Problem-Solving in Cognitive Psychology

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Cognitive skills that a person acquires throughout one’s life shape a personal background and allow interacting with other people through the experience of communication to overcome various barriers. Problem-solving is valuable attainment, and cognitive psychology is the industry that studies this phenomenon from the perspective of drivers and incentives to make decisions in favor of specific actions or ideas.

From a neurological perspective, problem-solving is characterized by the nature of the human desire to fill the space and identify the best methods to overcome specific barriers. At the same time, this skill may be applied to other areas where the experience gained is a crucial self-determining factor, for instance, differential or educational psychology. The problem-solving attainment is of high importance from the perspective of gaining individual adaptive and social habits. The abilities to analyze and make the right decision based on the proposed circumstances are the skills that distinguish the human species from most other living beings.

Neurological Foundations and Processes Related to Problem-Solving

Problem-solving is an active neurological process that occurs at the initiative of a person oneself and does not belong to the category of automatic and reflex properties. Any task requiring a solution is associated with the work of various cognitive skills that need to be applied to solve an individual problem (“Cognitive psychology,” 2020). This form of behavior is goal-directed and serves as a tool for performing specific actions but not as a ready-made set of behavioral reflexes (“Cognitive psychology,” 2020).

The abilities to find flexible solutions, adapt to the current conditions, divide tasks in accordance with the spectrum of their significance, assess specific actions or solutions adequately, and other attainments shape the neurological background of problem-solving. Brace (2014) lists various problem-solving strategies and notes that building a sequence of actions in a specific order to achieve the desired goal is evidence of cognitive development, which varies depending on complexity. Thus, the effectiveness of problem-solving may depend on the criteria of the complexity of a particular issue and the tools available to overcome it.

The ability to control cognitive functions to direct them towards solving a specific problem is a skill that is established from an early age. As one grows older and acquires new cognitive skills, the complexity of potentially solvable problems increases. A person learns to combine existing knowledge, for instance, in the context of problem-solving by analogy, which Brace (2014) describes as a process related to experience rather than knowledge. As Kolbert (2017) argues, collaborative groups, play a significant role in this process and stimulate solving different problems through the application of previously learned attainments. In this regard, one can conclude about the neurological connection between problem-solving and social adaptation.

Filling the space that has arisen due to the urgent need to overcome a specific obstacle does not carry unconditioned reflexes and is based on a conscious choice to search for optimal solutions. When a person analyzes, draws analogies, divides tasks into subtasks, and performs other actions related to problem-solving, cognitive skills are activated (“Cognitive psychology,” 2020). Unwillingness to deviate from the intended plan characterizes the innate ability to overcome barriers to achieve the desired goal. A baby who crawls towards one’s toy despite obstacles on the floor does this consciously. Thus, problem-solving may be characterized not only as a cognitive process that develops as people grow older and socialize but also as an integral and conscious personality trait.

Criticism of the Problem-Solving Theory

Despite the fact that problem-solving is the subject of cognitive psychology research and a recognized concept, certain aspects of this theory are questioned due to the similarity with other psychological models. In particular, Servant-Miklos (2019) argues that problem-solving and knowledge acquisition are processes that have much in common and are often discussed as related phenomena. As a result, contradictions between each of these theories arise. This context is based on the understanding of what knowledge is since the ability to use accumulated cognitive skills may be interpreted from the perspectives of both intelligence and a set of problem-solving attainments.

According to Servant-Miklos (2019), “both approaches are the product of the Cognitive Revolution in psychology,” but their differences presuppose the ability to use knowledge (p. 622). As a justification, the author draws attention to the generation of the late 20th century and notes that the emergence of computer technology has eliminated the urgent need to utilize knowledge for problem-solving (Servant-Miklos, 2019). Therefore, this interpretation of the theoretical foundations is the argument in favor of the approach in which problem-solving skills in cognitive psychology prevail over knowledge acquisition.

At the same time, despite conflicting positions regarding problem-solving and knowledge acquisition, evaluating these concepts from a critical perspective allows finding the relationship between them. Lieto et al. (2019) consider problem-solving through the prism of the goal-directed approach when the final task is the main one to achieve through overcoming appropriate obstacles. In this regard, the researchers consider this process “is based on the availability of novel, additional, knowledge that can be then used to select novel sub-goals or novel operations” (Lieto et al., 2019, p. 305).

