Learning Theory and Gambling Addiction | AQA A-Level Psychology Revision

Revision Notes
Aug 7
35 min read

Updated: Aug 14

For 7182 specification, first teach in September 2025

AQA A-Level Psychology | Free Revision Notes

Estimated study time: 60 to 75 minutes

Learning theory and gambling addiction A-Level Psychology revision examines how occasional and unpredictable rewards can maintain persistent gambling. A win acts as positive reinforcement, but because only some bets are rewarded, gamblers learn to continue through long sequences of losses.

You will explore partial reinforcement, variable reinforcement and the variable-ratio schedule commonly associated with gambling. You will also learn how to apply these principles to slot machines, card games, lotteries and online betting. AQA specifically requires learning theory applied to gambling, including partial and variable reinforcement.

Learning Objectives 🎯

By the end of this revision page, you should be able to:

Define operant conditioning and reinforcement.
Explain how winning may positively reinforce gambling.
Distinguish continuous reinforcement from partial reinforcement.
Explain why partial reinforcement produces resistance to extinction.
Explain variable reinforcement.
Distinguish variable-ratio from variable-interval schedules.
Apply reinforcement schedules to unfamiliar examples of gambling.
Evaluate learning theory as an explanation of gambling addiction.

Revision Notes 📚

Learning Theory and Gambling Addiction A-Level Psychology Revision Focus

Learning theory explains behaviour as the result of experience.

In gambling addiction, the main process is operant conditioning.

The basic sequence is:

Gambling response → occasional win → rewarding consequence → gambling becomes more likely to be repeated

A gambler does not need to win every time.

In fact, the unpredictable delivery of rewards can make gambling especially persistent because the person learns that another response might produce the next win.

AQA’s June 2023 mark scheme explains gambling through an association between a response and its consequence. Wins positively reinforce betting, strengthening the behaviour through repeated association.

Operant Conditioning

What Is Operant Conditioning?

Operant conditioning is learning through the consequences of behaviour.

A behaviour followed by reinforcement becomes more likely to occur again.

In gambling:

The behaviour is placing a bet, spinning a reel, buying a ticket or selecting a hand.
The consequence may be winning money, receiving excitement or gaining social approval.
The consequence may reinforce future gambling.

The process can be represented as:

A person places a bet.
The person wins.
The win produces money or excitement.
The outcome is rewarding.
The person becomes more likely to gamble again.

The Operant

An operant is a voluntary behaviour that acts upon the environment and produces a consequence.

Examples of gambling operants include:

Pressing the button on a slot machine.
Placing a bet on a sporting event.
Purchasing a scratchcard.
Buying a lottery ticket.
Selecting a number in roulette.
Choosing to remain in a card game.
Increasing the amount staked.

The consequence following the operant affects whether it will be repeated.

Reinforcement

What Is Reinforcement?

A reinforcer is a consequence that increases the probability of the behaviour it follows.

The defining feature is not whether the consequence appears pleasant to an observer.

The defining feature is:

Did the consequence increase the likelihood of the behaviour being repeated?

Positive Reinforcement

Positive reinforcement occurs when a rewarding stimulus is added after a behaviour, increasing the likelihood of that behaviour.

In gambling, possible positive reinforcers include:

Winning money.
Receiving a payout.
Experiencing excitement.
Receiving praise from friends.
Gaining status within a gambling group.
Unlocking an online reward.
Seeing celebratory sounds or images after a win.

For example:

A person places a bet and wins £20. The money and excitement positively reinforce betting, making another bet more likely.

Positive Does Not Mean Beneficial

In operant conditioning, positive means that something is added.

It does not mean:

Healthy.
Sensible.
Financially beneficial overall.
Morally good.

A person may lose much more money than they win, but an occasional payout can still reinforce the immediate gambling response.

Money as a Reinforcer

Money is normally described as a secondary reinforcer.

It has learned value because it can be exchanged for:

Food.
Possessions.
Entertainment.
Experiences.
Social status.

The payout therefore reinforces gambling even though money does not directly satisfy a biological need.

Excitement as Reinforcement

A gambler may also be reinforced by the emotional experience of gambling.

This may include:

Anticipation.
Suspense.
Risk.
Competition.
Relief.
Celebration.
Social interaction.

A person may therefore continue gambling even where financial profit is rare.

The rewarding consequence may be the experience itself rather than only the money.

Negative Reinforcement

What Is Negative Reinforcement?

Negative reinforcement occurs when a behaviour becomes more likely because it removes or reduces an unpleasant state.

A person might gamble because it temporarily removes:

Boredom.
Anxiety.
Stress.
Loneliness.
Low mood.
Worry about other problems.

For example:

A person feels anxious and begins gambling online. While concentrating on the game, their anxiety temporarily decreases. This relief negatively reinforces gambling.

Negative reinforcement may contribute to gambling addiction, but the required focus of this lesson is partial and variable reward.

Reinforcement Is Not Punishment

Both positive and negative reinforcement increase behaviour.

Process	What happens?	Effect on gambling
Positive reinforcement	A rewarding consequence is added	Gambling increases
Negative reinforcement	An unpleasant condition is removed	Gambling increases
Punishment	An unpleasant consequence occurs or something valued is removed	Gambling should decrease

Financial loss might appear to punish gambling.

However, because occasional wins occur unpredictably, losses may not stop the behaviour.

Reinforcement Schedules

What Is a Reinforcement Schedule?

A reinforcement schedule is the pattern determining when a response will be rewarded.

The schedule affects:

How quickly behaviour is learned.
How often the behaviour occurs.
How long it continues.
How resistant it is to extinction.

The main distinction for AQA is between:

Continuous reinforcement.
Partial reinforcement.
Variable reinforcement.

Continuous Reinforcement

What Is Continuous Reinforcement?

Continuous reinforcement occurs when every correct response is rewarded.

For example:

Every time a person presses a button, they receive £1.

Continuous reinforcement usually produces:

Rapid learning.
A clear association between behaviour and reward.
Rapid extinction when the reward stops.

The person quickly notices that the system has changed:

“This response used to produce a reward every time, but it no longer does.”

Why Real Gambling Is Not Continuously Reinforced

If every bet produced a profit:

The activity would not operate as ordinary gambling.
The reward would be entirely predictable.
Losses would not occur.
The organisation providing the gambling activity would continually lose money.

Instead, gambling normally involves rewards on only some occasions.

Partial Reinforcement

What Is Partial Reinforcement?

Partial reinforcement, also called intermittent reinforcement, occurs when only some responses are rewarded.

For example:

A gambler places ten bets but wins on only two of them.

The other eight responses receive no financial reward.

The key principle is:

The behaviour is reinforced occasionally rather than every time.

