With social developments, societies have changed to knowledge-centered societies that require high levels of knowledge. This change has subsequently increased the importance of the role of experts who lead social changes and developments. In general, experts are defined as those who consistently demonstrate exceptional abilities in a certain area. Dentists are also knowledge-oriented professionals who are always mentioned in the expert group. A study suggests that expertise requires systematic, high-intensity training of at least 10 years or 10,000 hours. Such definition of experts can be inferred from the definition of expertise, which is often variably defined based on context. Expertise allows an individual to efficiently collect and manipulate information and to perform better in their area of expertise. Many studies have sought to discover characteristics of expertise in experts. Ericsson estimated that professional musicians receive more than 10,000 hours of systematic training. In other words, their research suggests that at least 10 years of intense training is required to achieve expertise.
Various studies have been conducted to analyze the characteristics of experts. In the expert performance approach, studies conduct experiments to objectively evaluate performance. Here, the studies investigate the components of performance or comparatively analyze the differences between novices and experts to analyze the characteristics of experts.
Many studies have also investigated the components of expertise. In particular, knowledge, experience, and problem solving constitute the most basic components of generally accepted expertise. Experts perform typical activities at each of the following stages: recognizing problems, defining problems, finding solutions, carrying out solutions, and reflection. In experts, conceptually more abundant and organized representations occur, allowing them to solve given problems, and experts also tend to use abstract representation relying on in-depth knowledge. Here, knowledge representation refers to knowledge that externally expresses information organized within the cognitive framework. Especially, clinical experts have a high knowledge structure, and based on this understanding, experts widen and deepen the representations while focusing on the fundamental principles. Decision making, which refers to the process in which problems are recognized and solutions are selected upon consideration, is also defined as a process in which one reaches their selection among various possible alternatives through complex dental cognitive processes.
The brain consists of millions of neurons, and each neuron is connected to other neurons in various interrelationships. The interaction between these neurons, which can lead to learning, memory, behavior, decision making, and recognition, occur in synapses. Here, the information is transmitted in synapses through chemical substances, particularly due to the electric potential differences created by concentration gradients across the plasma membrane. Such electric potential differences were caused electric signals on the scalp, which are measured in EEG.
When compared to non-experts, experts have the ability to process unnecessary information without filtering and efficient neuronal networks. Clinical experts can also make accurate selections in given tasks due to their abundant experiences with the tasks. In addition, studies have also suggested that experts have higher activation of the frontal lobe, which is important for cognition in experts. and needed for prediction and observation of behaviors, and that experts and non-experts have different neuronal mechanisms.
This study was aimed to suggest a model of brain-based experience-knowledge in order to improve dentist’s decision making process. In order to decrease problems in decision making that can exert significant influences, this study was developed a model of dentists' experiential knowledge in decision making in order to improve dental experts' decision-making process. Dentists' EEG characteristics, which influence complex clinical decision making processes, were analyzed, and a brain-based learning model to improve experts' clinical decision making was proposed based on this.