Information Processing and Moral Problem Solving

2018 ◽  
Author(s):  
Cassey Lee
Keyword(s):  
Information Processing ◽  
Problem Solving ◽  
Moral Problem

scholarly journals AN OVERVIEW OF SWARM INTELLIGENCE IN ARTIFICIAL INTELLIGENT SYSTEMS

2021 ◽  
Vol 9 (08) ◽  
pp. 673-675
Author(s):  
Kalpana C. Dalwai ◽  
Keyword(s):  
Information Processing ◽  
Problem Solving ◽  
Swarm Intelligence ◽  
Intelligent Systems ◽  
Optimization Problems ◽  
Artificial Intelligent

Swarm intelligence refers to a kind of problem-solving ability that emerges in the interactions of simple information-processing units. The concept of a swarm suggests multiplicity, stochasticity, randomness, and messiness. Advancement of technology has led to problems that are complex and more challenging.Swarm intelligence techniques were mostly developed for solving optimization problems.

An Information Processing Analysis of Expert and Novice Teachers’ Problem Solving

1990 ◽  
Vol 27 (3) ◽  
pp. 533-556 ◽  
Author(s):  
H. Lee Swanson ◽  
James E. O’Connor ◽  
John B. Cooney
Keyword(s):  
Information Processing ◽  
Problem Solving ◽  
Novice Teachers ◽  
Expert And Novice

Ankle Bones, Rogues, and Sexual Freedom for Women

2011 ◽  
pp. 461-468
Author(s):  
Nigel K.L. Pope ◽  
Kevin E. Voges
Keyword(s):  
Information Processing ◽  
Data Analysis ◽  
Problem Solving ◽  
Computational Intelligence ◽  
History Of Mathematics ◽  
Volume Form ◽  
Paper Briefly ◽  
Sexual Freedom ◽  
History Of ◽  
And Control

In this chapter we review the history of mathematics-based approaches to problem solving. The authors suggest that while the ability of analysts to deal with the extremes of data now available is leading to a new leap in the handling of data analysis, information processing, and control systems, that ability remains grounded in the work of early pioneers of statistical thought. Beginning with pre-history, the paper briefly traces developments in analytical thought to the present day, identifying milestones in this development. The techniques developed in studies of computational intelligence, the applications of which are presented in this volume, form the basis for the next great development in analytical thought.

Hierarchical Organization as a Facilitator of Information Management in Human Collaboration

2009 ◽  
pp. 44-109 ◽  
Author(s):  
Khaled Ahmed Nagaty
Keyword(s):  
Information Processing ◽  
Problem Solving ◽  
Information Management ◽  
Structural Model ◽  
Hierarchical Organization ◽  
Team Collaboration ◽  
Management Processes ◽  
The Relationship ◽  
Role Of Information

The purpose of this chapter is to discuss the relationship between three entities: hierarchical organization, information management and human collaboration. This relationship is composed of two parts: the first part is the relationship between the hierarchical organization and information management where the role of the hierarchical organization to facilitate the information management processes is discussed. The second part is the relationship between information management and human collaboration where the role of information management to improve human collaboration in problem solving is discussed. The information management processes are illustrated through an information management life cycle model. This model has three major stages: active, semi-active and inactive stages and has three major phases: creation, searching and utilization phases. The creation phase includes: information creation and using, information authoring and modifying and information organization and indexing. The searching phase includes: information storage and retrieving and information exchange. The utilization phase includes: information accessing and filtering processes. The arguments about the role of hierarchical organization in information management and human collaboration are also discussed. The author showed that the hierarchical organization acts as a facilitator for common information management processes which are required in team collaboration such as: information gathering, organization, retrieving, filtering, exchange, integration or fusion, display and visualization. Human collaboration models are discussed with emphasis on the team collaboration structural model which has four unique but interdependent stages of team collaboration. These stages are: team knowledge construction, collaborative team problem solving, team consensus, and product evaluation and revision. Each stage has four levels: meta-cognition process which guides the overall problem solving process, the information processing tasks which is required by the team to complete each collaboration stage, the knowledge required to support the information processing tasks and the communication mechanisms for knowledge building and information processing. The author focused on the role of information management to improve human collaboration across the four collaboration stages of the team collaboration structural model. He showed that the hierarchical organization is more efficient for information management processes and team collaboration rather than other alternative organizations such as flat, linear and network organizations.

