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This paper describes an investigation of problem sequencing as part of a symposium presenting theoretical concerns and research findings regarding several diverse types of strategies for designing and presenting instructional materials. The first step involved analyzing a set of problems, to determine the knowledge (rules) required for solving the problems. A set of geometric construction problems was analyzed using a method for deriving and simplifying rules or algorithms for solving the problems. Next, assumptions were adopted concerning how subjects learn and apply rules to solve problems. A computer was programmed according to these assumptions, and given some of the simplified rules identified during the previous step, in order to simulate some aspects of subjects' problem-solving and learning. Various problem sequences were then given to the program, to identify those that were solvable and "learnable." Finally, for initial evaluation of the approach, sequences that were learnable for the program were given to subjects, whose performance was compared with the performance of subjects given random or learner-controlled sequences. (Author/MLF)

The first section of this course on programming introduces LISP as a programming language designed to do symbol manipulation, with consequent prevalence in auto-instructional (AI) work. A programming language specifies in its description a number of primitive operations which the computer knows how to perform. An algorithm is the set of instructions which constitutes a description of the method by which the task can be performed. This algorithm must be written in the programming language which the computer can deal with. The constructs (elements of LISP) that work in algorithms are described and an example task provided. LISP is a functional language, in that its instructions consist of directives to apply some function to some argument. Part 1 of the course concludes with a description of some of LISP's functions, and Part 2 deals with its symbol manipulation functions, specifically in manipulating LISP constructs known as lists. Part 3 gives instruction in writing inherently recursive functions non-recursively. Practice exercises follow each section of the course. (CLK)

Several computer programs were developed to solve various versions of the quadratic capacitated facilities location problem. Matrices, which represent various business costs, are defined for the factors of sites, facilities, customers, commodities, and production units. The objective of the program is to find an optimization matrix for the lowest cost, given the restrictions of the problem. The algorithms, COMPAT and SWITCH, are devised to solve portions of the problem with the subroutines, CHANGE and MUNKRES. These programs are tried on several different problems, and the different results are compared. Suggestions for future research, particularly using Gilmore's branch and bound technique, are made. (WH)