Feb 5, 2020 · This paper addresses a key challenge in MOOC dropout prediction, namely to build meaningful representations from clickstream data.
Abstract. This paper addresses a key challenge in MOOC dropout prediction, namely to build meaningful representations from clickstream data.
Feb 5, 2020 · This work proposes a clustering guided meta-learning-based training that optimizes the prediction model to exploit clusters of frequent ...
This paper addresses a key challenge in MOOC dropout prediction, namely to build meaningful representations from clickstream data.
In this paper, our goal is to predict if a learner is going to drop out within the next week, given clickstream data for the current week. To this end, we ...
This paper addresses a key challenge in MOOC dropout prediction, namely to build meaningful representations from clickstream data.
In this paper, our goal is to predict if a learner is going to drop out within the next week, given clickstream data for the current week. To this end, we ...
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Feb 5, 2020 · A multi-layer representation learning solution based on branch and bound (BB) algorithm, which learns from low-level clickstreams in an ...
Combining click-stream data with nlp tools to better understand MOOC completion. ... Predicting MOOC dropout over weeks using machine learning methods. In ...
Predicting MOOC Dropout over Weeks Using Machine Learning Methods. In Proceedings of the EMNLP 2014 Workshop on Analysis of Large Scale Social Interaction ...
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