Requirements Engineering (RE) approaches, following paradigms such as goal-oriented [1] or scenario-based [2], provide expressive model elements for requirements elicitation and analysis. However, these approaches are still struggling when it comes to managing the quality of their models. Problems in quality can cause difficulties in anaging and understanding requirements, which in turn leads to increased development costs. The models' quality should then be a permanent concern. We propose a quantitative assessment of the goal-oriented and scenario-based models' quality, namely its complexity, completeness, appropriateness recognizability, understandability and learnability. To this end, we propose a combination of techniques to be applied to the RE models, the modelling process, and the models' notation. We are going to define metrics about the models, through the Goal-Question-Metric (GQM) approach, and incorporate them in a common evaluation framework that helps in the requirements modelling process. The quality of the RE models, the modelling process and the model's notation will be measured by collecting biometric data from stakeholders, by using eye-tracking devices, electroencephalography (EEG) scanners, and electro-dermal activity (EDA) scanners. Furthermore, we will collect metrics about the model during the modelling process, and the subjective opinion of stakeholders about the usage of these models, through questionnaires like NASA TLX [4] (which measures perceived effort while working on tasks). All metrics and biometrics are going to be theoretically and experimentally evaluated, through a set of case studies and experiments with different types of participants (including researchers, practitioners and students).