Abstract

Abstract It often happens in teaching that due to complexity of a subject or unavailability of an expert instructor the subject undergoes in a situation that not only affects its outcome but the involvement and learning development of students also. Although contents are covered even in such a situation but their inadequate explanation leaves many question marks in students’ mind. Artificial Intelligence helps represent knowledge graphically and symbolically which can be logically inferred. Visual and symbolic representation of knowledge is easy to understand for both teachers and students. To facilitate students understanding teachers often structure domain knowledge in a visual form where all important contents of a subject can be seen along with their relation to each other. These structures are called ontology which is an important aspect of knowledge engineering. Teaching via ontology is in practice since last two decades. Natural Language Processing (NLP) is a combination of computation and linguistic and is often hard to teach. Its contents are apparently not tied together in a reasonable way which makes it difficult for a teacher that where to start with. In this article we will discuss the design of ontology to support rational learning and efficient teaching of NLP at introductory level.

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