APA 6th Edition Divjak, B. i Maretić, M. (2015). Geometry for Learning Analytics. KoG, 19. (19.), 48-56. Preuzeto s https://hrcak.srce.hr/151341
MLA 8th Edition Divjak, Blaženka i Marcel Maretić. "Geometry for Learning Analytics." KoG, vol. 19., br. 19., 2015, str. 48-56. https://hrcak.srce.hr/151341. Citirano 24.01.2020.
Chicago 17th Edition Divjak, Blaženka i Marcel Maretić. "Geometry for Learning Analytics." KoG 19., br. 19. (2015): 48-56. https://hrcak.srce.hr/151341
Harvard Divjak, B., i Maretić, M. (2015). 'Geometry for Learning Analytics', KoG, 19.(19.), str. 48-56. Preuzeto s: https://hrcak.srce.hr/151341 (Datum pristupa: 24.01.2020.)
Vancouver Divjak B, Maretić M. Geometry for Learning Analytics. KoG [Internet]. 2015 [pristupljeno 24.01.2020.];19.(19.):48-56. Dostupno na: https://hrcak.srce.hr/151341
IEEE B. Divjak i M. Maretić, "Geometry for Learning Analytics", KoG, vol.19., br. 19., str. 48-56, 2015. [Online]. Dostupno na: https://hrcak.srce.hr/151341. [Citirano: 24.01.2020.]
Sažetak Learning analytics is focused on the educational challenge of optimizing opportunities for meaningful learning.
Assessment deeply influences learning, but at the same time data about assessment are rarely considered and utilized by learning analytics.
Current approaches to analysis and reasoning about peer-assessment lack rigor and appropriate measures of reliability assessment. Our paper addresses these issues with a geometrical model based on the taxicab geometry and the use of the scoring rubrics. We propose and justify measures for calculation of the final grade in peer-assessment and related inter-rater and intra-rater reliability measures. We present and discuss a geometrical model for two important peer-assessment scenarios.