Algorithmic Explanations: an Unplugged Instructional Approach to Integrate Science and Computational Thinking.

Area of Science:

• STEM Education
• Computational Literacy
• K-12 Science Education

Background:

• Computational literacy is crucial for scientists and engineers, yet K-12 science education lags in incorporating computational thinking (CT).
• Teachers often lack the necessary experience and confidence to integrate CT into science courses, hindering widespread implementation.
• Existing approaches for integrating CT and science face limitations in accessibility and practical application within K-12 settings.

Purpose of the Study:

• To introduce a novel instructional approach, Computational Thinking through Algorithmic Explanations (CT-AE), for integrating CT into K-12 science education.
• To provide an accessible pedagogical strategy grounded in established CT frameworks, utilizing unplugged activities.
• To address the barriers hindering CT integration by offering a teacher-friendly and effective method.

Main Methods:

• Critique of current CT and science integration approaches.
• Introduction and detailed explanation of the CT-AE instructional model.
• Examination of CT-AE's theoretical underpinnings in constructionist writing-to-learn science theory.
• Discussion of pilot implementation findings and student learning outcomes.

Main Results:

• The CT-AE approach offers a viable, computer-free method for integrating computational thinking into science curricula.
• Pilot implementation suggests positive student learning outcomes, indicating the approach's potential effectiveness.
• The CT-AE model provides a practical framework for educators to build computational literacies in students.

Conclusions:

• The CT-AE instructional approach presents a promising solution to integrate computational thinking into K-12 science education effectively.
• Unplugged activities, as utilized in CT-AE, can bridge the gap in teacher preparedness and build student computational literacy.
• Further research and implementation of CT-AE can significantly enhance science education by incorporating essential computational skills.