Journal articles: 'Computational thinkink'

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Aho, A. V. "Computation and Computational Thinking." Computer Journal 55, no. 7 (June 29, 2012): 832–35. http://dx.doi.org/10.1093/comjnl/bxs074.

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LESSNER, Daniel. "ANALYSIS OF TERM MEANING "COMPUTATIONAL THINKING"." Journal of Technology and Information 6, no. 1 (April 1, 2014): 71–88. http://dx.doi.org/10.5507/jtie.2014.006.

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Ortega-Ruipérez, Beatriz. "Pedagogía del Pensamiento Computacional desde la Psicología: un Pensamiento para Resolver Problemas." Cuestiones Pedagógicas 2, no. 29 (2020): 130–44. http://dx.doi.org/10.12795/cp.2020.i29.v2.10.

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Computational thinking should be understood as problem-solving thinking, beyond its link to programming. Therefore, it is necessary to address this thought’s structure through its cognitive processes to obtain an operational definition that allows this thought’s pedagogy to be adequately addressed in the classroom, regardless its development source. In this article, five processes inherent to this thought are determined, identifying only those that are always used. These processes are operatively defined from a psychological and a pedagogical perspective. The processes are abstraction, generalization, evaluation, creation of algorithms and decomposition of the problem. The first four processes present an inherent relation to problem-solving that can be verified, while, the last one, decomposition, can be considered not fundamental in problem solving and, therefore, linked to computational thinking. The performed analysis and categorization prove that decomposition is the key and central process of computational thinking. Therefore, computational thinking teaching must always be approached from the decomposition of problems or tasks that allow the simplification of the rest of the processes involved. This should involve different resources such as programming, playing games, problem-solving, or the creation of projects.

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Moon, Gyo Sik. "On the Direction of the Application of the Concepts of Computational Thinking for Elementary Education." Journal of the Korea Contents Association 13, no. 6 (June 28, 2013): 518–26. http://dx.doi.org/10.5392/jkca.2013.13.06.518.

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ARSLAN NAMLI, Nihan, and Birsel AYBEK. "Bilgi İşlemsel Düşünme Becerisi Üzerine Bir İçerik Analizi." Cukurova University Faculty of Education Journal 51, no. 2 (August 31, 2022): 920–44. http://dx.doi.org/10.14812/cuefd.943909.

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Üniversitelerin temel işlevlerinden birisi araştırmalar yaparak yeni teknolojiler üretmektir. Bu bağlamda bu işlevleri gerçekleştirmek için lisansüstü eğitim ve öğretim sürecinde yapılan araştırmalar yol gösterici olmaktadır. Ülkemizde bilgi işlemsel düşünme kavramı ile yürütülen lisansüstü tezlere yönelik bir meta sentez çalışmasının olmadığı belirlendiğinden ve lisansüstü boyutta Türkiye’de, belirlenen ölçütlerde 2018 yılından beri bilgi işlemsel düşünme alanında tezlerin yükselişi gözlemlendiğinden, bu tezlerin detaylı bir biçimde incelenmesinin ve önerilerin sunulmasının eğitim ve bilişim teknolojileri alanına önemli katkılar sağlayacağı düşünülmektedir. Bu çalışmada, lisansüstü tezlerin incelenmesi, yapılan çalışmaların yapıldığı yıl, üniversite, yöntem, örneklem, veri toplama araçları, analiz teknikleri ve araştırma sonuçlarının belirlenmesi amaçlanmıştır. Araştırma nitel araştırma yöntemlerinden doküman inceleme yöntemi ele alınarak gercekleştirilmiştir. Yapılan araştırma doğrultusunda Yükseköğretim Kurulu (YÖK) ulusal tez merkezi veri tabanı incelenmiş “Bilgi işlemsel düşünme” tez adı ve özet filtresi ile belirlenmiş 47 tez incelenmiştir. Her bir tez, geliştirilen “Tez Sınıflama Formu” ile tümdengelimsel analize tabi tutulmuştur. Bu araştırmada yer alan lisansüstü tezlerin sonuçları ve çeşitli boyutlarda etkileri incelenerek sentezlenmiştir.

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Lim, Byeongchoon. "App Inventor 2 As a Tool for Enhancement of Computational Thinking." Journal of The Korean Association of Information Education 20, no. 5 (December 31, 2016): 519–26. http://dx.doi.org/10.14352/jkaie.20.4.519.

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Kartarina, Kartarina, Miftahul Madani, Diah Supatmiwati, Regina Aprilia Riberu, and Indah Puji Lestari. "Sosialisasi dan Pengenalan Computational Thinking kepada Guru pada Program Gerakan Pandai oleh Bebras Biro Universitas Bumigora." ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat 2, no. 1 (July 26, 2021): 27–34. http://dx.doi.org/10.30812/adma.v2i1.1271.

