The Psychology of Learning

brain

Learning is a subject that has been studied for centuries now. Freud said learning is controlled by our psyche (ego, id, and superego). Socrates said that “the soul is immortal and possesses all knowledge.” It has been a topic of great interest to educators, psychologists, philosophers and students. The ideas and concepts behind learning have evolved and changed like all ideas do. Learning was first defined in terms of remembering and memory by Ebbinghaus (1885). He is most remembered for his experiment with memorizing the nonsense syllables and relearning them later and the logarithmic forgetting curve he discovered (refer to Appendix a). Through this experiment, he found that we remember the first and last items better than the middle ones.Ebbinghaus’ idea of rote learning was based on the notion of learning through the process of memorizing by repetition. Other than Ebbinghaus, there have also been other people who defined learning as remembering such as Bartlett. He investigated learning and memory by using strange and incomprehensible stories and found that when people use schemas, it is much easier to remember the stories. Hence, the schema theory was developed. There have been many theories of learning since. Later on learning came to be thought of as information processing. George Miller (1956) who is knows for his experiment with the magical number 7 found that we cannot retain more than seven items in short-term memory.

Behaviourism is a straight-forward theory initiated by Skinner that focuses on observable behaviour. It says that leaning is controlled by our environment. There are two ways that we can learn – involuntarily through classical conditioning or voluntarily through operant conditioning. The most well known example of classical conditioning is Pavlov’s dogs. Through classical conditioning, Pavlov’s dogs learned that whenever they heard a bell, it was time for food (stimulus) and they would start to salivate (response). Operant conditioning on the other hand is learning based on the notion of consequences such as reinforcement (positive or negative) and punishment. For example, a dog learns through positive reinforcement to bring back the ball to its master when it is rewarded with food and negative reinforcement – that it doesn’t get any food if it does not bring back the ball. There are however criticisms of behaviourism as a learning theory because it does not account for all kinds of learning since it only focuses on observable behaviours and discounts mental activities. Behaviourism also fails to explain some kinds of learning such as new language patterns that are recognized by a child which is not learned by classical conditioning or operant conditioning. It also tends to support a more passive learning environment, where the teacher is the centre of attention and knowledge is given and absolute.

Bandura (1925) said that we learn through models. Social learning theory, a branch of behaviourism also focuses on observational learning. Observational learning can be seen most clearly in young children. A child learns many things through observing his or her surroundings. For example, a child observes an adult opening the door, and through these observations learns how to open the door himself. Social learning theory says that individuals are more likely to adopt a modelled behaviour if it results in valued outcomes and when it is displayed by someone we admire. This explains why children so often imitate their parents. Cognitivism grew in response to Behaviorism in an effort to better understand the mental processes behind learning. According to Cognitivism, knowledge is stored cognitively as symbols. Learning is defined as the “process of connecting symbols in a meaningful and memorable way” (Funderstanding). Piaget was one of the main pioneers of this study and focused mainly on child development and learning through cognitive structures. Piaget said that young children develop a sort of mental map in order to understand and respond to his or her physical environment. They continue to learn through integrating new information into the existing symbol system or adjusting their symbols system to make space for new information. Some of the criticisms of Cognitivism are that it does not account enough for individuality and differences in staged development and it places little emphasis on other important aspects such as motivation.

Currently, information and knowledge are growing at faster pace than ever before in the history of mankind. According to Simon, ‘knowing’ has changed from being able to remember information and repeat information to being able to find it and use it (cited in Bransford, 2004). Contemporary learning theories focus on differences between expert and novice learners. They found that experts notice meaningful patters that are not noticed by novices and that experts are more flexible when it comes to retrieving important information that has been learned and of course experts also have accumulated a vast amount of knowledge in their field. Understanding how experts learn can help us to improve our learning techniques.

