Engineering Modules For Statistics Courses
Author(s) -
Surendra K. Gupta
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--11619
Subject(s) - presentation (obstetrics) , session (web analytics) , computer science , class (philosophy) , engineering education , interpretation (philosophy) , descriptive statistics , statistics education , statistics , mathematics education , mathematics , artificial intelligence , engineering , world wide web , engineering management , programming language , medicine , radiology
Rochester Institute of Technology (RIT) consists of eight colleges, including Engineering and Science. An engineering student takes “core” math and science courses through the College of Science, and both basic and advanced engineering courses through the College of Engineering. This paper describes the collaborative efforts of a Professor of Statistics and a Professor of Mechanical Engineering to increase the motivation for engineering students to learn statistics, to increase the retention of what they learn, and to help them apply the concepts to engineering problems, both in their statistics class and in future engineering courses. Statistics textbooks have data from engineering applications, but the problems tend to be simplistic in nature. From the one or two sentences of background information that are usually provided with textbook problems, it is difficult to understand why someone would want to collect and analyze this data. We have created modules consisting of more complete problems, including why someone would want to examine this type of data and how the statistical method used will provide a solution. Each stand-alone module contains a background and description of an engineering problem. In some cases data is provided, in others the mechanism for data collection is provided. Statistical processing of data, presentation of reduced results, and interpretation are a part of each module. The modules can be assigned to students individually or in teams. Problems have been developed for a variety of topics in statistics, and include descriptive statistics for one and two variables, probability, and statistical inference for one and two samples. The problems in each “module” have been designed to encourage critical thinking and to motivate students with applications from their major. Problems are not limited to, but may be used in conjunction with, active learning and cooperative learning techniques. At this point, three modules have been completed, with plans for two or three more. We anticipate that by actively engaging students in applying statistical methods to engineering problems, they will be more motivated to learn the material, will see the connections between their courses in science and engineering, and will be better prepared for subsequent courses. These modules will provide faculty with an additional resource aside from the textbook. We also anticipate that, given materials and appropriate support (e.g. training), faculty will be more inclined to adopt changes in their courses. Feedback from students and faculty members will be collected to formally evaluate the effectiveness of each module.
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