Deakin University
Browse

File(s) under permanent embargo

Discovering learning patterns of male and female students by contrast targeted rule mining

Version 2 2024-06-06, 03:01
Version 1 2017-07-24, 08:51
conference contribution
posted on 2024-06-06, 03:01 authored by X Tian, J Kong, T Zhu, H Xia
In recent years, data mining techniques has attracted the attention from educational researchers and applied in educational research pervasively. As a famous data mining method, traditional association rules mining tend to ignore the infrequent data item and can only analyze a single dataset. To address these issues, a contrast targeted rule mining model is introduced in this paper. A complete analysis for the patterns and differences in the academic situation of male and female students is then conducted by the contrast targeted rule mining. Some useful association rules extracted by CTR are presented to demonstrate the difference of male and female students' learning patterns.

History

Pagination

196-202

Location

Melbourne, Victoria

Start date

2016-11-02

End date

2016-11-03

ISBN-13

9780769559841

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2016, IEEE

Title of proceedings

ES 2016 : Proceedings of the 4th International Conference on Enterprise Systems

Event

Enterprise Systems. International Conference (4th : 2016 : Melbourne, Victoria)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Usage metrics

    Research Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC