Pregled bibliografske jedinice broj: 1136456
Implementing M-Learning System for Learning Mathematics Through Computer Games and Applying Neural Networks for Content Similarity Analysis of an Integrated Social Network
Implementing M-Learning System for Learning Mathematics Through Computer Games and Applying Neural Networks for Content Similarity Analysis of an Integrated Social Network // International Journal of Interactive Mobile Technologies, 15 (2021), 13; 145-161 doi:10.3991/ijim.v15i13.22185 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1136456 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Implementing M-Learning System for Learning
Mathematics Through Computer Games and Applying
Neural Networks for Content Similarity Analysis of
an Integrated Social Network
(Implementing M-Learning System for Learning
Mathematics Through Computer Games and Applying
Neural Networks for Content Similarity Analysis
of
an Integrated Social Network)
Autori
Jurić, Petar ; Brkić Bakarić, Marija ; Matetić, Maja
Izvornik
International Journal of Interactive Mobile Technologies (1865-7923) 15
(2021), 13;
145-161
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
m-learning ; e-learning ; game-based learning ; Mathematics ; neural networks ; social network analysis
Sažetak
In order to make e-learning systems widely available, the majority of new systems are being developed in a form suitable for m- learning. The system implemented in this research uses educational computer games for learning Mathematics in primary schools and has an integrated social network, which is used for communication and publishing game-related content. The system is not restricted to desktop platforms, but provides equivalent user experience and functionality on smartphones and tablets. The research highlights the challenges involved in developing the system and illustrates the process of adapting the elearning system to m-learning. Besides analyzing platforms used for accessing the system (desktop/mobile), the paper also explores how to interpret messages when they contain concepts which are in a student jargon or generally unknown to teachers, and shows that these messages can be interpreted by applying neural networks.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Projekti:
--uniri-drustv-18-122 - Dubinska analiza tokova podataka za pametno upravljanje hladnim lancem (SmaCC) (SMACC) (Matetić, Maja) ( CroRIS)
Ustanove:
Fakultet informatike i digitalnih tehnologija, Rijeka
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus