Kind Of Problem Solving Research Articles

Reasons for early marriage of women in Zahedan, Iran: a qualitative study

BackgroundEarly marriage occurs in some regions of the world. Given that early marriage can have many negative consequences for girls by affecting their physical, mental, and social health, the purpose of this study was to investigate the reasons for early marriage from the perspective of women who had experienced it in Zahedan, Iran.MethodsThis qualitative research was conducted based on the qualitative content analysis method in 2020–2021. The target population included women aged 18–35 living in Zahedan who were married under the age of 18 years. Purposeful sampling was used to select the participants. In order to collect data, in-depth interviews were performed to decipher the reasons for early marriage from these women’s perspectives. A total of 36 interviews were conducted from October to December 2020 until reaching theoretical saturation. Conventional content analysis was used to analyze the data and extract the relevant concepts and categories.ResultsThe analysis of the interviews in this study revealed three main categories:(1) “early marriage as a transcendental coercion” ( early marriage as a cultural heritage and early marriage as a control tool, girls’ weaknesses and inability to resist, dominant attitudes toward gender and gender restrictions), (2) “early marriage as a solution or a kind of problem solving” (escape from undesirable family environment, escape from financial poverty, and strategic escape from an unpleasant situation), and (3) “early marriage as a voluntary act” (real agency and imaginary agency). To substantiate these findings, we presented excerpts from the interviews conducted with the participants.ConclusionThe results of this study suggest a multidimensional picture of early marriage. It seems that improving cultural conditions and empowering families and girls in various areas, including marriage, can reduce the rate of early marriage and/or at least mitigate its undesirable consequences.

AI, visual imagery, and a case study on the challenges posed by human intelligence tests

Observations abound about the power of visual imagery in human intelligence, from how Nobel prize-winning physicists make their discoveries to how children understand bedtime stories. These observations raise an important question for cognitive science, which is, what are the computations taking place in someone’s mind when they use visual imagery? Answering this question is not easy and will require much continued research across the multiple disciplines of cognitive science. Here, we focus on a related and more circumscribed question from the perspective of artificial intelligence (AI): If you have an intelligent agent that uses visual imagery-based knowledge representations and reasoning operations, then what kinds of problem solving might be possible, and how would such problem solving work? We highlight recent progress in AI toward answering these questions in the domain of visuospatial reasoning, looking at a case study of how imagery-based artificial agents can solve visuospatial intelligence tests. In particular, we first examine several variations of imagery-based knowledge representations and problem-solving strategies that are sufficient for solving problems from the Raven’s Progressive Matrices intelligence test. We then look at how artificial agents, instead of being designed manually by AI researchers, might learn portions of their own knowledge and reasoning procedures from experience, including learning visuospatial domain knowledge, learning and generalizing problem-solving strategies, and learning the actual definition of the task in the first place.

Crises and Systems Thinking

Tragedy, disaster or disorder precedes a situation labelled ‘crisis’, if it occurs. Tragedy, disaster or disorder is potentially present in all scenarios which function according to expectations or normally, they are dormant in any part of the world. A structural or linguistic model of a scenario reveals its constituents i.e. objects or agents, their properties and qualified interactions as seen by an investigator. Thus, objects and interactions are open to unravelling those features which are considered prone to tragedy or vulnerable to disasters or possibly incurring disorder, each to a varying degree. Therefore, new structures can be foreseen, planned, designed and introduced into a scenario to reduce chances of disasters occurring and possibly followed by crisis situations. A linguistic, operational model also allows the analysis and simulation of scenarios when real or imaginary crisis has occurred and crisis management has been introduced with effectiveness measured by ‘certainty factors’, for example. Currently workers in the field of crisis appear to concentrate on its nature and management and express their ideas in a descriptive manner. In this paper this is supplemented by showing how background scenarios can be operationally modelled in which potential tragedies, disasters or disorders are embedded. Crisis management is seen as a kind of problem solving and as such is amenable to being engineered by the method introduced here.

