Advantages and constraints of a hybrid model K-12 E-Learning assistant chatbot

Eric Hsiao Kuang Wu, Chun Han Lin, Yu Yen Ou, Chen Zhong Liu, Wei Kai Wang, Chi Yun Chao

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


E-Learning has become more and more popular in recent years with the advance of new technologies. Using their mobile devices, people can expand their knowledge anytime and anywhere. E-Learning also makes it possible for people to manage their learning progression freely and follow their own learning style. However, studies show that E-Learning can cause the user to experience feelings of isolation and detachment due to the lack of human-like interactions in most E-Learning platforms. These feelings could reduce the user's motivation to learn. In this paper, we explore and evaluate how well current chatbot technologies assist users' learning on E-Learning platforms and how these technologies could possibly reduce problems such as feelings of isolation and detachment. For evaluation, we specifically designed a chatbot to be an E-Learning assistant. The NLP core of our chatbot is based on two different models: a retrieval-based model and a QANet model. We designed this two-model hybrid chatbot to be used alongside an E-Learning platform. The core response context of our chatbot is not only designed with course materials in mind but also everyday conversation and chitchat, which make it feel more like a human companion. Experiment and questionnaire evaluation results show that chatbots could be helpful in learning and could potentially reduce E-Learning users' feelings of isolation and detachment. Our chatbot also performed better than the teacher counselling service in the E-Learning platform on which the chatbot is based.

Original languageEnglish
Article number9069183
Pages (from-to)77788-77801
Number of pages14
JournalIEEE Access
StatePublished - 2020


  • chatbot
  • detachment
  • E-Learning
  • isolation
  • QANet
  • retrieval-based model


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