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Currently school teachers, especially in Mataram City, West Lombok Regency, Central Lombok and East Lombok are not familiar with learning with the concept of computational thinking (Computational Thinking) so they cannot teach their students how to think computationally as an approach to solving existing problems. Considering one of the demands of the industrial revolution 4.0, where problem solving skills are one of the abilities that students must have. In this case, these abilities need to be taught by teachers at school. Therefore, this problem must be solved immediately by increasing the ability of teachers in learning computational thinking so that teachers can apply computational thinking learning methods to their students. From the problems listed, it is necessary to approach how to train teachers to teach computationally thinking to their students. In Lombok, West Nusa Tenggara, to apply Computational Thinking (CT) in formulating problems and revealing solutions, namely through socialization and training and mentoring of free computational thinking materials to teachers in schools in Lombok, NTB which was held in the form of CT Bebras socialization activities, which is expected to help introduce and apply Computational Thinking (CT) material as a creative learning method in schools in NTB.

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Park, Jungho. "Effects of Storytelling Based Software Education on Computational Thinking." Journal of The Korean Association of Information Education 19, no. 1 (March 30, 2015): 57–68. http://dx.doi.org/10.14352/jkaie.2015.19.1.57.

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Jeon, Soojin, and Seonkwan Han. "Descriptive Assessment Tool for Computational Thinking Competencies." Journal of The Korean Association of Information Education 20, no. 3 (June 30, 2016): 255–62. http://dx.doi.org/10.14352/jkaie.20.3.255.

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Shin, Seungki. "Designing the Instructional Framework and Cognitive Learning Environment for Artificial Intelligence Education through Computational Thinking." Journal of The Korean Association of Information Education 23, no. 6 (December 31, 2019): 639–53. http://dx.doi.org/10.14352/jkaie.2019.23.6.639.

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Lu, James J., and George H. L. Fletcher. "Thinking about computational thinking." ACM SIGCSE Bulletin 41, no. 1 (March 4, 2009): 260–64. http://dx.doi.org/10.1145/1539024.1508959.

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Bull, Glen, Joe Garofalo, and N. Rich Hguyen. "Thinking about computational thinking." Journal of Digital Learning in Teacher Education 36, no. 1 (January 2, 2020): 6–18. http://dx.doi.org/10.1080/21532974.2019.1694381.

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Wing, Jeannette M. "Computational thinking." Communications of the ACM 49, no. 3 (March 2006): 33–35. http://dx.doi.org/10.1145/1118178.1118215.

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Henderson, Peter B., Thomas J. Cortina, and Jeannette M. Wing. "Computational thinking." ACM SIGCSE Bulletin 39, no. 1 (March 7, 2007): 195–96. http://dx.doi.org/10.1145/1227504.1227378.

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Khenner, Evgeniy K. "COMPUTATIONAL THINKING." Education and science journal, no. 2 (March 2, 2016): 18–33. http://dx.doi.org/10.17853/1994-5639-2016-2-18-33.

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José Raimundo, Anderson, and Claudinea Angélica dos Santos. "COMPUTATIONAL THINKING." Journal of Interdisciplinary Debates 4, no. 01 (March 31, 2023): 47–69. http://dx.doi.org/10.51249/jid.v4i01.1253.

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Technology is present in the world so that its use becomes intuitive. The purpose of the study originated from the perception of people, especially young people who use technology practically all the time, but many of them do not use it to develop. In this case, the need to implement computing teaching in schools increases. The introduction of computing concepts from the early years of basic education gains a lot of importance. Computational thinking instructs people how to think about solving problems through concepts in the field of informatics. The unplugged activity presents great computing concepts, even without the need to use electronic devices, being an effective alternative in teaching. The method used is based on bibliographical reading on the subject and use of resources such as data show, cardboard, markers, cardboard, paper, glue, bond sheets and notebook. The general objective is to present the computer language and its importance by experiencing it in practice through the suggested games. As specific objectives, instigate students to learn by playing, increase interest in subjects such as mathematics, physical education, science, art and the Portuguese language, practice the programming language in known games in an interactive and unplugged way. As expected results are to contribute to computational thinking to become present and worked in schools in order to reframe the school teaching and learning process.

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Kafai, Yasmin B., and Chris Proctor. "A Revaluation of Computational Thinking in K–12 Education: Moving Toward Computational Literacies." Educational Researcher 51, no. 2 (November 5, 2021): 146–51. http://dx.doi.org/10.3102/0013189x211057904.

