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- [Shelley] Susan Maxwell is joining us from New Brunswick as is Amy Kang and Susan comes to us originally from Anglophone West School District, and Amy comes to us originally from the Anglophone East School District.

So representing central and southeastern New Brunswick, and right now they're both working with the autism learning partnership at New Brunswick Department of Education and Early Childhood Development.

They're both supporting the autism training framework across New Brunswick and autism specialists in the schools and the regions and the boards who are supporting school teams with learners with autism and with challenging behaviors.

So it's a real pleasure to have them with us.

They're also both working extremely hard in pursuit of behavior analysts board certification and they're both I know getting very, very close to getting to that point under the mentorship of another autism and education partner Marlene Breitenbach at Prince Edward Island.

So we're really excited to have Sue and Amy with us.

I will turn the floor over to them and again, if you have any questions or any comments throughout that you'd like to share with the presenters, go ahead and type those in the chat box or the Q&A and we'll make sure that those get asked to the presenters before the presentation is over.

So Amy and Sue, thanks so much for joining us and I'll turn it over to you.

- [Susan] We appreciate it and we are so very happy to be here and have this opportunity today.

As part of the, I guess you said it was the last webinar in this series.

So we're certainly very happy to be here today and we wanna thank the audience for being here as well.

So taking the time out of their schedule to be here, fantastic.

So Amy and I both come from a background of resource teachers and we've been resource teachers in the past for a long time and one of the things that we've done as resource teachers is incorporate token economies into our practice in the school setting, and it sometimes went really great and sometimes it didn't go so well.

So sometimes there were little inconsistencies that hampered the development and implementation and sometimes the learners didn't, I guess I would say that in my experience the learners didn't always meet with as much success with the token economies as we would have liked.

So that's really the impetus of why we're here today.

We wanna share information about understanding and incorporating token economies within the school setting and we also want to share ways to assist you if sometimes things aren't going quite as well as you'd like, and also some practical ways of figuring out what should I do if things aren't going quite as well as I would like?

So the objectives that we have for you by the end of this webinar is that we would have you be able to explain what a token economy is, and describe the essential components.

To understand the steps in creating an effective token economy, and recognize any potential pitfalls when implementing token systems, and also to problem solve practical solutions for each of those pitfalls.

Now Amy will be covering the first part, the central components and creating the token economy and I'll be working on sharing potential pitfalls and practical solutions.

So why should you use a token economy system in school settings?

I think we've all worked with students who are intrinsically motivated and then sometimes we work with students who aren't as intrinsically motivated, and really token economies can help so much with that.

So, first and foremost, importantly, they're evidence-based.

So I think that's really important to know about token economies and they can be used in multiple settings.

So you can use them in hospitals and group homes and classrooms and school wide setting throughout the whole school, and I think that that is basically because of their ease of implementation.

The other thing about token economies is that they're very flexible.

So you can use token economies with individuals.

So perhaps an individual who might work predominantly outside of the common learning environment, token economies can be used with individuals who work predominantly inside the common learning environment, and also with groups of learners or a whole class.

The token armies can be individualized to learners, and in fact, not only can they be but they should be individualized to the learners that you're working with and also token economy systems really provide a framework for staff so that there is no guesswork when you organize the token economy properly, devise it and implement it.

Staff understand what they need to do to create those reinforcement opportunities for learners and then the learners it's transparent in what the learner needs to understand and achieve behaviorally.

So we have a quote here by Hine and I think it's a really important quote.

So I'm gonna read it to you and it says due to widespread use, casual implementation of the token economy might result in inconsistencies in responding and therefore an overall skepticism in the procedure itself.

And so I think it's very important and really a powerful quote, and what does that mean?

So I think back to when I reflect on my practice as a resource teacher, I think that I did casually implement token economies.

In fact, I know I did and that there would be inconsistencies and sometimes that would lead to educators being skeptical.

You might hear an educator saying, "Well, I don't think they need it anymore." Or "I don't think it's working for them." But really, I think it was more to do with the casual implementation, in which I might have implemented it and sometimes there will be inconsistencies.

So that doubt came from that.

So you need to think about token economies being well-intentioned from the very, very beginning and the fact that they are, you need to have systematic implementation.

There absolutely can be nothing casual, absolutely nothing casual about their implementation.

Otherwise, you tend to land into common pitfalls and that's what we're wanting to share with you today.

How to avoid some of those pitfalls, and then if you do happen to fall into a pitfall, what can we do to solve for it?

So how can you compensate?

And I'll be talking more about the pitfalls and practicality section a little bit later.

But Amy's going to take us through the creation of a token economy first.

So I'm just going to mute my speakers.

- [Amy] Okay, can I just get a couple of little yeses if people can hear the audio that switched over to me?

I see in the chat box, perfect, okay.

So, we're gonna jump right into an ASR, which stands for Active Student Response, and so in the school setting, you can use active students responses to help you access prior knowledge, help your students access prior knowledge to get them to think about upcoming topics, to review content, or to apply the material that they've learned to real world examples, and so this ASR is a question to get you thinking about the topic of token economies.

A token economy consists of the following major components: target behavior, points, marks or tallies, and a menu of backup reinforcers.

A true, or b false, and as we go through our webinar today we're gonna have multiple ASRs and I encourage you if you so wish to share your answers in the chat box, and so right now you could put an a or b.

If you prefer to keep your answers to yourself, that's always fine as well.

So the answer to this ASR is true.

All token economies require these components to be effective.

So what is a token economy?

In the simplest terms possible, it's a behavior change system.

Token economies can also be called token systems, token economy systems, token reinforcement systems and we'll use all these terms interchangeably as we go through this webinar.

So let's unpack the terms token economy system to see if we can get a deeper understanding of what each term means.

A token is a symbol or an object that is exchanged for goods or services.

It has no intrinsic value on its own.

I think the best example that we're all familiar with is money.

It's a token that none of us can deny makes us happy when we receive it and makes us unhappy when we lose it.

But not because we use money itself as a snack to eat or to cover ourselves on a cold night or even to create light when it's dark.

It's an item that in and of itself does not have a use.

