Systematic community of Practice activities evaluation through Natural Language Processing: application to research projects

Abstract

Community of Practice (CoP) efficiency evaluation is a great deal in research. Indeed, having the possibility to know if a given CoP is successful or not is essential to better manage it over time. The existing approaches for efficiency evaluation are difficult and time-consuming to put into action on real CoPs. They require either to evaluate subjective constructs making the analysis unreliable, either to work out a knowledge interaction matrix that is difficult to set up. However, these approaches build their evaluation on the fact that a CoP is successful if knowledge is exchanged between the members. It is the case if there are some interactions between the actors involved in the CoP. Therefore, we propose to analyze these interactions through the exchanges of emails thanks to Natural Language Processing. Our approach is systematic and semi-automated. It requires the e-mails exchanged and the definition of the speech-acts that will be retrieved. We apply it on a real project-based CoP: the SEPOLBE research project that involves different expertise fields. It allows us to identify the CoP core group and to emphasize learning processes between members with different backgrounds (Microbiology, Electrochemistry and Civil engineering).

Natural language processing in-and-for design research

“…Goepp et al (2019, p. 165) identify the following speech acts from email exchanges: Information, Explication, Evaluation, Description and Request. These speech acts were associated with a set of verbs, for example, ‘Explication’ was associated with ‘explain’ and ‘clarify’.…”

Abordagem baseada em problemas no ensino do projeto de sistemas prediais hidráulicos e sanitários

“…A ABP forma um profissional com visão estratégica, capaz de pesquisar soluções dentro do contexto ambiental e social VEMURY et al, 2018;GOEPP et al, 2019;ELLZEY et al;.…”