Welcome to SensoryVerse

From “learning styles” to measurable traits

For decades, the idea of fixed “learning styles” (visual, auditory, kinesthetic, etc.) has been popular in education. However, large-scale research shows that teaching students strictly according to a declared style does not reliably improve learning outcomes. What does matter are measurable cognitive traits that influence how people process, remember, and apply information.

SensoryVerse focuses on these traits — such as attention rhythm, preference for rich vs. minimal sensory input, balance between analytical and associative thinking, and the role of emotion in learning. These factors are supported by evidence from cognitive psychology, neuroscience, and human–computer interaction.

Why this matters

Instead of asking learners to adapt to a fixed environment, adaptive systems can adjust the environment to the learner. This is especially relevant for neurodivergent learners, where differences in attention, sensory processing, or social pacing can become strengths when the context is tuned appropriately.

• Instructional design: tailoring representations (visual, verbal, embodied) and pacing to match cognitive needs.
• Focus tools: using music, rhythm, or rituals to support concentration and reduce distraction.
• Assessment: tracking how people adapt under cognitive load, rather than only testing recall.

How SensoryVerse gathers insight

Insights are derived in two complementary ways:

1. Questionnaires — structured self-report questions that reveal preferences in attention, processing, and engagement.
2. Micro-games — short, browser-based tasks that measure behavior such as reaction time, switching ability, memory for words vs. images, and tolerance for overstimulation.

Comparing these two signals increases accuracy: when self-perception and measured behavior agree, we gain confidence; when they diverge, it highlights areas for reflection or training.

Research directions

SensoryVerse is part of a growing effort to connect cognitive science with practical, inclusive learning design. Planned studies include:

• Evaluating the reliability of short tasks as measures of attention, flexibility, and sensory load.
• Testing whether adapting content and environment based on these traits improves engagement and retention.
• Sharing anonymized data and open methods to support reproducibility and collaboration.

Ethics and privacy

• Minimal data: only collect what is needed to generate feedback and improve design.
• Local first: whenever possible, analysis happens in your browser; exporting data is optional.
• De-identified: no personal identifiers are linked to performance data.
• Consent: participation in research is separate from using the tool for personal insight.