Overview
ISO/IEC TR 20748-1:2016 defines a reference model for learning analytics interoperability within the domain of information technology for learning, education and training (LET). The Technical Report lays out common terminology, stakeholder user requirements, representative use cases and a workflow-derived reference architecture that describes how learning analytics components (data sources, collection, storage, processing, analysis, visualization and feedback) should interoperate. The aim is to help organizations design systems that share learner- and course-related data reliably, ethically and at scale.
Key Topics
- Reference model & terminology – standardized definitions for learning analytics concepts (e.g., dashboard, data flow, data source, learning outcome).
- User requirements & use cases – requirements gathered from learners, teachers and institutions (tracking progression, early-warning, personalized recommendations, quality assurance).
- Workflow & architecture components – clear decomposition into processes such as learning activity, data collection, storing/processing, analysing, visualization and feedback.
- Data flow & exchange – considerations for data formats, APIs (including abbreviated terms like xAPI), storage and archival to enable interoperability.
- Analytics techniques – support for descriptive and predictive analytics, social network and discourse analytics, and dashboard-driven visualization.
- Operational constraints – attention to volume, velocity and variety of analytics data (big data implications), quality of service and scalable IT architectures.
- Ethics, privacy & accessibility – guidance on privacy, trust, control of learner data and accessibility preferences to ensure inclusive, responsible analytics.
Applications
ISO/IEC TR 20748-1 is practical for anyone designing or operating learning analytics solutions:
- EdTech vendors & LMS/VLE developers – to design interoperable analytics modules and dashboards.
- System architects & integrators – for specifying APIs, data pipelines and storage that meet analytics needs.
- Data engineers & analysts – to map data sources, formats and workflows for analytics pipelines.
- Institutions & administrators – to plan retention strategies, quality assurance and institutional reporting driven by interoperable analytics.
- Educators & instructional designers – to implement adaptive learning, early-warning systems and personalized learning pathways.
- Policy-makers & privacy officers – to align analytics practice with ethical and accessibility requirements.
Practical benefits include improved data portability across platforms, clearer requirements for analytics pipelines, faster deployment of dashboards and predictive services, and better protection of learner rights.
Related Standards
Using ISO/IEC TR 20748-1 helps organizations create interoperable, scalable and ethically responsible learning analytics ecosystems.