AQA specifically identifies partial reinforcement as required content in learning explanations of gambling addiction.

The Partial Reinforcement Sequence

The process may be:

The person gambles.
Most bets lose.
One bet produces a win.
The win is highly rewarding.
The person learns that persistence can eventually be rewarded.
Gambling continues through later losses.
Another unpredictable win strengthens the behaviour again.

Partial Reinforcement and Persistent Gambling

Under partial reinforcement, a loss does not clearly signal that rewards have ended.

The gambler has previously experienced:

Several losses before a win.
Long periods without reinforcement.
A reward that arrived after persistence.

A new series of losses may therefore be interpreted as part of the established pattern.

The person may continue because:

“A win has followed losses before, so another win may still occur.”

This persistence does not mean that a win is genuinely due.

It means that the reinforcement history has taught the person to keep responding when rewards are absent.

The Partial Reinforcement Extinction Effect

What Is Extinction?

Extinction occurs when a learned behaviour decreases because reinforcement is no longer provided.

For example:

If gambling never produced any reward, betting might gradually decrease.

Resistance to Extinction

Resistance to extinction means that the behaviour continues for a long time after reinforcement becomes absent or rare.

Behaviour acquired under partial reinforcement is usually more resistant to extinction than behaviour acquired under continuous reinforcement.

This is called the partial reinforcement extinction effect.

Why Partial Reinforcement Resists Extinction

Consider two conditions.

Continuous reinforcement history

A person has previously won after every response.

When several responses suddenly produce nothing, the change is obvious.

They may stop quickly.

Partial reinforcement history

A person has previously experienced many unrewarded responses between wins.

When several responses produce nothing, this seems normal.

They may continue because the next response could still be rewarded.

Reinforcement history	Experience when reward stops	Likely response
Continuous	Immediately different from previous experience	Rapid reduction in behaviour
Partial	Similar to previous periods without reward	Continued responding
Variable partial	Person cannot predict when reward should occur	Particularly persistent responding

Applying Resistance to Extinction

Tessa has previously won after long sequences of losing bets. She loses fifteen times in a row but continues because previous wins have also followed several losses.

Learning theory explains that:

Tessa has experienced partial reinforcement.
Losing has been part of her normal reinforcement history.
The absence of a reward does not clearly signal extinction.
Her gambling is therefore resistant to extinction.

Variable Reinforcement

What Is Variable Reinforcement?

Variable reinforcement occurs when rewards are delivered unpredictably.

The person does not know:

Which response will be rewarded.
How many responses will be required.
Exactly when the reward will occur.

The uncertainty encourages continued responding.

The person may think:

“The next attempt could be the winning one.”

Partial and Variable Are Not Identical

The terms are related but have different meanings.

Partial reinforcement: Only some responses are rewarded.
Variable reinforcement: The pattern of reinforcement is unpredictable.

A schedule can be both partial and variable.

Most gambling examples involve both:

Not every bet wins.
The person cannot reliably predict which bet will win.

Fixed and Variable Schedules

A schedule is fixed when reinforcement follows a predictable rule.

A schedule is variable when the requirement changes unpredictably.

Fixed schedule	Variable schedule
Reward follows a predictable pattern	Reward follows an unpredictable pattern
The person can anticipate when reinforcement is likely	The person cannot identify exactly when reinforcement will occur
Behaviour may pause when reward is known to be unavailable	Responding tends to remain steady because reward might occur

Ratio and Interval Schedules

Reinforcement schedules can also be divided according to whether reinforcement depends on:

The number of responses.
The passage of time.

Ratio Schedule

A ratio schedule links reinforcement to the number of responses made.

The question is:

How many responses must occur before reinforcement?

Interval Schedule

An interval schedule links reinforcement to the passage of time.

The question is:

How much time must pass before a response can be reinforced?

This produces four standard schedules.

Schedule	When is reinforcement available?
Fixed ratio	After a set number of responses
Variable ratio	After an unpredictable number of responses
Fixed interval	After a set period of time
Variable interval	After an unpredictable period of time

The AQA specification requires partial and variable reinforcement, not memorisation of every schedule. However, understanding the distinction improves application.

Fixed-Ratio Reinforcement

What Is a Fixed-Ratio Schedule?

On a fixed-ratio schedule, a reward follows a set number of responses.

For example:

Every tenth response produces a reward.

The person can predict approximately when reinforcement will occur.

This often produces:

A high response rate.
A brief pause after reinforcement.
Renewed responding as the next reward approaches.

Is Gambling Fixed Ratio?

Ordinary games of chance are not usually fixed-ratio schedules because the gambler cannot know that every tenth bet will win.

A reward scheme such as:

“Receive a free play after every ten paid games”

would be fixed ratio.

However, the gambling win itself would normally remain unpredictable.

Variable-Ratio Reinforcement

What Is a Variable-Ratio Schedule?

On a variable-ratio schedule, reinforcement occurs after an unpredictable number of responses.

For example:

A win may follow the third bet.
The next win may follow the fifteenth bet.
Another may follow the sixth bet.

The gambler cannot know which response will be rewarded.

Why Variable Ratio Produces Persistent Behaviour

A variable-ratio schedule produces persistent responding because:

Every response has the possibility of reinforcement.
The person cannot identify a safe point to stop.
A run of losses has occurred before previous wins.
The next response may be rewarded.
The schedule does not provide a clear signal that reinforcement has ended.

This makes the behaviour highly resistant to extinction.

Slot-Machine Example

Each spin is a response.

Only occasional spins produce a payout, and the player cannot reliably predict which spin will win.

The sequence might be:

Spin → loss → spin → loss → spin → small win → spin → loss → spin → loss → spin → larger win

The wins positively reinforce continued spinning.

Because they occur after varying numbers of responses, this is consistent with a variable-ratio schedule.

Scratchcard Example

Each purchase and use of a scratchcard can be treated as a response.

Some cards produce rewards, but the buyer does not know which purchase will be successful.

The occasional win reinforces purchasing more cards.

Online Betting Example

A person places repeated bets on events.

Occasional wins provide:

Money.
Excitement.
Confirmation that winning is possible.

Because the person cannot reliably predict which bet will win, betting may be maintained by variable reinforcement.

Resistance to Extinction

Suppose a gambler loses repeatedly.

Under a variable-ratio schedule:

Previous wins have also been unpredictable.
The current losses are not unusual.
No specific number of losses proves that reinforcement has ended.
The person continues to respond.

This is why variable-ratio reinforcement is often described as producing particularly persistent behaviour.

Fixed-Interval Reinforcement

What Is a Fixed-Interval Schedule?

On a fixed-interval schedule, the first response after a set period of time is reinforced.

For example:

The first response after every five minutes produces a reward.

Responding may increase as the expected reinforcement time approaches.

