Learning Frameworks in a Social-Intensive Knowledge Environment - An Empirical Study

• Tipo: Artigo em Revista Científica Internacional
• Data: 2017

Autores

Nuno Flores (Autor) FEUP; Ademar Aguiar (Autor) FEUP

Revista

Título: International Journal of Software Engineering and Knowledge Engineering

Vol. 27

Páginas: 699-725

ISSN: 0218-1940

Editora: World Scientific

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00N-CRF

DOI: 10.1142/s0218194017500267

Abstract (EN): Application frameworks are a powerful technique for large-scale reuse, but require a considerable effort to understand them. Good documentation is costly, as it needs to address different audiences with disparate learning needs. When code and documentation prove insuficient, developers turn to their network of experts. Nevertheless, this proves difficult, mainly due to the lack of expertise awareness (who to ask), wasteful interruptions of the wrong people and unavailability ( either due to intrusion or time constraints). The DRIVER platform is a collaborative learning environment where framework users can, in a non-intrusive way, store and share their learning knowledge while following the best practices of framework understanding (patterns). Developed by the authors, it provides a framework documentation repository, mounted on a wiki, where the learning paths of the community of learners can be captured, shared, rated, and recommended. Combining these social activities, the DRIVER platform promotes collaborative learning, mitigating intrusiveness, unavailability of experts and loss of tacit knowledge. This paper presents the assessment of DRIVER using a controlled academic experiment that measured the performance, effectiveness and framework knowledge intake of MSc students. The study concluded that, especially for novice learners, the platform allows for a faster and more effective learning process.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 27