While technology has helped improve process efficiency in several domains, it still has an outstanding debt to education. In this article, we introduce NAIRA, a Multimodal Learning Analytics platform that provides Real-Time Feedback to foster collaborative learning activities’ efficiency. NAIRA provides real-time visualizations for students’ verbal interactions when working in groups, allowing teachers to perform precise interventions to ensure learning activities’ correct execution. We present a case study with 24 undergraduate subjects performing a remote collaborative learning activity based on the Jigsaw learning technique within the COVID-19 pandemic context. The main goals of the study are (1) to qualitatively describe how the teacher used NAIRA’s visualizations to perform interventions and (2) to identify quantitative differences in the number and time between students’ spoken interactions among two different stages of the activity, one of them supported by NAIRA’s visualizations. The case study showed that NAIRA allowed the teacher to monitor and facilitate the learning activity’s supervised stage execution, even in a remote learning context, with students working in separate virtual classrooms with their video cameras off. The quantitative comparison of spoken interactions suggests the existence of differences in the distribution between the monitored and unmonitored stages of the activity, with a more homogeneous speaking time distribution in the NAIRA supported stage.

Incorporating technologies to support the monitoring, evaluation, and feedback of soft skills attracts great attention in the scientific community. For a team to have a good performance and manage itself, it can be helpful to identify the behavioral characteristics and social interactions established between its members. Here, we explore the relationships between Belbin’s behavioral roles, affinity sociograms, and audio interactions collected by the Naira multimodal analysis platform. We present a case study with university students designing with the Lego Serious Play methodology and incorporating agile practices that would stimulate collaborative work. The results are promising, allowing us to define new research hypotheses that will serve as guidelines for future work. The findings indicate that the Naira platform would enable us to recognize behavioral traces for the Social and Action natural roles.

This article presents a comprehensive methodology to monitor internal team climate in agile educational projects. The proposed approach integrates Peer Assessment, Process Evaluation, and product assessment using the Analytic Hierarchy Process (AHP) to calculate a dynamic Internal Team Climate Index (ITCI). Designed for Scrum-based project courses, the methodology enables instructors to identify behavioral patterns, anticipate potential dysfunctions, and guide effective pedagogical interventions. A case study involving 25 student teams over three sprints was conducted to validate the framework. Results show a strong correlation between early collaboration metrics and final team performance, with statistical evidence confirming significant improvements over time. The ITCI not only quantifies team dynamics but also offers a practical tool for formative assessment and continuous improvement in software engineering education. Survey data from 94 students further confirmed the framework’s perceived fairness, formative value, and motivational impact. The proposed methodology is validated in a Scrum-based software engineering course and demonstrates potential adaptability to similar educational contexts. Rather than constituting a purely psychological climate instrument, the Internal Team Climate Index (ITCI) is conceived as a formative composite indicator that integrates peer-perceived climate with process- and product-related contextual proxies.