Computational Thinking is a skill that guides the 21th century individual in the problems experienced during daily life and it has an ever-increasing significance. Multifarious definitions were attempted to explain the concept of Computational Thinking. However, it was determined that there was no consensus on this matter in the literature and several different concepts were mentioned in the definitions found in the literature. It was considered that this fact made it difficult to understand the concept of Computational Thinking. To establish a more comprehensive approach, the present study aimed to identify the concepts that are included in the Computational Thinking definitions that were presented in previous studies. It also aimed to reveal trends in the identified concepts throughout the years. As a result of the search, a total of 59 definitions were identified and a content analysis was conducted on these definitions. Analysis results demonstrated that Computational Thinking was defined based on several concepts such as problem solving, technology, thinking, individual and social qualities. Furthermore, it was determined that statements on thinking were prominent before 2006, and today, emphasis on problem solving and technology became more significant. It was considered that the present study would contribute to a better understanding of the Computational Thinking concept. At the end of the study, certain suggestions were presented for further research.
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.
The aim of the present study was to determine the views of pre-service teachers on artificial intelligence. In the present qualitative study, conducted with the phenomenology design, that data were collected from 94 pre-service teachers attending different departments at Manisa Celal Bayar University, Faculty of Education during the 2018-2019 academic year fall semester in Turkey. Data were collected with semi-structured interview form and written interview form, developed by the author. Collected data were analyzed by using content analysis method and classified under themes. Analyses demonstrated that pre-service teachers assigned different meanings to artificial intelligence, felt basically negative emotions for artificial intelligence, and did not want to live in a world ruled by artificial intelligence. Furthermore, it was found that pre-service teachers considered that artificial intelligence could have both several benefits and risks, and it might have both positive and negative effects on education. Based on the study findings, various recommendations were presented for future studies and implementations on the topic.
The aim of the present study was to investigate the properties of paper-and-pencil data collection instruments developed to measure Computational Thinking (CT) based on several variables. Thus, keywords were identified and used in searches conducted in various databases. The outcomes of the search were analyzed based on the inclusion/exclusion criteria and 64 studies that focused on CT measurement were identified. Content analysis findings were classified under several themes. Based the present study findings, it was determined that the number of tools developed to measure CT demonstrated an increasing trend over time. Furthermore, it was found that the above-mentioned studies included mainly tests. Moreover, it was observed that the processes of ensuring validity and reliability were not clearly specified for more than half of the paper-and-pencil data collection instruments designed to measure CT. Based on the findings, several recommendations were presented for future studies and implementations in the related field.
Halil İbrahim HASESKİ 1 Öz: Bu çalışmanın amacı öğretmen adaylarının yenilenen eğitim fakültesi müfredatında yer alan Bilişim Teknolojileri dersine yönelik görüşlerini belirlemektir. Bu kapsamda planlanan nitel araştırmada, 2018-2019 eğitim öğretim yılı güz döneminde Manisa Celal Bayar Üniversitesi Eğitim Fakültesi'nde farklı bölümlerde öğrenim görmekte olan 44 öğretmen adayından yarı-yapılandırılmış görüşmeler ve yazılı form aracılığıyla görüş alınmıştır. Elde edilen veriler içerik analizi ile analiz edilmiştir. Analiz sonucunda öğretmen adaylarının Bilişim Teknolojileri dersini önemli gördükleri ve bu derste faydalı bilgiler öğrendikleri belirlenmiştir. Diğer yandan öğretmen adayları, dersin süresinin kısa ve içeriğinin çok yoğun olduğunu ifade etmişlerdir. Araştırma sonunda ulaşılan sonuçlar temelinde ileriki çalışmalara ve uygulamaya yönelik çeşitli öneriler sunulmuştur.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.