Computational thinking and tinkering: Exploration of an early childhood robotics curriculum

Bers, Marina Umaschi; Flannery, Louise; Kazakoff, Elizabeth R.; Sullivan, Amanda

doi:10.1016/j.compedu.2013.10.020

Cited by 721 publications

(506 citation statements)

References 14 publications

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“…The educational phenomenon in the current study had two possible causes. First, in the in-design stage, designing flowcharts encouraged the students to use logical reasoning and computational thinking (Bers et al, 2014), such as applying if-then coding statements to facilitate their engineering designs. The second cause was robotics testing technique.…”

Section: Discussionmentioning

confidence: 99%

“…The consultation stage is similar to the final states of the processes described by StoneMacDonald et al (2015) and Bers et al (2014). Fernandez-Samsca, Barrera, Mesa, and Perez-Holguin (2017) proposed the following four-step engineering design process to emphasize robotics education for preschool students: (a) sensitization, (b) design, (c) construction, and (d) evaluation.…”

Section: Instructional Framework Of Maker Educationmentioning

confidence: 97%

“…To investigate children's computational thinking, Bers, Flannery, Kazakoff, and Sullivan (2014) simplified these eight steps by applying the following simple verbs: ask, imagine, plan, create, test, improve, and share. Stone-MacDonald, Wendell, Douglass, and Love (2015) adopted a similar engineering design process to that of Bers et al (2014) for incorporation into the following four-step process: (a) think about it, (b) try it, (c) fix it, and (d) share it.…”

Section: Instructional Framework Of Maker Educationmentioning

confidence: 99%

See 2 more Smart Citations

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

Chou

2018

EURASIA J MATH SCI T

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Instructional Framework Of Maker Educationmentioning

confidence: 97%

Section: Instructional Framework Of Maker Educationmentioning

confidence: 99%

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

Chou

2018

EURASIA J MATH SCI T

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“…The studies paid attention to the extent to which young children-including preschool and kindergarten children-were able to learn [31,[49][50][51][52][53][54][55][56]. Bers and her colleagues are key scholars in this area.…”

Section: Effects Of Robotics Education On Young Children's Learningmentioning

confidence: 99%

Systematic Review of Research Trends in Robotics Education for Young Children

2018

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This study conducted a systematic and thematic review on existing literature in robotics education using robotics kits (not social robots) for young children (Pre-K and kindergarten through 5th grade). This study investigated: (1) the definition of robotics education; (2) thematic patterns of key findings; and (3) theoretical and methodological traits. The results of the review present a limitation of previous research in that it has focused on robotics education only as an instrumental means to support other subjects or STEM education. This study identifies that the findings of the existing research are weighted toward outcome-focused research. Lastly, this study addresses the fact that most of the existing studies used constructivist and constructionist frameworks not only to design and implement robotics curricula but also to analyze young children's engagement in robotics education. Relying on the findings of the review, this study suggests clarifying and specifying robotics-intensified knowledge, skills, and attitudes in defining robotics education in connection to computer science education. In addition, this study concludes that research agendas need to be diversified and the diversity of research participants needs to be broadened. To do this, this study suggests employing social and cultural theoretical frameworks and critical analytical lenses by considering children's historical, cultural, social, and institutional contexts in understanding young children's engagement in robotics education.

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“…making activities include playing or making things and taking them apart to solve problems inspired by technology; they encourage students to cohesively combine multiple ideas into an organized process to produce something unexpected [12]. Prototyping and testing physical artifacts -also referred to as Tangible Programming (TP) -directly impacts a digital environment [13], thus tangibly representing CT; 3. tinkering [14] supports learning of CT concepts by exploring them in a creative way, allowing students to use materials and tools to represent CT. In agreement with Papert's constructionism model of learning [7], tinkering provides a rich context for developing and representing understanding through the experience and process of building something physical or digital; 4. remixing (or "hacking") involves critically looking at existing code, as well as practicing modifying it to suit new purposes; analyzing code, making connections and creating new applications from existing code require sophisticated reasoning and problem solving skills [3], all being essential elements for the development of CT. Lastly, it is worth pointing out that the effectiveness of existing tools seems pretty unsettled with respect to the many facets of CT: for instance, a 2008 study [15] involving 80 urban youth aged 8-18 reported learning of several CT elements through the use of Scratch in an after-school setting; nonetheless, the tool does not provide a mean of encapsulating functionalities into procedures and functions, somehow failing to tap into the abstraction skills.…”

Section: Eai Endorsed Transactions On Ambient Systemsmentioning

confidence: 99%

A Human-Centred Tangible approach to learning Computational Thinking

Turchi¹,

Malizia²

2016

ICST Transactions on Ambient Systems

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Computational Thinking has recently become a focus of many teaching and research domains; it encapsulates those thinking skills integral to solving complex problems using a computer, thus being widely applicable in our society. It is influencing research across many disciplines and also coming into the limelight of education, mostly thanks to public initiatives such as the Hour of Code. In this paper we present our arguments for promoting Computational Thinking in education through the Human-centred paradigm of Tangible End-User Development, namely by exploiting objects whose interactions with the physical environment are mapped to digital actions performed on the system.

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Computational thinking and tinkering: Exploration of an early childhood robotics curriculum

Cited by 721 publications

References 14 publications

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

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

Systematic Review of Research Trends in Robotics Education for Young Children

A Human-Centred Tangible approach to learning Computational Thinking

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