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Information 2017, 8(3), 92; doi:10.3390/info8030092

A Convolution-LSTM-Based Deep Neural Network for Cross-Domain MOOC Forum Post Classification

1
School of Software Engineering, Dalian University of Foreign Languages, Dalian 116044, China
2
School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
*
Author to whom correspondence should be addressed.
Received: 1 June 2017 / Revised: 21 July 2017 / Accepted: 26 July 2017 / Published: 30 July 2017
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Abstract

Learners in a massive open online course often express feelings, exchange ideas and seek help by posting questions in discussion forums. Due to the very high learner-to-instructor ratios, it is unrealistic to expect instructors to adequately track the forums, find all of the issues that need resolution and understand their urgency and sentiment. In this paper, considering the biases among different courses, we propose a transfer learning framework based on a convolutional neural network and a long short-term memory model, called ConvL, to automatically identify whether a post expresses confusion, determine the urgency and classify the polarity of the sentiment. First, we learn the feature representation for each word by considering the local contextual feature via the convolution operation. Second, we learn the post representation from the features extracted through the convolution operation via the LSTM model, which considers the long-term temporal semantic relationships of features. Third, we investigate the possibility of transferring parameters from a model trained on one course to another course and the subsequent fine-tuning. Experiments on three real-world MOOC courses confirm the effectiveness of our framework. This work suggests that our model can potentially significantly increase the effectiveness of monitoring MOOC forums in real time. View Full-Text
Keywords: MOOC; cross-domain; transfer learning; classification; neural network MOOC; cross-domain; transfer learning; classification; neural network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wei, X.; Lin, H.; Yang, L.; Yu, Y. A Convolution-LSTM-Based Deep Neural Network for Cross-Domain MOOC Forum Post Classification. Information 2017, 8, 92.

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