Naslov
Annotating Exam Questions Through Automatic Learning Concept Classification

Autori
Pintar, Damir ; Begušić, Domagoj ; Škopljanac- Mačina, Frano ; Vranić, Mihaela

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2018) / Rožić, Nikola ; Lorenz, Pascal - : Curran Associates, 2018, 123-129

ISBN
978-1-5386-6770-5

Skup
26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2018)

Mjesto i datum
Split, Hrvatska; Supetar, Hrvatska, 13.09.2018. - 15.09.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
educational data mining ; exam queries ; learning concepts ; classification ; e-learning

Sažetak
Educational data mining (or EDM) is an emerging interdisciplinary research field concerned with developing methods for exploring the unique types of data encountered in the field of education. One of the most valuable sources in the educational domain are repositories of exam queries, which were usually designed for evaluating how efficient the learning process was in transferring knowledge about certain taught concepts, but which commonly do not contain any additional information about concepts they are related to beyond the text of the query and offered answers. In this paper we present results of our research which involves using text mining methods to automatically annotate existing exam queries with information about concepts they relate to, enabling better insight into learning concept adoption after those queries are used in a exam. We apply this approach to real-life exam questions from a high education university course and show validation of our results performed in consultation with experts from the educational domain.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

POVEZANOST RADA