Fixed-interval schedule, often referred to as FI schedule, is a fundamental concept in the field of psychology, specifically in the study of operant conditioning and behavior modification. It is a type of reinforcement schedule that involves providing a reward or reinforcement at fixed, regular intervals of time, regardless of the individual’s behavior. Fixed-interval schedules have significant implications for understanding behavior patterns, motivation, and learning.
A fixed-interval schedule is a specific type of reinforcement schedule used in operant conditioning, a form of learning in which behavior is influenced by its consequences. In a fixed-interval schedule, reinforcements or rewards are delivered to an individual or animal at fixed, predetermined intervals of time, irrespective of the individual’s behavior. This means that the individual does not need to perform a specific action to receive the reward; they only need to wait until the specified time interval has elapsed.
Key characteristics of fixed-interval schedules include:
Fixed Timing: The intervals of time between reinforcements are consistent and unchanging. For example, a reinforcement might be delivered every 5 minutes, 30 minutes, or any other fixed time interval.
Response Not Required: Unlike other reinforcement schedules where a specific behavior must be performed to receive a reward, fixed-interval schedules do not require any particular action from the individual. The reinforcement is delivered automatically when the time interval elapses.
Scalloped Response Pattern: Behavior under a fixed-interval schedule typically exhibits a scalloped response pattern, where the rate of responding increases as the time for the next reinforcement approaches and then drops sharply after the reinforcement is received.
Predictability: Individuals or animals under fixed-interval schedules can predict when the next reinforcement will be available, leading to behavior that corresponds to the timing of the rewards.
Examples of Fixed-Interval Schedules
To better understand fixed-interval schedules, let’s explore a few real-life examples:
1. Paycheck Schedule
Consider an individual who receives a paycheck every two weeks. The individual knows that they will receive a paycheck every 14 days, regardless of their daily work performance. This is an example of a fixed-interval schedule.
2. Bus Schedule
A bus arriving at a bus stop every 30 minutes is another example. Passengers waiting for the bus know that it will arrive at fixed intervals, and they do not need to take any specific action to make it arrive.
3. Pigeon Pecking for Food
In behavioral experiments with pigeons, researchers might use a fixed-interval schedule to provide food rewards. If food is delivered to a pigeon every 5 minutes, the pigeon will gradually increase its pecking behavior as the 5-minute mark approaches.
Characteristics of Fixed-Interval Schedules
Fixed-interval schedules exhibit several distinct characteristics:
1. Scalloped Response Pattern
One of the hallmark features of fixed-interval schedules is the scalloped response pattern. This pattern is characterized by a gradual increase in the rate of responding as the time for the next reinforcement approaches, followed by a sharp drop in responding immediately after reinforcement delivery. This cyclical pattern continues throughout the interval.
2. Post-Reinforcement Pause
After receiving a reinforcement, individuals or animals tend to exhibit a pause in responding. This post-reinforcement pause occurs because they know that another opportunity for reinforcement will not occur until the fixed interval has elapsed.
3. Timing and Predictability
Under fixed-interval schedules, individuals or animals learn to time their responses based on their experience with the schedule. They become adept at predicting when the next reinforcement will be available and adjust their behavior accordingly.
4. Lower Response Rates
Compared to other reinforcement schedules, fixed-interval schedules tend to result in lower overall response rates. This is due to the fact that individuals or animals do not need to continuously engage in the target behavior to receive reinforcement.
Applications of Fixed-Interval Schedules
Fixed-interval schedules have practical applications and implications in various domains:
1. Employee Performance
In the workplace, certain jobs may offer fixed-interval reinforcement in the form of regular paychecks. Employees know that they will receive their salary at set intervals, which can influence their work patterns and motivation.
2. Academic Schedules
Schools often operate on fixed-interval schedules, with students receiving grades and feedback at the end of each grading period (e.g., every semester or quarter). This schedule can affect students’ study habits and academic performance.
3. Animal Training
Fixed-interval schedules are used in animal training to reinforce desired behaviors at regular intervals. For example, a dolphin might receive a reward every 10 minutes during a training session.
4. Public Transportation
Public transportation systems, such as buses and trains, operate on fixed-interval schedules. Passengers know when to expect the arrival of vehicles, allowing them to plan their travel accordingly.
5. Reinforcement in Clinical Settings
Fixed-interval schedules are sometimes used in clinical settings to provide reinforcement for specific behaviors. For instance, a therapist might use a fixed-interval schedule to reward a child for staying seated during a therapy session.
Advantages of Fixed-Interval Schedules
Fixed-interval schedules offer several advantages and insights into behavior:
1. Predictability
The predictability of fixed-interval schedules can be advantageous in certain contexts. Individuals or animals can anticipate when reinforcements will be available, which can lead to regular, reliable behavior patterns.
2. Control and Consistency
Fixed-interval schedules allow for precise control over the timing of reinforcements. This control is valuable in research settings and when establishing routine behaviors.