What makes money valuable to us is that as a token, we can exchange for other items.

We've all exchanged money for other items, maybe like buying five cent candies as a child, or using $20 bills at the grocery store, or even inputting our credit card number to buy furniture online.

We've used it so frequently and so consistently that it has become a conditioned token for our society.

Most of us enjoy the process of earning, accumulating and exchanging this token for items that we dream of buying.

Let's move on to the word economy.

This word describes the production, distribution, trade and consumption of goods and services.

We all have experience with the consumption of goods and services in our everyday lives.

Food that we eat, gas that we use to run our cars, hairdressers to help us with our unkempt hair.

Without an economic system in place, we would not have the means to access these goods and services in such an effortless way.

We use the word system here synonymously with framework, which is a term that we're all pretty familiar with in the education world.

It speaks to the structure that tells us how to plan, implement and monitor our program with a specific intention in mind.

So when you put it all together, when we talk about token economy systems, we're talking about using an economic base design, using specific components to bring about behavior change in learners who might need more of a structured reinforcement system than what is currently occurring in the natural environment.

Here's another ASR to get us thinking about everyday token economies.

In the chat box, give an example of a token system that you are familiar with.

Stickers, yep, stamps, marbles, tickets, okay.

Wow, they're just so great.

A puzzle of a favorite toy and cut it into pieces, great.

It seems like our audience has some experience with this and this is ASRs are really great way to get a good feel for how people are doing with the content and how much they already know and so that's really, really great.

And you can still put in answers if you want, but I'm just gonna close the chat box because I'm sharing my screen.

The slide is not advancing.

There we go.

So here are some examples of everyday token economies that I thought would be well known.

The Tim Hortons, sorry the McDonald's coffee coupon.

So we collect seven stickers and we get the free hot beverage.

The Tim Hortons Tim's reward card.

Previously, you would purchase seven beverages to claim a free hot beverage, but they've recently made a change to a point system and so now you can earn a certain number of points per visit and then you can use those points to purchase a variety of options from the menu.

That kind of gives it an advantage over the competition where you can only claim a free coffee.

The show "Survivor" recently added a little bit of spice to make it more exciting with the introduction of their fire tokens, and so participants can earn tokens for say, doing physical activities and then trade them in for certain advantages.

The Air Miles program, the PC Optimum points program, Costco Cashback and Starbucks points reward system.

All of these are tailored to allow consumers to earn points or a percentage of cashback of the money they spend with these retailers.

These loyalty programs encourage consumers to become repeat customers, with the goal of effecting a behavior change in you.

This behavior change is in the form of increased shopping and spending and you are rewarded for doing so with tokens of some form that you can then exchange for a range of possible items or member specific benefits.

Effective token economies are all about the right calibration between how you earn tokens, when you get to cash in those tokens and what you get the cash in those tokens for.

A personalized system tailored to our habits coupled with items that we like make them particularly appealing to us.

Let's dive into some of the essential components of token economies that need to be considered for the system to be effective at changing the behavior of your learners.

Hang on to your hats.

Some of these terms might be new to you but they will be referred to many times throughout our presentation.

We are going to explain what a backup reinforcer, conditioned reinforcer, token production schedule, exchange production schedule and token exchange schedule are.

These essential components all interplay to make token economies effective systems for behavior change.

So let's dig deeper into each one.

Backup reinforcers are also known as items, activities or privileges learners cash-in their tokens for.

An example here is a menu of items that the learner can select from when trading in their tokens, such as listening to music or going to the playground.

You may be familiar with backup reinforcers like the plane ticket, lawnmower or barbecue you can get with your Air Miles, or the free night stay at a Hilton hotel with your Hilton points.

As an FYI, we will use the terminology items, activities and privileges with backup reinforcer interchangeably over the course of this webinar.

Now you may be asking yourself, well, which item should I choose for my learners?

We're gonna talk more about that later.

Conditioned reinforcers are next.

We need to take a closer look at what the term condition means and how it occurs.

A conditioned reinforcer is an event, object or stimulus thing that is not initially reinforcing, but acquires the properties of a reinforcer after subsequent association or pairing with it.

In other words, the tokens we have selected only act as reinforcers, meaning they increase desired behaviors after the learner has had some experiences that teach them about what follows.

So the backup reinforcers.

This essential experience is called conditioning or pairing.

In a token economy, the learner earns tokens for engaging in the target behavior, and we pair the tokens with a variety of items available as backup reinforcers.

The more learners exchange their tokens for items or activities they find reinforcing, the stronger the association.

The token becomes a generalized reinforcer.

For some early learners, we may need to practice pairing initially by giving a token right away and then the backup reinforcer and then gradually increasing the number of tokens to earn before receiving the backup.

For others, for example, in a class wide system of more typically developing students, a careful explanation paired with role play and feedback may suffice.

So how do I condition a token to be a generalized reinforcer?

We'll talk more about that later.

Here's an ASR to review content that we've just learned, and again, you can put your answers in the chat box or you may refrain if you wish to.

Jacob traded in some tokens he earned to play Crazy 8s with a friend at lunchtime.

That makes the game Crazy 8s a backup reinforcer activity.

A true, or b false.

The answer is true.

Items and activities are privileges that learners trade their tokens in for are known as backup reinforcers.

So on to schedules.

The token production schedule is also known as what do I need to do to get a token?

Some examples listed here are, earn a token for raising your hand when you have a question or a comment.

Earn a token for each of the five items you put on to go out for recess.

So your hats, your scarf, your mitts, your boots and your coat, or earn a token per five cafeteria trays wiped and stacked.

This is akin to educators asking themselves, what is my job?

What do I need to do to get paid?

How much am I gonna be required to do before they earn a token?

We'll get more into that later.

The exchange production schedule.

It's also known as how often do I get to exchange my tokens for backup reinforcers?

Some ideas include using an I am working for board, which pre-determines how many tokens are required for a specific backup reinforcer, usually leading to the exchange within a shorter timeframe.

Another example would be that the learner can exchange tokens at the end of a time block, such as recess, lunch and end of day.

This allows more of a time delay between earning and exchanging tokens than the previous example.

