Skill Development and Knowledge Acquisition Cultivated by Maker Education: Evidence from Arduino-based Educational Robotics

Abstract

This study investigated elementary school students' learning performances and behaviors in a maker education program. An informal after-school learning environment entitled Robot MakerSpace was created at a public elementary school in Taiwan and 30 grade 5 students voluntarily participated in a 16-week educational experiment. The student participants were randomly divided into two experimental groups. Students in the maker group received weekly educational robotics lessons, whereas those in the nonmaker group only engaged in other after-school learning activities such as homework practice in traditional classrooms. Mixed methods research was used for data collection. An experiment with a pretest-posttest and control group design was employed to measure the students' electrical engineering and computer programming content knowledge and problem-solving skills. In addition, a qualitative approach with an emphasis on filed observation was adopted to evaluate the instructional implementation of the maker education program. The quantitative findings revealed that maker education training significantly improved the electrical engineering and computer programming content knowledge of the students and improved their problem-solving skills. The qualitative findings showed the students required considerable learning support from the instructor such as strategies for software and hardware debugging.

Using ScratchJr to Foster Young Children’s Computational Thinking Competence: A Case Study in a Third-Grade Computer Class

“…In Lindh and Holgersson (2009), 1-year CT training through Lego robotics programming improved some elementary school students’ logical-thinking skills. Chou (2018b) reported that one-semester CT training through Arduino-based robotics programming may enhance elementary school students’ overall problem-solving skills. This study focused on students’ cognitive-thinking skills (i.e., CT skills) identified in ScratchJr programming learning rather than knowledge transfer to other subjects.…”

“…In the modify stage, students modify someone’s coding patterns, and then they subsequently develop a new CT project in the create stage. To follow engineering design principles, Chou (2018b) integrated a predesign, in-design, and postdesign model into a robot-programming curriculum. The predesign and in-design stages are similar to the use and modify stages in the model of Lee et al.…”

“…(2016) developed a visual block creative computing test to assess elementary students’ CT competence after the students had received Scratch instruction. In Chou (2018b), an achievement test from a national programming competition was used to measure elementary school students’ understanding of Scratch programming. Strawhacker et al.…”

Observations on the Effects of Skill Transfer through Experience Sharing and In-Person Communication

“…Makerspaces are meant as a physical location where these elements are combined, and prototyping is subsequently facilitated. This view is shared by industrial (Jensen et al, 2016) and educational stakeholders (Chou, 2018;Forest et al, 2014), as their investments in establishing a "makerspace" within their entities show. While hardware, such as machines, tools, and materials, are easy to acquire, skills are linked to people and their experiences and are therefore hard to transfer, retain, and share in a structured way.…”

Computational thinking development through physical computing activities in STEAM education

“…Chou [6] presents the results of the study of the learning achievements and behavior of primary school pupils under the maker curriculum. Robot MakerSpace ‐ Arduino‐based educational robotics products in maker education programs were created at a public elementary school in Taiwan as an informal after‐school learning activity.…”