Meta-learning for predicting the best vote aggregation method: Case study in collaborative searching of LOs
نویسندگان
چکیده
The problem of recommending learning objects to a group of users or instructors is much more difficult than the traditional problem of recommending to only one individual. To resolve this problem, this paper proposes to use meta-learning for predicting the best voting aggregation strategy in order to automatically obtain the final ratings without having to reach a consensus between all the instructors. We have carried out an experiment using data from 50 groups of instructors doing a collaborative search of LOs in AGORA repository.
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