Alternatively, you could have a small store setup on a table either in the classroom or another location in school.

The store can then be open for shopping for specific hours, say 8:30 to 1:130 on Mondays, Wednesdays and Fridays.

This allows an even greater amount of time to elapse between earning and exchanging than the previous two examples.

Which schedule is best for your learner?

We'll talk more about that later.

The token exchange schedule.

This is also known as how much do these items or activities cost me and tokens?

Some examples of the token exchange could include, how many tokens does it cost to listen to music at lunchtime?

How many tokens do I need to play Go Fish with a peer?

How many tokens do I need to pay for an extra gym class with another class?

So how much should the backup items cost in tokens?

Again, we'll talk more about guiding questions for that later.

Here is a content review ASR.

Question, which schedule does the following statement apply to?

Mark will get to exchanges tokens at lunchtime every day.

A, the token production schedule.

B, the exchange production schedule.

C, the token exchange schedule, or D, the bell schedule.

The answer is B, exchange production schedule.

Determining how often the learner will get to exchange tokens is an important decision that needs careful consideration throughout the planning process, as it is a schedule that has the most control over responding.

Let's look at planning out a token economy for your learner.

You may wanna complete this process as a team to make the best possible choices in supporting your learner.

So let's identify the steps.

Step one, identify and define the target behavior.

Step two, select the tokens you'd like to use for your system.

Step three, identify backup reinforcers to create a menu of items that the learner can select from.

Step four, determine how learners can earn tokens for performing the skill or engaging in the target behavior.

Step five, decide on the cost of backup reinforcers and tokens, and step six, choose the schedule of how often the learner will get to exchange tokens for items or activities.

Each of these steps will be fully explained over the next few slides.

For future use during planning meetings there is a takeaway that we have created with guiding questions for each step.

As you plan out an individualized token economy for your learner.

It can be found in the resources section under the PowerPoint.

If you find that it does not meet your needs, I encourage you to create your own template with the guiding questions that makes sense to you.

Ensuring that you've included all of the steps necessary.

The first step is defining the target behavior.

In other words, the skill you want your learner to perform or the behavior you want them to engage in.

It is necessary to identify the target behavior before coming up with an observable and measurable definition.

There are some guiding questions you can follow to pinpoint exactly what it is you'd like to target.

You can use the SMART acronym that the majority of us are familiar with to guide you in this process.

S is for specific.

So ask yourself, what is the behavior of interest?

What skill do you want the learner to perform?

What does the target behavior look like, and is it observable?

An example of a target behavior that is non-observable would be the learner will participate more in class.

A better way to describe this in observable terms would be to say that the learner will answer questions during group instruction and respond to comments during think-pair-share opportunities.

This is observable to anyone giving you tokens and is clearer than just participation.

If the target behavior is not observable, we won't be able to take data on it and if we don't take data then we cannot track the effectiveness.

Another way to look at this is to ask ourselves, what does successful task completion look like for this learner?

During any behavior change program, we usually focus on the scale we wanna see an increase in.

Raising their hand to answer a question, staying on task until they have completed two sentences, reading three pages consecutively.

As opposed to the behavior that we wanna see a decrease in, such as blurting out or walking around the room after every word written or talking to our neighbor after every patriot.

If we are intentional during the planning phase, we can take the behavior we wanna see decrease, and actively choose to increase another alternative behavior in replace of it.

Both decreasing unwanted behavior and building appropriate skills at the same time.

M is for measurable.

The target behavior needs to be measurable in order to track progress.

So ask yourself, will it be measured by how many minutes the learner is engaged in an activity?

Will it be measured by something countable?

Like how many reading comprehension questions have been answered?

How many envelopes have been stuffed?

Or how many loads of laundry have been done?

We need to know exactly what one occurrence of the target behavior is so that we can measure it.

A is for attainable.

Ask yourself, is it possible for the learner to perform this skill in the near future?

Is it a skill that their peers are performing with proficiency at this time?

And if peers are not doing it, then is it realistic to expect the learner to do it?

Consider the level of difficulty in completing the task.

Are the science questions individualize to their level?

Can they even reach to the bottom of the washer to take the clothes out?

Do they have the fine motor skills to hold the tray with one hand and manipulate it to different angles, while the other hand wipes it dry with a cloth.

All of these questions funneled down into the general idea of making sure that the learner has the necessary prerequisite skills to attempt the target behavior you've chosen, and if you're not sure, how will you and your team find out.

R is for relevant.

Ask yourself, is this target behavior something that is useful for the learner to acquire?

Is it a skill that they can use in their everyday life?

Is it a skill that they can use in time to develop other skills that are important for functioning?

And last T is for trackable.

As with every other reinforcement system we put in place, we need to monitor data over time to ensure that the target behavior we've selected continues to be the behavior of interest.

If the learner is performing the skill with proficiency, perhaps it's time to fade the system or move on to a new skill.

If not, then we need to take a look at the design of the system to make changes.

The next step is token selection.

There are many examples of items that you could use as tokens.

Poker chips, plastic strips, checkers, holes punched in cards, tally marks, points, stickers, stamps and buttons.

You can even use Velcro on the back of small cards with characters or items that are especially motivating to the learner, such as door or airplanes.

The selection of tokens requires some thought on the following points.

Tokens should be safe.

So not easy to swallow or otherwise cause injury.

Tokens should be easy for the learner and staff to manipulate.

Tokens should be durable so that you don't have to replace them continually.

The token should be unique enough that they cannot be reproduced by learners.

The tokens need to be readily accessible to staff members the moment they need to be dispensed.

As we know immediate delivery of the token will maximize impact, and another consideration is, where are you going to store those tokens until they exchange?

In a bin, beaded on a necklace or maybe Velcro to the I am working for board.

The possibilities are endless, but it needs to be personalized to the learner and educator needs.

We've already discussed what backup reinforcers are.

Items or activities that you can exchange for a certain number of tokens.

So now let's take a look at some guidelines for choosing these items, activities or privileges.

Try to include a wide variety of items in your backup menu as much as possible.

You can and should start with a smaller number of items and then expand the menu as time passes.

Including naturally occurring activities makes the system easier to implement in a school setting.

