@misc{10498/30703,
year = {2018},
month = {9},
url = {http://hdl.handle.net/10498/30703},
abstract = {Wikis are appropriate tools for deploying authentic assessment experiences for learning and work scenarios in which a group of users are asked to develop a shared task. However, when the number of wiki users increases, the number of contributions can grow at a pace whereby accurately assessing them becomes a complex and non-scalable task. While different quantitative approaches have been shown to be scalable, they are usually coarse-grained and provide limited feedback about the assessment. This work proposes a scalable assessment methodology for wiki-based tasks, based on qualitative self- and peer assessment of wiki contributions. The methodology is implemented using a software tool and is applied as part of an undergraduate course, complementing a quantitative assessment approach. Positive evidence on the scalability of the method and how it implements a more fine-grained qualitative assessment than the regular quantitative approach is found, providing indicators for assessing both individual and group generic skills.},
publisher = {SPRINGER},
title = {Scalable authentic assessment of collaborative work assignments in wikis},
doi = {10.1186/s41239-018-0122-1},
author = {Balderas Alberico, Antonio and Palomo Duarte, Manuel and Dodero Beardo, Juan Manuel and Ibarra Saiz, María Soledad and Rodríguez Gómez, Gregorio},
}