The group brings together researchers in psychometrics, learning sciences, and AI to develop transparent, equitable, and multilingual approaches to assessment. A central aim of BEAM is to improve how learning and development are measured across time, contexts, and languages, with particular emphasis on within-person learning processes rather than static group comparisons.

Research focus

BEAM’s research addresses fundamental and applied challenges in educational and psychological measurement, including:

  • how learning unfolds within individuals over time
  • how assessment tools can be made fair, interpretable, and inclusive
  • how AI-based methods can support—not replace—sound measurement theory
  • how multilingual and cross-cultural contexts can be better represented in assessment systems

Across projects, BEAM prioritizes methodological transparency, open science, and ethical use of data.

Core pillars (2026–2029)

BEAM’s activities are organized around three interconnected pillars:

Theory and Method

We develop and test explanatory and within-person measurement models that move beyond static snapshots of ability and toward dynamic representations of learning and development.

Technology and Data Infrastructure

We design and implement GDPR-compliant, multilingual assessment tools and platforms, enabling scalable and responsible use of modern measurement approaches in research and practice.

Practice, Policy, and Impact

We translate research findings into educational, clinical, and policy-relevant applications, supporting more equitable assessment and decision-making across educational systems.

Activities and collaboration

BEAM’s work includes collaborative workshops, platform and tool development, empirical pilot studies, open-science dissemination, and preparation of major external funding proposals, including applications to the Research Council of Norway (RCN) and Horizon Europe.

The group serves as a collaborative hub for researchers, students, and external partners interested in advancing measurement science that supports inclusive and evidence-based education.