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Over the past decade, initiatives around the world have introduced computing into K–12 education under the umbrella of computational thinking. While initial implementations focused on skills and knowledge for college and career readiness, more recent framings include situated computational thinking (identity, participation, creative expression) and critical computational thinking (political and ethical impacts of computing, justice). This expansion reflects a revaluation of what it means for learners to be computationally-literate in the 21st century. We review the current landscape of K–12 computing education, discuss interactions between different framings of computational thinking, and consider how an encompassing framework of computational literacies clarifies the importance of computing for broader K–12 educational priorities as well as key unresolved issues.

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Kim, Hyeonsoo, and Seonkwan Han. "A Development Discrimination Test for Information Gifted Students using the Concepts of Computational Thinking." Journal of The Korean Association of Information Education 19, no. 3 (September 30, 2015): 271–78. http://dx.doi.org/10.14352/jkaie.2015.19.3.271.

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Park, Kyung-Eun, and Sang-Gu Lee. "Improving Computational Thinking Abilities Through the Teaching of Mathematics with Sage." Communications of Mathematical Education 29, no. 1 (February 15, 2015): 19–33. http://dx.doi.org/10.7468/jksmee.2015.29.1.19.

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Kim, Soohwan. "Effects of Teaching and Learning Strategies of Learner-Centered Learning for Improving Computational Thinking." Journal of The Korean Association of Information Education 19, no. 3 (September 30, 2015): 323–32. http://dx.doi.org/10.14352/jkaie.2015.19.3.323.

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Son, Young-Su, and Kwang-Jae Lee. "Computational Thinking Teaching Model Design for Activating IT Convergence Education." Journal of the Korea institute of electronic communication sciences 11, no. 5 (May 31, 2016): 511–22. http://dx.doi.org/10.13067/jkiecs.2016.11.5.511.

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Mendrofa, Netti Kariani. "Computational Thinking Skills in 21st Century Mathematics Learning." JIIP - Jurnal Ilmiah Ilmu Pendidikan 7, no. 1 (January 7, 2024): 792–801. http://dx.doi.org/10.54371/jiip.v7i1.3780.

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Computational thinking skills are a crucial mental skill in the 21st century, enabling individuals to solve problems, understand data, and make decisions with a structured and computational-based approach. Integrating computational thinking skills in mathematics learning has an important role in preparing students to become skilled in thinking computationally in the 21st century. The method used in this research is library research in which relevant data are collected from sources such as books, dictionaries, journals, magazines, and others without the need to conduct direct investigations in the field. Applying computational thinking in mathematics learning will foster skills such as decomposition (breaking down a problem into manageable parts), pattern recognition, abstraction, and algorithm design as well as developing analytical and abstract thinking skills.

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Khenner, E. K. "Computational thinking in the context of higher education: Analytical review." Education and science journal 26, no. 2 (February 13, 2024): 35–59. http://dx.doi.org/10.17853/1994-5639-2024-2-35-59.

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Introduction. Computational thinking is one of the categories that currently assess the quality of people’s preparedness for life, educational and professional activities in the modern world, saturated with information technologies and digital tools. Many issues related to university students’ computational thinking remain insufficiently studied as applied to general education.Aim. The present research aims to discuss the essence of the concept of “computational thinking” and, mainly, the composition of its structural elements, methods of their formation and assessment at the level of higher education; and to compare the requirements for university students’ computational thinking and digital competencies, which have similarities and differences.Methodology and research methods. The present review article has theoretical and applied aspects. Except for several fundamentally important works of general studies, which reveal the concept of “computational thinking”, the author analysed mainly review articles published in the past five years in order to identify and systematise modern solutions related to the purpose of the work.Results and scientific novelty. An analysis of the basic concepts associated with computational thinking showed that at the level of definitions, due to their certain abstractness, the computational thinking of university students does not have much specificity compared to the computational thinking of schoolchildren. This specificity is manifested at the level of the list of cognitive and non-cognitive skills associated with computational thinking, requirements for the level of their development and assessment methods. In computational thinking, cognitive skills include abstraction, decomposition, pattern recognition, algorithmisation, visualisation, logical thinking, communicative competence, the ability to present, structure and analyse data, and some others skills. Non-cognitive skills include self-confidence, communication skills, flexibility, and others.Methods for assessing the maturity of students’ computational thinking include the results of solving problems in block programming environments such as Scrath; knowledge/skill tests, self-assessment scales/surveys; tests on knowledge of the basics of computational thinking, interviews and observations; interviews, grades for assignments/courses, surveys/questionnaires, solving problems external to the class; the use of a special software environment, the use of criteria for assessing computational thinking and/or psychometric tools; assessments based on solving robotic problems or evaluating artifacts created during the game, and others.A comparison of computational thinking with digital competencies at the skill level leads to the conclusion that in computational thinking, skills represent a certain fixed set of meta-skills needed by a student regardless of solving specific problems (for example, abstraction skills). In digital competencies, skills are specified according to numerous types and are more specific.Practical significance. The results of this study can be used in the design of programmes for developing computational thinking and digital competencies of university students.