This creates a pattern sometimes called a scallop, involving:

Slow responding after a reward.
Increasing responding as the next reward time approaches.

This schedule is less directly characteristic of most chance-based gambling wins.

Variable-Interval Reinforcement

What Is a Variable-Interval Schedule?

On a variable-interval schedule, reinforcement becomes available after varying and unpredictable periods of time.

For example:

A response may be reinforced after two minutes.
The next reward may become available after nine minutes.
Another may become available after four minutes.

The person keeps checking or responding because they do not know when reinforcement will become available.

AQA’s June 2023 Terminology

In the June 2023 examination, participants won practice card games numbered 1, 2, 6, 8 and 10. AQA’s mark scheme described this as a partial reinforcement/variable interval condition and predicted that reinforced participants would be more likely to place high-stakes bets in the test game.

For exam answers, follow the structure of the question:

If reinforcement follows an unpredictable number of bets or responses, variable ratio is the precise term.
If reinforcement becomes available after unpredictable amounts of time, use variable interval.
If the stem simply shows irregular occasional wins, partial and variable reinforcement are safe and directly specification-linked terms.

The crucial point is that the reward is intermittent and unpredictable.

Comparing the Four Schedules

Schedule	Basis	Predictable?	Gambling example
Fixed ratio	Number of responses	Yes	A bonus after every ten paid plays
Variable ratio	Number of responses	No	A slot-machine payout after an unpredictable number of spins
Fixed interval	Passage of time	Yes	A reward becomes available after a set period
Variable interval	Passage of time	No	A reward becomes available after unpredictable periods

Most Important Schedule for Gambling

The variable-ratio schedule is especially useful for explaining repeated gambling responses because:

Wins occur after unpredictable numbers of bets.
The response rate can remain high.
The behaviour becomes resistant to extinction.
The gambler cannot know which bet might be rewarded.

However, AQA may use the broader phrase variable reinforcement or identify another schedule within a particular experimental stem.

Always read the exact information provided.

How Gambling Addiction Develops Through Reinforcement

Stage 1: Initial Gambling

The person begins gambling because of:

Curiosity.
Social influence.
Availability.
Sensation seeking.
A promotional opportunity.
Previous observation of other gamblers.

Learning theory does not need to claim that reinforcement caused the very first gamble.

Stage 2: An Early Win

An early bet produces:

Money.
Excitement.
Praise.
Relief.
A sense of achievement.

The win positively reinforces gambling.

Stage 3: Repetition

The person repeats the response because:

The previous behaviour produced a reward.
They expect that gambling can be rewarding again.
Gambling-related situations become associated with excitement.

Stage 4: Partial Reinforcement

The person begins losing on many bets.

However, occasional wins continue.

The gambler learns that:

Reward does not follow every response.
A sequence of losses does not prevent a later win.
Persistence is sometimes rewarded.

Stage 5: Variable Reinforcement

The timing of wins is unpredictable.

The gambler cannot identify which response will be successful.

This uncertainty encourages repeated betting.

Stage 6: Resistance to Extinction

Even during a long losing sequence, the person continues because previous rewards have also followed periods without reinforcement.

The gambling behaviour becomes difficult to extinguish.

Stage 7: Psychological Dependence

The person may become psychologically dependent on:

Excitement.
Anticipation.
Escape.
Social rewards.
The possibility of winning.

This connects with psychological dependence and tolerance [Lesson 1: Describing addiction].

Applying Learning Theory to Different Types of Gambling

Slot Machines

Response

Pressing the button or initiating a spin.

Reinforcer

An occasional payout, celebratory display or excitement.

Schedule

Partial and variable, usually described as variable ratio when the focus is the number of spins.

Effect

The player continues through losses because the next spin might be rewarded.

Roulette

Response

Placing a bet before each spin.

Reinforcer

An occasional financial win and excitement.

Schedule

Partial and variable.

Effect

Effect

Occasional successful predictions reinforce continued betting.

Skill and knowledge may influence some sporting judgements, but outcomes remain uncertain. Beliefs about possessing exceptional skill are addressed in the next lesson.

Card Games

Response

Entering a hand, remaining in play or placing a bet.

Reinforcer

Winning a hand or receiving money.

Schedule

Partial and variable.

Effect

Irregular wins strengthen continued participation and may encourage larger stakes.

Online Gambling

Online gambling may provide rapid sequences of:

Bets.
Wins.
Losses.
Visual feedback.
Sounds.
Bonus rewards.
Opportunities to continue immediately.

The short delay between response and outcome can strengthen the learned association.

The person can quickly connect:

“I placed that bet, and this rewarding outcome followed.”

Immediacy of Reinforcement

Why Immediate Rewards Matter

Reinforcement tends to be more effective when it follows the behaviour quickly.

A short delay makes it easier to learn the connection between:

The gambling response.
The rewarding consequence.

For example:

A button is pressed, and a payout appears immediately.

The contingency is clear.

Delayed Gambling Outcomes

Some gambling involves longer delays, such as:

Lottery draws.
Sporting events.
Future race results.

The behaviour may still be reinforced when the person:

Anticipates the result.
Receives social excitement while waiting.
Remembers previous wins.
Repeatedly checks the outcome.

However, immediate digital gambling may create especially rapid response-consequence learning.

Magnitude of Reinforcement

What Is Magnitude?

Magnitude refers to the size or value of the reward.

A large win may be especially memorable and reinforcing.

However, small wins can also maintain behaviour when they:

Occur more frequently.
Produce celebratory feedback.
Encourage another bet.
Give the impression that winning is common.
Return some of the money staked.

A Payout Is Not Necessarily a Profit

Suppose a person stakes £5 and receives £3 back.

They have lost £2 overall.

However, the return may still be accompanied by:

Sound.
Visual celebration.
Excitement.
A feeling of success.

A precise answer should distinguish:

Receiving a payout.
Making an overall profit.

Learning theory focuses on whether the consequence functions as reinforcement.

Discriminative Stimuli

What Is a Discriminative Stimulus?

A discriminative stimulus signals that reinforcement may be available.

In gambling, possible signals include:

A betting application.
A casino.
A sporting event.
An advertisement.
A notification.
A lottery shop.
A group of gambling friends.

These stimuli may increase gambling because they signal opportunities for reward.

Detailed cue associations are most central to learning theory and nicotine addiction [Lesson 5: Learning theory and nicotine addiction], but the same general learning principle can help explain why gambling environments trigger behaviour.

Secondary Reinforcement

Gambling-Related Cues Gain Value

A stimulus associated with winning may become rewarding in its own right.

Examples include:

The sound of coins.
A celebratory animation.
The sight of a gambling application.
Casino lights.
A betting slip.
A notification announcing a possible reward.

