Computational Thinking for All: Pedagogical Approaches to Embedding 21st Century Problem Solving in K-12 Classrooms

Yadav, Aman; Hai, Hong; Stephenson, Chris

doi:10.1007/s11528-016-0087-7

Cited by 329 publications

(181 citation statements)

References 6 publications

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“…On the other hand, studies on the integration of CT into the curriculum and the studies on the significance of CT in education were started to be conducted on 2013. However, these studies included significant findings such as the integration of CT in education (Israel et al, 2015;Navlakha & Bar, 2016, Voogt et al, 2015Yadav, Hong, & Stephenson, 2016), reorganization of the curriculum based on CT skills (Grover, Pea, & Cooper, 2015;Jun, Han, Kim, & Lee, 2014;Vallance & Towndrow, 2016;Zapata-Ros, 2015) and the requirement of including CT in teacher training (Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014, Yadav et al, 2016. However, it is important to understand and assess the constructs associated with CT in order to integrate this skill effectively into education.…”

Section: Conclusion and Recommendations For Future Researchmentioning

confidence: 99%

Publication Trends Over 10 Years of Computational Thinking Research

İliç¹,

Haseski²,

Tuğtekin³

2018

CONT ED TECHNOLOGY

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The current study aimed to review studies on computational thinking (CT) indexed in Web of Science (WOS) and ERIC databases. A thorough search in electronic databases revealed 96 studies on computational thinking which were published between 2006 and 2016. Studies were exposed to a quantitative content analysis through using an article control form developed by the researchers. Studies were summarized under several themes including the research purpose, design, methodology, sampling characteristics, data analysis, and main findings. The findings were reported using descriptive statistics to see the trends. It was observed that there was an increase in the number of CT studies in recent years, and these were mainly conducted in the field of computer sciences. In addition, CT studies were mostly published in journals in the field of Education and Instructional Technologies. Theoretical paradigm and literature review design were preferred more in previous studies. The most commonly used sampling method was the purposive sampling. It was also revealed that samples of previous CT studies were generally pre-college students. Written data collection tools and quantitative analysis were mostly used in reviewed papers. Findings mainly focused on CT skills. Based on current findings, recommendations and implications for further researches were provided.

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Section: Conclusion and Recommendations For Future Researchmentioning

confidence: 99%

Publication Trends Over 10 Years of Computational Thinking Research

İliç¹,

Haseski²,

Tuğtekin³

2018

CONT ED TECHNOLOGY

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“…Öğrencilerin bilgisayarca düşünme beceri düzeyleri ile problem çözme beceri düzeyleri arasında pozitif yönde, orta düzeyde ve anlamlı bir ilişkinin olduğu görülmektedir. Bilgisayarca düşünmenin mantıksal matematiksel zekâ (Barr, Harrison, & Conery, 2011) ve problem çözme becerisi ile ilişkisi olduğunu ifade eden (Gonzalez, Gonzalez, & Fernandez, 2016;Yadav, Zhou, Mayfield, Hambrusch, & Korb, 2011;Yadav, Hong, & Stephenson, 2016;Wing, 2010) çalışmalar bulunmaktadır. Bilgisayarca düşünmenin karmaşık problemlerin çözümü için sistem tasarlamada matematiksel düşünmeden faydalandığı bilinmektedir (Lu & Fletscher 2009;Wing 2008;Wing, 2010).…”

Section: Sonuç Ve Tartışmaunclassified

Üniversite Öğrencilerinin Bilgisayarca Düşünme Becerilerinin Mantıksal Matematiksel Zekâ ve Problem Çözme Becerileri Açısından İncelenmesi

