Robotics and Programming Integration as Cognitive-Learning Tools

Robotics and Programming Integration as Cognitive-Learning Tools

Nikleia Eteokleous (Frederick University Cyprus, Cyprus)
DOI: 10.4018/978-1-5225-7368-5.ch079

Abstract

Robotics and programming integration as cognitive-learning tools in selected teaching cases exploits its full potential; therefore, it upgrades and enhances the teaching and learning process and promotes school transformation. Employing a case study approach, the current study examines how robotics and computer programming can be integrated within the elementary teaching practice (2nd to 6th grade) in order to achieve learning objectives across disciplines beyond STEM (8 teachers and 169 students participated at the study). Results are discussed taking into account class size, robotics package used, teacher age, gender, experience, and teacher digital literacy/comfort level with technology. The innovative educational robotics curriculum developed by the Robotics Academy provides the theoretical and educational framework to achieve the above.
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Introduction

The technological improvements within the robotics field and its expansion to various fields such as medicine, industry and education, calls for robotics integration within the educational practice as learning tools. Alimisis (2012) supports that robotics draw the attention and interest of academicians, researchers and teachers in all educational levels as well as other stakeholders (policy makers and society leaders). Educational systems are responsible in preparing students (future citizens) for this ever-changing Hi-Tech, globalized, interconnected world. Numerous 21st century skills are reported in the literature as important to be developed by future citizens as the means to address the needs and demands of the society. Digital literacy is one of them and robotics and programing are becoming important elements within the educational settings. The students need to be provided with the opportunities to experience tinkering, fabrication, design and create technological artifact & interactive objects, construct their own meaningful projects, experience the scientific method of inquiry (Bers, 2008a; Bers, 2008b; Bers, Matas & Libman, 2013; Bernstein, Mutch-Jones, Cassidy, Hamner, & Cross, 2016; Eteokleous, 2016). Consequently, educators need to design learning environments enhanced by new technologies where students have the opportunity to experience them as cognitive-learning tools within their learning processes. In order for robotics to be integrated within the educational practice, teachers need to be appropriately and adequately prepared by universities (for pre-service teachers at the undergraduate level and in-service teaches at the graduate level) and professional development authorities (for in-service teachers) (Vollsted, Robinson, & Wang, 2007).

The current chapter takes into consideration numerous research studies suggesting that robotics integration for educational purposes is an effective teaching method; arguing that if robotics activities are appropriately designed and implemented have great potential to significantly improve and enhance the teaching and learning process (Bauerle, & Gallagher, 2003; Benitti, 2012; Bers, Flannery, Kazakoff, & Sullivan, 2014; Eteokleous, Demetriou, & Stylianou, 2013; Papert, 1993). Robotics in the classroom has taken a global momentum especially because of its positive contributions in the teaching of science, technology, engineering and mathematics (STEM) (Benitti, 2012; Bers, et al, 2014; Nugent, et al., 2009; Sullivan, 2008; Williams, Ma, Prejean, Lai, & Ford, 2007). Additionally, research has shown that robotics integration in education promotes the development of various non-cognitive skills, however extremely important life skills. For example, reasoning, problem solving, tinkerning, sequencing, computational thinking, decision making, scientific investigation, collaboration, knowledge construction, critical thinking, creativity, communication (Bers et al., 2002; Benitti, 2012; Bers, 2008a; Bers, et al., 2014; Chambers & Carbonaro, 2003; Eteokleous, 2015; Eteokleous, 2016; Miglino, Lund, & Cardaci, 1999; Resnick, Berg, & Eisenberg, 2000; Sullivan, 2008; Williams, et al., 2007; Williams, Ma, & Prejean, 2010).

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