In other words, an algorithm that involves searching for effective solutions and methods to overcome specific problems is inextricably linked with the acquisition of new knowledge that will subsequently be transformed into experience. According to Servant-Miklos (2019), the psychology of learning is built on the constant processing of information that comes through communication and personal drive to overcome barriers. The better the information studied, the higher the likelihood that the problem-solving process will be faster and more successful. Therefore, despite the criticism and differentiation of the concepts of problem-solving and knowledge acquisition, these two models are rather interrelated than separated.

Application of Problem-Solving to Other Fields

Problem-solving is a concept that finds its application not only in cognitive psychology but also in other fields. For instance, Xiong and Proctor (2018) state that this model fits into the area of educational psychology.

This is an approach that allows building the educational process based on the search for evidence and justification. In modern pedagogical practice, this technique is widely used because the trend to stimulate student activity through the development of critical thinking involves the ability to solve various problems on one’s own. Kovacs and Conway (2019), in turn, draw attention to differential psychology as the area in which problem-solving can be actively applied. In this field, the search for arguments for obtaining reasonable alternative conclusions shapes the basis of the cognitive process. As a result, the more successful an individual utilizes problem-solving skills, the higher the likelihood of the objective assessment of specific phenomena or challenges to overcome.

Problem-solving, as a methodological concept, is used not only in various branches of psychology but also in other areas where the assessment of cognitive processes is indirect. For instance, Kovacs and Conway (2019) analyze this approach for practical purposes and provide an example of recruiting tests used in hiring employees. Job applicants, as a rule, are asked to answer questions related to the assessment of individual situations, and the use of critical thinking skills to apply problem-solving attainments is a common approach.

Another area in which this concept is applied is computer technology. As Xiong and Proctor (2018) note, modern AI algorithms are built due to the methods that aim to train AI to overcome various problems through problem-solving. Advances in this area may prove that acquired information accumulated through knowledge is an objective and effective methodology to overcome barriers. Computers combine and synthesize different data, thereby transforming them into efficient problem-solving algorithms. Therefore, this concept finds its application in various fields as a necessary and relevant technique.


Problem-solving is a subject of study not only in cognitive psychology but also in other areas since this concept characterizes the individual from different perspectives and distinguishes people from other living beings. Applying critical thinking and combining experience with knowledge shape the basis of this model. Despite the existing criticism, the separation of problem-solving from knowledge acquisition is irrelevant because these theories are interrelated.

Utilizing appropriate skills in computer technology confirms that the collection and accumulation of valuable information is the core of the development of problem-solving skills. Therefore, further research on this topic can be devoted to a deeper analysis of such attainments in the technology industry, in particular, artificial intelligence, to identify basic algorithms and compare them with those in humans.


Brace, N. (2014). Thinking and problem-solving. In D. Groome (Ed.), An introduction to cognitive psychology: Processes and disorders (3rd ed., pp. 241-271). Psychology Press.

Cognitive psychology and cognitive neuroscience/reasoning and decision making. (2020). WikiBooks. Web.

Kolbert, E. (2017). Why facts don’t change our minds. The New Yorker. Web.

Kovacs, K., & Conway, A. R. (2019). A unified cognitive/differential approach to human intelligence: Implications for IQ testing. Journal of Applied Research in Memory and Cognition, 8(3), 255-272. Web.

Lieto, A., Perrone, F., Pozzato, G. L., & Chiodino, E. (2019). Beyond subgoaling: A dynamic knowledge generation framework for creative problem solving in cognitive architectures. Cognitive Systems Research, 58, 305-316. Web.

Servant-Miklos, V. F. (2019). Problem solving skills versus knowledge acquisition: The historical dispute that split problem-based learning into two camps. Advances in Health Sciences Education, 24(3), 619-635. Web.

Xiong, A., & Proctor, R. W. (2018). Information processing: The language and analytical tools for cognitive psychology in the information age. Frontiers in Psychology, 9, 1270. Web.

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