@inproceedings{a787578fbfff4b1f9c7b4c0b1f8daa84,
title = "Mining concept maps to understand university students{\textquoteright} learning",
abstract = "Concept maps, visual representations of knowledge, are used in an educational context as a way to represent students{\textquoteright} knowledge, and identify mental models of students; however there is a limitation of using concept mapping due to its difficulty to evaluate the concept maps. A concept map has a complex structure which is composed of concepts and their relationships that often have a weighted direction. This work explores the feasibility of the analysis of concept maps using data mining methods, and investigate the possibility of using concept maps as a research tool to understand college student{\textquoteright}s learning. A total of 111 college students participated in this study. The findings from frequent concept mining and sub-concept map mining suggest that students expect a traditional way of learning. The study also shows a promising area of further study in the area of data mining in education.",
author = "Yoo, {Jin Soung} and Cho, {Moon Heum}",
year = "2012",
month = jan,
day = "1",
language = "English (US)",
series = "Proceedings of the 5th International Conference on Educational Data Mining, EDM 2012",
publisher = "www.educationaldatamining.org",
editor = "Kalina Yacef and Zaiane, {Osmar R.} and Arnon Hershkovitz and Michael Yudelson",
booktitle = "Proceedings of the 5th International Conference on Educational Data Mining, EDM 2012",
note = "5th International Conference on Educational Data Mining, EDM 2012 ; Conference date: 19-06-2012 Through 21-06-2012",
}