Critical Algorithmic Literacy: Explorations of Algorithmic Bias in Elementary School
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Critical Algorithmic Literacy: Explorations of Algorithmic Bias in Elementary School

Abstract

This case study focuses on the implementation and analysis of critical algorithmic literacy (CAL) lessons in two grade 3/4 combination classes. The study involves one elementary school teacher and 36 students from a K-6 school in Southern California. By analyzing various data sources, I identified trends that could be helpful for future researchers and educators looking to introduce CAL in elementary education.The data indicate that merging computer science and Kellner and Share’s (2019) Critical Media Literacy Framework represents a promising method for teaching contextualized algorithmic literacy models, like CAL, to elementary students. The study examines the importance of clear instructional examples for helping students grasp the concept of algorithms and their societal effects. It also highlights that a student’s understanding of bias and basic computer science concepts can enhance their understanding of algorithmic bias and its societal impacts. This study also illustrates how lessons designed for older students can be successfully modified for elementary students. It examines both the challenges and potential for the CAL framework’s design. Furthermore, it uncovers various obstacles and effective practices for integrating CAL instruction with third and fourth graders. Future research aiming to foster CAL in classrooms should investigate how teachers evaluate student learning and the role of general computer science knowledge in enabling critical examination of algorithmically driven media.

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