On the Benefit of a Phenomenological Revision of Problem Solving

2017 ◽  
Vol 48 (2) ◽  
pp. 240-258 ◽  
Author(s):  
Alexander Nicolai Wendt
Keyword(s):  
Problem Solving ◽  
Theory Of Mind ◽  
Experimental Research ◽  
Historical Analysis ◽  
Computational Theory Of Mind ◽  
Computational Theory ◽  
Mechanistic Approach ◽  
Academic Psychology ◽  
Different Types ◽  
The Subject

AbstractProblem solving has been empirical psychology’s concern for half a century. Cognitive science’s work on this field has been stimulated especially by the computational theory of mind. As a result, most experimental research originates from a mechanistic approach that disregards genuine experience. On the occasion of a review of problem solving’s foundation, a phenomenological description offers fruitful perspectives. Yet, the mechanistic paradigm is currently dominant throughout problem solving’s established patterns of description. The review starts with a critical historical analysis of the state of problem solving in academic psychology. Subsequently, a phenomenological, contrastive approach is proposed. It questions the notion of problems as “goal-driven” behavior by making vivid experience the subject of discussion. As its given compounds, solvability, oppressiveness, and the problem’s horizon are discussed. Ultimately, an experience-based multimodal notion of the problem is elaborated that relates problems to challenges, fatalities and opportunities as different types of situations.

Methodological solipsism considered as a research strategy in cognitive psychology

1980 ◽  
Vol 3 (1) ◽  
pp. 63-73 ◽  
Author(s):  
J. A. Fodor
Keyword(s):  
Theory Of Mind ◽  
Mental Representations ◽  
Propositional Attitudes ◽  
Mental States ◽  
Research Strategy ◽  
Computational Theory Of Mind ◽  
Mental Processes ◽  
Computational Theory ◽  
Methodological Solipsism ◽  
Semantic Properties

AbstractThe paper explores the distinction between two doctrines, both of which inform theory construction in much of modern cognitive psychology: the representational theory of mind and the computational theory of mind. According to the former, propositional attitudes are to be construed as relations that organisms bear to mental representations. According to the latter, mental processes have access only to formal (nonsemantic) properties of the mental representations over which they are defined.The following claims are defended: (1) That the traditional dispute between “rational” and “naturalistic” psychology is plausibly viewed as an argument about the status of the computational theory of mind. Rational psychologists accept a formality condition on the specification of mental processes; naturalists do not. (2) That to accept the formality condition is to endorse a version of methodological solipsism. (3) That the acceptance of some such condition is warranted, at least for that part of psychology which concerns itself with theories of the mental causation of behavior. This is because: (4) such theories require nontransparent taxonomies of mental states; and (5) nontransparent taxonomies individuate mental states without reference to their semantic properties. Equivalently, (6) nontransparent taxonomies respect the way that the organism represents the object of its propositional attitudes to itself, and it is this representation which functions in the causation of behavior.The final section of the paper considers the prospect for a naturalistic psychology: one which defines its generalizations over relations between mental representations and their environmental causes, thus seeking to account for the semantic properties of propositional attitudes. Two related arguments are proposed, both leading to the conclusion that no such research strategy is likely to prove fruitful.

Welcome to Wales: Searle on the Computational Theory of Mind

1995 ◽  
Vol 38 ◽  
pp. 85-97
Author(s):  
Roger Fellows
Keyword(s):  
Artificial Intelligence ◽  
Blood Flow ◽  
Theory Of Mind ◽  
Cognitive Science ◽  
Recent Book ◽  
Computational Theory Of Mind ◽  
Computational Theory ◽  
Linguistic Understanding ◽  
Flow Through ◽  
Computational Processes

In a recent book devoted to giving an overview of cognitive science, Justin Lieber writes:…dazzingly complex computational processes achieve our visual and linguistic understanding, but apart from a few levels of representation these are as little open to our conscious view as the multitudinous rhythm of blood flow through the countless vessels of our brain.It is the aim of hundreds of workers in the allied fields of Cognitive Science and Artificial Intelligence to unmask these computation processes and install them in digital computers.

scholarly journals Usage of basic problem-solving techniques in the discipline of general physics in higher school

2020 ◽  
pp. 34-48
Author(s):  
Elizaveta Viktorovna Savchenko
Keyword(s):  
Problem Solving ◽  
Basic Problem ◽  
Electrical Network ◽  
Literature Analysis ◽  
Empirical Methods ◽  
General Physics ◽  
School Based ◽  
Different Types ◽  
The Subject

The subject of this research is the process of teaching students to solve problems in the discipline of general physics on their own, as well as develop skills of future engineers to break up the solution of the problem into stages. The article is aimed ad generalization, elaboration and implementation of the basic problem-solving techniques higher school based on the preliminary compiled classification of problems in accordance with certain characteristics. The author develops educational and methodological support for the discipline of general physics as the means of training students to solve problems on their own. The following methods were applied in the course of this work: analysis of psychological, pedagogical and scientific-methodical literature; analysis of curricula, textbooks, problem books, guidebooks on natural science disciplines, modeling of class activity of the students; empirical methods of observation, conversation, survey. As a result, the author incorporates the existing problem-solving techniques into the system, based on which students are capable to go through all stages of solving the problem on their own, better understand the study material, and acquire essential skills for articulation of the problem. The examples are provided on step-by-step solution of different types of problems on the topic “Calculation of an electrical network”.

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