Oluk

Çakır

2019

Kuramsal Eğitimbilim

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Although there is no consensus in our country on the concept of Computational Thinking which consists of many sub skills, it has started to attract more interest with recent curriculum studies. This study aimed to explore the relationship between vocational college students' computational thinking skills and their problem solving skills and logical mathematical intelligence self-perceptions by correlational survey method. A total of 237 students (126 females, 111 males) from different departments participated in this study. Computational thinking skill levels scale, logical mathematical intelligence self-perception scale, and problem-solving inventory were used as instruments. ANOVA test was run to examine the difference between departments the skill levels measured. Pearson correlation test was run on the data to investigate the relationships between these skills. As a result of the analyses, it was found that there was a positive significant relationship between the students' computational thinking skills and logical mathematical intelligence problems and problem solving skill levels. As a result of ANOVA analysis; there were significant differences among the departments on computational thinking skills and logical mathematical intelligence levels, but it was observed that problem-solving skills were not significant differences among the departments.Keywords: computational thinking, problem solving, logical mathematical intelligence. ÖZ:İçerisinde birçok alt becerisi kapsayan bilgisayarca düşünme (Computational Thinking) kavramı ülkemiz için henüz bir kavram birliğine ulaşılamamış olsa da son yapılan müfredat çalışmaları ile daha fazla dikkat çekmeye başlamıştır. Bu çalışmada ilişkisel tarama modeli kullanılarak meslek yüksekokulu öğrencilerinin bilgisayarca düşünme becerileri ile problem çözme becerisi ve mantıksal matematiksel zekâ özalgıları arasındaki ilişkinin incelenmesi hedeflenmiştir. Çalışmaya farklı bölümlerden 126 kız 111 erkek toplam 237 öğrenci katılmıştır. Bilgisayarca düşünme beceri düzeyleri, mantıksal matematiksel zekâ özalgı ölçeği ve problem çözme envanterinin kullanıldığı çalışmada bölümler arası farklılığı incelemek için ANOVA testi uygulanmıştır. Bu beceriler arasındaki ilişkiyi incelemek için verilere Pearson Korelason testi uygulanmıştır. Yapılan analizler sonucunda öğrencilerin bilgisayarca düşünme becerileri ile mantıksal matematiksel zeka özalgıları ve problem çözme beceri düzeyleri arasında pozitif yönde anlamlı bir ilişki olduğu bulunmuştur. Yapılan ANOVA analizleri sonucunda; bilgisayarca düşünme beceri ve mantıksal matematiksel zeka düzeyleri değişkenlerinin bölümler arasında anlamlı farklılıklar gösterdiği, fakat problem çözme becerilerinin bölümler arasında anlamlı bir farklılık olmadığı görülmüştür.

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“…However, students' problem-solving behavior is a complex process involving different stages -problem decomposition, abstraction, and execution [35,41]. It is critical to figure out different stages to better understand and predict their influence on individuals' performance [40] rather than treating it as a whole solving period.…”

Section: Problem-solving Feature Extractionmentioning

confidence: 99%

Why you should(n't) build your own game engine

Rivela¹

2019

ACM SIGGRAPH 2019 Talks

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Modeling student learning and further predicting the performance is a well-established task in online learning and is crucial to personalized education by recommending different learning resources to different students based on their needs. Interactive online question pools (e.g., educational game platforms), an important component of online education, have become increasingly popular in recent years. However, most existing work on student performance prediction targets at online learning platforms with a well-structured curriculum, predefined question order and accurate knowledge tags provided by domain experts. It remains unclear how to conduct student performance prediction in interactive online question pools without such well-organized question orders or knowledge tags by experts. In this paper, we propose a novel approach to boost student performance prediction in interactive online question pools by further considering student interaction features and the similarity between questions. Specifically, we introduce new features (e.g., think time, first attempt, and first drag-and-drop) based on student mouse movement trajectories to delineate students' problem-solving details. In addition, heterogeneous information network is applied to integrating students' historical problem-solving information on similar questions, enhancing student performance predictions on a new question. We evaluate the proposed approach on the dataset from a real-world interactive question pool using four typical machine learning models. The result shows that our approach can achieve a much higher accuracy for student performance prediction in interactive online question pools than the traditional way of only using the statistical features (e.g., students' historical question scores) in various models. We further discuss the performance consistency of our approach across different prediction models and question classes, as well as the importance of the proposed interaction features in detail.

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Computational Thinking for All: Pedagogical Approaches to Embedding 21st Century Problem Solving in K-12 Classrooms

Cited by 329 publications

References 6 publications

Publication Trends Over 10 Years of Computational Thinking Research

Publication Trends Over 10 Years of Computational Thinking Research

Üniversite Öğrencilerinin Bilgisayarca Düşünme Becerilerinin Mantıksal Matematiksel Zekâ ve Problem Çözme Becerileri Açısından İncelenmesi

Why you should(n't) build your own game engine

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