Computer-assisted Problem Solving Research Articles

ChemInform Abstract: Transparent Formal Methods for Reducing the Combinatorial Abundance of Conceivable Solutions to a Chemical Problem. Computer-Assisted Elucidation of Complex Reaction Mechanisms

Abstract Restraining the combinatorial flood of conceivable solutions to chemical problems by formal means is discussed. An algebraic model of the logical structure of constitutional chemistry not only serves as the theoretical foundation of the inference engines in strictly logic-orientated chemical computer programs, but also provides a conceptual framework for non-arbitrary, transparent procedures for reducing the combinational abundance of conceivable solutions to given chemical problems. Diverse procedures are available to provide efficient guidance on routes from a chemical problem to its chemically most meaningful solutions. The division of problems into subsidiary problems, the bilateral alternative to monolateral approaches, and the hierarchic classification of results, prior to selecting individual solutions, is highly effective in computer-assisted problem-solving.

Transparent formal methods for reducing the combinatorial abundance of conceivable solutions to a chemical problem : Computer-assisted elucidation of complex reaction mechanisms

Restraining the combinatorial flood of conceivable solutions to chemical problems by formal means is discussed. An algebraic model of the logical structure of constitutional chemistry not only serves as the theoretical foundation of the inference engines in strictly logic-orientated chemical computer programs, but also provides a conceptual framework for non-arbitrary, transparent procedures for reducing the combinational abundance of conceivable solutions to given chemical problems. Diverse procedures are available to provide efficient guidance on routes from a chemical problem to its chemically most meaningful solutions. The division of problems into subsidiary problems, the bilateral alternative to monolateral approaches, and the hierarchic classification of results, prior to selecting individual solutions, is highly effective in computer-assisted problem-solving.

The Phases of Computer-assisted Problem Solving

Knowledge and skill requirements: pupils should know the listing and sequence of basic phases in computer-assisted problem solving and should be given a general understanding of the methods of mathematical modeling.

What's Going On…

CAPS. The Computer Assisted Problem Solving (CAPS) Project is in its second year of development in the Rochester (Minnesota) Public Schools. The primary goal of CAPS is to provide elementary school students (K-6) with opportunities to practice the skills involved in problem solving in order to improve their confidence and competence as problem solvers. In the first year of the project, the staff reviewed learning theory and problem-solving research in order to develop a problem-solving skill matrix. The matrix includes problem-solving techniques and aids in the areas of memory, cognitive skills, cognitive control strategies, and creativity. The major focus of the project this year is to develop and field test computer software and classroom activities in the area of memory. Inservice training will also be prepared for teachers with an emphasis on recognizing the difference between problem-solving exercises (practice) and novel problems (true problem solving). CAPS is funded by Title IV-C. For more information contact Donna Stanger, Project Director CAPS, Rochester Public Schools, 903 West Center, Rochester, MN 55901.

Computer-Assisted Problem Solving in School Mathematics

Computer-Assisted Problem Solving in School Mathematics

Computer-Assisted Problem Solving in School Mathematics

Computer-assisted problem solving can be characterized by student-generated computer programs used to explore mathematical concepts, principles, and processes. This paper presents a brief rationale for using the computer as an inquiry tool to extend mathematical instruction. 2 investigations are reported in which seventh- and eleventh-grade mathematics students wrote computer programs in the programming language BASIC in their study of selected mathematical content. It was hypothesized that the activity of designing a computer program, studying its output, and refining or “debugging” the algorithm would positively affect mathematical performance. Data were collected on experimental and control Ss over a 2-year period, the second year representing a refinement and replication of the experiment. Comparisons involving criterion measures of learning, retention, and transfer were made using analysis of variance and covariance and item-proportions procedures. Results support this computer usage with selected content, process goals, and student abilities.