3Ms for Instruction, Part 2: Maple, Mathematica, and Matlab

Our intent with this Technology Review is to present a framework that helps educators make their own critical comparison of Maple, Mathematica, and Matlab as candidate computational productivity tools for use in their instructional programs. This is an alternative to our providing a critical comparison of our own, as would be conventional in a review. In the first installment, we provided a common set of talking points—concrete, understandable, existing applications as well as an idealized "paradigmatic" example—around which to build this framework. We also defined a particular subset of issues that undergraduate science and engineering educators face regarding computational technology. In this issue, we conclude this framework-building strategy by defining a compact, common feature set in which we can finally describe in some comparable detail how Maple, Mathematica, and Matlab work.