计算机科学 ›› 2012, Vol. 39 ›› Issue (3): 228-230.

• 人工智能 • 上一篇    下一篇

LS-Pre:在开放式学习环境中自适应地预测学习者学习风格

杨娟,张养力   

  1. (四川师范大学计算机科学学院 成都 610101)
  • 出版日期:2018-11-16 发布日期:2018-11-16

LS-Pre; Forecast the Learners' Learning Styles Adaptively in an Open Learning Environment

  • Online:2018-11-16 Published:2018-11-16

摘要: 学习者根据其不同的认知过程通常可以分为不同类型的学习风格,而自动获取学习者学习风格的方式相较 问卷来说可以得到更为准确的信息。现有的学习风格自动识别手段都有无法跨学习风格模型进行预测以及当学习环 境发生改变时无法自适应动态调整等问题。提出了一种利用学习者学习行为表象来预测学习者学习风格的方法— L}Prc。工}Prc使用非线性动态规划法构建预测学习风格的数学模型并使用模拟退火算法优化目标函数。通过工导 Pre预测的学习风格不仅包括在环境中可以通过具体行为观测到的维度,还包括那些无法观测到的以及跨模型的学 习风格维度。实验验证了该方法的有效性。

关键词: 学习风格,学习风格维度,行为表象矩阵

Abstract: Learners always have their learning style preferences according to their different cognitive processes. Auto- matically modeling the learners' learning style can get the more accurate information compared with the questionnaires which is free from the problem of inaccurate self-conceptions of the learners. There are many problems in the current LS detecting methods, like only can detect the I_S dimensions in a specific model, can not adaptively adjust the I_S prefer- ences in a different learning environment. We provided a new method to forecast the learners' LSs which is called LS- Pre. In LS-Pre, non-linear dynamic programming is used to construct the mathematic model while simulated annealing algorithm is used to optimize the goal function. We illustrated the effectiveness of I_S-Pre in part 4 of this paper.

Key words: Learning style(LS) , Learning style dimension, Behavior matrix

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