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Publication:
DuPort, Dan (2012) "Teaching quantitative methods to business and soft science students by using interactive workbook courseware,"Spreadsheets in Education (eJSiE): Vol. 5: Iss. 2, Article 3.
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Conference Presentations:
March 21-24, 2013: 25th International Conference on Technology in Collegiate Mathematics,
Westin Copley Boston, a Pearson learning event. See the presentation slides.
January 13 -15, 2013: International Higher Education Teaching and Learning Conference,
University of Central Florida, Orlando.
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Here's some (7 slide) slideshows that illustrate some of my courseware:
(click on the image to get to the slideshow)
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This is from the STEMLi course on elementary statistics. ​It is a game that one can play with an audience. Sally's commute time has a mean of 18 minutes and a standard deviation of 2 minutes. Can you create 70 walks to school that has such a distribution? The slides show how the easy graphing in STEMLi lets the game come to a good answer, even if the player is quite unaware of the mathematics of it!
This is a brief demonstration of how STEMLi can be used to explain standard deviation. This is done early on in the course, as is the idea of a distribution.
Actually, STEMLi is
an example of a presentation of descriptive statistics using the idea of a distribution. After all,
descriptive statistics is indeed distribution statistics!
This one tells the story of how interaction with the right visual tools can illicit the understanding of the subject. That the interaction is easy is fundamental.
The LP module is the original system that I devised and wrote about in the eJSiE journal. There are many interesting ideas about true technology enhanced learning expressed in the article.
This shows the use of the natural recursive features of Excel -- dragging rows and columns - to work in the
Mathematics of Finance. It also illustrates the stance that much of the study of finance can be done by concept equivalences. In reality, there are only few ideas in Finance, but there are many formulas. Most formulas can be seen to be equivalents of a fundemental set of them.
For instance, suppose you want to find the withdrawal amount so that a number of these equal withdrawals over a period of time will decrease an initial amount to zero. The formula could be derived by modeling. However, the formula can also be seen as the same one used to compute the deposit amount that one would put into an annuity to get the initial amount over the same period, irregardless of what is done with the withdrawals.
