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An FAQ dataset for E-learning system used on a Japanese University
Yasunobu Sumikawa1, Masaaki Fujiyoshi1, Hisashi Hatakeyama1
1Tokyo Metropolitan University, Japan.
Data in Brief
|July 12, 2019
Summary
This study introduces a Japanese FAQ dataset and its English translation, designed to train e-learning chatbot models. The dataset aids in developing more accurate chatbot responses and supports multilingual applications.
Area of Science:
- Natural Language Processing
- Educational Technology
- Data Science
Background:
- E-learning systems require effective communication tools like chatbots.
- Existing resources lack comprehensive FAQ datasets for Japanese e-learning contexts.
- User-reported difficulties in e-learning systems represent valuable data.
Purpose of the Study:
- To create a high-quality FAQ dataset in Japanese and English for training e-learning chatbots.
- To facilitate the development of more accurate and responsive chatbot models.
- To support multilingual applications and adaptations of e-learning resources.
Main Methods:
- Collected raw user-reported Q&A data from an e-learning system (April 2015 - July 2018).
- Categorized data into 11 distinct groups based on system features.
- Integrated similar questions and verified answers by domain experts.
Main Results:
- Developed a dataset comprising 427 questions and 79 answers.
- The dataset was validated by experts with over three years of e-learning system experience.
- Statistical analyses confirmed the dataset's quality.
Conclusions:
- The presented FAQ dataset is a valuable resource for training e-learning chatbots.
- The dataset supports academic research, translation (e.g., Japanese to Chinese), and adaptation for other systems.
- It enables the development of advanced language models for improved chatbot performance.
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