In an attempt to situate algorithms in some kind of context, many textbook authors and teachers employ story problems. This usually takes the form of embedding the values needed to solve an algorithm into a brief narrative or Situation.

In an attempt to make problem solving more meaningful, textbook authors, teachers, and professors assign story problems to students. These can be found at the backs of textbook chapters in virtually every science, mathematics, and engineering textbook in existence. Traditional methods for solving story problems require learners to

1. represent the unknowns by letters;
2. translate relationships about unknowns into equations;
3. solve the equations to find the value of the unknowns; and
4. verify values found to see if they fit the original problem (Rich, 1960).

Story problem solving requires not only calculation accuracy but also the comprehension of textual Information, the capacity to visualize the data, the capacity to recognize the semantic structure of the problem, the capacity to sequence their solution activities correctly, and the capacity and willingness to evaluate die procedure that they used to solve the problem.

Solving story problems is more difficult and ill-structured than algorithms because it requires the semantic comprehension of relevant textual information, the capacity to visualize the data, the capacity to recognize the deep structure of the problem, the capacity to correctly sequence their solution activities, and the capacity and willingness to evaluate the procedure that they used to solve the problem.