Strategies for rapid mental computation are explained, including multiplying by 11 (or 21, 31, etc.); adding columns of numbers; and multiplying 2-digit numbers. Rapid mental computation is suggested as a motivator for investigating the underlying mathematical principles. (DB)

Explains an algorithm which details procedures for solving a broad class of genetics problems common to pre-college biology. Several flow charts (developed from the algorithm) are given with sample questions and suggestions for student use. Conclusions are based on the authors' research (which includes student interviews and textbook analyses).…

The factors which have a major impact on the success in producing effective readable text in both the content as well as to the way it is presented are outlined. A discussion of the objectives of the learner and the characteristics of the text that facilitate student learning is presented. (KR)

Discusses the differences between problems and exercises in chemistry, and some of the difficulties that arise when the same methods are used to solve both. Proposes that algorithms are excellent models for solving exercises. Argues that algorithms not be used for solving problems. (TW)

Discusses the difference between a generic chemistry problem (one which can be solved using an algorithm) and a harder chemistry problem (one for which there is no algorithm). Encourages teachers to help students recognize these categories of problems so they will be better able to find solutions. (TW)

Discusses the differences between problems and exercises, the levels of thinking required to solve them, and the roles that algorithms can play in helping chemistry students perform these tasks. Proposes that students be taught the logic of algorithms, their characteristics, and how to invent their own algorithms. (TW)

Following a short introduction on the rationale and purpose for using algorithmic structures in the teaching of algebra, two topics from elementary algebra are presented in relation to control structures from computer programing, specifically: the multiplication of polynomials defined in terms of nested loops, and the distributive property…

Algorithmic and investigative approaches to mathematics are compared and discussed. Their mutually contradictory spirit is explored. Examples of the application of each method to a mathematics problem are presented. (CW)

Differentiates between problems, exercises and algorithms. Discusses the role of algorithms in solving problems and exercises in chemistry. Suggests that very real differences exist between solving problems and exercises, and that problem solving steps can be and should be taught in chemistry education. (TW)

Examines the hypothesis that there are preliminary stages in problem solving that are often neglected in teaching chemistry. Discusses correlations calculated between the student's ability to handle disembedding and cognitive restructuring tasks in the spatial domain and ability to solve chemistry problems. (TW)

Described are ideas for the development of problem solving in the context of chemistry. Strategies for improving students' problem solving abilities are included. (KR)

Proposed is a way for teachers to distinguish between rich, challenging material that encourages mathematical thinking and material that is unsuitable. Included are multistep problems that encourage a broader understanding of mathematics. (KR)

Described are four classroom activities that may be interspersed into a curriculum or offered as homework. Systematic procedures, alternative strategies, and trial and error are emphasized in these counting exercises. (KR)

Compares performances of students on gas-law problems that require two distinct approaches, either the algorithmic technique or the conceptual gestalt. Indicates that student effectiveness is considerably different utilizing each approach and that training or experience with the algorithm process should not be expected to facilitate the…

Defines M-demand as the maximum number of schemes that the subject must activate simultaneously in the course of executing a task. Discusses the effect of M-demand on problem solving. Uses algorithms to reduce M-demand. Describes the role of algorithms in problem solving. (MVL)