The Selection of Railway System Projects with Multi Creteria Decision Making Methods: A Case Study for Istanbul

Railway systems are preferred to solve traffic problems and are becoming backbones of transportation in cities especially in metropoles where transportation demands are high. At the point of enabling railway system investments which need big money source, decision taking at evaluation process especially for developing countries, is taking big import. In the literature, Net Present Value Analysis (NPVA), Benefit Cost Analysis (BCA) and Internal Efficiency Analysis (IEA) methods, which only take into account the numerical values, are used in the evaluation of transportation investments. Apart from these methods, another method used in this field is Multi Criteria Decision Making (MCDM). This method is not just evaluating economic sides of investments like previous methods, it is also making possible evaluating both verbal and economic values together by handling environment compatibility, relevance to historic tissue, integration with current transportation nets and using fields. In this study, prioritization will be made among alternative rail system projects planned to be used in Istanbul by utilizing the proposed MCDM methods to be used in the evaluation of transportation investments. For this purpose, Istanbul Metropolitan Municipality (IMM) projects, which are planned to be constructed throughout Istanbul, are considered as an alternative. As a result of the comprehensive literature study, the criteria were identified by determining the criteria used in the evaluation of transportation investments in the world and then by the experts who decided which of these criteria would be appropriate for Istanbul. At this stage, the most preferred Analytical Hierarchical Process (AHP) for transportation investment evaluation problems was used and alternative weights were found by using the Best Worst Method (BWM) which had not been used before in this kind of problem solving, and the comparison of two methods was made. As a result of the analysis, the findings were evaluated and several recommendations were made to determine the most appropriate project among the ones to be planned.

Problem Solving in Nishikant Kamat’s Movie Drishyam

.

Competition between Cognitive Control and Encapsulated, Unconscious Inferences: Are Aha-Experiences Special?

Competition between Cognitive Control and Encapsulated, Unconscious Inferences: Are Aha-Experiences Special?

Cognitive artifacts as a window on design

We are investigating information analysis as a kind of problem solving in which teams are presented with a collection of facts regarding people, places and events, and then identify underlying connections, patterns, and plans in order to draw specific conclusions. The teams spontaneously created a variety of artifacts to hold and organize problem information, and practices to simplify and regularize their collaborative interactions around these artifacts. In this paper, we analyze the artifacts and practices as a potential source of insight into how this problem solving activity could be supported by an interactive system design.

How to solve a mechanical problem: the relevance of visible and unobservable functionality for kea

Animals sometimes succeed quickly in solving a mechanical problem that is a modification of one they have previously learnt to solve. However, they may do so by attending to the visible features of the relevant physical dimension without knowing its causal functionality, if that is not directly perceivable. This kind of problem solving can be tested by simultaneously offering two mechanical devices with the same visual features but different inherent appropriateness for problem solving. Here, we provide data collected by following this procedure for the first time in a bird species. Captive kea, Nestor notabilis, a parrot species highly interested in the affordances of objects, were offered a mechanical problem in which they had to remove a baited tube from one of two upright poles where removal was blocked at the end of one pole but not the other. With extended but not with restricted exploration of a baseline apparatus, the kea immediately succeeded in removing the tube from an apparatus that had modified pole ends when they were able to visually observe (without touching) that one of these ends would block tube removal but the other would not. However, when the kea were allowed to explore two poles that had a removable and a fixed obstruction where the difference in function was not visible, they preferred the removable one during unbaited exploration but failed afterwards to push a tube to the end of the pole with the loose structure during subsequent baited test trials. Thus, in spite of the speed with which the kea learnt the tasks, there was no indication that they understood the underlying unobservable causal structure of the problem.

Preservice teachers’ performances at mathematical modeling process and views on mathematical modeling

In changing world conditions what we expect fundamentally from our students are to cope with the problems they confronted in their lives thinking creatively and analytically. Mathematical modeling is a kind of problem solving in which real life situations are expressed mathematically. The purpose of this study is to evaluate the preservice mathematics teachers’ performances in the mathematical modeling process and to determine their views of modeling process. With this aim 4 modeling activities were given to 60 preservice teachers in a teacher training program. Afterwards semi structured interviews were conducted with four of these students. Results were interpreted in the context of teachers’ competencies in modeling process.

