Learning Analytics Research Cluster

Athabasca University, Edmonton, Alberta
What the facility does

Automated assessment of learning and training experiences through AI techniques in both real-world and virtual environments, and this in academic and industrial domains

Areas of expertise

The Learning Analytics Research Cluster has developed a diversified expertise in various application domains, with the constant goal to support and study the learning processes of humans. First, optimized smart learning environments are designed to observe and capture through a variety of modalities and at several levels of granularity the learning and teaching processes that unfold within. This leads to the challenges of protecting the learners' privacy and guaranteeing the authenticity of learning experiences through the reliable and secure capture, transmission, and storage of learning data. Accumulating and connecting these big data together is however just one part of the story. Research methods also need to be adapted to the education and training sector to turn the pedagogical process into an evidence-based one, where the freedoms of individuals are preserved and the workflows of industries uninterrupted. Moreover, various forms of analytics are developed that are by nature descriptive to reconstruct learning episodes for retrospective insight, diagnostic to understand the real drivers of learning performance, predictive to foresee undesirable outcomes, and prescriptive to remedy suboptimal learning states through provision of formative feedback.

Research services

3D modeling, creation of immersive environments, automated essay scoring, automated competence assessment, development of learning analytics dashboard with self-regulation features, data analysis, causal inferencing with observational data, big data infrastructure

Sectors of application
  • Defence and security industries
  • Education
  • Energy (renewable and fossil)
  • Healthcare and social services
  • Information and communication technologies and media
  • Life sciences, pharmaceuticals and medical equipment
  • Policy and governance



HTC Vive

Virtual reality (VR) headset

Samsung Gear VR

Virtual reality (VR) headset

Microsoft HoloLens (1.0)

Mixed reality (MR) headset

Epson Moverio

Augmented reality (AR) headset

Vusix M100 smart glasses

Augmented reality (AR) headset

Falcon Northwest Tiki with NVIDIA GTX 1080 GPU

Development and rendering of immersive environments

Unity 3D

Software for AR/VR development

Bentley MicroStation (v8i and CONNECT), AutoDesk Navisworks

Creation and conversion of 3D models

Mootools Polygon Cruncher

3D optimization software


Software for 3D modeling

TensorFlow, Keras, Scikit-Learn, NumPy, Pandas, SHAP

AI/machine learning framework

  • CNRL/McGraw-Hill



Future of Training


Causal inferencing with observational data for evidence-based pedagogy: Adopting AI to education


Interview with Dr. Vivekanandan Kumar on his theories and accomplishments