Through association with financial wins, these cues may become secondary reinforcers.

They can increase:

Excitement.
Anticipation.
Motivation to continue.

Distinguishing the Win and the Cue

The financial win is a reinforcing consequence.
A sound repeatedly paired with wins may become a secondary reinforcer.
The sound can then encourage continued play even before another genuine win occurs.

Extinction in Gambling

What Would Extinction Require?

For gambling behaviour to extinguish through lack of reinforcement:

The person would repeatedly gamble without any reward.
The expected reward would fail to occur.
The response would gradually decrease.

However, extinction is difficult when occasional wins continue.

Each new win may:

Reinstate the learned association.
Restore expectation.
Strengthen persistence.
Interrupt extinction.

Why One Win Matters

Imagine that a person is close to stopping after many losses.

A single win may:

Provide financial reward.
Produce strong excitement.
Confirm that wins still occur.
Strengthen the response-reward association.
Increase future gambling.

The gambler does not need to win frequently for the behaviour to persist.

Spontaneous Recovery and Reinstatement

Spontaneous Recovery

Spontaneous recovery is the return of an extinguished response after a period without exposure.

A person may stop gambling for several months but later experience renewed urges when encountering a gambling opportunity.

Reinstatement

Reinstatement occurs when exposure to a reward or related experience restores a previously reduced response.

For example:

After a long period without gambling, a person receives a free bet and wins. The reward may reinstate persistent gambling.

These concepts help explain relapse, although AQA’s central required terminology remains partial and variable reinforcement.

Does Losing Punish Gambling?

Financial loss could act as punishment because it is an unpleasant consequence.

However, punishment may fail to eliminate gambling because:

Wins still occur occasionally.
Wins may be more emotionally memorable than losses.
The reward schedule teaches persistence.
Losses have previously been followed by wins.
Gambling may remove boredom or stress.
Social rewards may continue despite financial losses.
Cognitive biases may alter how losses are interpreted.

Learning theory therefore predicts competition between:

Punishing consequences from losses.
Reinforcing consequences from wins, excitement and relief.

The Role of Social Reinforcement

Gambling may also receive social reinforcement.

Friends may provide:

Praise for a successful bet.
Attention.
Inclusion.
Status.
Admiration for risk taking.
Shared excitement.

A person may continue gambling because it is part of group activity.

This connects with family, peers and social identity as addiction risks [Lesson 3: Personality and social influences].

Social rewards can operate alongside financial variable reinforcement.

The Role of Modelling

The person may observe:

Family members gambling.
Friends celebrating wins.
Other gamblers receiving attention.
Publicised winners.
Influential figures discussing successful bets.

Observation can create expectations that gambling is:

Exciting.
Normal.
Socially rewarded.
Potentially profitable.

However, the core learning explanation required for this lesson is operant conditioning and reinforcement schedules.

Partial Reinforcement and Tolerance

A gambler may gradually require:

Larger bets.
Riskier games.
More frequent gambling.
Longer sessions.

to obtain the previous level of excitement.

This is tolerance.

Partial and variable reinforcement may contribute because the gambler continues responding through losses, while occasional wins reinforce escalation.

However, increasing stakes may also involve:

Sensation seeking.
Cognitive bias.
Attempts to recover losses.

Do not treat every increase in gambling as solely a reinforcement-schedule effect.

Partial Reinforcement and Psychological Dependence

A person may become psychologically dependent on:

Anticipation of the next possible win.
The emotional excitement.
Escape from problems.
Gambling routines.
Social participation.

The unpredictability itself may become engaging because every response carries uncertainty.

The gambler may think repeatedly about:

When the next win will occur.
How to obtain money to gamble.
Which opportunity to choose.
Whether to continue after losses.

Partial Reinforcement and Withdrawal

When unable to gamble, the person may experience:

Restlessness.
Irritability.
Craving.
Preoccupation.
Boredom.
Low mood.

Returning to gambling may remove these unpleasant experiences, creating negative reinforcement.

The addiction may therefore be maintained by:

Positive reinforcement from wins and excitement.
Negative reinforcement from removing psychological discomfort.
Resistance to extinction under partial and variable schedules.

AQA June 2023 Applied Study

In the June 2023 paper, participants played ten practice card games.

One group won games 1, 2, 6, 8 and 10.
Another group won no practice games.
Participants then chose either high or low stakes in a test game.

Predicted Outcome

Learning theory predicts that:

More participants in the intermittently reinforced group would select high stakes.
More participants receiving no reinforcement would select low stakes.

Explanation

For the winning group:

Betting was followed by occasional wins.
The wins were positive reinforcers.
An association formed between gambling and reward.
The irregular pattern represented partial and variable reinforcement.
Gambling became more likely and potentially more persistent.
Participants may therefore be willing to risk more in the test game.

For the no-win group:

Gambling was never followed by a rewarding outcome.
The response received no positive reinforcement.
The association between betting and reward was not strengthened.
Lower subsequent betting would therefore be expected.

The official mark scheme awarded credit for predicting outcomes in both conditions and explaining the result through operant conditioning and positive reinforcement.

Applying Reinforcement Schedules

A Complete Application Method

When applying learning theory to a gambling scenario:

Identify the gambling response.
Identify the reward.
State that the reward is positive reinforcement.
Explain whether reinforcement is partial.
Explain whether it is unpredictable or variable.
Identify the appropriate schedule where possible.
Explain why the behaviour becomes resistant to extinction.
Link the explanation to continued or increased gambling.

Worked Example

Jamie uses an online slot machine. Most spins lose, but occasionally the machine produces a cash payout. Jamie never knows which spin will win and continues playing after long sequences of losses.

A developed application would state:

Pressing to spin is Jamie’s operant response.
Cash payouts are positive reinforcers.
Only some spins are rewarded, so reinforcement is partial.
Payouts follow unpredictable numbers of spins, making the schedule variable ratio.
Jamie has learned that losses can be followed by a later win.
A sequence without reinforcement therefore does not signal that winning is impossible.
The behaviour becomes resistant to extinction.
Jamie continues gambling because the next spin might produce reinforcement.

Weak Application

Jamie gambles because he is reinforced.

This does not identify:

The response.
The consequence.
The schedule.
The effect on persistence.

Applying Two Conditions in an Experiment

Suppose one group receives occasional wins and another receives no wins.

A strong comparison states:

Participants receiving occasional wins should gamble more because the wins positively reinforce the betting response under a partial and variable schedule. Participants receiving no wins should gamble less because their betting has not been reinforced.

Do not discuss only the reinforced group if the question asks about both conditions.

