Abstract
Chatbot for education has great potential to complement human educators and education administrators. For example, it can be around the clock tutor to answer and clarify any questions from students who may have missed class. A chatbot can be implemented either by ruled based or artificial intel-ligence based. However, unlike the ruled-based chatbots, artificial intelli-gence based chatbots can learn and become smarter overtime and is more scalable and has become the popular choice for chatbot researchers recently. Recurrent Neural Network based Sequence-to-sequence (Seq2Seq) model is one of the most commonly researched model to implement artificial intelli-gence chatbot and has shown great progress since its introduction in 2014. However, it is still in infancy and has not been applied widely in educational chatbot development. Introduced originally for neural machine translation, the Seq2Seq model has been adapted for conversation modelling including question-answering chatbots. However, in-depth research and analysis of op-timal settings of the various components of Seq2Seq model for natural an-swer generation problem is very limited. Additionally, there has been no ex-periments and analysis conducted to understand how Seq2Seq model handles variations is questions posed to it to generate correct answers. Our experi-ments add to the empirical evaluations on Seq2Seq literature and provides insights to these questions. Additionally, we provide insights on how a cu-rated dataset can be developed and questions designed to train and test the performance of a Seq2Seq based question-answer model.
Highlights
The potential of chatbots as an online tutor to provide assistance and answers to queries and questions by students is an interesting proposition and has great potential
Introduced originally for neural machine translation, the Seq2Seq model has been adapted for conversation modelling including question-answering chatbots
We investigated the comparative performance of word versus character embeddings and effects of dropout [12] on the quality of answer generated using Gated Recurrent Unit [13], a variant of Recurrent Neural Network (RNN)
Summary
The potential of chatbots as an online tutor to provide assistance and answers to queries and questions by students is an interesting proposition and has great potential. Question answering chatbots are intelligent systems that are able to converse with humans using natural language while providing answers. Chatbot or AI conversational tool is a prominent instrument in a personalized learning environment, which is built to improve student interaction and collaboration It helps the students with different learning paces absorb the knowledge according to their level, confined to the classroom and in distance education [4], [7]. Ii) We shared some examples on how a specialized dataset can be curated to train a model to enable it to learn and gain certain knowledge from the dataset and avoid depending on rules or pre-trained embeddings This is useful for unique datasets or in our case, dataset in Malay language.
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