Computational thinking in computer science teacher training courses in Brazil: A survey and a research roadmap

Abstract

The adoption of computational thinking in the classroom has been growing in the last years. Its use needs to be supported by the correct digital technologies and teaching methods, and for this, is required, capable teachers. This work aims to understand how computational thinking is addressed by Computer Science Teacher Education courses in Brazil, and which digital technologies and teaching methods are used to foster it. A survey was conducted, and a roadmap was built. Main obtained results are: Common and accessible technologies, used in everyday life, can help promote computational thinking; Researchers and teachers can explore the list of technologies surveyed and categorized to promote computational thinking; Teachers can analyze the teaching methods used and understand how these methods are applied in the teaching process; The teachers and researchers can use and explore the best technologies identified in the paper, to foster each computational thinking characteristic. Moreover, it is essential to enhance the knowledge about computational thinking, to apply the correct digital technologies and teaching methods in its promotion.

Computational thinking in mathematics education: A systematic review

“…The robotic activities constitute the second largest percentage (41%) in developing CT in education. There were only 2 studies conducted in ASEAN countries (Sun et al, 2021a(Sun et al, , 2021bYi Wu & Yu Sheng, 2021) and 12 researches conducted in non-ASEAN countries (Critten et al, 2021;Fanchamps et al, 2019;Garcia Angarita et al, 2017;Ioannou & Makridou, 2018;Jaipal-Jamani & Angeli, 2017;Menolli & Neto, 2021;Merino-Armero et al, 2021;Ozmutlu et al, 2021;Piedade et al, 2020;Relkin et al, 2021;Silva et al, 2021;Stewart et al, 2021). This comprehensive research reveals how non-ASEAN countries employed robotic operations to produce CT skills better effectively.…”

“…There were four studies performed in ASEAN countries (Cheng et al, 2017;Fang et al, 2017;Matere et al, 2021;Shorey et al, 2021) and 12 studies conducted in non-ASEAN countries (Çoban & Korkmaz, 2021;Critten et al, 2021;Jeng et al, 2020;Marcelino et al, 2018;Mecca et al, 2021;Menolli & Neto, 2021;Mouza et al, 2017;Quitério Figueiredo, 2017;Relkin et al, 2021;Rich et al, 2021;Sung & Black, 2020;Tucker-Raymond et al, 2021). This systematic review explains various types of teaching methods used in developing CT in mathematics, such as instant communication (IM) teaching method (Cheng et al, 2017), innovative curriculum design relying on an Internet-of-Things (IoT) programming course (Jeng et al, 2020), project-based learning and problem-solving learning method (Menolli & Neto, 2021), BootUp's model teaching method (Rich et al, 2021), technological pedagogical content knowledge (TPACK) educational technology course (Mouza et al, 2017), pre-programming (CS0) course (Quitério Figueiredo, 2017), elearning course employing Moodle as a learning management system (Marcelino et al, 2018), designbased learning (Matere et al, 2021), blending learning flipped class (Fang et al, 2017), physical body movement practice (Sung & Black, 2020), coding as another language (CAL) curriculum (Relkin et al, 2021), guided play activities (Critten et al, 2021), online performance-based assessment (Çoban & Korkmaz, 2021) and procedural programming course (Mecca et al, 2021). This includes delegating responsibility to students, encouraging independent problem-solving among students, co-learning with students, fostering interdependence among students, offering a variety of additional resources…”

“…Moreover, Jeng et al (2020) assessed the influence of enhancing students' motivation and CT ability in learning mathematics using an innovative curriculum design relying on the IoT programming course. Meanwhile, in Brazil, Menolli and Neto (2021) found a link between CT skills and project-based learning and problem-solving learning. Furthermore, Rich et al ( 2021) used BootUp's professional model to assess and improve the degree of CT among mathematic teachers.…”

“…Relying on the literature review, researchers discovered that six types of tools were used in developing CT in mathematics education. The tools are teaching method (Cheng et al, 2017;Çoban & Korkmaz, 2021;Critten et al, 2021;Fang et al, 2017;Jeng et al, 2020;Marcelino et al, 2018;Matere et al, 2021;Menolli & Neto, 2021;Mouza et al, 2017;Quitério Figueiredo, 2017;Relkin et al, 2021;Rich et al, 2021;Sung & Black, 2020;Tucker-Raymond et al, 2021;Yildiz Durak, 2020), game-based learning (Agbo et al, 2021;Croff, 2017;Hooshyar et al, 2021;Menolli & Neto, 2021;Ng & Cui, 2021), coding programming (Critten et al, 2021;Deng et al, 2020;Fanchamps et al, 2019;Marcelino et al, 2018;Mecca et al, 2021;Ng & Cui, 2021;Özmutlu et al, 2021;Piedade et al, 2020;Quitério Figueiredo, 2017;Relkin et al, 2021;Rich et al, 2021;Ríos Félix et al, 2020;Shorey et al, 2021;Silva et al, 2021;Sun et al, 2021a;Sung & Black, 2020;Yi Wu & Sheng Su, 2021;Yildiz Durak, 2020), robotic activities (Critten et al, 2021;…”

“…This comprehensive research reveals how non-ASEAN countries employed robotic operations to produce CT skills better effectively. Meanwhile, CT skills in collaborative robotics activities (Stewart et al, 2021), robotics activities in education (Ioannou & Makridou, 2018;Menolli & Neto, 2021;Silva et al, 2021), LEGO® WeDo robotics kits (Fanchamps et al, 2019;Jaipal-Jamani & Angeli, 2017), intensive coding course (Critten et al, 2021;Ozmutlu et al, 2021;Piedade et al, 2020), robotics club and course (Garcia Angarita et al, 2017;Yi Wu & Yu Sheng, 2021), BCTt and TechCheck (Relkin et al, 2021) and school extracurricular robotics activities (Merino-Armero et al, 2021) were used as effective tools in enhancing CT abilities. Unplugged programming exercises (Sun et al, 2021a(Sun et al, , 2021b and physical robot courses (Yi Wu & Yu Sheng, 2021) have also been shown to assist and improve CT skills in two ASEAN countries.…”