  Objective This study investigates what kind of conceptions primary school
students have about ML if they are not conceptually "primed" with the idea that
in ML, humans teach computers. Method Qualitative survey responses from 197
Finnish primary schoolers were analyzed via an abductive method. Findings We
identified three partly overlapping ML conception categories, starting from the
most accurate one: ML is about teaching machines (34%), ML is about coding
(7.6%), and ML is about learning via or about machines (37.1%). Implications
The findings suggest that without conceptual clues, children's conceptions of
ML are varied and may include misconceptions such as ML is about learning via
or about machines. The findings underline the importance of clear and
systematic use of key concepts in computer science education. Besides
researchers, this study offers insights for teachers, teacher educators,
curriculum developers, and policymakers. Method Qualitative survey responses
from 197 Finnish primary schoolers were analyzed via an abductive method.
Findings We identified three partly overlapping ML conception categories,
starting from the most accurate one: ML is about teaching machines (34%), ML is
about coding (7.6%), and ML is about learning via or about machines (37.1%).
Implications The findings suggest that without conceptual clues, children's
conceptions of ML are varied and may include misconceptions such as ML is about
learning via or about machines. The findings underline the importance of clear
and systematic use of key concepts in computer science education. Besides
researchers, this study offers insights for teachers, teacher educators,
curriculum developers, and policymakers.