Things like helper jobs, an extra specialty class, or eating lunch while watching a show.

But you may also include items that occur less often in the common environment, such as completing a puzzle, five minutes of free time, or playing non-educational games on the iPad.

How can you create this menu of backup reinforcers.

There are many ways.

You can interview the learner, they know themselves best.

You can use checklists or visual supports to support that if necessary.

Conduct a parent interview.

They may have ideas that have not yet been discovered in the school setting.

Schedule some time for a learner observation.

You can get a lot of information by doing an informal observation when your learner has free access to items or activities.

Conduct formal or informal preference assessments.

If you're not familiar with preference assessments there are multiple sources of information on this topic.

You can complete checklists of preferred items or activities, especially checklists that have activities commonly found in the school setting, such as helper for a day.

Let's make sure that we include items or activities that are already present in the natural learning environment, which decreases the amount of resources we have to put in upfront and also helps with fading the system back when the time comes.

Another consideration is how will you display the options to your learner?

Will you have a menu of items that they can browse and look through?

Will the items be set up on a desk or a table?

The last consideration is that we need to be careful not to use anything on the menu that is a basic human right.

So we can't hold back a trip to the bathroom until the learner has earned five tokens.

Time for an ASR.

This one is to review the potential methods to generate ideas for your backup brainteasers.

Which of the following is not a good way to determine a list of possible backup reinforcers?

A, observations, b, preference assessment, c, what the staff thinks the learner likes, d, a learner interview, or e, a parent or guardian interview?

The answer is c, what the staff thinks the learner likes.

So while it is perfectly fine to have conversations with educators on their opinion of what the learner likes, we shouldn't solely rely on this methods.

As studies show that oftentimes the items suggested do not actually work as reinforcers, even though the learner may like them.

It is important to know that just because we like something it does not always mean that we are willing to put work into earning it and that it may not motivate us to change our behavior.

Another ASR, let's take the information we've learned about the first three steps just covered and apply it to a real world situation.

June is planning to implement a token system with Jacob.

She will punch holes in an index card for appropriate classroom behavior that he will be able to exchange for items on a menu of backup reinforcers.

Which step did June miss?

A, define target behavior, b, select tokens, or c, identify backup reinforcers.

The answer to this ASR is a, defining the behavior.

Giving tokens for appropriate behavior is not specific enough for neither June nor Jacob.

June needs to know exactly what is a token and Jacob needs to know which behavior will earn them.

This prevents any variation to the system that is not planned, which could derail the effectiveness.

Let's continue with the steps to creating a token economy.

Step four is determining how learners can earn tokens for target behavior.

This is also known as a token production schedule.

The critical question here is how do we make sure learners earn tokens?

The starting point should be based on your target behavior definition and should be achievable.

We cannot set requirements too high in the beginning because we need to make sure that the learner gets to exchange those tokens for backup items.

Our learners will not be motivated to perform the target behavior if the requirements are too high.

It is always possible and even advisable to increase the amount of output required to earn tokens, but only after the system is in place and the learner begins to perform the skill with more proficiency and regularity.

You could start with the delivery of a token every time the learner engages in the target behavior, but then move to token delivery every second or third time they engage in the target behavior as time goes by.

Another consideration is will the target behavior be based on frequency, accuracy or time?

For example, a specific number of words written, how well the bed is made, or how many minutes the learner is engaged in browsing books?

It is important to make sure that there are enough opportunities for the learner to earn tokens.

If the only time a learner can earn tokens is during math, but there are only four math classes per week spread out over varying times of the day, then they might not have sufficient opportunities to earn enough tokens before making the scheduled exchange.

The act of delivering a token informs the learner that they have performed the skill of proficiency, but it is also critical in pairing ourselves with the token and by association, the backup reinforcer.

This lays the foundation for the system to be effective and it also helps to develop the relationship between the staff member and learner.

To understand this, think about grandparents who spoil their grandchildren by giving them gum, toys and unlimited access to television.

They have continuously paired themselves with strong reinforcers and as such, those children tend to favor their grandparents and enjoy spending time with them even when the gum, toys or television are not available.

With planning it is possible to ensure learners earn tokens for performing the target skill from the beginning.

But it is always important to plan ahead in case the requirements to earn a token are not met.

If that happens, what actions will the staff take to communicate and resolve this problem in a timely manner to get the system back on track?

Step five is deciding the price of the backup reinforcers and tokens.

This is also known as the token exchange schedule and should be in line with the decisions you've just made regarding how the learner will earn tokens.

This way you can calibrate the cost of items based on the number of opportunities the learner has to earn tokens.

The price of backup reinforcers needs to be low enough during the beginning part of implementation for the learner to be able to buy them.

Where is the incentive to earn tokens to change my behavior if I cannot actually purchase anything because the prices are too high?

So we need to start with a small enough price tag.

This might be why Air Miles eventually created their dual system, where you could trade in your miles for something other than air travel.

Now there are multiple options, such as home products, like barbecues or lawnmowers, or the option to cash in your points to get $10 off of a purchase at a participating retailer.

This way, no one is excluded from claiming a prize.

It just means that the reward you can afford ends up being commensurate with how many miles you've accumulated based on your spending.

Of course, the prices on the backup items in a token economy do not remain low forever.

As the learner begins to perform the skill with more proficiency and regularity, the price of the backup reinforcers will go up gradually, as the number of items available also increases.

Step six, how often will learn to get to exchange their earned tokens for backup reinforcers.

Remember that this is also called the exchange production schedule.

There is no one size fits all, but it is important to arrange for the exchange to happen frequently in the beginning, to allow the learner to contact that reinforcement.

This might mean as frequently as every period for some learners or even within the same period.

For other learners, this might mean at recess, lunch and end of day.

Of course, we don't keep the same exchange production schedule forever.

We need to gradually lengthen the time between exchanges.

This is not the same as requiring more occurrences of the target behavior to earn a token.

It only speaks to the number of opportunities over time to exchange tokens for backup items.

There are some considerations when designing the exchange process.

How will you structure the exchange to be as least intrusive as possible in the school setting?

