Although Rico consistently described problems according to their magnitude, Ms. Rao was concerned he would not be able to categorize real problems in his own life. She wanted to make sure Rico could describe the size of problems he encountered across school settings. In other words, she wanted to work on response generalization. She operationally defined a single objective:

• When Rico experiences one of 10 pre-taught problems and an adult asks him to describe the size of the problem, Rico will describe the problem as “small,” “medium,” or “large” without withdrawing from the problem situation, crying, or yelling during 90% of opportunities across at least three school settings.

With her objective operationally defined, Ms. Rao needed to determine an instructional setting and method to promote generalization. Ms. Rao contemplated small group instruction, but decided that the targeted skill did not really involve peers. Thus, she decided to use direct instruction in a 1-1 setting.

• Instructional Setting: 1-1
• Instructional Method: Direct instruction

Direct instruction would pair well with the generalization tactic, teaching multiple examples. Although she would focus on ten problems which were likely to occur at school, she would teach twenty different scenarios in total. This would help Rico identify the size of novel problems he might encounter at home and at school. 

Ms. Rao knew that identifying the size of a problem was not naturally reinforcing; Rico often cried or ran from adults when he encountered problems. So, she decided she would need to contrive reinforcement. She decided she would use external reinforcement in the form of Rico’s token system to reward Rico whenever he engaged in the target behavior.

• Generalization Tactic: Teach multiple examples
• Support Strategy: Reinforcement

Ms. Rao’s Lesson on “Identifying the Size of a Problem”

Preparing the Lesson

Ms. Rao prepared for the lesson by taking data on Rico for two weeks. She made a list of every problem Rico encountered and tallied the number of times each problem occurred. She then made a list of the 10 most common problems for focused instruction. Then, she generated a list of 10 additional scenarios in order to teach multiple examples. Fortunately, since Rico did not experience any “large” problems at school, Ms. Rao added five hypothetical “large” problems to the list of additional scenarios to make 25 additional scenarios in total.

Carrying Out the Direct Instruction Lesson

Ms. Rao began the 1-1 direct instruction lesson by reviewing the definitions of small, medium, and large problems. She explained that a small problem is easy to solve and nothing to worry about. For example, getting a B on one assignment is a small problem because it doesn’t significantly affect your overall grade, and even if it did, getting a B in a class is okay. A medium problem is something that takes more effort to resolve and might require some adult help. For example, if Rico lost a library book he would have to save up some money to replace the book, and he might not be able to check out another book until he replaced it. Finally, large problems are problems which require emergency help and/or longer periods of time to fix. For example, a house fire is usually a large problem because it requires 911 assistance and because fixing or replacing a burnt house takes several months.

Teaching Multiple Examples

In order to teach Rico multiple examples, Ms. Rao then read an example of a small, medium, and large problem. She explained how she knew the problem was small, medium, or large. Ms. Rao then reviewed seven more examples of small, medium, and large problems with Rico. Together, they discussed how they knew each problem was small, medium, or large. Finally, Ms. Rao asked Rico to label the remaining examples independently. She provided immediate corrective and reinforcing feedback and gave Rico a token for every 2-4 correct descriptions of problems. 

Reinforcing Knowledge

After the lesson, Ms. Rao reviewed Rico’s token system with him. She told him that every time he was able to correctly identify the size of the problem without engaging in the defined problem behavior, he would earn a token as reinforcement. Each time Rico earned three tokens, he would gain access to a reinforcement menu.