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Title Scratch-NB: A Scratch Extension for Introducing K-12 Learners to Supervised Machine Learning
Authors Patricio Quiroz, Francisco Gutierrez
Publication date 2024
Abstract Artificial Intelligence has rapidly
captured---again---the
attention of practitioners and the CS Education community. Several
initiatives have been spawning to identify effective ways to introduce
learners at college and high-school levels to the basics of AI. In this
context, we developed Scratch-NB, an extension to the Scratch programming
language to equip K-8 learners with foundational tools for developing a
Naive-Bayes classifier, explicitly transparenting its internal components.
We opted to use Scratch due to its popularity within the CS4All movement
and
its predominance in schools, and extend the language with a simple
implementation of the Naive Bayes classifier as a gateway for introducing
basic notions of supervised learning and AI. In this paper, we report the
design rationale of our tool and our experience of using it in an informal
workshop with children aged 10-12 with no prior knowledge of computational
thinking, coding, or AI. The obtained results show that Scratch-NB showed
high levels of acceptance among the participants, raised interest in AI,
and
effectively provided basic foundations, particularly when comparing
Scratch-NB with other state-of-the-art tools targeted to this learner
group.
We argue that our tool has the potential to illuminate further practical
and
research endeavors when exploring how to effectively introduce younger
populations to the foundational notions of AI in practical
contexts.
Pages 1077-1083
Conference name ACM Technical Symposium on Computer Science Education
Publisher ACM Press (New York, NY, USA)
Reference URL View reference page