Model Of Problem-solving Process Research Articles

A descriptive phase model of problem-solving processes

Complementary to existing normative models, in this paper we suggest a descriptive phase model of problem solving. Real, not ideal, problem-solving processes contain errors, detours, and cycles, and they do not follow a predetermined sequence, as is presumed in normative models. To represent and emphasize the non-linearity of empirical processes, a descriptive model seemed essential. The juxtaposition of models from the literature and our empirical analyses enabled us to generate such a descriptive model of problem-solving processes. For the generation of our model, we reflected on the following questions: (1) Which elements of existing models for problem-solving processes can be used for a descriptive model? (2) Can the model be used to describe and discriminate different types of processes? Our descriptive model allows one not only to capture the idiosyncratic sequencing of real problem-solving processes, but simultaneously to compare different processes, by means of accumulation. In particular, our model allows discrimination between problem-solving and routine processes. Also, successful and unsuccessful problem-solving processes as well as processes in paper-and-pencil versus dynamic-geometry environments can be characterised and compared with our model.

Development of a Knowledge Acquisition Support System Featuring Assembly of Logical Formulas and Logic Circuits Based on a Problem-Solving Process Model of the Japanese Patent Act

Development of a Knowledge Acquisition Support System Featuring Assembly of Logical Formulas and Logic Circuits Based on a Problem-Solving Process Model of the Japanese Patent Act

Self-Learning Support System about Learning Patent Act Based on the Problem-Solving Process Model Using Logical Structure of Legal Texts

Self-Learning Support System about Learning Patent Act Based on the Problem-Solving Process Model Using Logical Structure of Legal Texts

Development of a Collaborative Learning with Creative Problem-Solving Process Model in Ubiquitous Learning Environment

Development of a Collaborative Learning with Creative Problem-Solving Process Model in Ubiquitous Learning Environment

A Problem Solving Process Model for Personal Decision Support (PSPM-DS)

This article presents a Problem Solving Process Model for personal decision support (PSPM-DS). The model was used to provide decision support in the counseling of young adults facing difficulties in life decisions, in their career decision making, their intimate relationships, their choice of friends and life style, as well as, their academic or job performance. The model was also used as a consultancy methodology in the human resource department of two middle-size companies helping employees at all levels to cope with personal and interpersonal problems and conflicts within their organization. For the creation of the model, decision theory, systems thinking and soft system methodologies were used. The facilitating and counseling process follows the three generic phases of the decision making process, i.e. problem awareness, problem structuring, and problem evaluation, incorporating within them three different ways of problem representation, i.e. Future Scenarios frame, Multi-Attribute-Utility (MAU) frame, and Rule-base frame. The process focuses on the creation of a responsive, flexible and adaptive environment, which enhance exploration, creativity and freedom in the expression of feelings and desires and increase the awareness of the problem. The processes, frames and activities involved in the practical use of the three phases of the PSPM-DS are illustrated through a detailed case study.

Problem-solving restructuration: Elimination of implicit constraints

A general model of problem-solving processes based on misconception elimination is presented to simulate both impasses and solving processes. The model operates on goal-related rules and a set of constraint rules in the form of “ if (state or goal), do not (Action)” for the explicit constraints in the instructions and the implicit constraints that come from misconceptions of legal moves. When impasses occur, a constraint elimination mechanism is applied. Because successive eliminations of implicit constraints enlarge the problem space and have an effect on planning, the model integrates “plan-based” and “constraint-based” approaches to problem-solving behavior. Simulating individual protocols of Tower of Hanoi situations shows that the model, which has a proper set of constraints, predicts a single move with no alternative on about 61% of the movements and that protocols are quite successfully simulated movement by movement. Finally, it is shown that many features of previous models are embedded in the constraint elimination model.