Pregled bibliografske jedinice broj: 971134
Automatic extraction of learning concepts from exam query repositories
Automatic extraction of learning concepts from exam query repositories // Journal of communications software and systems, 14 (2018), 4; 312-319 doi:10.24138/jcomss.v14i4.605 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 971134 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Automatic extraction of learning concepts from exam query repositories
Autori
Pintar, Damir ; Begušić, Domagoj ; Škopljanac- Mačina, Frano ; Vranić , Mihaela
Izvornik
Journal of communications software and systems (1845-6421) 14
(2018), 4;
312-319
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
educational data mining ; exam queries ; learning concepts ; classification ; e-learning
Sažetak
One of the biggest challenges in the process of establishing modern e-learning systems is figuring out ways to leverage legacy course materials and integrating them in the new information systems. Existing exam query repositories in particular are a very valuable data source, but one which usually lacks enough metadata to help establish relationships between exam questions and corresponding learning concepts whose adoption is being evaluated. In this paper we present the continuation of our research regarding the usage of educational data mining methods able to automatically annotate pre-existing exam queries with information about learning concepts they relate to. In our novel approach we leverage both textual and visual information contained in the queries. By combining the power of natural language processing which focuses on the text of the question, and annotated data extracted from figures accompanying the questions, we are able to further refine our classification methods and achieve noticeably improved results. By identifying learning concepts more accurately we further facilitate automatic creation of exams as well as even better insight into learning concept adoption. Our approach is again applied on data gathered from a large scale university course, and the results were validated in consultation with educational domain experts.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-UIP-2014-09-2051 - Uporaba metoda i otvorenih tehnologija dubinske analize podataka za unaprijeđenje infrastrukture elektroničkog učenja (eduMINE) (Pintar, Damir, HRZZ ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Domagoj Begušić
(autor)
Mihaela Vranić
(autor)
Damir Pintar
(autor)
Frano Škopljanac-Mačina
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus