Describe how information processing theory explains learning
Educators are very interested in studying how humans learn. In fact, the way one learns, acquires new information and retains the above information guides the selection of long-term learning objectives and effective teaching methods. To this end, cognition as a field of psychological study goes beyond simply taking into account and retrieving information. It is a vast field dedicated to the study of the mind in a holistic way. Loftus and Loftus (2019), one of the most influential researchers in cognition, have defined it as a study of how people code, structure, store, retrieve, use or otherwise learn knowledge. Cognitive psychologists hypothesize a variable or set of variables that intervene between the environment and behavior, in contrast to behavioral theories.
One of the difficulties of teaching is to present students with often complex materials so that they can understand them. With a basic understanding of how students (and all human beings) learn, we, as teachers, can present the content to our students in a way that maximizes learning possibilities. The information processing model provides us with a theory of how humans treat information. Several authors, such as Barber (2015), study learning from the point of view of the information processing model and discuss how to use this information to improve the results of students in the classroom.
The basic idea of information processing theory is that the human mind is like a computer or information processor instead of behavioral notions that people simply respond to stimuli (Barber and Legge). , 2017). These theories equate thought processes with those of a computer, insofar as it receives inputs, processes and outputs. The information gathered from the senses (input), is stored and processed by the brain and finally leads to a behavior response (output).
The theory of information processing has been developed and expanded over the years. The “stage theory” of Atkinson and Shriffin is particularly notable in the design of information processing models. It presents a sequential method, as explained above, of the output-processing-output (Loftus and Loftus, 2019). Although influential, the linearity of this theory has reduced the complexity of the human brain and, therefore, several theories have been developed to deepen the evaluation of the inherent processes.
With this in mind, Craik and Lockhart have published the “treatment level” model (Lofftus and Loftus, 2019). They point out that information is developed (processed) in different ways (perception, attention, labeling and meaning), which affects their ability to access information later. In other words, the degree of development of the information will affect the quality of its acquisition.
Bransford expanded on this idea by adding that the information will be retrieved more easily if the way it is accessed is similar to the way it was stored (Lachman et al., 2015). The next major development in information processing theory is the connectionist model of Rumelhart and McClelland (2017), which is based on current research in neuroscience. It indicates that the information is stored simultaneously in different areas of the brain and is connected in a network. The number of connections of a single piece of information will affect the ease of recovery.
The general model of information processing theory includes three components:
In sensory memory, information is gathered via the senses through a process called transduction. Through receptor cell activity, it is altered into a form of information that the brain could process. These memories, usually unconscious, last for a very short amount of time, ranging up to three seconds. Our senses are constantly bombarded with large amounts of information. Our sensory memory acts as a filter, by focusing on what is important, and forgetting what is unnecessary. Sensory information catches our attention, and thus progresses into working memory, only if it is seen as relevant, or is familiar (Barber, 2015).
Working Memory/Short Term Memory
Baddeley (2001), quoted by Sharps (2017), has published a three-component working memory model. The executive control system supervises all the activities of the working memory, including the selection of the information, the method of treatment, the meaning, and finally decide whether to transfer them to the long-term memory. This system has two equivalents: the auditory loop, where the auditory information is processed, and the visual-spatial control block, where the visual information is processed. The sensory memories transferred into the working memory will last 15 to 20 seconds, with a capacity of 5 to 9 pieces or pieces of information. The information is stored in working memory by means of maintenance or elaborate repetition. Maintenance refers to repetition, while development refers to the organization of information (such as fragmentation or chronology).
The processing that occurs in working memory is affected by a number of factors. First, individuals have different levels of cognitive load or the amount of mental effort they can deploy at a given time because of their individual characteristics and intellectual abilities. Secondly, information that has been repeatedly repeated becomes automatic and therefore does not require a lot of cognitive resources (for example, cycling). Finally, depending on the task at hand, individuals use selective processing to draw attention to extremely relevant and necessary information (Barber, 2015).
Long Term Memory
Long-term memory includes various types of information: declarative (semantic and episodic), procedural (how to do something) and images (mental images). Unlike previous memory constructs, long-term memory has unlimited space. The crucial factor of long-term memory is the quality of the organization of information. These are affected by a correct coding (process of elaboration during the transfer in the long-term memory) and by processes of recovery (analysis in memory of the information and transfer in the working memory so that it can be used). As Bransford’s work points out, the degree of similarity between how information is coded and how it is accessed will determine the quality of the extraction process. In general, we retain much less information than what is actually stored there (Barber and Legge, 2017).
Learning is done in different ways. Some teachers would like their students to memorize certain information, or even use certain formulas, such as in subjects such as math and science, to solve problems or have the skills to use certain equipment or tools to perform a task. For example, the use of power point for project work, the use of musical instruments for music, the use of a hammer or key for the repair of works, etc. As a result, the learner shapes their knowledge by remembering, memorizing, practicing, and others (Lachman et al., 2015).
With a basic understanding of the learning process, Loftus and Loftus (2019) explain how we apply this information to improve student performance in the classroom. First of all, we must draw the attention of our students so that the information is not quickly filtered by their sensory memory. In a lesson, this can be achieved through a clear and concise learning objective. By directly indicating what students will do in a lesson, it becomes clear that the information we are about to present is important enough to warrant student attention.
Once the new content is presented to students, it is essential to get them involved in the lesson. Through a variety of cognitive and engagement strategies, it is possible to ensure that students process the information, which is vital for coding information in long-term memory. Systematically verifying understanding with higher order questions in a lesson helps ensure that all students use interactive repetition to make sense of the ideas presented in a lesson, making it easy to effectively code news and information by the students.
Finally, the learning process does not necessarily end at the end of a lesson, even though the majority of information is coded in long-term memory. Just as students need repetitions by repeating new information, they also need repetitions to retrieve previously learned information. This allows students to more efficiently retrieve information from their long-term memory in the future. Periodic review of the learned content provides students with access to coded information, which increases their chances of being able to retrieve it at the time of assessment (Barber, 2015).
The various scholars presented in this essay present a clear indication on the importance that the information processing theory has on learning and cognitive psychology. From the various definitions to the various iterations done by various scholars, the theory has been utilized for the past two centuries. Its application in classrooms was also discussed and analyzed.
Loftus, G.R. and Loftus, E.F., 2019. Human memory: The processing of information. Psychology Press.
Barber, P. and Legge, D., 2017. Perception and information. Routledge.
Barber, P.J., 2015. Applied cognitive psychology: An information-processing framework. Routledge.
Lachman, R., Lachman, J.L. and Butterfield, E.C., 2015. Cognitive psychology and information processing: An introduction. Psychology Press.
McClelland, J.L. and Rumelhart, D.E., 2017. Interactive processing through spreading activation. In Interactive processes in reading (pp. 37-60). Routledge.