When we have accumulated knowledge, the next step is to use this knowledge to perform tasks. This is what we call skill. There are many kinds of skills from basic skills such as counting to more complex skills such as playing football at a professional level. There is a big difference in the amount of time it takes to acquire a skill such as playing football at a professional level compared to acquiring a skill such as counting. How are these complex skills acquired? Like any skill, for example driving, a practiced skill becomes more and more automated until it no longer requires any cognitive involvement. And this gives space for our cognitive system to focus on more problematic aspects of the skill and improve the skill further. According to the power law learning, a skill can continue to improve and speed up right up until the point where the “equipment” reaches its limit. For example, the “equipment” could be the physical structure of a person. Therefore, using this example, a person could only type as fast as his physical limitations will allow him to; the time it takes for the brain to register the nerve impulses sent from receptors (Anderson, 2000). Skills go through three different developmental stages according to Fitts (1964) and Anderson (1982), being the cognitive stage, the associative stage and the associative stage. In the cognitive stage, the learner learns through examples and instructions and usually verbalizes the instructions to himself or herself and practices the skill with awkwardness. However, the most important thing that the learner must do in this first stage is to come up with a solution to the problem that is faced in the new task as performing a new task is closely linked to problem solving. In solving a problem, certain steps must be taken to ensure that the current state of the problem transforms into the goal that we have in mind to achieve. These steps are called operators by Anderson. There are two main operators that we usually use. The more commonly used is difference reduction. This is when we try to eliminate differences between the current state of the problem and the goal state little by little. Sometimes this somewhat natural way of solving problems by difference reduction can hinder us from solving problems that require us to increase the difference between the current state and the goal state in order to solve the problem.The second is called operator subgoaling and is when we set subgoals in order to reach the main goal. Therefore, “skill acquisition involves executing a complex sequence of many operators” (Anderson, 2000). The next stage is the associative stage where the learner slowly learns how to perform the task without error and more smoothly. Basically it is the process of converting “declarative knowledge of the domain into procedural knowledge” (Anderson, 2000). Declarative knowledge is basically a description of the information received. Whereas, procedural knowledge is using the information to perform a task. Dramatic changes in problem solving also take place in this stage. Something called as production rules where procedural learning is a matter of pattern-recognition rather than a structured thought process. The learner need not verbalize instructions to himself anymore or think about what to do next. “Production rules are condition-action pairs that are postulated to represent procedural knowledge” (Anderson, 2000). For example, if I want to turn on the television, then I have to press the red button. New production rules are sometimes learned when people become more expert in a domain. It was also found that memory is one of the key factors that differentiates experts from novices and strengthens production rules because it enables them to remember information about problems specific in their domain. Finally, in the autonomous stage, the skill becomes more automatic and faster and cognitive involvement eventually disappears. Skills are an outcome of motor programs rather than of our cognitive system. There are two different kinds of motor programs. Open-loop performance is a sequence of actions that are performed without checking later or feedback. Close-loop performance on the other hand is when one waits for feedback or checks before moving on to the next step. How are these motor programs acquired? According to Schmidt in his schema theory, a learner develops recall memory – “a prepackaged sequence of actions” and recognition memory – a representation of the desired outcome (Anderson, 2000). The learner adjusts the motor program or the recall memory accordingly to the desired outcome or recognition memory. Feedback is an important element of learning and through motor programs; learners develop a kind of internal feedback through which they can detect their own errors without being told. However, research indicates that too much external feedback can be harmful towards learning because learners begin to depend too much on it and then cannot perform without feedback. The time taken to process the feedback may also disrupt learning. Transfer among skills becomes less and less as a consequence of the specialization of skills and as the skills become more advanced (Henry, 1968, cited in Anderson, 2000).

It is not enough to be able to learn something but more importantly is whether we are able to transfer this information. Transfer is defined as “the ability to extend what has been learned in one context to new contexts” (Bradshaw, 1998). For example, transferring what we have learned in school to everyday life. Measures of how much that has been learned is being transferred is usually used to test the quality of people’s learning experiences. Researchers have found that some kinds of learning lead to transfer and others not. For example, learning that is merely based on remembering certain facts hardly leads to transfer. In order for transfer to take place, the student has to understand the facts. Early research on learning and transfer were conducted by Thorndike and his colleagues and were “guided by theories that emphasized the similarity between conditions of learning and conditions of transfer” (Bradshaw, 1998). For example, if teachers want that students are able to transfer the knowledge they gain in classrooms to their everyday lives, they should try to include elements of the transfer context in their lessons. They could perhaps include examples and problem-solving questions from everyday life. Practice that takes learner characteristics such as existing knowledge and strategies into account are emphasized in modern theories of learning and transfer (Bradshaw, 1998). It was found that initial learning is important for transfer because a major factor that influences successful transfer is the degree of mastery of the original subject, hence when students have not learned enough about a subject, successful transfer is unlikely. Rushing the learning process and trying to compress too much information in a short period of time also hinders the transfer process. Even talented people need a great deal of time and practice in order to become experts. Students need to be given enough time to learn, process information and to make connections between relevant facts and organize these facts accordingly. According to Ericsson (1993), learning is most effective “when people engage in “deliberate practice” that includes active monitoring of one’s learning experiences” (Bradshaw, 1998). Monitoring here means always seeking feedback about one’s progress. Feedback about how much of what the student has learned is really understood is very important for successful transfer to occur. Motivation is also a very important factor contributing to successful transfer because “motivation affects the amount of time that people are willing to devote to learning” (Bradshaw, 1998). Motivation affects different people differently. People who are learning oriented are excited and motivated by new challenges, whereas people who are performance oriented are motivated when they perform well and try to avoid learning challenges that might cause them to perform badly. However, generally tasks should be at an optimum level of difficulty in order to keep students motivated and avoid boredom. McCombs, Pintrich and Schunk (1996) found that learners are motivated when they feel that they can use what they have learned to contribute to others (cited in Bradshaw, 1998). The context of original learning also affects the transfer of learning. For example, street children who used mathematics when making sales in the streets could not answer similar mathematical problems in school (Bradshaw, 1998). The degree of connection between learning and its contexts depends on how the knowledge is acquired (Eich, 1985 cited in Bradshaw 1998). Research shows that when a subject is taught in many contexts rather than in just one context, transfer takes place easier (Bjork and Richardson-Klavhen, 1989 cited in Bradshaw, 1998).

