A computational lens on design research

Hoyles, Celia; Noss, Richard

doi:10.1007/s11858-015-0731-2

Cited by 11 publications

(3 citation statements)

References 25 publications

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“…The researchers define "design-based research as a systematic but flexible methodology aimed to improve educational practices through iterative analysis, design, development, and implementation, based on collaboration among researchers and practitioners in the real-world set[ting]" (Wang & Hannafin, 2005, p. 6). The researchers adopted the following features of DBR (Bertrand et al, 2022): (a) co-designing the model features (of selecting tools, designing tasks, and teaching approaches) of maker education workshops for teacher candidates; (b) analysing classroom data in collaboration with teacher candidates (Hoyles & Noss, 2015) participating as Students as Partners (SaPs) (Cook-Sather et al, 2014); and (c) over time, refining of the model in the iteration cycle (diSessa & Cobb, 2004). Coupling the case study method with DBR was necessary to implement and redesign the curriculum.…”

Section: Design-based Research and Case Studymentioning

confidence: 99%

Reimagining the Mathematics Curriculum Through a Cross-Curricular and Maker Education Lens

Namukasa

Bertrand

Tangredi

et al. 2023

International Journal of Teacher Education and Professional Development

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Despite the positive impact of maker education on student learning, challenges towards its implementation in formal school settings still exist. There is limited research on maker education in teacher education programs and a lack of knowledge on how to integrate it into the mathematics classroom. To address these issues, the following research questions were examined: What is the nature of the productive design features of maker education for teacher candidates? What are the benefits and challenges of these opportunities for teacher candidates learning to teach mathematics? The methods used were a case study interlinked with design-based research. A total of 114 teacher candidates participated in the study. The research findings have implications for educators who design/implement maker education curricula into STEM courses. For educators and researchers, the maker education opportunities from this study contribute to further re-imagining learning competencies, pedagogy, and resources in teaching mathematics and other STEM disciplines.

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Section: Design-based Research and Case Studymentioning

confidence: 99%

Reimagining the Mathematics Curriculum Through a Cross-Curricular and Maker Education Lens

Namukasa

Bertrand

Tangredi

et al. 2023

International Journal of Teacher Education and Professional Development

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“…The drawing of this route includes four steps, which are decomposition that involves breaking the problem down into smaller, more manageable parts, pattern recognition, where the similarities and connections between different parts are identified by analyzing the data, abstraction, which involves identifying the information relevant to the problem and eliminating other unnecessary details, and algorithmic thinking, which is a process development phase that includes step by step solution to a problem so that the work can be repeated by humans or computers. The first three steps of computational thinking, namely decomposition, pattern recognition and abstraction, constantly feed the last step, algorithmic thinking (Hoyles & Noss, 2015;Rodríguez-Abitia et al, 2021;Shute et al, 2017). Understanding, testing, developing, or designing an algorithm refers to algorithmic thinking (Denning & Tedre, 2021).…”

Section: Introductionmentioning

confidence: 99%

An Evaluation of the Effect of Activity-Based Computational Thinking Education on Teachers: A Case Study

Saltalı

Özmutlu

ERGAN>

et al. 2023

Participatory Educational Research

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This study aimed to conduct an in-depth evaluation of the activity-based computational thinking teaching practices performed to improve computational thinking and teaching skills of the basic education teachers. Based on the aim of the study, the case study design, one of the qualitative research methods, was selected. As a result of the collaborative work of five experts, a 20-hour education program built on two core competencies, four sub-competencies and eight thinking skills was implemented. The participants were 40 teachers, 20 of whom were classroom teachers and 20 of whom were pre-school teachers. Data were collected from three different sources using five data collection tools in order to conduct an in-depth analysis of the practices. Quantitative and qualitative data collection tools were used in a combined fashion in the research. The data were analyzed through content analysis and non-parametric analyses. Our findings revealed that thanks to the teaching practices performed, classroom teachers had significantly higher problem solving, diverse thinking, algorithmic thinking, and computational thinking total scores, while preschool teachers achieved significantly higher total scores in algorithmic thinking skills and computational thinking. It was observed that the participants defined computational thinking on the basis of 18 different thinking skills. The explanations of the participants about the functions of computational thinking skills were grouped under seven categories. When the principles that should be considered in the teaching of computational thinking skills were examined, it was seen that the need for utilizing scaffolds was stated the most.

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“…CT can also be viewed as thinking algorithmically by using principles from computer science as a guiding structural and sometimes metaphorical framework (Shodiev, 2015). Hoyles and Noss (2015) defined CT as entailing abstraction (seeing a problem at different levels of detail), algorithmic thinking (the propensity to see tasks in terms of smaller connected discrete steps), decomposition (solving a problem by solving a set of smaller problems) and pattern recognition (seeing how a new problem is related to problems previously encountered). Despite its obvious relevance to computer science, CT as a cognitive skill is applicable in every discipline via problem‐solving processes and can also have a positive impact over time on one's analytical ability (Barr & Stephenson, 2011; Yadav et al, 2011), as well as on students' interest in taking future computing courses or pursuing a career requiring computing skills (Hambrusch et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Experimenting with computational thinking for knowledge transfer in engineering robotics

Chichekian,

Trudeau,

Jawhar

et al. 2023

Computer Assisted Learning

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BackgroundDespite its obvious relevance to computer science, computational thinking (CT) is transdisciplinary with the potential of impacting one's analytical ability. Although countless efforts have been invested across K‐12 education, there is a paucity of research at the postsecondary level about the extent to which CT can contribute to sustainable learning outcomes.ObjectivesThe current study examines how a series of Arduino‐based robotics learning activities capture the fuller essence of concepts related to CT.MethodsCollege students (n = 50) completed a series of six robotics learning activities. Think‐alouds, student reflections and performance scores were used to assess students' CT through a robotics challenge in virtual and physical learning environments.Results and ConclusionsStudents verbalized CT concepts related to algorithmic thinking much more than abstraction, problem decomposition and testing and debugging. Students exposed to active learning performed better in a virtual robotics challenge compared to their peers in a traditional‐oriented classroom. Students' scores on the physical robotics challenge increased as a function of the number of references they made to CT concepts during the think‐alouds. It is possible to design pedagogical experiences that tap into various dimensions of CT at incremental levels of complexity through a series of Arduino‐based robotics activities. With the integration of an online simulation, students can visualize and transfer their CT skills between a virtual and physical learning environment, thus leading to more sustainable learning outcomes.

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A computational lens on design research

Cited by 11 publications

References 25 publications

Reimagining the Mathematics Curriculum Through a Cross-Curricular and Maker Education Lens

Reimagining the Mathematics Curriculum Through a Cross-Curricular and Maker Education Lens

An Evaluation of the Effect of Activity-Based Computational Thinking Education on Teachers: A Case Study

Experimenting with computational thinking for knowledge transfer in engineering robotics

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