The document describes the SOLO taxonomy for assessing student understanding when building with LEGO bricks. The taxonomy has five levels - prestructural, unistructural, multistructural, relational, and extended abstract - that represent increasing depth of understanding. At the prestructural level, a student does not understand what LEGO is or its purpose. At the unistructural level, a student understands what LEGO looks like but not how to use it. At the multistructural level, a student understands LEGO is for building but cannot yet relate the pieces together. At the relational level, a student can successfully build objects by understanding how the pieces fit. At the extended

1. SOLO LEGO Building
SOLO TAXONOMY Description of Lego Building Stage Self Review
Prestructural:
What stage of building (or understanding) did you
Unconnected information, Student: What is LEGO? What does it look like? achieve with LEGO and explain why in the appropriate
with no organisation spaces below:
“I need help or direction”
Unistructural Student: I know what LEGO looks like, but what does it do?
“I have 1 idea about this
topic”
Multistructural Student: Ok…it’s for building…but it’s still just a pile of
bricks…let’s put the pieces together to make something!
“I have various ideas about
a topic but cannot relate
these ideas together”
Relational
Student: Look, I made a spaceship! I know how the pieces fit
“I can find full relationships together and I have a relational understanding of LEGO. I
and connections between probably still need the instructions though.
various ideas in a topic”
Extended Abstract
Student: I have taken what I know about putting LEGO together
I go beyond the subject and to make something new without instructions!
link my understanding to
other concepts

2. SOLO LEGO Building
SOLO Taxonomy = TheStructure of Observed
Learning Outcomes
What is SOLO taxonomy?
It is a common language of learning for both STUDENTS and TEACHERS which allows
both to understand the DEPTH of student learning
Prestructural to extended Abstract
Surface to deep learning
Simple to complex understanding