[论文解读] A Model for an Intelligent and Adaptive Tutor based on Web by Jackson's Learning Styles Profiler and Expert Systems

Hossein Movafegh Ghadirli, Maryam Rastgarpour|arXiv (Cornell University)|Apr 15, 2013

Learning Styles and Cognitive Differences参考文献 9被引用 4

一句话总结

本文提出了一种基于网络的智能辅导系统，通过使用杰克逊学习风格量表和专家系统技术，根据学习者的风格进行自适应调整。通过问卷调查评估个体学习偏好，系统提供个性化的前测、定制内容和后测，并通过迭代方式更新学习者模型，实现自适应的、随时随地的访问，从而提升学习效果。

ABSTRACT

Todays, Intelligent and web-based E-Learning is one of the important area in E-Learning. This paper integrates an intelligent and web-based E-Learning with expert system technology to be able to model the learning styles of the learners using Jackson's model. It is intelligent because it can interact with the learners and offer them some subjects in Pedagogy view. Learning process of this system is in the following. First it determines learner's individual characteristics and learning styles based on a questionnaire in Jackson's learning styles profiler. Learning styles profiler is a modern measure of individual differences in learning style. Then learner's model is obtained and an Expert system simulator plans a "pre-test" and rates him. The concept would be presented if the learner scores enough. Subsequently, the system evaluates him by a "post-test". Finally the learner's model would be updated by the modeler based on try-and-error. The proposed system can be available Every Time and Every Where (ETEW) through the web. It improves the learning performance and has some important advantages such as high speed, simplicity of learning, low cost and be available ETEW.

研究动机与目标

• 开发一种基于网络的智能电子学习系统，根据个体学习风格个性化教学。
• 将杰克逊学习风格量表与专家系统技术相结合，实现自动化评估与内容分发。
• 实现随时随地（ETEW）的自适应学习体验访问。
• 通过基于前测和后测结果的迭代模型更新，提升学习效果。
• 通过自动化、个性化的辅导降低学习成本，提高效率。

提出的方法

• 学习者完成基于杰克逊学习风格量表的问卷，以确定其个体学习偏好。
• 专家系统模拟器根据学习者档案生成前测并评估表现。
• 仅当学习者在前测中取得足够分数时，才呈现内容。
• 内容交付后，进行后测以评估学习成效。
• 通过试错机制，迭代更新学习者模型，以优化未来推荐。
• 整个系统通过网络基础设施部署，确保ETEW（随时、随地）可访问性。

实验结果

研究问题

• RQ1 杰克逊学习风格量表如何有效整合到基于网络的智能辅导系统中？
• RQ2 专家系统技术在多大程度上能根据学习风格个性化前测和内容分发？
• RQ3 通过前测和后测进行的迭代模型更新如何改善学习成果？
• RQ4 在基于网络上部署自适应辅导系统有哪些实际优势？
• RQ5 此类系统能否在电子学习交付中实现高速度、低成本和简便性？

主要发现

• 该系统成功将杰克逊学习风格量表与专家系统技术整合，提供个性化的学习体验。
• 学习者仅在通过前测证明准备就绪后才能获得内容，确保了更好的准备程度。
• 后测结果用于评估学习成效，并指导模型更新。
• 该系统实现了随时随地（ETEW）访问，增强了学习的灵活性。
• 该方法在电子学习交付中实现了高速度、低成本和简便性。
• 通过试错机制进行的迭代模型更新，随时间推移提高了学习者画像的准确性。