APA 6th Edition Stickel, C., Ebner, M. i Holzinger, A. (2008). Useful Oblivion Versus Information Overload in e-Learning Examples in the Context of Wiki Systems. Journal of computing and information technology, 16 (4), 271-277. https://doi.org/10.2498/cit.1001394
MLA 8th Edition Stickel, Christian, et al. "Useful Oblivion Versus Information Overload in e-Learning Examples in the Context of Wiki Systems." Journal of computing and information technology, vol. 16, br. 4, 2008, str. 271-277. https://doi.org/10.2498/cit.1001394. Citirano 06.03.2021.
Chicago 17th Edition Stickel, Christian, Martin Ebner i Andreas Holzinger. "Useful Oblivion Versus Information Overload in e-Learning Examples in the Context of Wiki Systems." Journal of computing and information technology 16, br. 4 (2008): 271-277. https://doi.org/10.2498/cit.1001394
Harvard Stickel, C., Ebner, M., i Holzinger, A. (2008). 'Useful Oblivion Versus Information Overload in e-Learning Examples in the Context of Wiki Systems', Journal of computing and information technology, 16(4), str. 271-277. https://doi.org/10.2498/cit.1001394
Vancouver Stickel C, Ebner M, Holzinger A. Useful Oblivion Versus Information Overload in e-Learning Examples in the Context of Wiki Systems. Journal of computing and information technology [Internet]. 2008 [pristupljeno 06.03.2021.];16(4):271-277. https://doi.org/10.2498/cit.1001394
IEEE C. Stickel, M. Ebner i A. Holzinger, "Useful Oblivion Versus Information Overload in e-Learning Examples in the Context of Wiki Systems", Journal of computing and information technology, vol.16, br. 4, str. 271-277, 2008. [Online]. https://doi.org/10.2498/cit.1001394
Sažetak Information overload refers to the state of having too much information to make a decision or remain informed about a topic. We present a novel approach of filtering, adapting and visualizing content inside a Wiki knowledge base. Thereby we follow the question of how to optimize the process of learning, with respect to shorter time and higher quality, in face of increasing and changing information. Our work adopts a consolidation mechanism of the human memory, in order to reveal and shape key structures of a Wiki hypergraph. Our hypothesis so far is that visualization of these structures enables a more efficient learning.