Assessment Centers: What's New?

Introduction: What are Assessment Centers While assessment centers may include a variety of testing techniques, all assessment centers include job simulation exercises. In fact, the core concept in assessment centers is simulation. Assessment centers allow candidates to demonstrate job-related dimensions of performance (worker characteristics) in job simulation exercises that replicate the important situations that occur on the job. It is extremely important that the exercises simulate the important conditions and contexts that occur on the target job(s). The reason job-related simulations are so important is that the contexts within which the performance dimensions are measured have a strong effect on the achieved by candidates. For example, candidate will vary on a performance dimension such as problem depending on the types of exercises used to measure the dimension. This occurs because the exercise, in effect, further defines the dimension or what aspects of the dimension are being evaluated. For example, the behaviors associated with problem solving are different in a group discussion exercise dealing with current organizational issues from the behaviors demonstrated in a written exercise dealing specifically with budget issues. These two exercises measure different kinds of problem solving. Since competence is at least partially situation specific, it is of little value to learn that candidates are highly effective in situations or contexts that rarely, if ever, occur on the job. So, the goal of assessment center exercise selection and development is to simulate the most important tasks of the target job(s) in order to provide the candidates with the opportunity not only to demonstrate the important skills/dimensions, but also the opportunity to demonstrate the extent to which those worker characteristics can be applied effectively in the most important situations and settings on the job. The best definition and explanation of what assessment centers are (and are not) is provided by the Guidelines and Ethical Considerations for Assessment Center Operations (Guidelines). The fourth and most recent edition of these guidelines was endorsed by the 28th International Congress on Assessment Center Methods and published in IPMA's Public Personnel Management, Volume 29, No. 3, Fall 2000. As explained in the Guidelines, a procedure should not be represented as an assessment center unless it includes at least one, and usually several, job-related simulations that require the assessee to demonstrate a constructed response. These guidelines also provide recommendations on all of the major components of the assessment center method, including job analysis, assessor training, candidate orientation and rights of participants. How are assessment center results being used? While the majority of assessment centers (ACs) in the public sector are being used to assist in making selection and promotion decisions (and the majority of these for law enforcement and fire service promotions), ACs can also be valuable as career development, organizational development and succession planning tools. A major difference when using assessment centers for these purposes (in addition to how the information is used) is that the exercises are much less job specific. Rather than using dimensions and exercises related to a specific target job or job level, the focus becomes broader. The target for dimension selection and exercise development becomes several levels of management and the skills and situations common to all or most of those higher management levels. When used primarily for career development, the focus shifts from the accuracy of the scores to the quality of the assessor comments. Rather than the primary goal being an accurate rank-ordered list of candidates, the goal becomes quality performance feedback and developmental suggestions for every participant. …

A new approach to ADT specification support based on reuse of similar ADT by the application of Case-Based Reasoning

Abstract Data Type (ADT) is a powerful tool having a very good mathematic basis called many-sorted algebra and is also combined into several Formal Description Techniques (FDTs). By using ADT, a protocol or a software system can be specified in a very abstract way. It also facilitates the verification and validation of the specified system. However, in practice ADT is rarely used because it is difficult for a non-ADT expert to specify. As a consequence of this, in order to promote the widespread use of ADT and FDT, a support method for ADT specification is necessary. Unfortunately, there is almost no such a support method so far. We propose an ADT specification support method in terms of support system based on Case-Based Reasoning (CBR) which is a kind of problem solving by reusing solutions of the existing similar problem with some appropriate modifications. CBR has been used in some researches. But there is no research which uses this technique for ADT specification support so far. The support system can ease the specification of ADT and prevent the user from spending too much time and effort in specifying the whole ADT from the beginning. Our support system consists of four parts: (1) Case base of ADTs; (2) Requirement Acquisition Template; (3) Search mechanism for finding the most similar case in (1); (4) Modifier for modifying the retrieved case to meet the requirement of user. Among these parts, the core of the support system is the search mechanism which is based on the definition of similarity of ADTs. In this paper, we first propose an ADT specification model which defines a data carrier part of an ADT as a combination of constructors of four patterns. Based on the specification model, a similarity definition is given. Furthermore, we have designed the support system. Finally, in order to evaluate the effectiveness of the system, we experimented with data types of service and protocol in the data communication field. From the evaluation, the effectiveness of the system is ensured.

