01
Research workflow systems
Tooling for study setup, participant operations, team coordination, and research support processes that are too important to leave fragmented.
Relevant guidance: WCAG 2.1 AA, UK GDPR, ICO accountability expectations.
Research support and innovation
Research systems, analytics, and workflow design for education technology teams.
EdTechLab helps universities, institutions, and research teams design the digital infrastructure around structured studies, pilot programmes, learning innovation, and product R&D.
Core capabilities
- Researcher tooling and workflow support
- Experiment, pilot, and intervention platforms
- Learning analytics and evidence systems
- AI and automation applied responsibly
Capability areas
We support research work across workflows, experimentation, analytics, and product development.
02
Experiment and intervention platforms
Digital environments for pilots, prototypes, teaching interventions, and product studies where the user experience and experimental design both matter.
Relevant standards: 1EdTech LTI where LMS integration matters, WCAG 2.1 AA, privacy-first rollout planning.
03
Analytics and reporting architecture
Event design, data capture, dashboards, and reporting layers that give researchers and institutions clearer evidence about what is happening and what to do next.
Relevant standards: xAPI, 1EdTech Caliper, FAIR data principles, UK GDPR.
04
AI and automation, applied responsibly
Careful use of automation and AI where it improves research support, summarisation, routing, or operational speed without obscuring accountability.
Relevant guidance: UK GDPR, ICO guidance on accountability, clear human oversight.
How collaboration works
A practical engagement pattern from research question to working system.
Stage 1
Map the research context
Clarify the research goals, participants, data needs, operational constraints, and what successful adoption would look like.
Stage 2
Shape the tool or system
Turn the problem into workflow design, product direction, data structure, and an implementation plan that can be tested and improved.
Stage 3
Build, validate, and refine
Deliver with attention to usability, analytics quality, governance needs, and the real research environment the product has to support.
Where this applies
Typical conversations begin when a team needs a credible route from research problem to working product.
Research team workflow redesign
A team needs better tooling around participant handling, coordination, or day-to-day research operations.
Pilot, intervention, or experiment platform
A university or institution needs a digital surface for a study, pilot, teaching intervention, or product evaluation.
Analytics and evidence improvement
Existing data is hard to trust, compare, or explain and the reporting layer needs to be rebuilt around real decision-making.
Read the latest Lab NoteNew product or lab initiative
A research-led idea needs discovery, prototyping, and a stronger product foundation before it can become a durable offering.
Discuss a product idea