Understanding Mediated Variables in Open Data through Naive Mode of Address

Potential Abstract: This study investigates the impact of mediated variables within the context of open data education, focusing on the application of a naive mode of address. Drawing on theories of artificial intelligence and educational psychology, we examine how learners interact with and interpret open data sources when a naive mode of address is employed. By exploring the role of mediated variables, such as visualizations, feedback mechanisms, and instructional scaffolding, we aim to uncover strategies that enhance students’ understanding and utilization of open data in educational settings. This research contributes to the growing body of literature on the intersection of AI and education, shedding light on the potential of leveraging technology to support data literacy skills in learners.

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