Will it be in the classroom, or will the exchange take place in an alternate setting?

Who will be responsible for overseeing the exchanges?

And where will the tokens be kept until the exchange?

In or on the learners desk, on a shelf or with the educator?

These last three steps covered all interplay to make token economies effective.

The main point is to start small to get the system in place and then gradually increase the requirements over time.

So now that we've covered the structure of a token economy system, let's look at one variation to that system, response cost.

In a response cost procedure tokens are taken away when inappropriate behavior occurs.

As in a token reinforcement system, the behavior that results in token loss should be clearly defined to the staff and learner.

Response cost is meant to decrease inappropriate behavior and while it can be effective at decreasing unwanted behavior, it certainly does not include a process to teach the appropriate replacement behavior.

It has also been found in the literature that educators tend to act more negatively towards learners when implementing a response cost procedure than with a token reinforcement system, which does not contribute to a positive learning environment.

Another problem with response cost is that it devalues tokens.

It takes away their power.

It pairs punishment with the educator taking them away, which may decrease their effectiveness as generalized condition reinforcers and erode the relationship the staff member has with the learner.

There are other problems that may accompany response costs, such as aggression towards others, and emotional responding like crying and tantrums.

Lastly, and most importantly, we have a duty to use reinforcement based systems, as opposed to punishment based systems within the school setting.

So we must try other reinforcement based methods before implementing punishment procedures, such as a response cost procedure.

So you've planned the system, but it's not time to start yet.

For three to five days tally token delivery as if tokens were actually being earned, but none are given during this time period.

This gives an opportunity to look at baseline levels of performance and get a sense of how often the skill is being performed and what to expect in the number of opportunities to earn tokens, and when you review that data ask yourself, is the learner truly deficient in the target behavior?

Is the learner already demonstrating mastery with this skill?

Is the learner not receiving tokens at all?

If the numbers don't look good, you may need to make adjustments to calibrate one or more of the three schedules with the others.

The token production schedule, the exchange production schedule, or the token exchange schedule.

Let's try an application ASR June priced each backup reinforcer low enough at the outset that Jacob will be able to buy one of several items.

She planned to let Jacob exchange his tokens for the items whenever there was down time during math.

She did a test run before she trained her staff to implement the system.

What did June miss?

A, determining the cost of the items or activities.

B, choosing a consistent schedule to exchange tokens, or C performing a test run prior to actual implementation.

The answer is B, choosing a consistent schedule to exchange tokens.

We can't be sure that there will be downtime every time there is a math class.

So it is unclear for both the staff and the learner about how often the learner gets to exchange the tokens over the week.

I'm not sure about you, but if my paycheck was going to come maybe Thursday, or maybe Friday, or even maybe the following Monday, it may affect my performance in completing my duties.

This is so important.

It has been shown in the literature that of the three schedules, the exchange production schedule, so how often a learner gets to exchange their tokens for backup items disproportionately controls the response rate.

That means it is crucial to take time to choose the schedule carefully and monitor the system to ensure that the learner is continuing to be motivated to engage in that target behavior.

Here's another application ASR.

June considered all of the steps in planning a token economy and the token system is in place.

Jacob earns tokens for target behavior, but also loses tokens for inappropriate behavior.

Unfortunately, at the end of this math class, there are no tokens left.

When Jacob realizes that there are no tokens left, he kicks his chair and runs out into the hallway.

What should June have taken into consideration?

Submit your answer to the checkbox if you're comfortable, and we're gonna pull that out right now.

Response cost, learner response, yep.

Reinforcements not frequent enough.

So that can happen with response cost.

The learner loses all of their tokens, we are left with nothing to exchange.

Schedule of exchange.

So these are all really great answers, and not to devalue other people's answers, but I'm starting with gaining first before taking away.

So those are all really important considerations to think about before you would implement a response cost procedure.

So now that you've taken the time to plan the system, it's time to train the staff on implementation.

Training staff can be a really big investment in time but can be efficient and effective when you choose the right method.

With the hands on skill like implementing a token economy, behavior skills training or what we call an hour BST is an excellent method to follow.

The steps would look like this.

So there is a written and verbal explanation to the staff.

In this case orally explaining the implementation of the token economy, a company with a written plan that includes details like who's responsible for which actions.

The next step is rehearsal, sometimes called role playing, where the educator will direct the staff member to perform the skill and immediately deliver a token.

The educator will then rehearse the exchange step with the backup reinforcer with a staff member as if they were the learner.

The next step is going to be modeling.

The token economy will be implemented with the learner in the school setting.

The educator is expected to model the correct implementation of the token delivery when the learner performs to target skill behavior and also model the exchange of the token for the backup reinforcer.

The last step is when the staff member takes over implementation of the process.

In this case, the staff member will practice delivering the token to the learner when they perform the target behavior and then take part in the exchange process with the learner while the educator observes.

After the staff member practices implementation with the learner, the educator provides structured feedback on implementation fidelity, generally using some sort of a competency checklist to structure the feedback in written form.

The educator should be prepared to repeat steps as necessary to ensure correct implementation of the system.

Eventually, staff can integrate self monitoring checklists, usually structured very similar to the competency checklist that the educator used during the training.

This allows the educator to fade back monitoring over time and gives the staff member agency to self-monitor their own performance.

Much like staff members, learners also need to be taught to use the system.

For learners, we focus on establishing the value of the tokens, called the conditioning process.

In other words, to develop reinforcing properties of the token by pairing it with a bag of items frequently, so that the receipt of the token is just as good as getting access to those backup reinforcers.

Am I really trying to tell you that getting a token will make them just as happy as getting that backup reinforcer?

Yes, I am, and if you're in doubt, then I'd like to ask you if you aren't happy when you find a $10 bill on the ground?

Which is just a token that represents access to other items.

Much like the staff members, we start by describing a system to the learner.

You can use a script if necessary and you can include information like labeling the token as a token, explaining how they can earn tokens in learner friendly language, telling them that they can earn more tokens as they continue to engage in that target behavior.

Also explained in learner friendly language.

Tell them they will be able to exchange the tokens for items.

Maybe you can have them in pictures or on a table set up in front of them.

