CLICKER: A Computational LInguistics Classification Scheme for Educational Resources
This provides a structured framework for organizing educational materials in CL/NLP, which is incremental as it adapts existing classification concepts to a new domain.
The authors tackled the lack of a comprehensive classification system for Computational Linguistics and Natural Language Processing by proposing CLICKER, a taxonomy with 334 topics derived from analysis of 77 university courses, focusing on educational resources.
A classification scheme of a scientific subject gives an overview of its body of knowledge. It can also be used to facilitate access to research articles and other materials related to the subject. For example, the ACM Computing Classification System (CCS) is used in the ACM Digital Library search interface and also for indexing computer science papers. We observed that a comprehensive classification system like CCS or Mathematics Subject Classification (MSC) does not exist for Computational Linguistics (CL) and Natural Language Processing (NLP). We propose a classification scheme -- CLICKER for CL/NLP based on the analysis of online lectures from 77 university courses on this subject. The currently proposed taxonomy includes 334 topics and focuses on educational aspects of CL/NLP; it is based primarily, but not exclusively, on lecture notes from NLP courses. We discuss how such a taxonomy can help in various real-world applications, including tutoring platforms, resource retrieval, resource recommendation, prerequisite chain learning, and survey generation.