This paper uses graphics and animations to illustrate how to construct root and weight diagrams for Lie algebras, and how the root and weight diagrams can be used to identify subalgebras.

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A Biological ESTEEM module from the Ecology Category. This worksheet compares user-input growth data with predictions under linear, exponential, and logistic models of growth.

An **article** that shows how to implement the Lanchester Combat Model in an interactive Excel spreadsheet

This gallery of images and animations shows many examples of how the POVray ray-tracing software can be used to display examples in three-dimensional geometry.

Osslets (open source, sharable mathlets) are free and flexible interactive components you can easily add to your Web pages. The collection includes ready-to-use curriculum units.

An **article** on the impact of technology in the teaching and learning of mathematics courses preceding calculus.

This dynamic Java applet developed with support from the NSF (Dynamic Visualization Tools for Multivariable Calculus, DUE-CCLI Grant #0736968)) allows the user to simultaneously graph multiple 3D surfaces, space curves, parametric surfaces, vector fields, contour plots, and more in a freely rotatable 3D plot. This tool is intended as a dynamic visualization and exploration environment for multivariable calculus. Use it to illustrate the geometric relationships of many of the concepts of multivariable calculus, including dot and cross products, velocity and acceleration vectors for motion in the plane and in space, the TNB-frame, the osculating circle and curvature, surfaces, contour plots and level surfaces, partial derivatives, gradient vectors and gradient fields, Lagrange multiplier optimization, double integrals as volume, defining the limits of integration for double and triple integrals, parametric surfaces, vector fields, line integrals, and more. See the corresponding web page for documentation and a list of guided explorations developed for students to use with this exploration applet.

This ESTEEM module in the Biometrics Category leads the user through several different methodologies for applying Bayesian probabilities to real life examples and problems.