Cognitive processes in well‐defined and ill‐defined problem solving

AbstractWe investigated the relationship between two kinds of problem solving using Kitchener's model of hierarchical cognitive processing. We predicted that performance on well‐defined problems (i. e. those with a single, guaranteed solution) would be independent of ill‐defined problems (i. e. those with multiple, non‐guaranteed solutions). We also predicted that self‐reported epistemic beliefs (i. e. assumptions about the nature and acquisition of knowledge) would be related to ill‐defined, but not well‐defined, solutions. Results confirmed these predictions. We concluded that well‐defined and ill‐defined problems require separate cognitive processes and that epistemic beliefs play an important role in ill‐defined problem solving. These findings supported Kitchener's three‐level model of problem solving.

Teaching Mathematics With Technology: Finding Number Patterns

Students need to know which technological tool is appropriate to use with various kinds of problem solving. The computer is not always the most efficient device to use.

Creativity in Small Groups

A study of how small groups of people can combine for maximum creativity. Hare's approach is to treat creativity as a kind of problem solving, and to look at the general characteristics of small groups. The first part of the book introduces four theoretical perspectives for understanding group activity. Part Two is written for the theorist who wishes to have a framework for understanding group structure and dynamics. Part Three compares individual and group problem-solving, highlighting the differences in patterns of interaction associated with the size of the group. A review for researchers, theorists, and those more actively involved in groups, this book draws on Hare's extensive research and practical experience. `Hare does a very commendable job of presenting a well-documented account of the major areas developed by small-group research...I heartily recommend the book to persons working in a small-group context, especially if they are interested in traditional functionalists' thought.' -- Contemporary Sociology, Vol 12 No 3, May 1983

Learning in Medicine

"MEDICINE begins in philosophy; philosophy ends in medicine" is an aphorism attributed to Aristotle. I like its demand to connect our thinking as physicians with our thinking in other dimensions. I begin by asking the question: If medicine begins in philosophy, what is the philosophy? I do so in the belief that we stand in serious need of revised designs for medical education and that any such designs must be based on an answer to this question.I will develop the thesis that practicing medicine is a kind of problem solving. Physicians help their patients to face, define and solve . . .

The ubiquity of discovery

As scientists interested in studying the phenomenon of “intelligence”, we first choose a view of Man, develop a theory of how intelligent behavior is managed, and construct some models which can test and refine that theory. The view we choose is that Man is a processor of symbolic information. The theory is that sophisticated cognitive tasks can be cast as searches or explorations, and that each human possesses (and efficiently accesses) a large body of informal rules of thumb (or heuristics) which constrain his search. The source of what we colloquially call “intelligence” is seen to be very efficient searching of an a priori immense space. Some computational models which incorporate this theory are described. Among them is AM, a computer program that develops new mathematical concepts and formulates conjectures involving them; AM is guided in this exploration by a collection of 250 more or less general heuristic rules. The operational nature of such models allows experiments to be performed upon them, experiments which help us test and develop hypotheses about intelligence. One interesting finding has been the ubiquity of this kind of heuristic guidance: intelligence permeates everyday problem solving and invention, as well as the kind of problem solving and invention that scientists and artists perform. The ultimate goals of this kind of research are (i) to de-mystify the process by which new science and art are created, and (ii) to build tools (computer programs) which enhance man's mental capabilities.

An information-processing model of one kind of problem solving.

An information-processing model of one kind of problem solving.