Data Mining Techniques for Detecting Behavioral Patterns of Gifted Students in Online Learning ...

@inproceedings{10869,
   author = {Lustigová, Zdena},
   address = {Fiorenze},
   keywords = {behavioural patterns; gifted students; virtual learning environment; data mining},
   language = {eng},
   location = {Fiorenze},
   publisher = {Pixel Associazione Culturale},
   title = {Data Mining Techniques for Detecting Behavioral Patterns of Gifted Students in Online Learning Environment (Case Study)},
   year = {2014}
}

TY  - JOUR
ID  - 10869
AU  - Lustigová, Zdena
PY  - 2014
TI  - Data Mining Techniques for Detecting Behavioral Patterns of Gifted Students in Online Learning Environment (Case Study)
PB  - Pixel Associazione Culturale
CY  - Fiorenze
KW  - behavioural patterns
KW  - gifted students
KW  - virtual learning environment
KW  - data mining
N2  - This paper presents selected results of data mining analysis of psychological and educational data, collected within 5 years (2006-2011), on the group of 91 children, who participated in a specific online program for gifted children, organised by faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. The information record for each case (student) is represented by 151 variables, of both categorical and metric nature, describing 1) personal characteristics, including motivation and intelligence 2) behavioral and action records, including individual decision making records, and 3) particular educational results and learning path. The study is based on comparison of students with very similar personal characteristics like motivation and intelligence and their study results. The success in a selected online course seems to be related to the nature of particular student talent. Student, who had chosen the right courses, that matched his/her nature of talent, succeed. An individual, who for some reason chooses the course that does not match his /her nature of talent, is more likely to fail.
ER  - 

LUSTIGOVÁ, Zdena. \textit{Data Mining Techniques for Detecting Behavioral Patterns of Gifted Students in Online Learning Environment (Case Study)}. Fiorenze: Pixel Associazione Culturale, 2014, 8 s.