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• W2337137055 abstract "We live in a digital universe that is estimated today to contain about 5 zettabytes (approximately 5×10 21 ) data. This huge amount of data processed on computers extremely fast with optimized techniques, allows one to find insights in new and emerging types of data and content, to answer questions that were previously considered beyond reach. This is the idea of Big Data. The objectives of this project, of constructionist character, are to investigate how the teaching and learning of Exact Sciences develops, when mediated by computer and free public Big Data application software, such as Google Correlate and Google Trends, to develop teaching strategies that take the best advantage of these tools for the teaching and learning of Exact Sciences, and thereby to conclude on the feasibility of using Big Data as a mediator in the teaching of Exact Sciences, aimed at preparing our students for both the scientific challenges proposed for Big Data to the real world and a better understanding of the notions of phenomenon, observation, measurement, physical laws, and causal theory, among others. The aim of this work is to investigate the feasibility of this proposal through the first application of the use of Big Data in Science Teaching. In methodological terms, the application was developed within the 'History and Epistemology of Physics' course, from the pre-service Physics teacher training program at Ulbra Lutheran University of Brazil, which has this researcher as the lecturer, and was held during the first school semester 2014, counting with 7 students from different periods of the course. The students were asked to search freely for search terms correlations related to Physics Teaching in Google Correlate. Once the best correlate search terms were obtained, the students deepened their research on these correlations from several other sources, looking for possible scientific explanations (causation) for them. As a final activity for the course partial evaluation, the results of their research were presented and discussed in seminar fashion to the class. At the end of the semester, a questionnaire focusing on the contributions of Big Data activities for their learning and applied structured with participants about their perceptions of overall activity interviews were conducted. In this paper, the results of the first application of our didactic proposal were presented. It is aimed at preparing students to the scientific challenges posed by Big Data to the real world as well on a better understanding of the concepts of phenomenon, observation, measurement, physical laws, theory, and causality, among others. On the one hand, this application showed that the proposal seems feasible: students in general enjoyed the activities with the tools and demonstrated to understand the distinction between correlation and causation. On the other hand, however, it highlighted the need for its improvement in several aspects which include: to facilitate the appropriation of tools by students, to develop strategies to circumvent the students’ difficulty of finding terms that have a causal relationship, and to easy the connection of the activity with the process of construction of physical knowledge." @default.
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• W2337137055 date "2014-01-01" @default.
• W2337137055 modified "2023-09-27" @default.
• W2337137055 title "Aprender-com-Big-Data no ensino de ciências Learning-with-Big-Data in science teaching" @default.
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