3. Resource Management
In situations where resources or rewards are limited, fixed-interval schedules can help distribute them evenly and efficiently, preventing overconsumption or wastage.
4. Observing Timing Behavior
Fixed-interval schedules provide insights into how individuals or animals time their responses in anticipation of rewards. This can be valuable for studying timing-related behaviors.
Drawbacks and Limitations
Despite their advantages, fixed-interval schedules have limitations and drawbacks:
1. Scalloped Response Pattern
The scalloped response pattern, characterized by a post-reinforcement pause, may not be suitable for situations requiring consistent and continuous behavior.
2. Low Response Rates
Fixed-interval schedules often result in lower response rates compared to other schedules. This can be problematic when high levels of engagement or productivity are needed.
3. Lack of Precision
While fixed-interval schedules provide control over timing, they may lack precision when it comes to shaping specific behaviors or response rates.
4. Potential for Timing Manipulation
Individuals or animals may learn to manipulate the timing of their responses to maximize reinforcement, leading to suboptimal behavior.
Comparison to Other Reinforcement Schedules
Fixed-interval schedules are just one type of reinforcement schedule. Other common schedules include:
Fixed-Ratio Schedule (FR): In a fixed-ratio schedule, reinforcement is delivered after a fixed number of responses. This schedule typically results in high response rates.
Variable-Interval Schedule (VI): In a variable-interval schedule, reinforcement is provided at variable, unpredictable time intervals. This schedule tends to produce steady, moderate response rates.
Variable-Ratio Schedule (VR): In a variable-ratio schedule, reinforcement is given after a variable number of responses. This schedule often leads to high and steady response rates.
Conclusion
Fixed-interval schedules play a crucial role in the study of operant conditioning and behavior modification. They provide insights into how timing and predictability influence behavior patterns. While fixed-interval schedules offer advantages such as predictability and resource management, they also come with limitations, including a scalloped response pattern and lower response rates. Understanding the dynamics of fixed-interval schedules contributes to our knowledge of human and animal behavior and has practical applications in various fields, from education to public transportation.
Convergent thinking occurs when the solution to a problem can be found by applying established rules and logical reasoning. Whereas divergent thinking is an unstructured problem-solving method where participants are encouraged to develop many innovative ideas or solutions to a given problem. Where convergent thinking might work for larger, mature organizations where divergent thinking is more suited for startups and innovative companies.
The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman in 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty.
Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.
Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.
Bounded rationality is a concept attributed to Herbert Simon, an economist and political scientist interested in decision-making and how we make decisions in the real world. In fact, he believed that rather than optimizing (which was the mainstream view in the past decades) humans follow what he called satisficing.
The Dunning-Kruger effect describes a cognitive bias where people with low ability in a task overestimate their ability to perform that task well. Consumers or businesses that do not possess the requisite knowledge make bad decisions. What’s more, knowledge gaps prevent the person or business from seeing their mistakes.
Occam’s Razor states that one should not increase (beyond reason) the number of entities required to explain anything. All things being equal, the simplest solution is often the best one. The principle is attributed to 14th-century English theologian William of Ockham.
The Lindy Effect is a theory about the ageing of non-perishable things, like technology or ideas. Popularized by author Nicholas Nassim Taleb, the Lindy Effect states that non-perishable things like technology age – linearly – in reverse. Therefore, the older an idea or a technology, the same will be its life expectancy.
Antifragility was first coined as a term by author, and options trader Nassim Nicholas Taleb. Antifragility is a characteristic of systems that thrive as a result of stressors, volatility, and randomness. Therefore, Antifragile is the opposite of fragile. Where a fragile thing breaks up to volatility; a robust thing resists volatility. An antifragile thing gets stronger from volatility (provided the level of stressors and randomness doesn’t pass a certain threshold).
Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. It is about thinking non-linearly, and understanding the second-order consequences of actions and input into the system.
Vertical thinking, on the other hand, is a problem-solving approach that favors a selective, analytical, structured, and sequential mindset. The focus of vertical thinking is to arrive at a reasoned, defined solution.
Maslow’s Hammer, otherwise known as the law of the instrument or the Einstellung effect, is a cognitive bias causing an over-reliance on a familiar tool. This can be expressed as the tendency to overuse a known tool (perhaps a hammer) to solve issues that might require a different tool. This problem is persistent in the business world where perhaps known tools or frameworks might be used in the wrong context (like business plans used as planning tools instead of only investors’ pitches).
The Peter Principle was first described by Canadian sociologist Lawrence J. Peter in his 1969 book The Peter Principle. The Peter Principle states that people are continually promoted within an organization until they reach their level of incompetence.
The straw man fallacy describes an argument that misrepresents an opponent’s stance to make rebuttal more convenient. The straw man fallacy is a type of informal logical fallacy, defined as a flaw in the structure of an argument that renders it invalid.
