4.5 Article

SECOL: a semantic environment based on social media to support organisational learning

期刊

BEHAVIOUR & INFORMATION TECHNOLOGY
卷 36, 期 4, 页码 364-389

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/0144929X.2016.1236836

关键词

Organisational learning; ontologies; learning objects; unit of learning; social software

资金

  1. Fundacao Araucaria de Apoio ao Desenvolvimento Cientifico e Tecnologico do Estado do Parana (Foundation in Support of the Scientific and Technological Development of the State of Parana, Brazil)

向作者/读者索取更多资源

Organisational learning (OL) helps companies to significantly improve their processes through the reuse of experiences, making knowledge accessible to the whole organisation. However, establishing learning in software development companies is not a trivial task, since it is an area in which processes and knowledge are usually hidden inside the employees' mind. Generally, employees prefer to look for knowledge via Internet search engines rather than using the knowledge produced inside the company. Hence, we explored how better organising content produced within the company may minimise this problem. We investigated how a semantic collaborative environment, titled semantic collaborative environment for organisational learning (SECOL), based on social software, learning objects (LOs), and units of learning (UL) may assist to improve OL for software development companies. We defined an approach to generate LOs and UL from social software's content used by companies. The environment was implemented based on ontologies in order to represent and organise acquired knowledge. Furthermore, an experiment was conducted using qualitative data analysis. The results indicated that the use of the environment is appropriate to improve OL in software development teams and the use of SECOL is efficient, particularly in order to acquire new knowledge, assisting the promotion of the use of organisational patterns and minimising repeated solutions.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据