SOLO Taxonomy

A framework for understanding
how students learn.

SOLO Taxonomy (Structure of Observed Learning Outcomes) was developed by John Biggs and Kevin Collis in 1982. It describes five levels of increasing complexity in student responses — from no understanding through to abstract generalisation.

In Quizite, AI classification and analytics use four levels — Unistructural through Extended Abstract. Prestructural responses are treated as below the first measurable level.

How Quizite uses SOLO

Every AI-generated question is tagged with a SOLO level. Every student response is auto-classified. Every report shows you exactly where each student sits.

Question tagging
Each question targets a specific SOLO level, so your quiz has intentional depth distribution.
Auto-classification
Open-text responses are classified by SOLO level using AI, saving hours of manual marking.
Growth tracking
Coming soon
Longitudinal SOLO trajectories across assessments are on our roadmap. Per-quiz analytics are available today.

The research behind SOLO

SOLO Taxonomy was developed by John Biggs and Kevin Collis and published in their 1982 book Evaluating the Quality of Learning. It emerged from studies of how students at different grade levels responded to academic tasks across multiple subject domains.

Unlike Bloom's Taxonomy — which categorises types of cognitive objectives — SOLO focuses on the structure of observed learning outcomes: how many elements students work with and whether those elements are connected into a coherent understanding.

The taxonomy has been widely adopted in Australia, New Zealand, and the United Kingdom, and is increasingly being used in curriculum design, formative assessment, and teacher professional learning worldwide.