Investigating “Problem-Solving With Datasets” as an Implementation of Computational Thinking: A Literature Review

Abstract

This study aims to investigate problem-solving with dataset (PSWD) as a computational thinking learning implementation as reflected in academic publications. Specifically, the purpose is to specify the scope of PSWD, which overlaps with the data literacy, thinking with data, big data literacy, and data-based thinking concepts in the literature. Subaims of the study are to identify the conceptual structure of PSWD based on definitions in academic publications and to classify the reasons given in the literature to show the need for PSWD. For the purposes to investigate PSWD conceptually, to classify the reasons given for the need for PSWD, the obtained 54 publications were analyzed via content analysis. Moreover, this study investigates the most frequently suggested or used teaching strategies (in terms of instructional methods, instructional tools, and grade level) for PSWD in the literature. The frequencies of used words in selected publications referring instructional methods, instructional tools, and grade levels were shown in the findings of study. The importance of the study stems from its focus on a new approach to computational thinking instructional implementation.