Chained Schedules and The Goal Gradient Effect


    When looking at operant conditioning, there are many different types of schedules of reinforcement. One category of the schedules is called a chained schedule. A chained schedule is when there is a sequence of two or more simple schedules. Each simple schedule has its own discriminative stimulus, and the last link of the chain has a reinforcer that signals the end of the sequence. An example of this process given in the textbook is: A pigeon pecks (response) on a green key (discriminative stimulus) with a VR 20 schedule which then changes to a red key (secondary reinforcer/discriminative stimulus). The pigeon then pecks (response) on the red key with a FI 10 second schedule and is given the terminal reinforcer of food. Each portion of the chain is called a link, and through different trials with chained schedules it has been noted that there tends to be a larger amount of responding in the last link. (Powell et al., 2015)

       An explanation for why there seems to be greater responding in the last link is based on the goal gradient effect. The goal gradient effect is when the efficiency and/or strength of a response increases as an individual gets nearer to their end goal. (Powell et al., 2015) An example from a field experiment showed that people involved in a cafe reward program tended to buy coffee more often as they became closer to the end reward of receiving a free drink. (Batterbee) Extending to a personal example, when doing a workout, sometimes I complete the exercises towards the end faster than the ones towards the beginning because I know I am reaching the end of the workout. The immediate reinforcement of finishing in the end is more enticing than the beginning when the reinforcement feels delayed. I do feel that the goal gradient effect is a valid explanation for why individuals may behave the way that they do in a chained schedule, however I also see how when a chained schedule is a little too long, one might be discouraged in the beginning and not attempt to complete the links because of how delayed the terminal reinforcer is.

As seen in the visual, the runner took less time running as they neared the end sections of the run.

Powell, R. A., Honey, P. L., & Symbaluk, D. G. (2015). Introduction to Learning and Behavior. Cengage Learning.

Batterbee, I. (2020, May 17). Designing for Motivation with the Goal-Gradient Effect. UX Collective.

Goal Gradient Effect and How to Get Customers to Buy. Conversion Uplift.