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Ejsing-Duun, Stine, Morten Misfeldt, and Daniel Gorm Andersen. "Computational thinking karakteriseret som et sæt af kompetencer." Learning Tech, no. 10 (December 16, 2021): 405–29. http://dx.doi.org/10.7146/lt.v6i10.125258.

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Når Teknologiforståelse rammer klasseværelset, står lærere og elever overfor et nyt fag, de endnu ikke er bekendte med. Faget er deﬁneret igennem læreplan og fælles mål blandt andet gennem kompetenceområdet computationel tankeg 1ang . I denne artikel sætter vi fokus på, hvilke kompetencer der knytter sig til computational thinking ved at undersøge, hvordan de er beskrevet og deﬁneret i tidligere forskning. Formålet er igennem denne begrebskortlægning at skabe et mere nuanceret sprog for indholdet af kompetenceområdet. Artiklen bygger på en litteraturgennemgang af international forskningslitteratur, der omtaler ”computational thinking” og kompetencer fra 2013, hvor en større litteraturgennemgang blev fortaget, og frem til 2018, hvor forsøget om Teknologiforståelse blev udrullet i Danmark, samtidigt med at en lang række andre lande påbegyndte egentlig implementering af programmering og computational thinking i grundskolen.

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Bombasar, James Roberto, André Raabe, and Rafael De Santiago. "Ferramentas para o Ensino-Aprendizagem do Pensamento Computacional: onde está Alan Turing?" International Journal on Computational Thinking (IJCThink) 1, no. 1 (October 9, 2017): 3. http://dx.doi.org/10.14210/ijcthink.v1.n1.p3.

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INTRODUCTION: Since 2006, when Jeannette Wing popularized the term "Computational Thinking" as an essential skill for people in the twenty-first century, there is great interest from the scientific community and governments of various countries in the Computational Thinking exploration in K-12. Although Wing describes Computational Thinking as a process of problem solving that is based on the limits of computing, and more fundamentally addresses the question "What is computable?", little attention has been given to this question in practice. OBJECTIVES: The primary objective of this study was to present a theoretical reflection about the importance of the notion of computability for Computational Thinking, and present a game project for its introduction in K-12. METHODS: Through the bibliographical research method, a study was carried out on the Computational Thinking, Theory of Computation and technologies used in the exploration of Computational Thinking. RESULTS: Based on the studies carried out, the design of a logic game inspired by computational models was elaborated. CONCLUSION: The game proposed in this article may represent a new strategy for the Computational Thinking exploration in K-12, because in addition to bringing notions of computability to the fore, it leads to a thinking way based in states changes, which represents an adequate model of the brain conscious functioning.

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Kool, Wouter, Samuel J. Gershman, and Fiery A. Cushman. "Planning Complexity Registers as a Cost in Metacontrol." Journal of Cognitive Neuroscience 30, no. 10 (October 2018): 1391–404. http://dx.doi.org/10.1162/jocn_a_01263.

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Decision-making algorithms face a basic tradeoff between accuracy and effort (i.e., computational demands). It is widely agreed that humans can choose between multiple decision-making processes that embody different solutions to this tradeoff: Some are computationally cheap but inaccurate, whereas others are computationally expensive but accurate. Recent progress in understanding this tradeoff has been catalyzed by formalizing it in terms of model-free (i.e., habitual) versus model-based (i.e., planning) approaches to reinforcement learning. Intuitively, if two tasks offer the same rewards for accuracy but one of them is much more demanding, we might expect people to rely on habit more in the difficult task: Devoting significant computation to achieve slight marginal accuracy gains would not be “worth it.” We test and verify this prediction in a sequential reinforcement learning task. Because our paradigm is amenable to formal analysis, it contributes to the development of a computational model of how people balance the costs and benefits of different decision-making processes in a task-specific manner; in other words, how we decide when hard thinking is worth it.

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Santeri, Nelly Rima, Arif Sholahuddin, and Andi Ichsan Mahardika. "E–MODUL IPA BERBASIS COMPUTATIONAL THINKING UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR LOGIS PESERTA DIDIK." Journal of Banua Science Education 4, no. 1 (March 2, 2024): 53–63. http://dx.doi.org/10.20527/jbse.v4i1.256.

