DocumentCode :
544022
Title :
Monitoring conceptual development with text mining technologies: CONSPECT
Author :
Wild, Fridolin ; Haley, Debra ; Bülow, Katja
Author_Institution :
Open Univ., Milton Keynes, UK
fYear :
2010
fDate :
27-29 Oct. 2010
Firstpage :
1
Lastpage :
8
Abstract :
This paper evaluates CONSPECT, a service that analyses states in a learner´s conceptual development. It combines two technologies - Latent Semantic Analysis to analyse text and Network Analysis (NA) to provide visualisations - into a technique called Meaningful Interaction Analysis (MIA). CONSPECT was designed to help both online learners and their tutors monitor their conceptual development. This paper reports on the validation experiments undertaken to determine how well LSA matches first year medical students in clustering concepts and in annotating text. The validation used several techniques, including card sorting and Likert scales. CONSPECT produces almost `peer´ quality results and what remains to be tested is whether it improves with more advanced learners. One of the experiments showed an average 0.7 correlation between humans and CONSPECT.
Keywords :
computer aided instruction; data mining; data visualisation; natural language processing; pattern clustering; text analysis; CONSPECT; card sorting; latent semantic analysis; leaner conceptual development monitoring; likert scale; meaningful interaction analysis; medical student; network analysis; online learner; text analysis; text annotation; text mining; Context; Correlation; Feeds; Humans; Monitoring; Reliability; Semantics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
eChallenges, 2010
Conference_Location :
Warsaw
Print_ISBN :
978-1-4244-8390-7
Type :
conf
Filename :
5756563
Link To Document :
بازگشت