BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and Learning
The increasing automation in data collection, either in structured or unstructured formats, as well as the development of reading, concatenation and comparison algorithms and the growing analytical skills which characterize the era of Big Data, cannot not only be considered a technological...
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| Format: | Article |
| Language: | English |
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Universitat Politècnica de València
2017-04-01
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| Series: | Multidisciplinary Journal for Education, Social and Technological Sciences |
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| Online Access: | http://polipapers.upv.es/index.php/MUSE/article/view/6350 |
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| author | J.L. Peñaloza Figueroa C. Vargas Perez |
| author_facet | J.L. Peñaloza Figueroa C. Vargas Perez |
| author_sort | J.L. Peñaloza Figueroa |
| collection | DOAJ |
| description | The increasing automation in data collection, either in structured or
unstructured formats, as well as the development of reading, concatenation and comparison algorithms and the growing analytical skills which characterize the era of Big Data, cannot not only be considered a technological achievement, but an organizational, methodological and analytical challenge for knowledge as well, which is necessary to generate opportunities and added value.
In fact, exploiting the potential of Big-Data includes all fields of community activity; and given its ability to extract behaviour patterns, we are interested in the challenges for the field of teaching and learning, particularly in the field of statistical inference and economic theory.
Big-Data can improve the understanding of concepts, models and techniques used in both statistical inference and economic theory, and it can also generate reliable and robust short and long term predictions. These facts have led to the demand for analytical capabilities, which in turn encourages teachers and students to demand access to massive information produced by individuals, companies and public and private organizations in their transactions and inter- relationships.
Mass data (Big Data) is changing the way people access, understand and organize knowledge, which in turn is causing a shift in the approach to statistics and economics teaching, considering them as a real way of thinking rather than just operational and technical disciplines. Hence, the question is how teachers can use automated collection and analytical skills to their advantage when teaching statistics and economics; and whether it will lead to a change in what is taught and how it is taught. |
| format | Article |
| id | doaj-art-7171b75f131e4b66aaadf7e8e8dd8223 |
| institution | Kabale University |
| issn | 2341-2593 |
| language | English |
| publishDate | 2017-04-01 |
| publisher | Universitat Politècnica de València |
| record_format | Article |
| series | Multidisciplinary Journal for Education, Social and Technological Sciences |
| spelling | doaj-art-7171b75f131e4b66aaadf7e8e8dd82232025-01-02T11:55:22ZengUniversitat Politècnica de ValènciaMultidisciplinary Journal for Education, Social and Technological Sciences2341-25932017-04-0141648710.4995/muse.2017.63505244BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and LearningJ.L. Peñaloza Figueroa0C. Vargas Perez1Universidad Complutense de MadridUniversidad Complutense de MadridThe increasing automation in data collection, either in structured or unstructured formats, as well as the development of reading, concatenation and comparison algorithms and the growing analytical skills which characterize the era of Big Data, cannot not only be considered a technological achievement, but an organizational, methodological and analytical challenge for knowledge as well, which is necessary to generate opportunities and added value. In fact, exploiting the potential of Big-Data includes all fields of community activity; and given its ability to extract behaviour patterns, we are interested in the challenges for the field of teaching and learning, particularly in the field of statistical inference and economic theory. Big-Data can improve the understanding of concepts, models and techniques used in both statistical inference and economic theory, and it can also generate reliable and robust short and long term predictions. These facts have led to the demand for analytical capabilities, which in turn encourages teachers and students to demand access to massive information produced by individuals, companies and public and private organizations in their transactions and inter- relationships. Mass data (Big Data) is changing the way people access, understand and organize knowledge, which in turn is causing a shift in the approach to statistics and economics teaching, considering them as a real way of thinking rather than just operational and technical disciplines. Hence, the question is how teachers can use automated collection and analytical skills to their advantage when teaching statistics and economics; and whether it will lead to a change in what is taught and how it is taught.http://polipapers.upv.es/index.php/MUSE/article/view/6350New technologiesParadigmLogical reasoningInstrumental skillsScenariosInteractivityModelling and simulation |
| spellingShingle | J.L. Peñaloza Figueroa C. Vargas Perez BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and Learning Multidisciplinary Journal for Education, Social and Technological Sciences New technologies Paradigm Logical reasoning Instrumental skills Scenarios Interactivity Modelling and simulation |
| title | BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and Learning |
| title_full | BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and Learning |
| title_fullStr | BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and Learning |
| title_full_unstemmed | BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and Learning |
| title_short | BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and Learning |
| title_sort | big data and the challenges for statistical inference and economics teaching and learning |
| topic | New technologies Paradigm Logical reasoning Instrumental skills Scenarios Interactivity Modelling and simulation |
| url | http://polipapers.upv.es/index.php/MUSE/article/view/6350 |
| work_keys_str_mv | AT jlpenalozafigueroa bigdataandthechallengesforstatisticalinferenceandeconomicsteachingandlearning AT cvargasperez bigdataandthechallengesforstatisticalinferenceandeconomicsteachingandlearning |