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Improving human computer interaction in intelligent tutoring systems

机译:改善智能辅导系统中的人机交互

摘要

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.
机译:ITS(智能辅导系统)提供了一种解决一些传统CAI(计算机辅助教学)系统无法解决的问题的方式-个体学习需求和个体学习能力以及用户水平-从而使用户处于控制之中他们的学习经验。 ITS需要能够针对现实情况提供能够成功满足用户需求的解释。为确保相关说明内容,ITS必须基于合理的计划原则和辅导知识以及领域和用户的知识。为了确保连贯的解释结构,需要在充分认识领域和用户知识的情况下应用辅导知识。为了使用户知识模型有效,系统应该能够使用它来增强所生成解释的灵活性和响应性。用户模型应指导解释的生成,以便将其推向用户现有知识的正确水平;模型应该能够积极地支持用户的需求,从而最大程度地减少用户在寻找信息方面的努力。这项研究的目的是通过开发比当前可用ITS软件更好的解释功能,在教育软件系统中生成有效,灵活和响应迅速的解释。为了实现这一目标,我正在推动对对话计划和用户建模的研究。所描述的解释工具满足以下需求:针对用户需求量身定制的解释,从中构造特定解释的合理理论以及可以准确表示用户行为和信念的用户模型。我的研究贡献包括从用户和导师的角度明确,形式化地表示话语计划/推理,以便可以在ITS中清楚地理解和表示它们。较新的计划人员采用了一些方法,这些方法的特征可以是采用经典计划方法的改编,并使用非正式指定的计划算法和计划语言。没有对动作和计划算法的清晰,明确和完整的描述,我们将无法确定此类计划者制定的计划。我采用基于经典计划理论的理论上严格的方法-应该明确表示计划者可以使用的操作,计划语言和算法,以确保计划是完整且一致的。经典回归计划使用动态计划,因此使系统在各种情况下都具有灵活性,并提供了ITS所需的响应能力。在该领域现有研究的基础上,我采用理论上严格的方法来构建明确的话语模型。我提供了一个辅导模块,该模块能够通过将动作与用户的目标相关联来找到一种激励用户采取推荐动作的方法,并且能够对文本结构进行推理以产生有效的解释-将几个文本条款,同时保持连贯性。作为开发用于激励,启用和推荐的结构以及构造文本的结构的一部分,我使用了基于以下原则的教学模型:(i)建议用户采取行动(ii)激励用户想要采取行动;以及(iii)确保用户知道如何采取行动。我对用户建模采取了一种清晰而现实的方法,为用户的行为和信念建立了明确的模型。我采用理论上严格的方法,正式区分了用户的推理和他们的行为,因此可以将其分别关注。正式地进行这种区分,更容易使用户推理的模型适合于各个用户。为了使导师考虑要传递给用户的信息对用户的全部影响,我使用了不同的计划空间。我明确指出了用户和导师的不同观点,以便可以分别关注他们,以生成适合用户的解释。在我的方法中,关于用户的技能,规则和知识的推理独立于关于导师的技术,规则和知识的推理。

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  • 作者

    Wheeldon Alan;

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  • 年度 2007
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  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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