Pedagogy of teaching with large datasets: Designing and implementing effective data-based activities

Area of Science:

• Environmental science education
• Data science education

Background:

• Large datasets offer unique opportunities for developing students' skills and conceptual knowledge.
• Effective integration of big data in teaching requires careful activity design and accessible tools.

Purpose of the Study:

• To discuss core components for developing effective large dataset activities aligned with the 5E learning cycle.
• To provide strategies for overcoming barriers when working with large datasets in educational settings.

Main Methods:

• Structuring data-based activities around relevant questions using authentic, publicly accessible data.
• Scaffolding activities to include student choice and opportunities for results discussion.
• Ensuring accessibility of data manipulation, analysis, and visualization software for students.

Main Results:

• Data-based activities should be inquiry-driven, utilize real-world data, and incorporate student agency.
• Strategies like pre-organizing code, using cloud-based software, and minimizing syntax errors reduce barriers to working with large datasets.
• Resources such as Data Carpentry and Project EDDIE support teaching with large datasets.

Conclusions:

• Effective large dataset activities foster critical thinking and data literacy skills.
• Accessible tools and pedagogical strategies are crucial for successful implementation of big data in education.
• Professional development and learning resources are available to support educators in teaching with large datasets.