A Method of Studying Errors in Flight Crew Communication,

1989 ◽  
Vol 69 (3-1) ◽  
pp. 719-722 ◽  
Author(s):  
Claude Navarro
Keyword(s):  
Information Processing ◽  
Problem Solving ◽  
Information Exchange ◽  
Flight Test ◽  
Two Dimensions ◽  
Flight Crew ◽  
Communication Errors

We present a method of studying errors in flight crew communication, based on the information-processing paradigm. The taxonomy of errors proposed here is based on two dimensions, Type of Communication Errors (Transmission, Detection, Identification, Interpretation, plus Action linked to communication), Type of Adjustment (Individual: problem-solving by the operator concerned; interactive: problem-solving by crew). This taxonomy, tested during certification flight test, seems to be useful in all work situations based on information exchange between operators.

Anxiety and Cognitive Processes in Problem Solving

1974 ◽  
Vol 18 (3) ◽  
pp. 239-254 ◽  
Author(s):  
Kenneth E. Sinclair ◽  
Terence A. Heys ◽  
Stephen de C. Kemmis
Keyword(s):  
Information Processing ◽  
Problem Solving ◽  
Cognitive Processing ◽  
Cognitive Processes ◽  
Coping Styles ◽  
Human Problem

In this paper a trait-state conception of anxiety is presented which incorporates a number of extensions to current theorizing. The conception is a cognitive one in that it emphasizes information processing that occurs with respect to both the trait and state components of anxiety. The conception indicates a number of insights into human problem solving that can be made through a consideration of cognitive processing, anxiety processing, and their interaction. In particular, the role of coping styles in threat reduction and the influence of A-state on specific cognitive processes are examined. Implications for theory and further research are discussed.

Cognitive Early Education

2020 ◽  
Author(s):  
H. Carl Haywood
Keyword(s):  
Information Processing ◽  
Cognitive Development ◽  
Problem Solving ◽  
Executive Functions ◽  
Early Education ◽  
Self Regulation ◽  
Learning Tools ◽  
Mediated Learning ◽  
Cognition And Learning ◽  
The Mind

Cognitive early education, for children between ages 3 and 6 years, is designed to help learners develop and apply logic tools of systematic thinking, perceiving, learning, and problem-solving, usually as supplements to the content-oriented preschool and kindergarten curricula. Key concepts in cognitive early education include metacognition, executive functions, motivation, cognition, and learning. Most programs of cognitive early education are based on conceptions of cognitive development attributed to Jean Piaget, Lev S. Vygotsky, A. R. Luria, and Reuven Feuerstein. Piagetians and neoPiagetians hold that children must construct their personal repertoire of basic thinking processes on the basis of their early experience at gathering, assimilating, and reconciling knowledge. Vygotskians and neoVygotskians believe that cognitive development comes about through adults’ mediation of basic learning tools, which children internalize and apply. Adherents to Feuerstein’s concepts likewise accord a prominent role to mediated learning experiences. Followers of Luria believe that important styles of information processing underlie learning processes. Most programs emphasize, to varying degrees, habits of metacognition, that is, thinking about one’s own thinking as well as selecting and applying learning and problem-solving strategies. An important subset of metacognition is development and application of executive functions: self-regulation, management of one’s intellectual resources. Helping children to develop the motivation to learn and to derive satisfaction from information processing and learning is an important aspect of cognitive early education. Widely used programs of cognitive early education include Tools of the Mind, Bright Start, FIE-Basic, Des Procedures aux Concepts (DPC), PREP/COGENT, and Systematic Concept Teaching.

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