Present and compare students' different solutions to the problem. Do this with the class as a whole. Discuss the pros and cons of each solution.
Note that several solutions may be equally valid. Assure students that it's OK for some problems to have more than one acceptable answer, and help them see that they may have the expertise to determine for themselves which solutions are better than others and which are equivalent.
Review relevant terminology that has been introduced in context. One way to do this is to have the terms on a transparency * and ask the class to come up with definitions.
Review the lists of assumptions and questions about them that students made during the modeling process. Add to it as needed, and discuss which assumptions are better and worse. Point out to students that re-examining the assumptions is an important part of the modeling process. Remind them that the assumptions made can affect the quality or validity of the solution to the problem that was modeled.
Remind students that investigating often begins with one problem, but it ends with posing new extension problems that arose out of the investigative activities of solving the original problem.
Ask for observations and questions, reminding students of standard question openers (perhaps on a transparency*), and add the questions to the list begun before.
Work to include questions that motivate touring Algorithms, Applications, or Abstractions in the bottom diamond. Examples of such questions are available in Summary.
Copyright © 1999-2000 SciMathMN