Assessing feedback of measurement data: relating Schlumberger RPS practice to learning theory

摘要

Schlumberger RPS successfully applies software measurement to support their software development projects. It is proposed that the success of their measurement practices is mainly based on the organization of the interpretation process. This interpretation of the measurement data by the project team members is performed in so-called 'feedback sessions'. Many researchers identify the feedback process of measurement data as crucial to the success of a quality improvement program. However, few guidelines exist about the organization of feedback sessions. For instance, with what frequency should feedback sessions be held, how much information should be presented in a single session, and what amount of user involvement is advisable? Within the Schlumberger RPS search to improve feedback sessions, the authors explored learning theories to provide guidelines to these type of questions. After all, what is feedback more than learning?.