Cognitive Learning

Cognitive psychology is a theoretical perspective that focuses on the realms of human perception, thought, and memory. It portrays learners as active processors of information--a metaphor borrowed from the computer world--and assigns critical roles to the knowledge and perspective students bring to their learning. What learners do to enrich information, in the view of cognitive psychology, determines the level of understanding of that they ultimately achieve.

Cognition is defined as “the mental process or faculty of knowing.” To help the students reach a cognitive state about a certain subject should be one of the goals of both teaching and learning. Thus, the below discussions were the teaching learning and the rehearsal learning.

3.3.1 Teaching Learning

As articulated by Piaget (1969)[37], students learn better when they can discover knowledge through the way of inquiry and experimentation instead of acquiring facts presented by a teacher in class. Since the learner is portrayed as an active processor who explores, discovers, reflects, and constructs knowledge, the trend to teach from this

perspective is known as the constructivist movement in education. As Bruning (1995)[38]

explains, “The aim of teaching, from a constructivist perspective, is not so much to transmit information, but rather to encourage knowledge formation and development of metacognitive processes for judging, organizing, and acquiring new information.” Several theorists have embellished this theme. Rumelhart (1981)[39], following Piaget, introduced the notion of schemata, which are mental frameworks for comprehension that function as scaffolding for organizing experience. At first, the teacher provides instructional scaffolding

that helps the student construct knowledge. Gradually, the teacher provides less scaffolding until the student is able to construct knowledge independently.

Recently, there has been some interests in developing formal models of teaching [40, 41, 42, 43, and 44] through which we can develop a better understanding of how a teacher can most effectively speed up the training process. Although, the formal models of teaching that have been introduced in the learning theory community is that they place stringent restrictions on the learner to ensure that the teacher is not just providing the learner with an encoding of the target. In particular, the teaching models allow the teacher to present a set of examples for which only the target function is consistent. Thus, teaching under these models is made unnecessarily difficult since the problem reduces to teaching an obstinate learner that tries as hard as possible not to learn while always outputting a hypothesis consistent with all previous examples. In other words, teaching learning is necessary to a learner to reduce the complexity learn process.

3.3.2 Reinforcement-Rehearsal (R-R) Learning

Reinforcement Learning

There are several kinds of learning theories from behaviorists. You may be familiar with “conditioned response theory” developed by Pavlov 1903, whereby a response that already occurs in the presence of one stimulus can be “conditioned” to occur following a

different stimulus. This learning theory is very important for emotional learning, but has little relevance to most learning of invariant tasks. Far more relevant is “reinforcement theory,” first developed by E. L. Thorndike (1913) [33] and further developed by B.F.

Skinner (1956)[24] and others. In reinforcement theory, an invariant task is viewed as a

“response” and is learned when it becomes “associated” with an appropriate stimulus. For example, “3.14” is a response that should become associated with “Pi”. This learning process occurs whenever “reinforcement” follows the response. For example, each time a learner responds with “3.14”, a reinforcer such as “Right!” or “Good!” or even just a smile with a nod will increase the probability of the learner responding the same way in the future.

With sufficient repetition of these stimulus-response-reinforcement events, the response will come to occur automatically in the presence of the stimulus.

Also, the learning classifier system is a machine learning system with close links to reinforcement learning and genetic algorithms. LCS consists of a population of binary rules on which a genetic algorithm altered and selected the best rules. Instead of a using fitness function, rule utility is decided by a reinforcement learning technique.

Rehearsal Learning

Besides the reinforcement learning, rehearsal learning differs from it. A rehearsal strategy is used by the repeated practice of information to learn it. When a student receives the specific information that needs to be learned, such as a list, often he will attempt to memorize the information by repeating it over and over. He may read the words out loud, or he may sub vocalize the information (read it in his own mind). The repeated practice increases the student's familiarity with the information. For many people, the learning of our social security number, our telephone number, or the items we want to pick up at the grocery store prompts us to use a rehearsal strategy.

This strategy originally documented by Belmont and Butterfield (1971) [45] examines how regular review and recall techniques aid the transfer of information into LTM. Buzan

[46] goes on to propose a pattern that the rehearsal strategy should follow. By monitoring recall rates during, and immediately after learning has taken place and at timed intervals thereafter, Buzan concludes that “The first review should take place about 10 minutes after a one hour learning period and should itself take 5 minutes. This will keep recall high for approximately one day when the next review should take place, this time for a period of 2 to 4 minutes. After this, recall will probably be retained for approximately a week, when another 2 minutes review can be completed followed by a further review after about one month. After this time the knowledge will be lodged in LTM”.

Rehearsal strategies can be used to learn relatively brief amounts of information, and is good for learning “foundation information” or “correct information”. Foundation and correct information is necessary to be learned before more complex learning can take place.

If you are using rehearsal to teach information that contributes to a larger concept or skill, keep in mind that lots of practice may be required for the students to learn the information to a level of automaticity. After initial learning takes place, you will need to review many times to ensure that the students have retained the information. We have all memorized information that we have promptly forgotten when we stopped rehearsing. For example, it is more concerning that “3.14” is a “True” response that should become associated with “Pi”.

This learning process occurs whenever “Rehearsal” follows the response. Contrary to the

“Reinforcement”, “314” is a “False” response that should become associated with “Pi”.

This learning process occurs whenever “Reinforcement” follows the response. It is still practicable in the reinforcement learning process.

In spite of the mechanism of LCSs, it has the reward ability similar to the rehearsal learning as well. The truth of the rehearsal learning cognition is that teachers take the foundation or correct information to educate the students and students practice the information by themselves. The proper correct information or knowledge is worth to do the rehearsal. That is the difference of reinforcement and rehearsal. Furthermore, the fullness

explanation of information process theory, the narrow terms of cognitive psychology would be detailed next.