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本文主要讲智能教学系统的介绍,动画教学代理和智能辅导是智能辅导系统中越来越常见的接口组件。交互式学习环境也可以利用它。最早和最著名的一些关于使用智能辅导的研究是“Herman the Bug”。Lester等人(1997)建议使用这些形式的智能和交互式学习环境,这将有助于儿童在更有利的环境中学习。智能学习环境的设计者专注于认真考虑软件开发的形式和特点,以提高学生的学习,在各种辅导领域的动画教学代理的潜在利益范围已被很好地记录”(Lester et al., 1997)。本篇assignment代写文章由澳洲论文通AssignmentPass辅导网整理,供大家参考阅读。

Animated pedagogical agents and intelligent tutoring are increasingly common interface components that are made use of in intelligent tutoring systems. Interactive learning environments also make use of it. Some of the earliest and prominent studies that were done in the use of intelligent tutoring were “Herman the Bug”. Lester et al. (1997) recommends the use of these forms of intelligent and interactive learning environments that would be helpful for children to learn in a more conducive setting. The designers of intelligent learning environments are focused on giving serious consideration to the forms and features of development of software so that it improves student learning, the range of potential benefits of animated pedagogical agents in various tutoring domains were well documented” (Lester et al., 1997).
Although the use of animated pedagogical agents and intelligent tutoring systems are seen to be more frequently in use in the case of the current learning environment, an important aspect to be understood is how directly the benefits reach the people in question. Do all students receive these benefits or are these benefits constrained to only some of the students are some questions of equity that rise here? The purpose of this pedagogical inquiry is to assess and critically analyze the effect of intelligent tutoring on existing educational inequities. The assessment will focus on whether the use of intelligent tutoring tools will worsen the situation of inequality or make it better. Based on an understanding of the benefits intelligent tutoring holds, it is recommended that steps are taken to solve the associated issues of equity.
The intelligent tutoring system is one that is holds much benefit to students. It is seen to improve student proficiency on a very large scale compared to the traditional tutoring systems. In particular where students are seen to suffer with some pre-existing learning disabilities, customized tools are seen to help them to be better. In homogeneous approaches it is observed that intelligent tutoring systems are seen to help the child holistically. However, these forms of benefits are not observed everywhere. Primarily, the first issue of inequity that is observed is how intelligent tutoring systems are seen to fail in considering differing requirements of children. It has been observed that intelligent tutoring systems are seen to be focused on different segments of children and hence cannot be applied as a general solution.
Different students come from educational backgrounds that either motivate them or make them fear the intelligent tutoring system. Students hence require motivation to accept use of these systems in a more diligent way, where this fails issues of inequities remain. The economic angle is perhaps the most daunting here as it is observed that intelligent tutoring systems are developed at considerable cost. The cost of development to the cost to deployment in educational sectors takes a toll on the institution. Students from rural sectors or students living in low economic zones face accessibility issues here. Intelligent systems for learning hence make more sense only when these inequity issues are addressed.


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