Pregled bibliografske jedinice broj: 888974
Analyzing Heterogeneous Learning Logs using the Iterative Convergence Method
Analyzing Heterogeneous Learning Logs using the Iterative Convergence Method // Proceedings of the International Conference on Teaching, Assessment, and Learning for Engineering 2017 (IEEE TALE 2017)
Hong Kong, 2017. (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 888974 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Analyzing Heterogeneous Learning Logs using the Iterative Convergence Method
Autori
Krstulović, Roko ; Botički, Ivica ; Ogata, Hiroaki
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the International Conference on Teaching, Assessment, and Learning for Engineering 2017 (IEEE TALE 2017)
/ - Hong Kong, 2017
Skup
International Conference on Teaching, Assessment, and Learning for Engineering 2017 (IEEE TALE 2017)
Mjesto i datum
Hong Kong, Kina, 12.12.2017. - 14.12.2017
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
mobile learning ; learning log analysis ; iterative convergence method
(mobile learningmobile learning ; learning log analysis ; iterative convergence method ;)
Sažetak
This paper presents the use of iterative convergence method in analyzing learning log data from a three year mobile learning project. The authors of the paper propose the use of iterative convergence method as a non-standard student’ evaluation method based on lessons’ weights. During the project duration a large amount of log data on competitive, collaborative and augmented reality digital lesson use was collected and stored in a proprietary database. The method calculates lessons’ weights and students’ success in a scenario where there are no prior lessons’ weights or students’ success known, and where not all students complete the same set of lessons. After the application of the algorithm, the students’ success data on the three different types of lessons is compared and correlated. The main implications coming for the analysis is that students have better success in competitive and augmented reality lessons and that there is negative correlation between students’ success on competitive and augmented reality lessons on one side and collaborative lessons on another.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Ivica Botički
(autor)