The Streisand Effect is a paradoxical phenomenon where the act of suppressing information to reduce visibility causes it to become more visible. In 2003, Streisand attempted to suppress aerial photographs of her Californian home by suing photographer Kenneth Adelman for an invasion of privacy. Adelman, who Streisand assumed was paparazzi, was instead taking photographs to document and study coastal erosion. In her quest for more privacy, Streisand’s efforts had the opposite effect.
As highlighted by German psychologist Gerd Gigerenzer in the paper “Heuristic Decision Making,” the term heuristic is of Greek origin, meaning “serving to find out or discover.” More precisely, a heuristic is a fast and accurate way to make decisions in the real world, which is driven by uncertainty.
The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.
The representativeness heuristic was first described by psychologists Daniel Kahneman and Amos Tversky. The representativeness heuristic judges the probability of an event according to the degree to which that event resembles a broader class. When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.
The take-the-best heuristic is a decision-making shortcut that helps an individual choose between several alternatives. The take-the-best (TTB) heuristic decides between two or more alternatives based on a single good attribute, otherwise known as a cue. In the process, less desirable attributes are ignored.
The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.
The Barnum Effect is a cognitive bias where individuals believe that generic information – which applies to most people – is specifically tailored for themselves.
First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.
The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.
Goodhart’s Law is named after British monetary policy theorist and economist Charles Goodhart. Speaking at a conference in Sydney in 1975, Goodhart said that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.
The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.
The Mandela effect is a phenomenon where a large group of people remembers an event differently from how it occurred. The Mandela effect was first described in relation to Fiona Broome, who believed that former South African President Nelson Mandela died in prison during the 1980s. While Mandela was released from prison in 1990 and died 23 years later, Broome remembered news coverage of his death in prison and even a speech from his widow. Of course, neither event occurred in reality. But Broome was later to discover that she was not the only one with the same recollection of events.
The bandwagon effect tells us that the more a belief or idea has been adopted by more people within a group, the more the individual adoption of that idea might increase within the same group. This is the psychological effect that leads to herd mentality. What in marketing can be associated with social proof.
Moore’s law states that the number of transistors on a microchip doubles approximately every two years. This observation was made by Intel co-founder Gordon Moore in 1965 and it become a guiding principle for the semiconductor industry and has had far-reaching implications for technology as a whole.
Disruptive innovation as a term was first described by Clayton M. Christensen, an American academic and business consultant whom The Economist called “the most influential management thinker of his time.” Disruptive innovation describes the process by which a product or service takes hold at the bottom of a market and eventually displaces established competitors, products, firms, or alliances.
Value migration was first described by author Adrian Slywotzky in his 1996 book Value Migration – How to Think Several Moves Ahead of the Competition. Value migration is the transferal of value-creating forces from outdated business models to something better able to satisfy consumer demands.
The bye-now effect describes the tendency for consumers to think of the word “buy” when they read the word “bye”. In a study that tracked diners at a name-your-own-price restaurant, each diner was asked to read one of two phrases before ordering their meal. The first phrase, “so long”, resulted in diners paying an average of $32 per meal. But when diners recited the phrase “bye bye” before ordering, the average price per meal rose to $45.
Groupthink occurs when well-intentioned individuals make non-optimal or irrational decisions based on a belief that dissent is impossible or on a motivation to conform. Groupthink occurs when members of a group reach a consensus without critical reasoning or evaluation of the alternatives and their consequences.
A stereotype is a fixed and over-generalized belief about a particular group or class of people. These beliefs are based on the false assumption that certain characteristics are common to every individual residing in that group. Many stereotypes have a long and sometimes controversial history and are a direct consequence of various political, social, or economic events. Stereotyping is the process of making assumptions about a person or group of people based on various attributes, including gender, race, religion, or physical traits.
Murphy’s Law states that if anything can go wrong, it will go wrong. Murphy’s Law was named after aerospace engineer Edward A. Murphy. During his time working at Edwards Air Force Base in 1949, Murphy cursed a technician who had improperly wired an electrical component and said, “If there is any way to do it wrong, he’ll find it.”
The law of unintended consequences was first mentioned by British philosopher John Locke when writing to parliament about the unintended effects of interest rate rises. However, it was popularized in 1936 by American sociologist Robert K. Merton who looked at unexpected, unanticipated, and unintended consequences and their impact on society.
Fundamental attribution error is a bias people display when judging the behavior of others. The tendency is to over-emphasize personal characteristics and under-emphasize environmental and situational factors.
Outcome bias describes a tendency to evaluate a decision based on its outcome and not on the process by which the decision was reached. In other words, the quality of a decision is only determined once the outcome is known. Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.
Hindsight bias is the tendency for people to perceive past events as more predictable than they actually were. The result of a presidential election, for example, seems more obvious when the winner is announced. The same can also be said for the avid sports fan who predicted the correct outcome of a match regardless of whether their team won or lost. Hindsight bias, therefore, is the tendency for an individual to convince themselves that they accurately predicted an event before it happened.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
