A rule-based approach in Bloom's Taxonomy question classification through natural language processing

This paper describes a rule-based approach to analyze and classify written examination questions through natural language processing for computer programming subjects. In general, Bloom's Taxonomy or the Taxonomy of Educational Objectives (TEO) acts as a main guideline in assessing a student�...

Full description

Saved in:
Bibliographic Details
Published in2012 8th International Conference on Computing and Convergence Technology pp. 410 - 414
Main Authors Haris, Syahidah Sufi, Omar, Nazlia
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2012
Subjects
Binary trees
Bloom's Taxonomy
Classification algorithms
Encapsulation
Information science
Natural language processing
Programming profession
Rule-based
Symbols
Tagging
Taxonomy
Training
Online AccessGet full text
ISBN1467308943
9781467308946

Cover

More Information
Summary:This paper describes a rule-based approach to analyze and classify written examination questions through natural language processing for computer programming subjects. In general, Bloom's Taxonomy or the Taxonomy of Educational Objectives (TEO) acts as a main guideline in assessing a student's cognitive level. However, academicians need to design the appropriate questions and categorize it to the cognitive level of TEO manually. Our aim is to provide lecturers with a tool that can ease their task to assess the student's cognitive levels from the written examination questions. This paper describes a natural language processing technique to analyze the cognitive levels of Bloom's taxonomy for each question through the development of rules. Preliminary results from the experiments show that it is a viable approach to help categorize the questions automatically according to Bloom's Taxonomy.
ISBN:1467308943
9781467308946