Behaviorism

Through observable behaviors, we can see that learning occurs when someone interacts with their environment and encounters an external stimuli that reinforces or discourages behavior.  Behaviors that are followed up with positive reinforcement are likely to be repeated. Behaviors that are followed by negative reinforcement are unlikely to recur.

Key figures in behaviorism include BF Skinner, Ivan Pavlov, and Edward Thorndike. 

In 1903, Russian physiologist Ivan Pavlov discovered classical or operant conditioning. He realized that the dogs he was studying would salivate whenever they saw the research assistant appear with their food. He then began ringing a bell just before serving their food. Eventually, he would ring the bell and the dogs would salivate, even in the absence of food because they had formed an association between the bell and the service of food.  Classical conditioning can influence teaching and learning because when a desired behavior occurs, a positive reinforcement is provided. Eventually the reinforcement does not always have to be provided to elicit the desired behavior. This has a lot of implications in classroom management. We also see this at work in gaming when the player is rewarded in certain situations and so the player continues to seek out those situations as the game continues. 

In 1910, American psychologist, Edward Thorndike, introduced his laws of learning. They included:

1. The Law of effect. This states that a person's response to a  situation followed by a reward will make those responses stronger. As a result, the responses become habits in the future when the situation occurs again. If a response prevents an individual from achieving a reward, this response becomes weaker.

2. Law of readiness. This states that a set of responses can be linked together in order to arrive at a desired outcome. If the person is prevented from achieving this outcome, this will cause “annoyance”. 

3. Law of exercise. Associations that are made more often become strengthened. Associations that are rare or unpredictable become weaker.

Thorndike's laws connect to teaching and learning because the laws can be used to create strong associations among concepts using positive and negative reinforcement.  Utilizing Thorndike's laws could potentially result in deeper learning and retention of concepts.

In the 1950s, American psychologist BF Skinner came up with the "Skinner Box" in which a rat or pigeon was placed inside.  At some point the rat would notice and then press a bar that would release food.  The rat realized that each time it pressed the bar, a reward (food) was presented.  Skinner concluded that when a person or animal is exposed to a stimulus which prompts a response, and then response is reinforced. This is what conditions behaviors. Skinner's theories on operant conditioning connect to teaching and learning because when a teacher or a learning machine presents a task or question, the student is rewarded with positive praise ("that's correct!" or given a reward such as candy) or a negative reinforcement ("That is incorrect. Try again." or the absence of candy). 

In 1965, American educational psychologist Robert Gagné suggested 8 types of learning based on his experience with behaviorist learning theories. Most of these learning types are based on stimulus-response learning. These learning types led to his Nine Events of Instruction which details a 9-step set of events for a well-rounded learning experience. More details about his 8 learning types and 9 events of instruction can be found here. 

Implications for Instructional Design

1. Drag and drop activities encourage a learner to determine whether or not something belongs to certain categories. This is called discrimination. Drag and drop activities allow a learner to reinforce their correct ideas or prove they are incorrect because the course provides immediate feedback to the learner. Incorrect responses are given opportunities to try again.

2. Generalization is a way for learners to synthesize what they understand about patterns or trends. One way for learners to practice this is to be provided with examples and non-examples and then provide a written generalization or "rule" for the patterns.

3. When learners are presented with information in context, they form associations (see Thorndike).  Presenting learners with opportunities for practical application is a good way to help them form the desired associations as defined by the objectives of the course. 

4. Chaining involves designing a series of activities that lead the learner through a complex set of concepts, one step at a time. Activities that provide a way for learners to sequence concepts, such as drag and drop or matching activities can help reinforce learning. 

Opinions

Behaviorism has interesting implications for designing learning activities in the sense that a teacher must know how to encourage the student to continue learning and know when to halt learning that is unproductive. It works well for classroom management. When the students behave in the desired ways, they are rewarded. When the students behave in undesired ways there is an absence of a reward or there is a direct consequence. The problem with behaviorism is that it ignores the complex mental processes that often occur alongside learning. For example there is no real way  in behavorism to reward metacognition or reward the process, only the final outcome. Behaviorism tends to favor the final result which means that the journey to get to the final result is often ignored. Behavorism also ignored intrinsic motivation. A student may be motivated to do a task or set of tasks because it is intruiging or fun and learn quite a lot through the process. However, if the final result is deemed to be incorrect, then the journey and the learning along the way may be completely negated because of the negative reinforcement at the end of the task. I personally prefer methods that value the journey more than the end result and if the end result is incorrect, provides an environment for learners to reflect and revise to achieve the correct result. 

Scenario:

In this scenario, I am creating a professional development about a math concept for elementary school teachers to teach to their students. The concept is called "compensation." The underlying math idea is that in a subtraction problem, I can add or subtract the same amount to the minued and subtrahend so that the difference between the two numbers remains the same. For example, in 1000-367 a student may need to do a lot of regrouping. But if I subtract 1 from both numbers, I get 999-366, which can be done without regrouping, if not mentally, to find the difference of 633. That's the same result as if I had subtracted 1000-367. 

In the learning activity, I would provide the stimulus, a drag and drop activity, where learners would have more choices than targets. The image at left displays a sample of this activity. Learners would have to analyze the presented choices and decide what to drag and drop to carry out the steps of compensation in a subtraction problem.  Learners could try to add 16 to both numbers or subtract 254. When all numbers are placed and a "submit" button is pressed, feedback would appear to state whether the learner was correct or needed to try again. If correct, the course would automatically move on. If incorrect, the interactive would reset and learners would not be able to move on until the numbers were placed correctly.  This is the positive or negative reinforcement. In order to avoid learned helplessness, incorrect answers would only reset the interactive a certain number of times (maybe 3-5 incorrect attempts) before the correct answers would be provided and the course would move on. 

After the learner correctly carries out one way, the interactive would reset and the learner would have to try with the other set of numbers. The back end data would tell me how many attempts the learner needed to correctly place the numbers. I would follow this up with a written reflection about why both adding 16 and subtracting 254 would work to ensure the learner has an opportunity to cement the idea. This would be an example of "chaining."