Context: Requirements Engineering approaches provide expressive model techniques
for requirements elicitation and analysis. Yet, these approaches struggle to manage the
quality of their models, causing difficulties in understanding requirements, and increase
development costs. The models’ quality should be a permanent concern. Objectives: We
propose a mixed-method process for the quantitative evaluation of the quality of requirements
models and their modelling activities. We applied the process to goal-oriented (i*
1.0 and iStar 2.0) and scenario-based (ARNE and ALCO use case templates) models, to
evaluate their usability in terms of appropriateness recognisability and learnability. We
defined (bio)metrics about the models and the way stakeholders interact with them, with
the GQM approach. Methods: The (bio)metrics were evaluated through a family of 16
quasi-experiments with a total of 660 participants. They performed creation, modification,
understanding, and review tasks on the models. We measured their accuracy, speed,
and ease, using metrics of task success, time, and effort, collected with eye-tracking,
electroencephalography and electro-dermal activity, and participants’ opinion, through
NASA-TLX. We characterised the participants with GenderMag, a method for evaluating
usability with a focus on gender-inclusiveness. Results: For i*, participants had better
performance and lower effort when using iStar 2.0, and produced models with lower accidental
complexity. For use cases, participants had better performance and lower effort
when using ALCO. Participants using a textual representation of requirements had higher
performance and lower effort. The results were better for ALCO, followed by ARNE, iStar
2.0, and i* 1.0. Participants with a comprehensive information processing and a conservative
attitude towards risk (characteristics that are frequently seen in females) took
longer to start the tasks but had a higher accuracy. The visual and mental effort was also
higher for these participants. Conclusions: A mixed-method process, with (bio)metric
measurements, can provide reliable quantitative information about the success and effort
of a stakeholder while working on different requirements models’ tasks