Learning Theory Compared with Cognitive Theory

Learning theory	Cognitive theory
Explains gambling through consequences	Explains gambling through thoughts and beliefs
Wins positively reinforce betting	Cognitive biases distort understanding of chance
Partial schedules teach persistence through losses	Gambler’s fallacy may produce the belief that a win is due
Variable schedules make rewards unpredictable	Illusion of control creates belief that outcomes can be influenced
Focuses on observable behaviour	Focuses on internal mental processes
Environmental explanation	Cognitive explanation

The explanations may operate together.

For example:

Occasional wins reinforce gambling.
Partial reinforcement teaches persistence.
The gambler develops the belief that continued effort will soon be rewarded.
Cognitive bias strengthens the learned behaviour.

Cognitive explanations are examined in irrational thinking and cognitive bias in gambling [Lesson 7: Cognitive explanations of gambling addiction].

An Important Distinction: Schedule Versus Gambler’s Fallacy

A variable schedule means:

The reward is unpredictable.

It does not mean:

A win becomes more likely because several losses have occurred.

The gambler’s fallacy is the mistaken belief that a run of losses must soon be followed by a win.

Under many chance-based games, individual outcomes remain independent.

Do not use the variable-ratio schedule itself as proof that a win is due.

Learning theory explains persistence because wins have occurred unpredictably before.

Cognitive theory explains the inaccurate belief that previous losses alter the probability of the next independent outcome.

Evaluating Learning Theory

Strength: Clear and Testable Predictions

Learning theory produces clear predictions.

For example:

A group receiving occasional wins should gamble more than a group receiving no wins.
Behaviour reinforced intermittently should persist longer during extinction.
Unpredictable rewards should produce more persistent responding than predictable rewards.
Increasing reward value should increase responding.

These variables can be operationalised and tested experimentally.

The June 2023 AQA study was constructed around the prediction that participants receiving intermittent wins would later select higher stakes.

Scientific Value

Researchers can manipulate:

Frequency of wins.
Pattern of wins.
Size of reward.
Delay before reward.
Number of gambling responses.

They can measure:

Number of bets.
Amount staked.
Length of play.
Persistence during losses.
Time before stopping.

This supports objective and replicable research.

Strength: Experimental Control

Laboratory gambling tasks allow researchers to control:

Which participants win.
When wins occur.
The value of rewards.
Number of trials.
Instructions.
Gambling format.

This control can strengthen conclusions about cause and effect.

For example:

If two randomly allocated groups differ only in their reinforcement schedules, a difference in later betting can more confidently be attributed to reinforcement.

Limitations of Experimental Control

High control may create artificial gambling.

Participants may know:

The money is not their own.
The task will soon end.
Losses are limited.
They are taking part in research.
No serious debt is possible.

The psychological experience may differ from real gambling addiction.

Limitation: Artificial Gambling Tasks

A computer card game in a laboratory may lack:

Genuine financial risk.
Emotional investment.
Social pressure.
Long-term reinforcement history.
Debt.
Secrecy.
Family conflict.
Strong craving.

This reduces ecological validity.

A person might select higher stakes in a brief study without developing persistent gambling outside the laboratory.

Prediction Versus Addiction

A laboratory experiment may show that reinforcement affects immediate betting.

It does not necessarily demonstrate:

Psychological dependence.
Long-term tolerance.
Continued gambling despite harm.
Withdrawal.
Addiction.

Learning effects in a short study provide support for the mechanism, but not complete evidence of gambling addiction.

Strength: Explains Persistence Despite Losses

A major strength is the explanation of why gambling continues even though most bets lose.

Under partial reinforcement:

Losses are expected.
Rewards have never followed every response.
A period without reward is not unusual.
Behaviour becomes resistant to extinction.

This directly addresses a central feature of gambling:

The behaviour may continue despite repeated non-reward.

A continuous-reinforcement explanation would struggle to account for persistence through long losing sequences.

Strength: Explains the Power of Unpredictability

Variable reinforcement explains why unpredictability can sustain high levels of responding.

The gambler does not know:

Which bet will win.
How long the losing sequence will last.
Whether stopping now would mean missing the next reward.

The schedule therefore provides no clear behavioural stopping point.

Strength: Applies Across Gambling Activities

The same learning principles can be applied to:

Slot machines.
Lotteries.
Scratchcards.
Roulette.
Sports betting.
Card games.
Online gambling.

The exact response and reward differ, but the general process remains:

Occasional unpredictable reward reinforces continued gambling.

This gives the explanation broad practical application.

Strength: Practical Applications

If variable reinforcement maintains gambling, interventions might attempt to:

Reduce opportunities to gamble.
Interrupt rapid response-reward cycles.
Remove gambling-related rewards.
Block access during high-risk periods.
Prevent small wins immediately funding further bets.
Teach the person to recognise the reinforcement schedule.
Use competing rewards for non-gambling behaviour.

Learning theory also provides the basis for behavioural interventions used to reduce addiction [Lesson 9: Aversion therapy and covert sensitisation].

Prevention Implications

Education could explain that:

Occasional wins are part of the reinforcement schedule.
A win does not mean long-term profit.
Previous losses do not make the next win due.
Unpredictability encourages persistence.

Understanding the schedule may help people recognise why stopping is difficult.

Limitation: Not Everyone Becomes Addicted

Many people experience occasional gambling wins without developing addiction.

This suggests that reinforcement schedules are not sufficient.

Individual differences may include:

Impulsivity.
Sensation seeking.
Genetic vulnerability.
Reward sensitivity.
Self-control.
Stress.
Social support.
Cognitive bias.

The same variable schedule produces different outcomes in different people.

Learning theory explains an environmental mechanism but not every individual difference.

Limitation: Initiation Is Not Fully Explained

Reinforcement cannot affect gambling until the person has performed the behaviour at least once.

Learning theory may not fully explain:

Why the first bet was placed.
Why one person entered a casino.
Why gambling was accessible.
Why the person accepted a friend’s invitation.
Why the person selected gambling rather than another activity.

Initiation may involve:

Social influence.
Modelling.
Personality.
Availability.
Advertising.
Stress.

Learning theory is generally stronger as an explanation of repetition and maintenance.

Limitation: Rewards Differ Between Individuals

The same outcome may not reinforce everyone equally.

For one person:

A £5 win may be exciting.

For another:

It may be insignificant.

Some people may be more reinforced by:

Social status.
Competition.
Escape.
Suspense.
Financial reward.

Learning theory must therefore consider the subjective value of the reinforcer.

Simply receiving a consequence does not prove that it functioned as reinforcement.

Limitation: Financial Losses Should Punish Behaviour

Repeated loss is an unpleasant consequence and might be expected to punish gambling.

Learning theory must explain why punishment does not outweigh reinforcement.

Possible explanations include:

Occasional wins are highly salient.
Rewards are unpredictable.
The person has learned to persist through losses.
Gambling provides excitement even during losing.
Social rewards remain available.
Cognitive biases alter the interpretation of losses.