Show them the price and tokens on each item.

Tell them what they will get to exchange, when they will get to exchange the tokens and tell them they can only buy items they have enough tokens for, and if they want something they don't have enough tokens for they can save them until the next exchange time.

Now, some individuals may not comprehend extensive explanations, so we may alter or skip this step completely for some learners.

Next, we direct the learner to perform the target skill or behavior, and we may need to use prompting to get a correct response.

Then we deliver the token immediately, and always be sure to pair this step with praise.

Lastly, take the learner through the exchange of the token for a backup reinforcer as soon as they have earned it.

Make sure that there are a couple of items available on the menu for the one token that they've just earned in the previous step.

This process may need to be repeated several times for some learners.

As with any reinforcement system that is above and beyond what normally occurs in the school setting, token economies eventually need to be faded away to allow the contingencies that occur in the natural environment to take over.

The intricacies of fading the system is learner specific and outside the scope of this presentation.

For now, we'll focus on a few general ideas of how to gradually scale down the system.

So the number of responses required to earn a token could increase over time and should increase over time.

The number of minutes per day that the learner can earn tokens could be gradually decreased over time.

Items that function as reinforcers in the natural environment should be gradually increased on the menu of backup items.

The more desirable items on the menu should increase in price, while keeping a lower price on the items that are not as desirable.

The physical evidence of the token can be faded over time.

For example, to fade poker chips, you can shift to slips of paper, then to an index card that is kept on the learners desk.

Then that index card is kept on the teacher's desk or the educators desk, but can be checked for points at any time.

Then the points can only be checked at the end of day and then the end of every other day and so on until the system is no longer active, and though not directly related to scaling down the system, social praise should always accompany token delivery, so that it can serve to maintain behavior after the token withdrawal.

- [Susan] So we want to have this section because pitfalls are something that you can fall into and we wanna have practical solutions to compensate for those.

So when I thought of pitfalls, I thought, okay, what is the definition?

So I looked up the definition of pitfalls, or pitfall, and it's a hidden or unsuspected danger or difficulty, and to be quite honest, when I was implementing token economies as a resource teacher that's exactly how it seemed to me that sometimes when they weren't working the way I expected them to or the learner wasn't possibly responding the way I'd expected, it was like there were some sort of unsuspected difficulties that were causing problems and I wasn't sure why I could not figure it out, and we've probably all experienced that.

And then other times that I was implementing token economies with learners, they worked beautifully and we've probably all experienced that.

So I couldn't figure it out why sometimes they worked well and why sometimes they couldn't or didn't work well and I think it was this dichotomy that really puzzled me.

So why was that happening?

So now I know that I probably had fallen into a pitfall.

I'd probably bypass these bright orange cones and fallen straight into the hole and that is something that we want for you folks to be able to avoid.

So we've developed nine questions really identifying nine pitfalls and corresponding practical solutions to compensate for them.

So Amy has already explained everything that you really need to know about the underlying mechanics of a token economy system and now we're going to take a look at those pitfalls, because it's really crucially important.

Remember, there's nothing casual about the implementation and token economy systems are only evidence based if they're done correctly.

So it's really important to do that.

So each of these guiding questions that we're going to put up with, that would correspond to the pitfall is I guess they basically served as an aha moment for me.

So I wish I had had these pitfalls and these guiding questions and then the practical solutions that go along with them when I was a resource teacher, they would have really helped me with that and I appreciate having them now.

So now it's time for an ASR.

So we'll be speaking about backup reinforcers more in this upcoming section and Amy has certainly talked about backup reinforcers before.

So the ASR is about backup reinforcers and people are already chatting that, that's great.

The overall effectiveness of a token economy is largely dependent on the relative strength of the backup reinforcers.

Would this be a, true or b, false?

So I can see from the answers that are coming that people are saying true, and you are correct.

The answer is true.

So you'll see even more reasons why backup reinforcers are so important in the upcoming slides.

So for our next ASR, we have what are some of the pitfalls that you've encountered when implementing a token economy?

If you have, if you've experienced what we would call one of those unsuspected difficulties in implementing the token economy.

If you would chat your answer we would appreciate that.

Being consistent, envy from other students.

Consistency between staff.

When reinforcers change frequently, buy in, staff buy in and consistency, absolutely.

Transitioning away from that token economy or reaction, keeping it interesting.

These are great answers.

So what I would ask that you do is if you would hold in your mind as we go through the next section the answer that you've already given or the one that you're thinking about now, if you would hold it in your mind and see if the questions that we've developed that are regarding the pitfalls and then those practical solutions, if they would have helped you avoid some of those pitfalls, let's say or compensated for them.

So the image of on the right hand side here you'll see Mr.

Magoo, and when I was thinking about pitfalls, I immediately thought of Mr.

Magoo.

He was an absolute master at avoiding falling into pitfalls and for those people in the audience who are, I guess, as we would say, the same vintage as myself, you might understand exactly what I'm talking about with regards to Mr.

Magoo.

So we want to absolutely be like him and avoid any potential pitfalls.

So pitfall number one, is the Association of the token and the backup reinforcer strong enough?

Ask yourself if the learner's responding isn't the way you want and you don't think the token economy is going the way that it should, ask yourself this question, is the association of the token and the back of reinforcer strong enough?

And Amy mentioned this earlier.

She talked all about how the token will likely not have a reinforcing influence over the learners behavior if the token is not paired with a backup reinforcer, as efficient enough time or close enough in time.

So we'll move on to the pitfall or the practicalities rather for this pitfall and think back to what Amy talked about in that pairing process and so you would need to pair the token with the backup reinforcer more often, more consistently, and more quickly closer in time.

So pitfall number two also related to big backup reinforcers are there enough quality backup reinforcers.

This difficulty may appear if the learner stops readily exchanging tokens for the backup reinforcers.

So you might see that there's a decrease in his or her responding, or they might even discard the token instead of exchanging.

Pitfall number two is like pitfall number one in that you need to investigate these initially, these two pitfalls, these two questions that you need to ask yourself to see if this could be the cause of the difficulty regarding the effectiveness of the token economy.

