Teaching and Learning Iterative Methods for Solving Linear Systems Using Symbolic and Numeric Software

An integral approach is presented to strengthen the teaching and learning processes in the environment of the undergraduate course Numerical Analysis (NA) for engineering, examining tha advantages of combining the symbolic and numeric paradigms. In particular, the methodology is illustrated with the iterative methods: Gauss-Seidel (GS) and Conjugated Gradient (CG), for the numeric solution of Linear Systems (LS). The computer tools MATLAB and MAPLE are used in a pedagogic model that requires the explicit definition of Prospective Learnings and Activities of Learning