The need for these additional processes suggests that reinforcement schedules alone may not provide a complete account.

Limitation: Does Not Explain Irrational Thinking

Learning theory explains why behaviour is repeated after rewards.

It does not fully explain beliefs such as:

“I am due to win.”
“My lucky ritual affects the outcome.”
“I can control the machine.”
“A near miss means I am improving.”
“I remember winning more often than losing.”

These cognitive biases can maintain gambling even when reinforcement is rare.

A cognitive explanation may therefore account more directly for how gamblers interpret chance outcomes.

Limitation: Environmental Reductionism

Learning theory may be described as environmentally reductionist because it reduces gambling addiction to:

Responses.
Rewards.
Reinforcement schedules.
Extinction.

This has scientific advantages:

Variables can be measured.
Predictions can be tested.
Experimental control is possible.

However, it may overlook:

Thoughts.
Emotions.
Genes.
Neurochemistry.
Personality.
Social identity.
Financial circumstances.
The meaning gambling has for the person.

This connects with the strengths and limitations of reductionist explanations [Lesson 5: Holism and reductionism].

Environmental Determinism

Learning theory may imply that behaviour is controlled by external consequences.

A strongly deterministic account suggests:

Exposure to variable reinforcement produces persistent gambling.

However:

Not everyone responds identically.
People may recognise the schedule.
Gamblers can learn coping strategies.
Access can be restricted.
Individuals can stop.
Alternative rewards can be developed.

A more balanced position is that reinforcement schedules exert a powerful influence without eliminating personal control.

Limitation: Real Reinforcement Histories Are Complex

A real gambler may receive several consequences at once.

One bet may involve:

Financial loss.
Excitement.
Peer approval.
Temporary relief from boredom.
A celebratory display.
Regret.
Hope of a future win.

It may therefore be difficult to determine which consequence maintained the behaviour.

Real gambling cannot always be reduced to:

Bet followed by win.

Limitation: Classification of Schedules Can Be Ambiguous

The schedule identified may depend on what is treated as:

The response.
The reward.
The interval.
The unit of analysis.

For example:

Unpredictable wins after varying numbers of spins are variable ratio.
Reinforcement available after unpredictable periods is variable interval.
A lottery draw occurs at a scheduled time, but the winning ticket remains unpredictable.

AQA’s June 2023 mark scheme referred to irregular practice-game wins as partial reinforcement or a variable-interval condition.

The safest exam approach is to:

Use the terminology indicated by the stem.
Explain why the reward is partial.
Explain why it is unpredictable.
Link the schedule to persistent behaviour.

Interaction with Neurochemistry

Winning may activate brain reward systems involving dopamine.

Learning theory and biological explanations can therefore complement one another.

Neurochemical level

A win activates reward-related processes.
Dopamine contributes to motivation and reinforcement.

Learning level

The rewarding consequence follows a gambling response.
The response becomes more likely to be repeated.
Variable schedules maintain persistence.

The biological explanation describes how reward is processed.

Learning theory describes how the consequence changes future behaviour.

Interaction with Personality

A variable schedule may be particularly influential for someone high in:

Sensation seeking.
Impulsivity.
Reward dependence.

For example:

An impulsive sensation seeker may respond strongly to the uncertainty and immediate excitement of repeated online bets.

This connects with personality as an addiction risk factor [Lesson 3: Personality and social influences].

Interaction with Social Influence

Peers may:

Model gambling.
Provide access.
Praise wins.
Encourage risk.
Make gambling part of group identity.

A person may begin through social influence and continue through financial and emotional reinforcement.

The explanations answer different questions:

Social influence explains exposure and approval.
Reinforcement explains how consequences strengthen behaviour.

Interaction with Cognitive Bias

The learning and cognitive explanations may form a cycle:

A person receives an occasional win.
The win reinforces gambling.
The person remembers the win more strongly than losses.
They develop inaccurate expectations.
Cognitive bias encourages further gambling.
Another occasional win reinforces the belief and behaviour.

This interaction is more complete than either explanation alone.

Ethical and Social Implications

Understanding variable reinforcement raises questions about:

The design of gambling activities.
Rapid opportunities to place repeated bets.
The use of celebratory feedback.
The availability of gambling at any time.
The vulnerability of people with addiction risks.

The explanation may reduce moral blame by showing that persistent gambling is shaped by powerful learning processes.

However, an overly deterministic interpretation could make people believe that change is impossible.

The same learning principles that maintain gambling can also inform prevention and behaviour change.

Overall Evaluation

Learning theory explains gambling addiction primarily through operant conditioning. Financial wins, excitement and social approval may positively reinforce betting. Because only some responses are rewarded, gambling operates through partial reinforcement.

Rewards are often unpredictable. Where wins follow varying numbers of bets, this is a variable-ratio schedule. The gambler cannot know which response will be rewarded, so responding remains persistent. Previous experience of long periods without reward means that losing does not clearly signal extinction. This produces the partial reinforcement extinction effect.

The explanation is scientifically testable, applies to many gambling activities and successfully explains persistence despite frequent losses. AQA’s June 2023 applied question directly tested the prediction that intermittently reinforced participants would later gamble at higher stakes.

However, laboratory tasks may not represent genuine addiction, and not everyone exposed to variable reinforcement becomes addicted. Learning theory also explains maintenance better than initiation and overlooks cognitive biases, biological vulnerability, personality and social influences.

The strongest conclusion is interactionist. Partial and variable reinforcement help explain why gambling persists, while individual and cognitive factors explain who becomes addicted and how rewards and losses are interpreted.