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Penelitian ini bertujuan untuk meghasilkan e-modul IPA berbasis computational thinking yang layak digunakan untuk meningkatkan kemampuan berpikir logis peserta didik. Penelitian pengembangan ini menggunakan model ADDIE, meliputi Analyze, Design, Develop, Implementation, dan Evaluation. Pengumpulan data menggunakan instrumen validasi e-modul, angket respon guru dan peserta didik, dan tes kemampuan berpikir logis. Hasil penelitian menunjukkan bahwa nilai validitas e-modul IPA berbasis computational thinking adalah 0,78 termasuk kategori validitas tinggi. Hasil kepraktisan dari angket respon guru 90,93% dan respon peserta didik 85,68% dengan ketegori sangat praktis, hasil keefektifan kemampuan berpikir logis peserta didik pada uji coba terbatas dan uji coba lapangan meningkat, nilai N-gain pada uji coba terbatas dan uji coba lapangan masing-masing 0,73 dan 0,77 dengan kategori tinggi. Dengan demikian e-modul IPA berbasis computational thinking yang dikembangkan layak digunakan untuk meningkatkan kemampuan berpikir logis dalam pembelajaran IPA.Kata kunci: Berpikir Komputasi, E-modul, Berpikir Logis. This study aims to produce thinking computation-based science e-modules that are feasible to use to improve students' thinking skills. This development research uses the ADDIE model, including Analysis, Design, Development, Implementation, and Evaluation. Data collection uses e-module validation instruments, teacher and student response questionnaires, and logical thinking ability tests. The results showed that the validity value of the thinking computation-based science e-module was 0.78 which was included in the high validity category. The results of the practicality of the teacher's response questionnaire were 90.93% and the responses of students were 85.68% with the very practical category, the results of the effectiveness of students' logical thinking skills in limited trials and field trials increased, the N-gain value in limited trials and field tests try field respectively 0.73 and 0.77 with high category. Thus the thinking computation-based science e-module that has been developed is feasible to use to improve logical thinking skills in science learning.Keywords: Computational Thinking, E-Module, Logical Thinking.

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Balari, Sergio, and Guillermo Lorenzo. "Computational Phenotypes: Where the Theory of Computation Meets Evo-Devo." Biolinguistics 3, no. 1 (April 6, 2009): 002–60. http://dx.doi.org/10.5964/bioling.8685.

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This article argues that the Chomsky Hierarchy can be reinterpreted as a developmental morphospace constraining the evolution of a discrete and finite series of computational phenotypes. In doing so, the theory of Morphological Evolution as stated by Pere Alberch, a pioneering figure of Evo–Devo thinking, is adhered to.

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Curzon, Paul, Joan Peckham, Harriet Taylor, Amber Settle, and Eric Roberts. "Computational thinking (CT)." ACM SIGCSE Bulletin 41, no. 3 (August 25, 2009): 201–2. http://dx.doi.org/10.1145/1595496.1562941.

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Henderson, Peter B. "Ubiquitous Computational Thinking." Computer 42, no. 10 (October 2009): 100–102. http://dx.doi.org/10.1109/mc.2009.334.

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Garcia-Penalvo, Francisco Jose. "Editorial Computational Thinking." IEEE Revista Iberoamericana de Tecnologias del Aprendizaje 13, no. 1 (February 2018): 17–19. http://dx.doi.org/10.1109/rita.2018.2809939.

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Shute, Valerie J., Chen Sun, and Jodi Asbell-Clarke. "Demystifying computational thinking." Educational Research Review 22 (November 2017): 142–58. http://dx.doi.org/10.1016/j.edurev.2017.09.003.

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CACM Staff. "Rethinking computational thinking." Communications of the ACM 59, no. 7 (June 24, 2016): 8. http://dx.doi.org/10.1145/2949401.

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Kirkpatrick, Keith. "Parallel computational thinking." Communications of the ACM 60, no. 12 (November 27, 2017): 17–19. http://dx.doi.org/10.1145/3148760.

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Kim, Jeong-sook, and Min-jeong Baek. "Classical Reading Curriculum Design Using Computational Thinking Strategies." JOURNAL OF HUMANITIES STUDIES 125 (December 31, 2021): 117–49. http://dx.doi.org/10.46346/tjhs.125..5.

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Jeong, Inkee. "Development of Materials for Programming Education based on Computational Thinking for Club Activities of Elementary School." Journal of The Korean Association of Information Education 19, no. 1 (June 30, 2015): 243–52. http://dx.doi.org/10.14352/jkaie.2015.19.2.243.

