ABSTRACT

Learning trend has been shifted from a conventional way to a digital way in the form of E-learning, but it faces a high dropout ratio. Lack of engagement is one of the primary factors reported for this issue as the same type of course content is presented to learners despite their different background, knowledge and learning styles. Different researchers used adaptive learning techniques to increase students’ performance and engagement, but it has not affected too much for reducing the dropout ratio. One of the major problems with these adaptive techniques is to focus on one thing. To target this issue we have proposed the framework that provides adaptive content to each student based on his learning dimensions and knowledge background as per Bloom’s Taxonomy. The results of the experiment show a significant increase in students’ engagement and performance.

摘要

学习趋势已从传统方式转向以E-learning形式的数字化方式，但面临着较高的辍学率。缺乏参与是该问题报告的主要因素之一，因为尽管学习者的背景、知识和学习方式不同，但仍向他们呈现相同类型的课程内容。不同的研究人员使用适应性学习技术来提高学生的表现和参与度，但对于降低辍学率并没有太大影响。这些自适应技术的主要问题之一是专注于一件事。为了解决这个问题，我们提出了一个框架，根据布鲁姆分类法，根据每个学生的学习维度和知识背景，为每个学生提供自适应内容。