Key Words 🔑

Key word	Student-friendly definition	How it may be used in an exam
Learning theory	An approach explaining behaviour through experience and environmental consequences	Introduce the explanation
Operant conditioning	Learning through the consequences of behaviour	Explain gambling being strengthened by wins
Operant	A voluntary behaviour producing a consequence	Identify placing a bet or spinning a reel
Reinforcement	A consequence that increases the likelihood of behaviour	Explain why gambling is repeated
Reinforcer	A consequence that strengthens the response it follows	Identify money, excitement or approval
Positive reinforcement	Adding a rewarding consequence to increase behaviour	Explain a financial win
Negative reinforcement	Removing an unpleasant state to increase behaviour	Explain gambling to escape stress
Punishment	A consequence that reduces behaviour	Contrast financial losses with reinforcement
Secondary reinforcer	A learned reward that has value through association with other rewards	Explain money or gambling-related cues
Reinforcement schedule	The pattern determining when behaviour is rewarded	Introduce partial and variable reinforcement
Continuous reinforcement	Rewarding every response	Contrast with gambling schedules
Partial reinforcement	Rewarding only some responses	Explain why losses occur between wins
Intermittent reinforcement	Another term for partial reinforcement	Describe occasional rewards
Variable reinforcement	Providing rewards unpredictably	Explain uncertainty in gambling
Fixed reinforcement	Providing rewards according to a predictable rule	Contrast with variable schedules
Ratio schedule	A schedule based on the number of responses	Explain response-based gambling
Interval schedule	A schedule based on the passage of time	Explain time-based reinforcement
Fixed-ratio schedule	Reward after a set number of responses	Contrast with unpredictable payouts
Variable-ratio schedule	Reward after an unpredictable number of responses	Explain slot-machine gambling
Fixed-interval schedule	Reward becomes available after a set period	Contrast with variable interval
Variable-interval schedule	Reward becomes available after unpredictable periods	Apply where timing varies
Extinction	Reduction of behaviour when reinforcement stops	Explain stopping gambling
Resistance to extinction	Persistence after reinforcement is absent	Explain continued betting through losses
Partial reinforcement extinction effect	Greater resistance to extinction after intermittent reinforcement	Evaluate gambling persistence
Response	The behaviour performed by the gambler	Identify placing a bet
Consequence	The outcome following behaviour	Identify a win or loss
Contingency	The relationship between behaviour and its consequence	Explain learning from wins
Immediacy	How quickly reinforcement follows behaviour	Explain rapid online gambling
Magnitude	The size or value of reinforcement	Explain the effect of a large win
Discriminative stimulus	A signal that reinforcement may be available	Explain a betting notification
Psychological dependence	A perceived emotional need to continue an activity	Link reinforcement with addiction
Tolerance	Needing greater intensity to obtain the previous effect	Explain increasing stakes
Maintenance	Continuation of addictive behaviour	Identify what reinforcement explains well
Initiation	The beginning of the addictive behaviour	Identify a limitation of learning theory
Relapse	Returning to gambling after trying to stop	Explain renewed exposure to rewards
Environmental reductionism	Explaining addiction through simplified environmental processes	Evaluate the theory
Environmental determinism	The view that behaviour is governed by external consequences	Evaluate personal control
Interactionism	The view that learning combines with biological, cognitive and social factors	Reach a balanced conclusion

Hints from the Examiner Reports 💡

Explain Both Conditions in an Applied Study

Examiner hint: Where a question describes two groups, explain the likely outcome for both.

The June 2023 examiner report stated that many students discussed only one condition. Full marks required a clear prediction for the intermittently reinforced group and the group receiving no reinforcement.

For example:

Participants receiving occasional wins should be more likely to choose high stakes because wins positively reinforced betting. Participants receiving no wins should be more likely to choose low stakes because their betting received no positive reinforcement.

Use Reinforcement Schedules Explicitly

The examiner report noted that very few students referred to schedules of reinforcement.

Do not stop at:

They won, so they gambled more.

Develop the explanation:

The participants received partial and variable reinforcement because only some games were rewarded and the winning games were irregular. This schedule produces persistent responding and resistance to extinction.

Identify the Response and the Reward

A clear answer specifies:

Response: Placing a bet.
Reward: Winning money or experiencing excitement.
Effect: Betting becomes more likely to be repeated.

Explain Positive Reinforcement Correctly

A win is added after the gambling response.

Because it increases future gambling, it acts as positive reinforcement.

Do not say that winning is positive reinforcement simply because it is pleasant. Link it to increased future behaviour.

Distinguish Partial and Variable Reinforcement

Partial means not every response is rewarded.
Variable means the pattern is unpredictable.

A gambling activity can involve both.

Select the Schedule from the Stem

Use variable ratio when reinforcement follows an unpredictable number of responses.

Use variable interval when reinforcement becomes available after unpredictable periods of time.

Where the stem simply describes irregular occasional wins, explicitly explain partial and variable reinforcement.

Explain Resistance to Extinction

Do not merely state:

Partial reinforcement is hard to extinguish.

Explain why:

The gambler has learned that long periods without reward can still be followed by a win. A new losing sequence therefore does not signal that reinforcement has ended.

Do Not Use the Gambler’s Fallacy as the Schedule

A variable schedule does not mean that a win is due after losses.

The belief that previous losses make the next independent outcome more likely is a cognitive bias.

Keep reinforcement and cognitive explanations distinct.

Do Not Predict Higher Stakes for the No-Win Group Without Justification

The 2023 examiner report noted that some students claimed people who had lost every practice game would choose higher stakes because they felt compelled by their earlier losses.

That explanation relies more on loss chasing or cognitive bias.

The straightforward learning prediction is:

Reinforced gambling increases.
Unreinforced gambling is less likely to increase.

Use Specialist Terminology

Strong terminology includes:

Operant conditioning.
Positive reinforcement.
Partial reinforcement.
Variable reinforcement.
Variable-ratio schedule.
Resistance to extinction.
Response-consequence association.

Evaluate the Mechanism, Not Gambling in General

A relevant evaluation asks whether reinforcement schedules:

Cause persistent gambling.
Generalise from laboratory studies.
Explain individual differences.
Explain initiation.
Account for cognitive interpretation.

Avoid drifting into general arguments about whether gambling should be legal.

Separate Immediate Gambling from Addiction

An experiment showing a larger bet after reinforcement supports short-term learning.

It does not necessarily demonstrate:

Dependence.
Withdrawal.
Long-term harm.
Addiction.

How to improve:

Distinguish gambling behaviour from gambling addiction.

Mistake 15

Mistake: Applying only one condition in a two-group study.

Why this limits AO2:

The question may require a comparative prediction.

How to improve:

Predict and explain the behaviour of both groups.

Exam-Style Questions ✍️

Question 1

What is meant by partial reinforcement? [2 marks]

Question 2

What is meant by variable reinforcement? [2 marks]

Question 3

Explain why a financial win may act as positive reinforcement for gambling. [3 marks]

Question 4

Explain one difference between a variable-ratio schedule and a variable-interval schedule. [4 marks]

Question 5

Luca uses an online slot machine. Most spins lose, but occasionally he receives a payout. He cannot predict which spin will win and continues after long sequences of losses.

Use learning theory to explain Luca’s gambling. [6 marks]

Question 6

Explain why gambling learned through partial reinforcement may be more resistant to extinction than behaviour learned through continuous reinforcement. [4 marks]

Question 7

A researcher assigns 60 participants to two conditions.

In Condition A, participants win four of ten practice games at unpredictable points.
In Condition B, participants win none of the practice games.

Participants then choose either a high-stakes or low-stakes test game.

