Data has been known to provide reliable answers to various problems facing humanity. One of the significant issues that are currently facing humankind is the Corona Virus pandemic. The virus has affected all activities and operations of daily human life. Berikan & Özdemir (2019) researched to investigate how to resolve the problem with a dataset as the execution of computational thoughts. The purpose of the study was to specify PSWD’s scope, which overlies with the data-based reasoning, data literacy, and significant data literacy perceptions in the literature. The article identifies the conceptual framework of PSWD and assembles the reasons from the literature to indicate the necessity of PSWD.
The article has various strengths emerging from the scope of data, research methodology, findings, analysis and application of research outcomes. The range of the research is quite broad as it can be applied to solve problems in any field. Berikan & Özdemir (2019) also analyzed a total of 54 publications via content analysis. The authors, therefore, used great sources to come up with their findings. The authors also applied a new advance to computational reasoning instructional thinking, a factor that makes their research unique and reliable. The authors also identified the background of their research through analysis of past studies, and the differences they hold with their own. For instance, the concept of machine learning has been discussed by authors to show its relationship with their research. The analysis was conducted effectively with the aid of computer systems to ensure that errors were avoided. Another factor that makes the study valid and reliable is that it uses CT, which is a problem-solving approach that applies advanced methods and concepts of computing. CT is a fundamental approach that has proved to be reliable and effective in solving significant problems.
The article, however, has various weaknesses. First, the authors majorly utilize the CT framework, which cannot meet all the research needs on its own. Secondly, the article only focuses on PSWD, and not any other approaches to problem-solving. Therefore, the piece is limited in terms of the approaches to problem-solving. The authors also used data from previous studies which might be erroneous. Systematic literature review methodology also has its weaknesses, especially in the modern world of big data analytics.
The literature review can significantly help in a research proposal. The literature provides guidelines on how significant problems can be resolved through the PSWD approach. A research proposal aims to request for a research project and funding to come up with a solution to a specific problem affecting the society. Through the application of the concepts learned from the article, one can come up with a sound research proposal. Corona Virus is one of the problems that scientists are still looking for solutions. By integrating PSWD with modern technology, one can come up with a research proposal on how to address the issue of Corona Virus. Currently, research is still ongoing to determine how the virus spreads among human beings. The application of PSWD concepts such as CT, data literacy and inferential thinking can play a crucial role in formulating a sound research proposal on Corona Virus.
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In this research it investigates problem-solving with dataset (PSWD) as a computational thinking learning implementation as reflected in academic publications. The main purpose of the study is to specify the scope of PSWD which is overlapped by the data literacy, thinking with data, big data literacy, and data-based thinking concepts in the literature. The researchers tried to investigate the best approaches to teach the skills at the K-12 level and propound new tools and new methods for teaching the skills. As in the ongoing research the researchers aims to propound an implementation called PSWD to improve Computational thinking (CT) for the students. The researchers used content analysis as their data analysis for this research as it allows the researchers to examine the definition and structure of a phenomenon from data without prejudice (Mayring, 2014). During this analysis categories and themes are formed. Content analysis will help in identifying the patterns in recorded communication and for this the data from a set of texts are to be collected either visual or oral. It can be qualitative and quantitative.
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