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Teaching Courses On Probability And Statistics For Engineers: Classical Topics In The Modern Technological Era
Author(s) -
Natarajan Gautam
Publication year - 2020
Publication title -
2009 annual conference and exposition proceedings
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--4578
Subject(s) - curriculum , mandate , computer science , mathematics education , class (philosophy) , probability and statistics , statistics , mathematics , artificial intelligence , psychology , pedagogy , political science , law
Most Industrial Engineering departments offer courses on applied probability and/or statistics to engineering students. These courses often tend to be perceived as dry and far removed from engineering. This poses a significant challenge for instructors, especially junior faculty members that have been assigned to teach such courses. Not only do they have to spend significant amount of time away from research to make interesting classroom material, but they also have to teach material that is not even remotely close to what they do for research. To make matters worse, since the High School curriculum in the United States does not mandate a basic foundation in probability and statistics, most students are extremely unprepared and hence the instructors have to start at a phenomenally fundamental level. The objective of this paper is to describe some strategies to overcome the concerns mentioned above and effectively educate engineering students on topics in applied probability and statistics. The first aspect is to teach a predominantly chalk-and-talk type of class by carefully using technology in strategic places and avoiding technology in certain other places. We quantitatively evaluate the effectiveness of our strategies and provide insights. Next, a good portion of this paper is devoted to one specific use of technology which is in laboratory-like exercises. These exercises were developed to teach more difficult concepts such as Central Limit Theorem and show how it applies to project evaluation and review technique (PERT). As a result, not only did the student understanding of complex material improve, but also the material was covered in a much shorter time. Finally the paper concludes with a qualitative discussion of issues where it is unclear whether technology boosts or hinders understanding of concepts in applied probability and statistics.

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