Governmental Problem-Solving: A Computer Simulation of Municipal Budgeting.

1969 ◽  
Vol 24 (5) ◽  
pp. 1026
Author(s):  
Gordon Tullock ◽  
John P. Crecine ◽  
Donald Gerwin
Keyword(s):  
Computer Simulation ◽  
Problem Solving ◽  
Municipal Budgeting

Integrated Learning: Explicit Strategies and Their Role in Problem-Solving Instruction for Students with Learning Disabilities

1993 ◽  
Vol 59 (5) ◽  
pp. 444-455 ◽  
Author(s):  
Maurice Hollingsworth ◽  
John Woodward
Keyword(s):  
Computer Simulation ◽  
Learning Disabilities ◽  
Problem Solving ◽  
Secondary Students ◽  
Comparison Group ◽  
Strategy Group ◽  
Integrated Learning ◽  
Students With Learning Disabilities ◽  
Simulation Games ◽  
Experimental Group

This study investigated the effectiveness of an explicit strategy as a means of linking facts, concepts, and problem solving in an unfamiliar domain of learning. Participants were 37 secondary students with learning disabilities. All students were taught health facts and concepts, which they then applied to problem-solving exercises presented through computer-simulation games. Students in the experimental group were taught an explicit strategy for solving the problems; the comparison group was given supportive feedback and encouraged to induce their own strategies. The explicit strategy group performed significantly better on two transfer measures, including videotaped problem-solving exercises.

Health ways: a computer simulation for problem solving in personal health management

1986 ◽  
Vol 9 (2) ◽  
pp. 60-63 ◽  
Author(s):  
John P. Woodward ◽  
Douglas Carnine ◽  
Lorraine G. Davis
Keyword(s):  
Computer Simulation ◽  
Problem Solving ◽  
Health Management ◽  
Personal Health

scholarly journals From Penrose Equations to Zhang Neural Network, Getz–Marsden Dynamic System, and DDD (Direct Derivative Dynamics) Using Substitution Technique

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Dongqing Wu ◽  
Yunong Zhang
Keyword(s):  
Neural Network ◽  
Computer Simulation ◽  
Problem Solving ◽  
Dynamic System ◽  
Generalized Inverse ◽  
Computer Experiment ◽  
Time Discretization ◽  
Theoretical Derivation ◽  
Depth Study ◽  
Zhang Neural Network

The time-variant matrix inversion (TVMI) problem solving is the hotspot of current research because of its frequent appearance and application in scientific research and industrial production. The generalized inverse problem of singular square matrix and nonsquare matrix can be related to Penrose equations (PEs). The PEs implicitly define the generalized inverse of a known matrix, which is of fundamental theoretical significance. Therefore, the in-depth study of PEs might enlighten problem solving of TVMI in a foreseeable way. For the first time, we construct three different matrix error-monitoring functions based on PEs and propose the corresponding models for TVMI problem solving by using the substitution technique and ZNN design formula. In order to facilitate computer simulation, the obtained continuous-time models are discretized by using ZTD (Zhang time discretization) formulas. Furthermore, the feasibility and effectiveness of the novel Zhang neural network (ZNN) multiple-multiplication model for matrix inverse (ZMMMI) and the PEs-based Getz–Marsden dynamic system (PGMDS) model in solving the problem of TVMI are investigated and shown via theoretical derivation and computer simulation. Computer experiment results also illustrate that the direct derivative dynamics model for TVMI is less effective and feasible.

scholarly journals Learning Support Assessment Study of a Computer Simulation for the Development of Microbial Identification Strategies

2001 ◽  
Vol 2 (1) ◽  
pp. 18-24
Author(s):  
TRISTAN E. JOHNSON ◽  
CLARK GEDNEY
Keyword(s):  
Computer Simulation ◽  
Problem Solving ◽  
Cognitive Processing ◽  
Cognitive Skills ◽  
Identification Problem ◽  
Strategy Development ◽  
Bacterial Identification ◽  
Microbial Identification ◽  
Problem Solving Strategy ◽  
Solving Strategy

This paper describes a study that examined how microbiology students construct knowledge of bacterial identification while using a computer simulation. The purpose of this study was to understand how the simulation affects the cognitive processing of students during thinking, problem solving, and learning about bacterial identification and to determine how the simulation facilitates the learning of a domain-specific problem-solving strategy. As part of an upper-division microbiology course, five students participated in several simulation assignments. The data were collected using think-aloud protocol and video action logs as the students used the simulation. The analysis revealed two major themes that determined the performance of the students: Simulation Usage—how the students used the software features and Problem-Solving Strategy Development—the strategy level students started with and the skill level they achieved when they completed their use of the simulation. Several conclusions emerged from the analysis of the data: (i) The simulation affects various aspects of cognitive processing by creating an environment that makes it possible to practice the application of a problem-solving strategy. The simulation was used as an environment that allowed students to practice the cognitive skills required to solve an unknown. (ii) Identibacter (the computer simulation) may be considered to be a cognitive tool to facilitate the learning of a bacterial identification problem-solving strategy. (iii) The simulation characteristics did support student learning of a problem-solving strategy. (iv) Students demonstrated problem-solving strategy development specific to bacterial identification. (v) Participants demonstrated an improved performance from their repeated use of the simulation.

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