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Personalized course delivery: an empirical analysis of the feasibility of adapting distance learning courses to individual students' learning preferences

机译:个性化课程交付:对远程学习课程适应个别学生学习偏好的可行性的实证分析

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Personalization will be a key element in the future of executive education. Personalization is based on a match between student characteristics (user model) and didactic treatments (teaching model). This article distinguishes two matching strategies: an educational institution can deliver on demand, or can anticipate the demand and offer students the most appropriate treatment based on prior knowledge of each student's characteristics. Anticipating demand is the most challenging strategy. Its validity depends on the independence of the students' characteristics: in the case of interdependency, prediction of an optimal match is virtually impossible. The assumption of independence was investigated for a subset of students' characteristics - that of learning preferences. A conceptual model, consisting of four dimensions, was used to construct 16 combinations of didactic treatments. We found evidence in favour of a high degree of interdependency among the dimensions of the conceptual model. With these results in mind, students must be allowed to choose for themselves whether more didactic treatments should be made available.
机译:个性化将是未来高管教育的关键要素。个性化基于学生特征(用户模型)和教学方法(教学模型)之间的匹配。本文区分了两种匹配的策略:教育机构可以根据需求提供服务,或者可以根据需求并根据每个学生的特征的先验知识为他们提供最合适的待遇。预测需求是最具挑战性的策略。它的有效性取决于学生特征的独立性:在相互依赖的情况下,预测最佳匹配实际上是不可能的。对独立性的假设进行了调查,以研究学生的部分特征-学习偏好。一个由四个维度组成的概念模型被用来构建16种教学方法的组合。我们发现了支持概念模型各维度之间高度相互依赖的证据。考虑到这些结果,必须允许学生自己选择是否应提供更多的教学方法。

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