Structural learning is an instructional theory outlined by Joseph Scandura in the 1970s that focuses on the organization of information in meaningful patterns and structures. As a teaching method, this theory helps students create mental structures to organize, understand, and retain information. Through this theory, learners don't have to memorize massive amounts of information; they are encouraged to unlock and process underlying patterns in order to retain knowledge more effectively and develop critical thinking and problem solving skills. In this article, we will discuss the baseline of the structural learning theory and the necessary frameworks of the model, along with potential contexts for its application.
Structural learning is a cognitive strategy that emphasizes the importance of detecting and recognizing the structures of any given piece of information. Scandura's theory encourages students to analyze and connect different pieces of information in order to solve problems and make decisions rather than relying on rote memorization of data. However, through Scandura's theory, students are encouraged to organize information into hierarchical structures that represent the relationship between different facets of a problem, which allows them to discern how every idea or concept fits into a larger framework. This helps learners sharpen their critical thinking skills and develop a problem-solving mindset.
According to the structural learning theory, knowledge consists of rules that need to be learned and can be divided into lower-order rules and higher-order rules. Lower-order rules are the most basic elements one needs to learn from a specific domain. These rules are specific and describe the relationships between individual elements of a concept within a domain. In order to form higher-order rules, one needs to combine lower-order rules and actions. These rules can generate new rules as solutions are devised for each problem. Lastly, higher-order rules encompass lower-order rules, as they essentially explain the relationship between the lower-order rules that form them.
Both lower-order and higher-order rules are determined by domain, procedure, and range. These parameters determine the ways a problem will be structured and, eventually, solved.
Refers to the area of knowledge the learner intends to learn. It can be any area of study or expertise.
This involves all the steps and processes used to apply lower-order and higher-order rules within the specified domain.
Refers to the variety of problems that can be addressed using the lower-order and higher-order rules within the specified domain.
Every problem has to accommodate inputs and outputs. These can take any form, whether a concept or even a process. Inputs are the stimuli or information an individual receives from their environment. This can happen through sensory inputs like sounds, sights, smells, or tactile sensations, or it can be received as information through language or other communication means. On the other hand, outputs refer to the actions a person responds with when they receive input. These can take the form of verbal responses and emotional or physical reactions. A higher-order rule can have other rules as input or output. To connect these parameters with their input/output potential, let's say:
To effectively implement the structural learning theory in the real world, a methodology called structural analysis is required. Structural analysis separates and identifies higher-order rules so the learner can break them down into lower-order ones. As mentioned previously, the structural learning theory is ideal for teaching and developing problem solving skills, enabling learners to deep-process information. Implementing the structural analysis method requires the following steps:
The intention of the structural learning model and structural analysis as a methodology is to help learners discover the path to solving complex problems by first teaching them the path toward simple solutions. Scandura has singled out three principles in his analysis:
Through its systemized approach to problem solving, the structural learning model has been largely applied in mathematics. Scandura himself applied the theory in an example attempting to teach subtraction. Along with mathematics, the theory can also be applied to science education by teaching students how to separately identify components of a concept to fully comprehend it. Moreover, the structural learning theory can be used in language learning contexts since grammar and vocabulary rules are dictated by patterns that can be grouped and organized for easier retention. Lastly, the theory can be applied in corporate contexts to illustrate the ways departments or processes jointly optimize a company's operations, as well as teach how to target problem solving within a business effectively.
The structural learning theory emphasizes the importance of understanding the underlying structures of any piece of information to develop critical thinking abilities. It helps students process information, recognize how to identify a problem, break it down into manageable increments, and devise solutions. If you want to discover other interesting Instructional Design models and theories, check out our list!
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