Connecting computational thinking in everyday reasoning and programming for elementary school students

Abstract

Computational thinking (CT) has been advocated as an essential problem solving skill students need to develop. Emphasizing on CT applied in both programming and everyday contexts, we developed a humanoid robotics curriculum and a computerized assessment instrument. We implemented the curriculum with six classes of 125 fifth graders. Quantitative methods were used to compare students’ performance from pretest to posttest. Learning analytics techniques were applied to examine students’ problem solving processes. The results showed that students’ CT performance improved in both programming and everyday reasoning contexts and that the curriculum benefited students with varied initial performance. The study shed light on how to connect and assess CT in everyday reasoning and programming contexts.

Keywords:

• Computational thinking
• robotics
• programming
• everyday reasoning
• problem-solving patterns

Disclosure statement

The authors declare that they have no conflict of interest.

Additional information

Funding

This study was funded by U.S. National Science Foundation (grant number DRL1523010). Any opinions, findings, and conclusions expressed in this poster are those of the authors and do not necessarily reflect the views of the NSF.

Notes on contributors

Ji Shen

Ji Shen is an associate professor of STEM Education at the University of Miami. Dr. Shen's scholarly work focuses on developing and researching innovative, technology-enhanced learning environments, interdisciplinary and integrated STEM learning and assessment, and modeling-based instruction.

Guanhua Chen

Guanhua Chen obtained his PhD from University of Miami. His research focuses on analyzing students' learning processes using big data and new algorithms.

Lauren Barth-Cohen

Lauren Barth-Cohen is an assistant professor of Educational Psychology at the University of Utah. With a research focus on student learning in science, she works to translate that research in ways that can be useful to K-12 teachers.

Shiyan Jiang

Shiyan Jiang is an assistant professor of Learning, Design and Technology at North Carolina State University. Dr. Jiang's research focuses on integrating digital literacy in STEM learning.

Moataz Eltoukhy

Moataz Eltoukhy is an associate professor of Kinesiology and Sport Sciences at the University of Miami. Dr. Eltoukhy's scholarly work focuses on the development of home-based, cost-effective movement analysis tools for patients, and the development of innovative use of humanoid robots in the classroom environment.