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Shin, Seungki. "Designing the Framework of Evaluation on Learner’s Cognitive Skill for Artificial Intelligence Education through Computational Thinking." Journal of The Korean Association of Information Education 24, no. 1 (February 28, 2020): 59–69. http://dx.doi.org/10.14352/jkaie.2020.24.1.59.

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Park, Sung Hee. "Study of SW Education in University to enhance Computational Thinking." Journal of Digital Convergence 14, no. 4 (April 28, 2016): 1–10. http://dx.doi.org/10.14400/jdc.2016.14.4.1.

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Martins, Danielle Juliana Silva, and Fábio Cristiano Souza Oliveira. "PENSAMENTO COMPUTACIONAL PARA CRIANÇAS POR MEIO DO PROJETO DE EXTENSÃO ACADEMIA HACKTOWN." Cadernos CEDES 43, no. 120 (May 2023): 33–44. http://dx.doi.org/10.1590/cc271373.

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RESUMO Este trabalho apresenta o relato de experiência realizada no sertão de Pernambuco, por meio do Projeto Academia HackTown, que promove atividades de ensino que potencializam o pensamento computacional em crianças de 7 a 10 anos, em cursos de programação em jogos e robótica. Os cursos oferecidos fazem uso de metodologias como gamificação, computação desplugada, game learning, storytelling, clube de leitura, robótica educacional e programação, bem como adotam a ludicidade nas atividades propostas e compreendem que a diversidade metodológica promove a aprendizagem significativa.

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CACM Staff. "Computational thinking is not necessarily computational." Communications of the ACM 60, no. 9 (August 23, 2017): 8–9. http://dx.doi.org/10.1145/3128899.

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Mazzone, Marian. "Andy Warhol: Computational Thinking, Computational Process." Leonardo 53, no. 2 (April 2020): 179–82. http://dx.doi.org/10.1162/leon_a_01574.

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This article positions Andy Warhol as a model for computational thinking and art-making, linking him to concepts in new media art. Warhol's work is analyzed for its variability in form generation and output, both in painting and on the early Amiga computer. His work becomes a simulation of the abstraction of process and methods of production familiar to us in electronic computational art of today. Rather than seen as banal mass production on the modern assembly line, Warhol's work can be seen as inspiration for new media arts practitioners.

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Tissenbaum, Mike, Josh Sheldon, and Hal Abelson. "From computational thinking to computational action." Communications of the ACM 62, no. 3 (February 21, 2019): 34–36. http://dx.doi.org/10.1145/3265747.

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Jenkins, Craig W. "Classroom Talk and Computational Thinking." International Journal of Computer Science Education in Schools 1, no. 4 (October 31, 2017): 3–13. http://dx.doi.org/10.21585/ijcses.v1i4.15.

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This paper is part of a wider action research project taking place at a secondary school in South Wales, UK.Â The overarching aim of the project is to examine the potential for aspects of literacy and computational thinking to be developed using extensible â€˜build your own blockâ€™ programming activities.Â This paper examines classroom talk at an extracurricular programming club and focuses in particular on dialogue relating to computational thinking.Â Learners spent a number of weeks carrying out an activity designed using the Snap programming tool.Â The activity was themed around language and the task was to devise a collection of fixed-form poetry.The findings are in two parts.Â First is a dialogue analysis using the SEDA coding scheme.Â This analysis revealed a number of learner interactions showing evidence of reasoning.Â Second, examples of talk sequences are provided in order to examine how the reasoning identified in the interactions relate to what we may recognise as computational thinking.Â The paper concludes by considering how dialogic approaches in the classroom potentially have an important role to play in the process of teaching young people to think computationally.

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Wing, Jeannette M. "Computational thinking and thinking about computing." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366, no. 1881 (July 31, 2008): 3717–25. http://dx.doi.org/10.1098/rsta.2008.0118.

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Computational thinking will influence everyone in every field of endeavour. This vision poses a new educational challenge for our society, especially for our children. In thinking about computing, we need to be attuned to the three drivers of our field: science, technology and society. Accelerating technological advances and monumental societal demands force us to revisit the most basic scientific questions of computing.

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Suktiningsih, Wiya, Diah Supatmiwati, Ni Gusti Ayu Dasriani, Apriani Apriani, and Ismarmiaty Ismarmiaty. "Pengenalan Pemikiran Computational Thinking untuk Guru MI dan MTs Pesantren Nurul Islam Sekarbela." Jurnal Karya untuk Masyarakat (JKuM) 2, no. 1 (January 28, 2021): 91–102. http://dx.doi.org/10.36914/jkum.v2i1.490.

