Pregled bibliografske jedinice broj: 836342
Automated extraction and visualization of learning concept dependencies using Q-matrices and exam results
Automated extraction and visualization of learning concept dependencies using Q-matrices and exam results // 24th International Conference on Software, Telecommunications and Computer Networks - SoftCOM 2016 / Rožić, Nikola ; Begušić, Dinko (ur.).
Split: Fakultet elektrotehnike, strojarstva i brodogradnje Sveučilišta u Splitu, 2016. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Automated extraction and visualization of learning concept dependencies using Q-matrices and exam results
Autori
Vranić, Mihaela ; Pintar, Damir ; Humski, Luka
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
24th International Conference on Software, Telecommunications and Computer Networks - SoftCOM 2016
/ Rožić, Nikola ; Begušić, Dinko - Split : Fakultet elektrotehnike, strojarstva i brodogradnje Sveučilišta u Splitu, 2016
ISBN
978-953-290-061-3
Skup
24th International Conference on Software, Telecommunications and Computer Networks - SoftCOM 2016
Mjesto i datum
Split, Hrvatska, 22.09.2016. - 24.09.2016
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Transactional data; Learning concepts; Annotated exams; Education improvement; Association rule; Q-matrix; Frequent itemsets; Visualization; Tree-like structures; Concept maps
Sažetak
Information systems of educational organizations often represent a potential well of useful information which can be discovered and interpreted by using specific methods. Exam results in particular are commonly used as a single-use measure of individual knowledge states, after which they are archived and subsequently never used again. Our approach suggests using past exam results as a rich data source for extracting knowledge about learning concepts, especially regarding their mutual relationships. To achieve this goal, we adopt our method for interactive visualization of patterns in transactional data and apply it to knowledge state matrices generated from real- life exam results and Q-matrices constructed by domain experts, providing the end user with rich, easily interpretable and visually engaging dendrogram structures.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb