PME-NA

Teaching and Adapting Machine Learning Curriculum in High School Statistics

• In Event: Teaching and Adapting Machine Learning Curriculum in High School Statistics

Description

The rise of machine learning (ML) has raised questions about how to teach it in K-12 classrooms. This study explores three cases of classroom enactments of ML-CURRICULUM: a co-designed series of ML lessons aligned to high school statistics standards. Each teacher was encouraged to adapt ML-CURRICULUM as they saw appropriate. Drawing from Brown’s Design Capacity for Enactment framework (2002), this study closely examines the frequency and substance of teachers’ adaptations of ML-CURRICULUM, and the design resources that enabled their adaptations. We found that teachers’ prior knowledge of ML, their statistics pedagogical content knowledge, and their knowledge of students supported their ability to adapt ML-CURRICULUM. From these findings, we illustrate triumphs and challenges that statistics teachers who are new to ML may face when teaching about it.

Author

• Victoria Delaney, San Diego State University