Artificial Intelligence and Machine Learning in the STEAM classroom
Analysis of performance data and reflections of international high school students.
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Keywords:Artificial intelligence education, machine learning education, machine perception education, high school, minimum spanning trees, artificial neural networks
This research aims in shedding light on international high school students’ perceptions, awareness, and prior knowledge about Artificial Intelligence and Machine Learning, as well as to investigate the effect of taking a relevant learning unit within a STEAM course on students’ dispositions toward and understanding about Artificial intelligence. The analysis of performance and reflection data from 62 individuals revealed low prior student engagement with Artificial Intelligence and Machine Learning content, a positive shift in the anticipated societal impact of Artificial Intelligence and an active engagement with online Artificial Intelligence applications during the unit, as well as no correlation between student performance and gender. It is suggested that the development and implementation of learning designs that focus on conceptual understanding of Artificial Intelligence and Machine Learning could benefit all students.
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