So the practicalities here, tokens can maintain their reinforcing properties despite fluctuating preferences, if they can be exchanged for a variety of high quality reinforcers and can become much more flexible as a reinforcer.

So additionally, if tokens can effectively be exchanged for many different backup reinforcers the convenience increases by not requiring educators to keep a wide range of reinforcers constantly and immediately available.

Instead, keep rotating the backup reinforcers.

You can conduct periodic preference assessments, as Amy mentioned earlier, and definitely have an assortment of backup reinforcers, so important.

Pitfall number three, again, related to backup reinforcers.

Do backup reinforcers continue to be motivating?

Even after ensuring a strong pairing between tokens and their backup reinforcers the learners responding may still be inconsistent.

So why would that be?

One potential cause, is do the backup reinforcers continue to be motivating?

To prevent inconsistencies in the effectiveness of backup reinforcers shown by how the learner is responding.

Educators can investigate the effect of what's happening in the moment.

So for example, if a learner will phys ed class for 40 minutes, and the backup reinforcers were all related to physical activity, if you ask yourself, would the backup reinforcers continue to be motivating?

Possibly not, but if the learner has just done 40 minutes of seat work with difficult math work that they find particularly challenging and backup reinforcers are related to physical activity.

If you ask yourself, do the backup reinforcers continue to be motivating at that point in time?

The answer is probably yes.

So that's important to think about.

So the practicalities that could go with this is knowing if the backup reinforcers obviously continue to be motivating and that is a huge advantage to educators because they can regulate the amount of access to the single backup reinforcer.

Obviously, only letting the learner have access to the backup reinforcers inside that token economy, not at any part of the time of the day but within that token economy, and again, providing rotation and choice amongst multiple backup reinforcers.

So now let's do an ASR.

Which of the following options can help to repair the token with the backup reinforcer?

A, pair of the token with the backup reinforcer more often.

B, pair the token with the backup reinforcer more consistently.

C, pair the token with the backup reinforcer more quickly, or D, A, B and C.

Great, lots of answers coming in, and the answer is D, it's A, B, and C.

So that actually goes right back.

This ASR goes right back to pitfall number one.

So if you think about pitfall number one, here's the answer to that whole repairing process or the pairing process.

Pitfall number four.

Think about the token exchange schedule that Amy mentioned earlier and here we're also talking about backup reinforcers.

So pitfall number four, the question to ask yourself is, are the backup reinforcers too expensive?

The actual price of the backup reinforcer is better determined by the combined effects of how often responses result in tokens.

How often the individual can exchange tokens and also the number of tokens required to exchange for specific reinforcers.

So think back to the essential components that Amy talked about earlier today and if you think about the token production schedule as an employee's wage, and the exchange production schedule as the effort required to purchase the item, like driving to the store, or getting cash out of the bank, and the token exchange schedule as the number listed on the price tag, within token economies, those tasks that require more effort can be associated with more preferred reinforcers.

So reinforcers that are less preferred maybe suited better for maintaining less effortful tasks or responses.

So let's say for example, if an individual is able to use tokens to purchase high quality reinforcers that aren't available at other times, but only after a period of effortful tasks like perhaps really difficult math work, as I said, for a sustained period of time.

Therefore, less preferred reinforcers could be available for periods that involve less effortful tasks, like eating your snack at the table.

Pitfall number five relates to token production schedule and you can ask yourself, have you considered the schedule of when a token will be given?

So really the question is fixed or variable.

Most token economy systems in the school system, school setting is a fixed schedule and that's probably due to ease of implementation and the predictability.

So basically, you could ask yourself, is this the best fit schedule for the learner?

You really have to think about that.

So think back to what Amy discussed a little bit earlier with the token production schedule.

Educators will need to decide whether to provide tokens after a fixed or variable number of responses, after a fixed or variable duration of engaging in targeted behavior, or after the first response following a fixed or variable amount of time.

Portion of your thought process will probably be related to the target behavior.

During the learning of the target behavior, educators have the option to begin with continuous token production schedules so that every occurrence of the new behavior provides reinforcement.

Remember, having reinforcement opportunities is absolutely critical and I cannot really stress this enough, because behavior goes where reinforcement flows.

That's something that one of my teachers when I was attending the Florida Institute of Technology used to say, "Behavior goes where reinforcement flows." And that's really what we need is those reinforcement opportunities.

So as the learner gains experience with the token economy system, educators can systematically adjust the production schedule to a thinner schedule.

Because really what you want to achieve you're trying to aim to achieve a natural, what a student would encounter with regards to reinforcement opportunities in the natural setting.

So you need to certainly systematically increase the number of responses to earn a token.

Pitfall number six.

Is the learner having difficulty making a token exchange for a backup reinforcer?

We've probably all had the experience of receiving a paycheck and cashing that paycheck and we've all had long histories with token economies.

So it might be tempting to think that the learner will be able to spontaneously make that exchange, but that would be a pitfall.

So watch out, just like this girl is falling into the hole.

That would be a pitfall, you really need to explicitly teach the exchange process and to help the learner master that process.

So the practicalities with that really is just as I've said, don't assume the learner has mastered the token exchange.

Make sure to teach it and you can use graduated guidance.

You can use errorless teaching, time delay, video modeling all kinds of things to teach that process, but really, it must be done.

Initially, the act of exchanging tokens should be the primary task which the individual engages in in order to gain access to the reinforcer.

You will also need to think about the ease and efficiency of the token exchange.

So if the response effort is too great that will be very difficult for the learner.

So let's say the learner had to walk across the room, get a bin, make a communicative response in order to get the educator to help with the backup reinforcers all those things really are a lot of effort for the learner and you need to consider that as well.

So now it's time for another ASR.

In order for Jacob to exchange his tokens for a backup item, he has to go to the breakout room, get his tokens off the shelf, ask the educator to help him open it, count his tokens to see how many he has in total, discuss with the educator which of the options from the menu he can afford, and then he gets to choose his backup reinforcer.

Over the next few days, the educator notices that Jacob is not motivated to engage in the target behavior.

What do you think could be the reason?

Exchanging the tokens for the backup items is too much effort.

