Metaheuristics are optimization algorithms that efficiently solve a variety of complex combinatorial problems. In psychological research, metaheuristics have been applied in short-scale construction and model specification search. In the present study, we propose a bee swarm optimization (BSO) algorithm to explore the structure underlying a…

The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…

Learning path generation involves the computation of learning trajectories to personalize academic instruction to prevent school problems. The Educational Planning Problem (EPP) considers generating personalized learning paths by scheduling activities that satisfy expected grades while minimizing plans makespan. In this work, we propose two…

Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…

Student assignment algorithms have far reaching implications for families, the education system, and for society as a whole. Motivated by operational challenges faced by the San Francisco Unified School District (SFUSD), we use a mechanism design framework to develop, operationalize, and streamline algorithmic student matching policies in San…

Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical…

Presents a variation of a "greedy" algorithm that can be used in test-assembly problems. The algorithm, the normalized weighted absolute-deviation heuristic, selects items to have a locally optimal fit to a moving set of average criterion values. Demonstrates application of the model. (SLD)

Describes an interactive procedure for multiobjective asymmetric unidimensional seriation problems that uses a dynamic-programming algorithm to generate partially the efficient set of sequences for small to medium-sized problems and a multioperational heuristic to estimate the efficient set for larger problems. Applies the procedure to an…

The algo-heuristic theory is concerned with identifying unobservable cognitive processes and their unconscious component cognitive operations, including learning how to describe them algorithmically and heuristically, and how to devise specific instructional tools (algorithmic and heuristic) to develop cognitive processes much faster. (BW)

Discusses algorithmic problem solving in computer science education, particularly algorithmic insight, and focuses on the relevance and effectiveness of the heuristic simplifying constraints which involves simplification of a given problem to a problem in which constraints are imposed on the input data. Presents three examples involving…

Three experienced and eight novice physicians were asked to solve three problems. Results indicated that the ability to incorporate contextual information contributed to effective solutions. Experienced physicians tended to use more inclusive approaches, although both groups demonstrated premature diagnostic bias. (SK)

This introductory article defines and delimits expert systems. The discussion covers the concepts of artificial intelligence, the components of an expert system, and the significance of expert systems when compared to more traditional decision making tools. (CLB)

Views information as residual or catalytic form of energy which regulates other forms of energy in natural and artificial systems. Parallel human information processing (production systems, algorithms, heuristics) and information measurement are discussed. Suggestions for future research in area of parallel information processing include a matrix…

Considers three powerful techniques--heuristics, context trees, and search via backward chaining--that a knowledge engineer might employ to develop an expert system to automate performance engineering, i.e., the branch of instructional technology that focuses on the problems of business and industry. (MBR)

Many important human activities involve accomplishing goals without a script. There is no formula for true problem-solving. Heuristic, cognitive "rules of thumb" are the problem-solver's best guide. Learners should understand heuristic tools such as means-end analysis, working backwards, successive approximation, and external representation. Since…