It is generally assumed that there are two different kinds of knowledge; declarative knowledge and procedural knowledge. More elaborate distinctions of knowledge do exist and have been widely researched. De Jong and Ferguson- Hessler developed a knowledge matrix based on four different types of knowledge and five different qualities of knowledge (1996). The first type of knowledge is situational knowledge and it is defined as knowledge of problem situations. It is essential to be aware of the problem at hand before attempting to solve the problem. Next, the learner has to acquire conceptual knowledge or declarative knowledge, which is “static knowledge about facts, concepts and principles that apply within a certain domain” (De Jong & Ferguson-Hessler, 1996). It is basically extra information that learners can use to solve the problem. According to Bransford, one of the factors that separate experts from novices is the expert’s detailed and organized comprehension of important facts and information in their specific domain (2004). Transfer from one problem state to another is made easier with procedural knowledge that functions to carry out the actions or tasks needed to solve the problem. Lastly, strategic knowledge is used to organize and structure the problem solving process by coming up with a general plan of action. One example of a quality of knowledge is the level of knowledge. Deep-level of knowledge is associated with understanding abstract principles and using critical judgment and evaluation. Surface-level of knowledge is associated with learning through trial and error and a lack of critical judgment. Further examples of qualities of knowledge are such as structure of knowledge (isolated or structured), automated or non-automated knowledge and modality of knowledge.

The focus of education has also changed because of our evolving views of learning. Educators are developing new curriculum to ensure that the learning process is more holistic, effective and able to meet the demands of our current situation. According to Zhou Nan-Zhao, education in this information intensive age has to meet two demands – it has to transmit an increasing amount of evolving knowledge and it has to enable learners not to be overwhelmed by all the information (Zhou Nan-Zhao, 2000). Zhou Nan-Zhao proposes a new curriculum based on ‘The Four Pillars of Learning’ which are ‘learning to know’, ‘learning to do’, ‘learning to live together’ and ‘learning to be’. ‘Learning to know’ is more than just knowing the facts and information related to a domain, rather it is learning to think critically, learning problem-solving skills, and to reason. It is described as a discovery process that requires time and patience. ‘Learning to do’ focuses on communication and interpersonal skills, learning to adapt to new situations, the ability to transform knowledge into new ideas and innovation, and to be able to resolve and manage conflicts effectively. In our ever increasingly globalized world, it is important that we learn to appreciate cultural differences and understand ourselves and others. ‘Learning to live together’ focuses on this and also other cooperative social behaviors such as empathy, caring, sharing and working together towards a common objective. Finally, ‘learning to be’ is basically learning to be human through acquiring knowledge, skills and values advantageous to personality development and also cultivating imagination and creativity. This aspect of learning grew out of the fear that people would be dehumanized as an outcome of technical change in the world today.

So what is the answer to the question of what should be acquired? In order for us to learn we need to acquire certain skills and certain types and qualities of knowledge. When we have acquired a general learning structure or strategy that contains previous, existing knowledge, problem-solving skills, initial information, facts and knowledge about the domain and skills such as pattern-recognition, we can use this knowledge database to solve future problems. Deliberate practice is also important to maintain and improve a skill. The question of what should be acquired should also focus on changing times and society and should be adjusted to be beneficial to ever-changing circumstances. Because of the information overload we face today, we need to find the most optimal way of learning. It would be impossible to memorize everything we need to know because there is just too much. Therefore one possibility could be to learn from expert learners and mimic their learning strategies and also adjust these strategies to custom-fit us as individuals because we are all unique and have our different ways of learning. Personally, I think ‘The Four Pillars of Learning’ would be very beneficial to our current times. There are of course many more new curriculums that could be beneficial and we should not limit our options, but keep our minds open to new ideas of learning.

References

Anderson, J.R. (2000). Learning and Memory. Chap 9: Skill Acquisition (pp.304-337).New York:Wiley.

Bransford, J.D. et al. (Eds.) (2004, expanded edition). How People Learn. Washington: National Academy Press.

De Jong, T. & Ferguson-Hessler, M.G.M. (1996). Types and Qualities of Knowledge. Educational Psychologist, 31,(pp. 105-113). Rumelhart.

Ebbinghaus’ Forgetting Curve. Retrieved 10, March 2006 from: www2.psych.purdue.edu/…/5-forgettingcurve.htm

Funderstanding. Retrieved 10, March, 2006 from: http://www.funderstanding.com/

Learning Theories. Retrieved 11, March, 2006 from:http://www.learningcurve.gov.uk/

Zhou Nan- Zhao. (2000). Four ‘Pillars of Learning’ for the Reorientation and Reorganization of Curriculum: Reflection and Discussions. Retrieved 10, March, 2006 from http://www.ibe.unesco.org/cops/Competencies/PillarsLearningZhou.pdf

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