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Affinity-based learning object retrieval in an e-learning environment using evolutionary learner profile

机译:使用进化学习者档案的电子学习环境中基于亲和力的学习对象检索

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With the abundance of learning objects (LOs) available across the web, there arises a demand for retrieving the LOs that exactly suit the learners’ requirements. In order to achieve this, the learner profile (LP) should exactly mimic the subject specific requirements of the learner as well as evolve over the learning cycle. Moreover, each LO should project itself in such a way that the learning management system is able to find it as a suitable candidate for a specific learner requirement. This paper proposes a novel method that fetches appropriate LOs for the learner by mapping his/her learner profile with those of the LOs. The LOs thus retrieved are then re-ranked according to their affinity towards the particular learner’s requirements and then presented to the learner. The experimental results demonstrated the effectiveness of the proposed method in retrieving appropriate learning content for learners.
机译:随着网络上大量学习对象(LO)的出现,需要检索完全符合学习者要求的LO。为了实现这一目标,学习者档案(LP)应该准确地模仿学习者的学科特定要求,并在整个学习周期中不断发展。此外,每个LO都应以一种方式进行自我投影,以使学习管理系统能够找到它作为满足特定学习者需求的合适人选。本文提出了一种新颖的方法,该方法通过将学习者的个人资料与LO的学习者个人资料进行映射来为学习者获取适当的LO。然后,根据对特定学习者要求的亲和力,将这样检索到的LO进行重新排序,然后将其呈现给学习者。实验结果证明了该方法在为学习者检索适当的学习内容方面的有效性。

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