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The Shape Of Data: Using 3D Simulation Data Models to encourage Critical-Thinking and Student Engagement in the Analysis of Large Datasets

Author Robert J. Loughnane, Cian Twomey, Adam Loughnane
Abstract The purpose of this research paper is to develop a pedagogy for the effective use of Microsoft Excel-based 3D simulation modelling algorithms to encourage student engagement and the development of critical-thinking skills in relation to the analysis of large datasets amongst third-level business students. We will develop and subsequently test a number of such 3D simulation modelling algorithms with a specific group of thirdlevel business students in Galway, Ireland. These will focus primarily on a number of fundamental issues in economics, finance, and business data analytics. We will employ standard quantitative techniques to analyse student understanding of these threshold concepts before and after our intervention to gauge the effectiveness of this innovative pedagogical approach. We expect that our findings will demonstrate that when the students are taught through exposure to the 3D simulation algorithms, their engagement with the material and their critical-thinking skills are enhanced with this being further reinforced by an improvement in their test results. Furthermore, we hope this study will show that allowing the students to experiment with the 3D algorithms encourages higherorder critical-thinking and an enhanced engagement with their studies. We feel that our pedagogical methods have universal applications, and that the teaching of academic disciplines other than Business Studies and Economics could be vastly enhanced by their use. There also exists the potential to expand our investigations into other concepts, including those from Applied Science and Engineering. Finally, the 3D models themselves could be made more sophisticated by the use of cutting-edge advanced techniques in Microsoft Excel, Python and NumPy.
Keywords 3D simulation algorithms, critical-thinking, student engagement, Markov processes, large datasets, data models, economic data, Microsoft Excel, Python, NumPy, OpenPyxl, R, universal application, self-reflection, self-evaluation
Published In ICEP Proceedings
Year 2018
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