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Abstrak: Computational thinking (CT) adalah konsep berpikir secara komputasi dalam menyelesaikan suatu permasalahan. Metode pembelajaran dalam CT meliputi 4 pilar utama yaitu: Dekomposisi, Abstraksi, Algoritma dan Pengenalan Pola. CT melatih siswa untuk berpikir komputasi ketika memecahkan permasalahan soal di semua bidang ilmu. Berpikir Komputasi adalah proses berpikir yang terlibat dalam merumuskan masalah dan mengungkapkan solusinya seperti pada sebuah komputer dimana manusia atau mesin yang penyelesaian masalaha dilaksanakan secara efektif. Metode pembelajaran CT membentuk siswa untuk kreatif dan inovatif, serta mampu berkomunikasi dan berkolaborasi. Saat ini CT tidak hanya bisa diterapkan di bidang ilmu teknik informastika, tetapi sudah bisa diintegrasikan dengan bidang ilmu lain seperti bahasa Indonesia, Bahasa Inggris, Matematika dan IPA. Program kegitan pengabdian kepada masyarakat ini melakukan pengenalan konsep CT bagi guru-guru MI dan MTs yang ada di Pondok Pesantren Nurul Islam – Pagesangan, Mataram. Dengan harapan para guru dapat memasukkan CT ke dalam mata pelajaran yang diajarkan, sehingga siswa terbiasa dengan pemecahan masalah melalui cara computational thinking, kelangsungan hidup computational thinking, suatu masalah dapat diselesaikan dengan baik, cepat dan optimal. Abstract: Computational thinking (CT) is the concept of thinking computationally in solving a problem. The learning method in CT includes 4 main pillars, namely: Decomposition, Abstraction, Algorithm and Pattern Recognition. CT trains students to think computationally when solving problems in all fields of science. Computational Thinking is a thought process involved in formulating a problem and expressing its solution as in a computer where a human or machine problem solving is carried out effectively. The CT learning method shapes students to be creative and innovative, and able to communicate and collaborate. Currently CT can not only be applied in the field of informatics engineering, but can be integrated with other fields of science such as Indonesian, English, Mathematics and Science. This community service activity program introduces the concept of CT for MI and MTs teachers at Nurul Islam Islamic Boarding School - Pagesangan, Mataram. With the hope that teachers can incorporate CT into the subjects being taught, so that students get used to solving problems through computational thinking, the survival of computational thinking, a problem can be resolved properly, effectively and optimally.

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Pramudiani, Puri, Fitri Alyani, Maarten Dolk, and Wanty Widjaja. "Investigating fraction computation problem-solving among pre-service primary school teachers." Jurnal Elemen 10, no. 3 (October 5, 2024): 685–710. http://dx.doi.org/10.29408/jel.v10i3.27462.

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The ability to solve problems involving fractions is a fundamental aspect of mathematics education. This study explores how Pre-Service Primary School Teachers approach problem-solving in fractional computations. A workbook is designed to support pre-service primary school teachers ' computational thinking in fraction-context challenges. The study employs a qualitative descriptive method encompassing interviews, study documentation, and observation to assess fraction computation problem-solving abilities. Twenty-seven participants were involved in this study. They were first-year students enrolled in the Primary School Teacher Education Department at one of the private universities in Jakarta, Indonesia. The findings reveal a notable outcome in pre-service primary school teachers ' understanding of fraction computation problem-solving, marked by recognizable strategies in their problem-solving approach. This research suggests that designing a series of workbooks containing various strategies in computational fractions and building a strong fractional number sense can help pre-service teachers reduce misconceptions and better understand fraction operations. These findings offer guidance for mathematics teacher education on how to effectively teach and embed the concept of fraction calculations to their future students so that they can only teach procedurally if they understand the meaning of fraction operations.

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Azevedo, Greiton Toledo de, Marcus Vinicius Maltempi, and Arthur Belford Powell. "Contexto Formativo de Invenção Robótico-Matemática: Pensamento Computacional e Matemática Crítica." Bolema: Boletim de Educação Matemática 36, no. 72 (April 2022): 214–38. http://dx.doi.org/10.1590/1980-4415v36n72a10.

