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A search of MERLOT materialsCopyright 1997-2014 MERLOT. All rights reserved.Mon, 1 Sep 2014 08:29:58 PDTMon, 1 Sep 2014 08:29:58 PDTMERLOT Search - category=2513http://www.merlot.org:80/merlot/images/merlot.gif
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4434Cut-the-Knot!
http://www.merlot.org/merlot/viewMaterial.htm?id=78198
This site is the parent site of an extensive collection of interactive mathematics authored by Alexander Bogomolny and includes an interactive monthly column . The content is accessible to the casual reader but offers much depth along with links to other high-quality resources. Altogether, this site is a mathematician's delight.Fibonacci Numbers and the Golden Section
http://www.merlot.org/merlot/viewMaterial.htm?id=89324
This excellent site contains a large and interesting selection of material on Fibonacci Numbers and their myriad related concepts. It includes web and text references to the rich literature of Fibonacci numbers. It also features a variety of images, graphics and animations. Many of the topics include student investigations for NCTM standard type explorations. The content includes standard motivational examples and applications in nature, but also mathematical explanations and puzzle pages. The site has already won several awards.MacTutor History of Mathematics Archive
http://www.merlot.org/merlot/viewMaterial.htm?id=89142
An award-winning site concerning the history of mathematics. In-depth coverage of numerous people, topics, mathematical curves, and more. Extensively cross-linked; powerful search engine. Rich and growing source of materials.Larry Green's Applet Page
http://www.merlot.org/merlot/viewMaterial.htm?id=77279
Contains dozens of interactive tutorials and discovery exercises for beginning, intermediate, and college algebra.Rice Virtual Lab in Statistics
http://www.merlot.org/merlot/viewMaterial.htm?id=79148
Online statistics open textbook and additional resources to assist students in understanding of statistics. Topics covered include Analysis of Variance, Boxplot, Confidence interval, Contrast among means, Correlated t-test, Correlation, Histogram, Independent groups t-test, Regression, Repeated measures ANOVA, and t-test. The applets in the simulations, demonstrations, an d caste studiesare in the public domain and can therefore be used without restriction. Simulations and demonstrations and source code are available for download. To view a video of the award winning author, go to View Rice Virtual Lab - Statistics Award Winner 2007 video StatCrunch
http://www.merlot.org/merlot/viewMaterial.htm?id=74665
The package was created to solve many of the problems which exist with the delivery and use of modern statistical software. Many times statisticians develop procedures in languages such as Splus, SAS, Minitab, etc.., which are very specific to statisticians. Students and other potential users may not have access to these languages, and therefore may not be able to use the procedures. By using Java and the World Wide Web, StatCrunch should reach the broadest possible audience of any statistical software of its kind. StatCrunch was chosen as the 2005 Classics Award winner for the Statistics discipline for several reasons. StatCrunch allows any student with internet access the ability to have a reasonably full featured statistical analysis program for minimal cost. This means that students who are taking courses through distance education can now have the same software as students on campus. Students who are working on a statistics assignment at home can now have the same software as they would in a lab on campus. We also believe that StatCrunch represents the beginning of a paradigm shift. As time moves forward we believe that most introductory statistics courses will be taught not with installed software but with internet based software. It is proof that the major obstacles that stand in the way of integrating statistical software into the introductory classroom can be surmounted.Exploring Multivariable Calculus
http://www.merlot.org/merlot/viewMaterial.htm?id=437177
The main goal of this project is to improve student understanding of the geometric nature of multivariable calculus concepts, i.e., to help them develop accurate geometric intuition about multivariable calculus concepts and the various relationships among them.To accomplish this goal, the project includes four parts:· Creating a Multivariable Calculus Visualization applet using Java and publishing it on a website: web.monroecc.edu/calcNSF· Creating a series of focused applets that demonstrate and explore particular 3D calculus concepts in a more dedicated way.· Developing a series of guided exploration/assessments to be used by students to explore calculus concepts visually on their own.· Dissemination of these materials through presentations and poster sessions at math conferences and through other publications.Intellectual Merit: This project provides dynamic visualization tools that enhance the teaching and learning of multivariable calculus. The visualization applets can be used in a number of ways:- Instructors can use them to visually demonstrate concepts and verify results during lectures.- Students can use them to explore the concepts visually outside of class, either using a guided activity or on their own.- Instructors can use the main applet (CalcPlot3D) to create colorful graphs for visual aids (color overheads), worksheets, notes/handouts, or tests. 3D graphs or 2D contour plots can be copied from the applet and pasted into a word processor like Microsoft Word.- Instructors will be able to use CalcPlot3D to create lecture demonstrations containing particular functions they specify and/or guided explorations for their own students using a scripting feature that is being integrated with this applet.The guided activities created for this project will provide a means for instructors to get their students to use these applets to actively explore and “play” with the calculus concepts.Paul Seeburger, the Principal Investigator (PI) for this grant project, has a lot of experience developing applets to bring calculus concepts to life. He has created 100+ Java applets supporting 5 major calculus textbooks (Anton, Thomas, Varberg, Salas, Hughes-Hallett). These applets essentially make textbook figures come to life. See examples of these applets at www.monroecc.edu/wusers/pseeburger/.Broader Impacts: This project will provide reliable visualization tools for educators to use to enhance their teaching in calculus and also in various Physics/Engineering classes. It is designed to promote student exploration and discovery, providing a way to truly “see” how the concepts work in motion and living color. The applets and support materials will be published and widely disseminated through the web and conference presentations.Graph Theory Lessons
http://www.merlot.org/merlot/viewMaterial.htm?id=84776
The applets contain topics typically found in undergraduate graph theory and discrete structures classes like null graphs, the handshaking lemma, isomorphism, complete graphs, subgraphs, regular graphs, platonic graphs, adjacency matrices, graph coloring, bipartite graphs, simple circuits, Euler and Hamilton circuits, trees, unions and sums of graphs, complements of graphs, line graphs, spanning trees, plane graphs, shortest paths, minimal spanning trees. The applet utilizes Petersen software written by the author. Peterson can draw, edit and manipulate simple graphs, examine properties of the graphs, and demonstrate them using computer animation.Rossman/Chance Applet Collection (Statistics/Probability)
http://www.merlot.org/merlot/viewMaterial.htm?id=89688
A collection of applets designed to illustrate various topics in statistics and probability. Topics include Simulating Confidence Intervals for Population Parameter, Behavior of Regression Line, Reeses Pieces, Histogram Bin Width, Sampling Senators, Sampling Pennies, Dotplot Summaries, Guess the Correlation.Algebra2go: An Online Supplemental Instruction Tool Array
http://www.merlot.org/merlot/viewMaterial.htm?id=377756
Algebra2go is a free unrestricted collection of pre-algebra and algebra related study materials designed to address the affective dimensions of student learning.