Condition	High stakes	Low stakes
A: occasional unpredictable wins	21	9
B: no wins	8	22

Calculate the percentage of participants in each condition who selected high stakes. Explain the results using learning theory. [6 marks]

Question 8

Explain one limitation of using a laboratory gambling task to investigate partial reinforcement. [3 marks]

Question 9

Explain one strength and one limitation of learning theory as an explanation of gambling addiction. [6 marks]

Question 10

Discuss learning theory as an explanation for gambling addiction. Refer to partial and variable reinforcement in your answer. [16 marks]

Answers and Mark Scheme

Question 1

Award one mark for each of the following:

Only some responses are followed by reinforcement.
Other responses receive no reward, but the occasional rewards maintain behaviour.

Maximum: 2 marks

Question 2

Award one mark for each of the following:

Reinforcement is delivered according to an unpredictable pattern.
The person does not know which response or when a response will be rewarded.

Maximum: 2 marks

Question 3

Award one mark for each linked point:

The gambler places a bet or performs another gambling response.
Winning money is a rewarding consequence added after the response.
The consequence increases the likelihood of future gambling.
The response-reward association is strengthened.

Maximum: 3 marks

Question 4

Award up to two marks for each schedule.

Possible answer:

A variable-ratio schedule provides reinforcement after an unpredictable number of responses, such as a payout after an unknown number of slot-machine spins. A variable-interval schedule makes reinforcement available after unpredictable periods of time. Ratio schedules are therefore based on response number, whereas interval schedules are based on time.

Question 5

Award up to six marks for effective application:

Initiating each spin is Luca’s operant response.
A payout is a rewarding consequence.
The payout positively reinforces spinning.
Only some spins win, so reinforcement is partial.
Luca cannot predict which spin will win.
Payouts follow varying numbers of spins, so the schedule is variable ratio.
Previous wins have followed losing sequences.
Losses therefore do not clearly signal extinction.
His behaviour becomes resistant to extinction.
The expectation of another possible reward maintains gambling.

A full-mark answer should explain the reinforcement schedule rather than merely state that Luca enjoys gambling.

Question 6

Award one mark for each relevant linked point, up to four marks:

Under continuous reinforcement, every response has previously been rewarded.
When reward stops, the change is immediately noticeable.
Behaviour may therefore extinguish quickly.
Under partial reinforcement, unrewarded responses have always occurred.
A period without reward resembles the previous reinforcement history.
The person continues because another response may still be rewarded.
The partially reinforced behaviour is therefore more resistant to extinction.

Question 7

There are 30 participants in each condition.

Award one mark for each correct calculation:

Condition A=3021×100=70%Condition B=308×100≈26.7%

Award up to four marks for explanation:

A higher percentage chose high stakes after occasional wins.
Wins positively reinforced gambling.
Condition A involved partial reinforcement because only some games were rewarded.
The wins were delivered unpredictably, producing variable reinforcement.
The response-reward association was strengthened.
Participants receiving no wins experienced no positive reinforcement.
Their gambling was therefore less likely to increase.
The result supports learning theory but does not demonstrate long-term gambling addiction.

Question 8

Award one mark for identifying a limitation and up to two marks for development.

Possible answer:

A laboratory gambling task may lack ecological validity because participants usually know that the session is brief and their financial risk is limited. They may not experience the debt, craving, emotional pressure or long reinforcement history of a person with gambling addiction. Behaviour in the task may therefore fail to represent real persistent gambling.

Other creditworthy limitations include:

Demand characteristics.
Participants not risking their own money.
Short exposure.
Low emotional involvement.
Volunteer-sample bias.
Difficulty generalising to different gambling activities.

Question 9

Award up to three marks for one developed strength and up to three marks for one developed limitation.

Possible strength:

Learning theory explains why gambling persists despite repeated losses. Under partial and variable reinforcement, previous wins have followed periods without reward, so a new losing sequence does not clearly signal extinction. The gambler continues because the next response might produce reinforcement.

Possible limitation:

The explanation is environmentally reductionist because it focuses on rewards and reinforcement schedules. It cannot fully explain irrational beliefs such as the gambler’s fallacy or why only some people exposed to identical gambling schedules become addicted. Cognitive, personality and biological factors must also be considered.

Other creditworthy points include:

Clear testable predictions.
Experimental control.
Practical applications.
Artificial laboratory research.
Better explanation of maintenance than initiation.
Different subjective reward values.
Environmental determinism.

Question 10

A high-level response should include accurate knowledge and developed evaluation.

Indicative AO1 Content

Learning theory.
Operant conditioning.
Behaviour being shaped by consequences.
Gambling response and rewarding outcome.
Positive reinforcement through financial wins.
Excitement and social rewards.
Possible negative reinforcement through removal of stress or boredom.
Reinforcement schedules.
Continuous reinforcement.
Partial or intermittent reinforcement.
Only some gambling responses being rewarded.
Variable reinforcement.
Fixed compared with variable schedules.
Ratio compared with interval schedules.
Variable-ratio reinforcement.
Reward after unpredictable numbers of responses.
Possible variable-interval reinforcement.
Resistance to extinction.
Partial reinforcement extinction effect.
Persistent gambling through losing sequences.
Immediacy and magnitude of reinforcement.
Secondary reinforcement.
Maintenance and possible relapse.

Indicative AO3 Content

Clear and testable predictions.
Experimental manipulation of reinforcement schedules.
AQA’s June 2023 reinforcement study.
Explanation of persistence despite losses.
Broad application to different gambling activities.
Practical implications for prevention and intervention.
Artificiality of laboratory gambling.
Limited financial and emotional stakes.
Short-term betting not demonstrating addiction.
Not everyone exposed to variable reinforcement becoming addicted.
Individual differences.
Subjective value of reinforcers.
Financial loss potentially punishing behaviour.
Incomplete explanation of initiation.
Cognitive biases not fully explained.
Interaction with genetic vulnerability.
Interaction with personality and social influence.
Environmental reductionism.
Environmental determinism.
Ambiguity when classifying schedules.
Stronger explanation of maintenance than initiation.
Need for an interactionist account.

Thirteen to sixteen marks: Knowledge is accurate and generally detailed. Partial and variable reinforcement are clearly distinguished and applied to gambling. Discussion is thorough and effective, with reasoned consideration of evidence, laboratory methods, persistence, individual differences and alternative explanations. Specialist terminology is used precisely.

Nine to twelve marks: Knowledge is mostly accurate and discussion is generally effective. Operant conditioning and reinforcement schedules are explained, although some application or evaluation may lack depth.

Five to eight marks: Some relevant knowledge is present, but the answer is mainly descriptive. Wins may be identified as reinforcement without a clear explanation of partial, variable or resistance-to-extinction effects.

One to four marks: Knowledge is very limited or confused. The response may confuse reinforcement with punishment, describe partial reinforcement as receiving part of a prize or fail to apply learning theory to gambling.