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Resumo Neste artigo buscamos identificar e compreender as características do contexto formativo em Matemática de estudantes quando produzem jogos digitais e dispositivos robóticos destinados ao tratamento de sintomas da doença de Parkinson. Norteados pelas ideias da metodologia qualitativa de pesquisa, interagimos com alunos do Ensino Médio visando a construção de um jogo eletrônico com dispositivo robótico, chamado Paraquedas, destinado a sessões de fisioterapia de pacientes com Parkinson. Os alunos foram estimulados a propor e desenvolver ideias em ambientes voltados à experimentação e invenções eletrônicas para beneficiar pessoas em sociedade. Os dados foram analisados à luz dos pressupostos teóricos do Pensamento Computacional e da Matemática Crítica e consistem de discussão-análises do desenvolvimento científico-tecnológico, colaborativo-argumentativo e inventivo-criativo de tecnologias, indo além dos muros da sala de aula de Matemática. Como resultado, identificamos as seguintes características do contexto formativo em Matemática: independência formativa; imprevisibilidade de respostas; aprendizagem centrada na compreensão-investigação-invenção; e conexão entre áreas de conhecimento. Compreendemos que tais características se originam e mutuamente se desenvolvem dinâmico e idiossincraticamente nas concepções de planejamento, diálogo e protagonismo dos sujeitos, os quais fomentam a exploração de problemas aberto e inéditos de Matemática em-uso e descentralizam a formalização excessiva do rigor de objetos matemáticos como ponto nevrálgico à formação em Matemática.

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Villalba-Condori, Klinge Orlando, and Luis Magdiel Oliva-Córdova. "Teacher Training to Develop Computational Thinking at the Primary Education Level." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10 (October 31, 2019): 91–98. http://dx.doi.org/10.5373/jardcs/v11i10/20193010.

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Kadir, Shaifany Fatriana, Wahju Wulandari, and Sodik Sodik. "COMPUTATIONAL THINKING DALAM MEMASUK DIGITAL NATIVE BAGI GURU DAN SISWA PENDIDIKAN ANAK USIA DINI." Conference on Innovation and Application of Science and Technology (CIASTECH) 6, no. 1 (December 30, 2023): 868. http://dx.doi.org/10.31328/ciastech.v6i1.5328.

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Tujuan pengabdian adalah memberikan kesulitan guru untuk mengikuti perkembangan teknologi dalam sistem pembelajaran dengan digital native. Seorang guru dan siswa Kelompok Bermain Alquran Nurul Huda harus mampu berkolaborasi untuk saling mengisi dalam metode pembelajaran secara digital. Computation Thinking (CT) mampu memberikan jalan untuk membuat metode pembelajaran menjadi mudah. Metode pelaksanaan dengan melalui: 1). Pengenalan Computational Thinking (CT) Pada Anak Usia Dini (PAUD), 2). Melaksanakan Kegiatan yang mengandung 4 Unsur Computational Thinking (CT). Solusinya adalah memberikan materi pembelajaran berupa topik guru; meronce sedotan warna-warni, topik peralatan dokter, dan 7 langkat mencuci tangan. Hasil yang diperoleh bahwa semua siswa sebanyak 14 orang mampu menerapkan semua pembelajaran berbasis Computational Thinking (TC) dengan senang, perhatian, dan mampu mengerjakan dengan baik. Kesuksesan metode ini sangat menggembirakan baik bagi guru dan siswa. Guru menjadi senang untuk membuat modul pembelajaran yang lebih inovatif.

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Xu, Ruiyang, Chunmao Jiang, and Lijuan Sun. "A Novel Three-Way Decision Model for Improving Computational Thinking Based on Grey Correlation Analysis." Scientific Programming 2022 (January 25, 2022): 1–15. http://dx.doi.org/10.1155/2022/3575457.

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Computational thinking (CT) is an approach that applies the fundamental concepts of computer science to solve problems, design systems, and understand human behavior, which can help students develop lifetime learning and generate new topics. It has been the elements of competency expected of the next generation of talents. However, the current research on computational thinking evaluation is still at a relatively weak stage. The existing related evaluation research is still limited to traditional curriculum evaluation methods. Therefore, the training effect of computational thinking cannot be well quantified, and the characteristics of students cannot be further explored. In this work, we propose a three-way decision model for improving computation thinking. We first developed a system of evaluation metrics, including five specific primary indicators and several secondary indicators. Next, the weight of each indicator was determined by applying an expert similarity measure, consequently getting the best metric sequence. We employ a grey correlation analysis to calculate the distance of each test result from this optimal sequence. Then, we trisect the set of testers based on the distance to build three regions of high score sequences, medium score sequences, and low score sequences inspired by the three-way decision. We can then exploit these rules on target students in the relatively low regions to improve their computational thinking. An example analysis illustrates the effectiveness and applicability of the method. This article provides a solid theoretical basis for improving students’ computational thinking ability. Teaching administrators can conveniently formulate computational thinking teaching strategies, and timely warning and intervention for students with poor computational thinking ability can effectively improve students’ computational thinking ability. The corresponding training measures are given to students of different ability levels to achieve differentiated and personalized training.

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Journal articles on the topic 'Computational thinkink'

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