Pregled bibliografske jedinice broj: 955122
Discovering e-Learning Process Models from Counterexamples
Discovering e-Learning Process Models from Counterexamples // Proceedings of the 41st International Convention on Information and Communication Technology, Electronics and Microelectronics MIPRO 2018 / Skala, Karolj (ur.).
Rijeka: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2018. str. 0593-0598 doi:10.23919/MIPRO.2018.8400112 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 955122 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Discovering e-Learning Process Models from
Counterexamples
Autori
Blašković, Bruno ; Škopljanac-Mačina, Frano ; Zakarija, Ivona
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 41st International Convention on Information and Communication Technology, Electronics and Microelectronics MIPRO 2018
/ Skala, Karolj - Rijeka : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2018, 0593-0598
ISBN
978-953-233-096-0
Skup
41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2018)
Mjesto i datum
Opatija, Hrvatska, 21.05.2018. - 25.05.2018
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
adaptive e-learning systems ; process mining ; Angluin’s L* algorithm
Sažetak
In our paper we are examining the application of process mining techniques in the development of adaptive e-learning systems such as Intelligent Tutoring Systems. Process mining techniques can discover business process models from event log data. Here, we will use process mining to discover and add new useful tutoring sessions (learning paths) to our adaptive e- learning system. E- learning knowledge base is an ontology (union of taxonomies) of a chosen domain. Using data in the ontology we build a directed acyclic graph with nodes (states) and labeled transitions (questions), or more formally, as a deterministic finite automaton (DFA). Each tutoring session is a run of the DFA, or in process mining terminology: one learning process model. We will apply well- known Angluin's L* algorithm on the data from e- learning system log files to discover new useful tutoring sessions which can be added to the e- learning system DFA. We will present use case examples based on our e-learning system used on our course Fundamentals of Electrical Engineering.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Sveučilište u Dubrovniku
