Higher cognitive items generation algorithms

Ebenezer Aggrey, Maiga Chang, Rita Kuo, Xiaokun Zhang

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


The main goal of this research is to design item generation algorithms which can be integrated into the Online Test System developed earlier by the authors. The algorithms will be capable of generating items belong to higher cognitive level based on Bloom Taxonomy from a knowledge map created by a teacher (or co-created by a group of teachers). With the help of such integrated system teachers can reduce the time and effort they spend to prepare tests for assessing students’ mastery and understanding level of what they taught in class. This paper discusses the proposed algorithms in details and explains the experiment design in the end.

Original languageEnglish
Title of host publicationLecture Notes in Educational Technology
Number of pages10
Publication statusPublished - 2018

Publication series

NameLecture Notes in Educational Technology
ISSN (Print)2196-4963
ISSN (Electronic)2196-4971


  • Concept Schema
  • Hierarchical concept map
  • Item generation
  • Knowledge map
  • Test items generation algorithms


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