Improving Data Analysis Skills in First Year Undergraduate Engineering Students: A Constructive Approach

With the advent of the information-age and digitization, vast amounts of data is getting generated and collected by trillions of devices. Decision making in day to day life has become increasingly data driven. In the context of engineering work, the collection of meaningful data, subsequent analysis and drawing of relevant inferences is of importance in designing technological solutions to real world problems. One of the enablers in achieving this fluency is statistics education. But the path to Statistics education is replete with challenges which are outlined in the work. In this study, the authors present the content, pedagogy and assessment for fostering the competency of descriptive Statistics in an introductory first year undergraduate engineering course titled, “Engineering Exploration”. This work involves organizing the students' existing body of knowledge and addressing their misconceptions by adopting constructivist learning approach and active learning strategies. In addition an attempt to enhance their ability to apply the statistics knowledge on socially and contextually rich data is also done using real world datasets (UNESCO, India census-2011 data). A study of prior knowledge in descriptive Statistics and graphing techniques is done along with attempting to know how freshmen having a statistics background compare with their peers from a non-Statistics background in their application of knowledge in descriptive Statistics and graphing techniques. The results showed that the intervention done resulted in a significant difference in learning for non-statistics background students and marginal improvement for statistics background students. The paper discusses the details of the experimentation and discusses the observed results of this effort.