The backup items are too expensive, or the tokens are not acting as conditioned reinforcers.

You folks are getting really good at responding to these ASRS, that's great.

Absolutely, all, absolutely.

As are coming in left and right here.

I mean, really Jacob all had to do back flips and handstands to get to get this opportunity to exchange the tokens for the backup, for the backup items, and it was just too much effort.

So, and sometimes I think that we don't even notice that we're doing that, that we've added all these things to that exchange, but really that is that is a pitfall, you've got to watch out for it.

So pitfall number seven relates to the exchange production schedule that Amy was talking about.

So how often is the learner given the opportunity to exchange tokens for backup reinforcers?

Sometimes educators focus too much on the token production and not enough on the exchange production.

Watch out, doing so would be an absolute pitfall.

So remember, it is the exchange production schedule and Amy already talked about this, but remember, it's the exchange production schedule that disproportionately controls the overall rate of learner responding.

So, you've noticed that the learner's responding is decreasing.

Make sure to think about these two questions.

Is it too much work that's required to earn a token?

And or has too much time elapsed between exchange opportunities?

So for example, if a learner receives a token after washing five cafeteria trays and it can exchange the tokens after accumulating on average, five tokens, all of the things accounted for, you could expect that the learner would be relatively rapid in their responding.

But if the educator abruptly changes that and now the learner has to wash 50 cafeteria trays and can only exchange those tokens and that would get them the token, and then they could only exchange those tokens after an average of 100 tokens excuse me, or both, we would probably see learner decrease cafeteria trays are able they're actually willing to wash, in fact, they might not wash any at all.

So, this can be avoided by increasing the response requirements gradually and by increasing the importance of the backup reinforcers.

So, pitfall number nine, should a response cost procedure be considered to address challenging behavior?

So as Amy mentioned, response cost procedures are punishment procedures and need to be used with caution.

So once again, make sure that the token is functioning as a conditioned reinforcer and the response cost procedure can be effective within any type of token production schedule as long as the tokens are acting as conditioned reinforcers.

If you still think the response cost is a necessary procedure that you think would benefit your learner, then you certainly can use it.

But once again, as I've just mentioned and as Amy has mentioned, it is a punishment procedure and can have negative effects.

So make sure that you have exhausted reinforcement procedures and make sure that everyone involved understands the response cost procedure, and that they know what's involved and that they agree to it.

That's really important.

And you might find yourself in this position that the learner has lost all their tokens because of the response cost procedure before the exchange time, and then they would have to wait so long before they could have that opportunity to earn them back.

So really think about response cost procedures before you put them into place.

So at the beginning of the section, the pitfalls and practicalities I mentioned that these questions and then the practical solutions would act as a tool of sorts to help you with your practice in school setting and so I hope that that would be beneficial for you and we would like to thank everyone for being here today and we hope that here's our contact information.

We wanna thank you for participating, especially in all those ASRs, you were great doing that, and we wanna thank you very, very much for participating and we hope that you'll find this useful, and I'd like to remind you about that ASR that I had at the beginning of the pitfalls, that you had the question in your mind and I'm hoping that some of the things that we've covered today might have answered the question that you had, or might have helped with some of those difficulties that you answered in the ASR.

So thank you so much.

We certainly appreciate it.

So we're going to stay for a little bit of time because people might have questions.

- [Shelley] But there were a couple that I just think would be important to kind of throw back at you to make sure that everyone's on the same page.

So would you say that the primary goal of a token economy or token reinforcement system is reinforcing positive behaviors rather than extinguishing negative behaviors?

- [Susan] I saw that question pop up when Amy was going through that section, and we've talked about this before.

So basically, in our viewpoint and based on all the research, we would definitely want to teach a behavior that's a positive behavior, because I think if you're thinking of what might be an appropriate behavior, you can always spin it around into a positive behavior.

So for example, let's say you want to decrease blurting out in class, because that sometimes comes up.

We've had lots of opportunity with that, but you could also turn that into a positive behavior or an appropriate behavior, I guess I should say, by having the learner raise their hand.

- [Shelley] So you did address I think, the kind of shaping and fading so you can kind of start with a lower level of difficulty and increase the level of difficulty as the learner starts to become more skilled.

There was a question about possibly including more than one behavior.

So if there are behaviors that are closely related, for example, asking questions in class discussion and contributing to a think-pair-share activity, could you include both of those as targets in the token economy?

- [Susan] But I think you need to really think about the smart slide and what you're defining so that the educators know exactly what's happening, that they're reinforcing the learner for and that the learner knows exactly what is expected of them behaviorally that they would be earning the tokens for, but I think that that's really important.

I don't know if Amy, you wanna say any more than that, but I think you can incorporate more than one target behavior.

But really, in the beginning, if you're just starting out with a token economy, think one behavior is probably good to start with and then as the learner masters the token economy, whole process, then perhaps you could look at more than one, and I think it's at once again, based on the learners needs.

- [Shelley] Those were the only questions that I noticed that weren't almost immediately answered.

So everyone who was asking question anticipated where you were going next in the presentation, which was great.

I just want to again, say thank you so much to you Sue and you Amy, as well for sharing this information with us.

I know, speaking for myself, I probably encountered almost all of those pitfalls at some point when implementing token reinforcement systems with students and supporting school teams to do that.

So having those as kind of problem solving check-ins I think is really great and as I mentioned at the beginning, Sue and Amy have developed some additional resources that we'll be sending out following the presentation either later today or tomorrow with a SurveyMonkey feedback link.

So you can also give us some feedback on the presentation and also on future topics that you would like to see.

So thanks again.

Susan and Amy, we really appreciate you joining us today.

It's really valuable to have such practical information presented and people can take away and use right away or at least when they're back together with students and school teams they're supporting, which is different from province to province, but hopefully soon for everyone.

So thanks so much.

Thanks, everyone for participating and joining us for so many of our webinars this year and we look forward to seeing everyone in the fall.

If there are topics you'd like us to make sure that we include in next year's webinar series then certainly, let us know that in the SurveyMonkey links that you'll be receiving today or tomorrow and we will do what we can to make sure that we're providing the most valuable information for you.