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Using a correlational survey model, it surveys Turkish education faculty pre-service teachers and measures them with a personal information form, a computational thinking skills scale, and an online self-regulatory learning scale. Quantitative analyses include descriptive methods, independent-samples t-test, one-way ANOVA, Kruskal–Wallis test, and Pearson correlation. Results show most participants reach high computational thinking and high online self-regulated learning levels, with a moderate positive and significant relationship between the two.",{"@graph":14,"@context":77},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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is the purpose of the study?","Question",{"text":63,"@type":64},"To examine pre-service teachers’ computational thinking skill levels and their online self-regulated learning levels in terms of various variables, and to determine the relationship between them.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What research design and analysis methods were used?",{"text":68,"@type":64},"The study uses a correlational survey model and applies descriptive analysis, independent samples t-test, one-way ANOVA, Kruskal–Wallis H test, and Pearson correlation.",{"name":70,"@type":61,"acceptedAnswer":71},"What were the main findings about computational thinking and online self-regulated learning?",{"text":72,"@type":64},"Most pre-service teachers reported high or very high computational thinking skills, and most also reported high or very high online self-regulated learning skills.",{"name":74,"@type":61,"acceptedAnswer":75},"How are computational thinking skills related to online self-regulated learning?",{"text":76,"@type":64},"A moderate, positive, and significant relationship was found between the two variables.","https://schema.org",{"og:url":32,"og:type":79,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":81,"canonical":32},"index,follow",{"doc_id":83,"site_id":7},600199,1792160641,{"code":4,"msg":86,"data":87},"success",[88,92,96,100,105,110,114,118,123,126,130],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Story & 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Online\u003Cbr>Self-Regulated Learning Levels |\n| --- | --- |\n\nGülçin Zeybek, Karamanoğlu Mehmetbey University  \nAbstract  \nThe aim of this study was to examine the computational thinking skill levels and online self-regulatory learning levels of pre-service teachers in terms of various variables and to determine the relationship between their computational thinking skill levels and online selfregulatory learning levels. The design of the research is the correlational survey model, one of the quantitative research designs. The study group of the research consisted of preservice teachers studying at the education faculty of a state university in Turkey and voluntarily participating in the research. A personal information form, computational thinking skills scale and online self-regulatory learning scale were used as measurement tools in the research. Within the framework of quantitative data analysis, descriptive analysis techniques, independent samples t-test, one-way ANOVA, Kruskal-Wallis H test for independent samples and Pearson Correlation technique were used. When the research findings were examined, it was seen that 63% of the pre-service teachers participating in the research had a high level of computational thinking skills and 36% had a very high level. It was also seen that 72% of the pre-service teachers had a high level of online self-regulated learning skills, 18% had a very high level, and 9% had a medium level. In addition, there was a moderate, positive and significant relationship between pre-service teachers’computational thinking skills and online self-regulatory learning levels. The research findings were interpreted in line with the relevant literature and various suggestions were made for practice and future research.  \nKeywords: computational thinking, online learning, self-regulated learning, 21st century skills  \nIntroduction  \nTechnology, which is one of the essentials of today, has affected and facilitated human life in many ways. Although education is one of the fields where technology has gained significant momentum, technology also makes significant contributions to education. One of these contributions has undoubtedly been distance education, which is free from spatial constraints. While information increases and changes at a rapid pace, schools, which are formal education institutions, have been insufficient to meet the education needs and distance education has become an important tool to provide lifelong education. On the other hand, the increasing number of students, developing tech-  \n265 Critical Questions in Education 13:3 Fall 2022  \nnology and changes in learning approaches has resulted in schools benefiting from distance education. In the information society we live in, benefiting from low-cost and student-oriented methods and tools that create equal opportunities and that people can plan for themselves without the limitations of time and space has made learning more effective at all levels (Özkanal & Özgür, 2017) .  \nAccording to the ‘Digital 2019 in Turkey’ report, in Turkey, which has a population of 82.4 million, 59.36 million people, who make up 72% of the population, are internet users and there was a 9% increase in the usage rate compared to the previous year (Bayrak, 2020) . In addition, many technologies that can be used in classroom and virtual environments and facilitate learning are mentioned (Ünlü, 2019) . It can be said that the internet, which is increasingly used every year, increases the opportunities for accessing and sharing information, as well as positively affecting access to educational opportunities and different learning paths. Thus, online learning, which is an independent learning model alongside face-to-face education, is gaining importance day by day.  \nLiterature Review  \nOnline Learning  \nIn the process of change, in which the transition from the industrial age to the ","cbCaig9WjBCNZfJV","https://ap.wps.com/l/cbCaig9WjBCNZfJV","pdf",454619,25,"English","# Abstract\n# Introduction\n# Literature Review\n## Online Learning","[{\"question\":\"What is the purpose of the study?\",\"answer\":\"To examine pre-service teachers’ computational thinking skill levels and their online self-regulated learning levels in terms of various variables, and to determine the relationship between them.\"},{\"question\":\"What research design and analysis methods were used?\",\"answer\":\"The study uses a correlational survey model and applies descriptive analysis, independent samples t-test, one-way ANOVA, Kruskal–Wallis H test, and Pearson correlation.\"},{\"question\":\"What were the main findings about computational thinking and online self-regulated learning?\",\"answer\":\"Most pre-service teachers reported high or very high computational thinking skills, and most also reported high or very high online self-regulated learning skills.\"},{\"question\":\"How are computational thinking skills related to online self-regulated learning?\",\"answer\":\"A moderate, positive, and significant relationship was found between the two variables.\"}]","The Relationship between Pre-Service Teachers’ Computational Thinking Skill Levels and Online Self-Regulated Learning Levels - research article | PDF",1792090224,63]