan (2007) Improving human computer interaction in intelligent tutoring systems. PhD thesis, Queensland University of Technology.
ITSs (Intelligent Tutoring Systems) provide a way of addressing some of the issues that the more traditional CAI (Computer Aided Instruction) systems do not address - the individual learning needs and individual learning abilities and levels of users - so that the user is in control of their learning experience. An ITS needs to be able to provide an explanation, for a real world situation, that successfully meets the needs of the user. To ensure relevant explanation content requires the ITS be based on sound planning principles and tutoring knowledge as well as knowledge of the domain and the user. To ensure a coherent explanation structure requires that the tutoring knowledge be applied with full recognition of the knowledge of the domain and the user. For a model of the user's knowledge to be effective, the system should be able to use it to enhance the flexibility and responsiveness of explanations generated. A user model should guide the generation of explanations so they are pitched at the correct level of the user's existing knowledge; models should be able to actively support the needs of the user so that the user's efforts in seeking out information are minimised. The aim of this research is to generate effective, flexible and responsive explanations, in educational software systems, through developing better explanation facilities than exist in currently available ITS software. In achieving this aim, I am advancing research into dialogue planning and user modelling. The explanation facilities described meet the requirements of an explanation that is tailored to the user's needs, a sound theory from which particular explanations are constructed, and a user model that can accurately represent the behaviour and beliefs of the user. My research contributions include explicitly and formally representing discourse planning / reasoning, from both the user's view and the tutor's view so that they can be clearly understood and represented in the ITS. More recent planners have adopted approaches that can be characterised as using adaptations of the classical planning approach, with informally specified planning algorithms and planning languages. Without clear, explicit and full descriptions of actions and the planning algorithm we can not be certain of the plans that such planners produce. I adopt a theoretically rigorous approach based on classical planning theory - the actions available to the planner, the planning language and algorithm should be explicitly represented to ensure that plans are complete and consistent. Classical regression planning uses dynamic planning thus enabling the system to be flexible in a variety of situations and providing the responsiveness required for an ITS. I take a theoretically rigorous approach in constructing a well specified model of discourse, building upon existing research in the area. I present a tutoring module that is able to find a way to motivate the user to take a recommended action, by relating the action to the user's goals, and that is able to reason about the text structure to generate an effective explanation - putting together several clauses of text whilst maintaining coherency. As part of developing such constructs for motivating, enabling and recommending, as well as constructs for structuring text, I use a pedagogic model based on the principled approach of (i) advising the user to take an action (ii) motivating the user to want to take the action and (iii) ensuring the user knows how to do the action. I take a clear and realistic approach to user modelling, making explicit models of the user's behaviour and beliefs. I adopt a theoretically rigorous approach, formally distinguishing between the user's reasoning and their actions, so they can be focused on separately. Formally making this distinction, more easily enables models of the user's reasoning to be tailored to the individual user. To enable the tutor to consider the full impact on the user, of the information to be delivered to the user, I use different plan spaces. I explicitly identify the different perspectives of the user and the tutor so that they can be focused on separately to generate an explanation that is tailored to the user. In my approach, reasoning about the user's skills, rules and knowledge is independent from reasoning about those of the tutor.
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|Item Type:||QUT Thesis (PhD)|
|Supervisor:||Reye, James& Bruce, Christine|
|Keywords:||intelligent tutoring systems, explanatory dialogue, dialogue planning, classical planning, user, model, motivation, computational linguistics, rhetorical structure theory.|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
Past > Schools > Information Systems
|Department:||Faculty of Information Technology|
|Institution:||Queensland University of Technology|
|Copyright Owner:||Copyright Alan Wheeldon|
|Deposited On:||03 Dec 2008 14:06|
|Last Modified:||29 Oct 2011 05:49|
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