Interdependent Group-Oriented Contingencies: Randomly Selected Components to the Rescue

Abstract

Class-wide academic performance can be increased by overlaying existing instructional and classroom management procedures with supplemental interdependent group-oriented bonus rewards. The bonus reward strategies may be particularly effective for under-motivated, low-performing students. When applying supplemental interdependent group-oriented bonus rewards, rewards are delivered to all members of a class for meeting a group-oriented performance criterion. A description of supplemental interdependent group-oriented bonus rewards is provided, followed by reasons for using unknown, randomly-selected rewards and criteria for earning rewards. Guidelines for establishing a pool of possible rewards and criteria are provided that are designed to allow teachers to develop their own supplemental interdependent group-oriented bonus rewards.

Mrs. Burkhaut teaches in an inclusive second-grade classroom. After scoring students’ independent seatwork, Mrs. Burkhaut hands back assignments along with stickers for those who scored above 90% correct. Her students really like stickers, but once again she feels frustrated as the same four or five students fail to complete even 60% of their in-class independent seat work accurately. The students are disappointed to not receive a sticker. Mrs. Burkhaut wonders if this is a skill development problem or a performance problem. If students lack the prerequisite skills, they may not be able to complete the work at a high level. Alternatively, a performance problem would suggest that they can do the work but are not sufficiently motivated to apply their best effort to these assignments.

Mrs. Burkhaut has engaged in excellent assessment of her students’ academic skills and has observed their behaviors when presented with classwork. Her students’ inconsistent performance and frequent off-task behaviors lead Mrs. Burkhaut to deduce that in most instances, she is dealing with performance or motivation problems. It appears that her students have the skills required to complete the work but are often undermotivated (Shapiro, 2011). Regardless, Mrs. Burkhaut is concerned that if these students continue to perform poorly on academic assignments, they will fail to develop skills, which will hinder their short-term and long-term development and academic achievement (Shapiro, 2011).

Interdependent Group-Oriented Bonus Rewards

One strategy that may mitigate motivation challenges is to provide supplemental interdependent group-oriented bonus rewards (SI-GOBRs) delivered to all members of the class based on the class’s average assignment performance meeting a criterion (Skinner et al., 2020). SI-GOBRs play an integral role in the Good Behavior Game (Barrish et al., 1969; Bowman-Perrott et al., 2016), classwide peer tutoring (Greenwood et al., 1984), classwide function-related intervention teams (Wills et al., 2014), and many collaborative and cooperative learning interventions (Slavin, 1991).

SI-GOBRs are

contingencies, which establish an if–then relationship between behavior (e.g., assignment performance) and consequences (e.g., rewards);

positive reinforcement, because a stimulus (e.g., sticker) or the opportunity to engage in a preferred behavior (e.g., extra computer time) is delivered contingent upon a behavior and this contingency increases the probability of this behavior;

supplemental, because they can be overlaid on preexisting classroom management and reward structures without replacing these structures;

interdependent, because the criterion for success depends on some aspect of groups behavior (e.g., class average assignment performance) rather than individual performance;

group oriented, because the entire group receives the reward when they meet the group-oriented criteria; and

bonus rewards, because a member of the group can receive an additional reward that was previously not available under typical classroom procedures.

Figure 1 provides an example of this type of reward. Like all reinforcement contingencies, SI-GOBRs include rewards and criteria for earning rewards. In this example, all students in the class earn 3 minutes of extra recess if the class average is 85% or higher on a language arts assignment.

Figure 1

An example of a supplemental interdependent group-oriented bonus reward

SI-GOBRs have been used to enhance students’ academic assignment performance in general education (e.g., Winett et al., 1975; Scott et al., 2017), special education (e.g., Jacquett et al., 2020; Popkin & Skinner, 2003), and inclusive (e.g., Zibreg Hargis et al., 2016) classrooms. Additionally, these contingencies have been used to enhance performance across a variety of different assignments (e.g., Jacquett et al., 2020; McCurdy et al., 2008; Shapiro & Goldberg, 1986; Sharp & Skinner, 2004; Speltz et al., 1982). In Mrs. Burkhaut’s classroom, the same few students consistently score below the criterion (90% correct) required to earn a reward (e.g., a sticker). Repeatedly failing to meet criteria for earning a reward can cause students to stop trying (Johnson, 1981; Scott et al., 2017). Because lowered expectations tend to lead to lower performance (Fuchs et al., 1985; Hattie, 2009), teachers should be reluctant to lower the classwide criteria for each student to earn an individual reward (e.g., 90% to earn a sticker). Instead of reducing their classwide standards for individual students to receive rewards, teachers can enhance the motivation of all students by providing the opportunity for the entire class to earn an additional bonus reward contingent upon the class average meeting a criterion (Popkin & Skinner, 2003; Scott et al., 2017; Zibreg Hargis et al., 2016).

SI-GOBRs With Unknown, Randomly Selected Rewards and Criteria

In their typical application, each SI-GOBR contingency component is preestablished and communicated to students; thus, students know each contingency component (Little et al., 2015). Alternatively, rewards and criteria for rewards do not have to be communicated to students; instead, they can be unknown and randomly selected. Using unknown, randomly selected contingency components may enhance SI-GOBRs’ effectiveness in strengthening academic performance while reducing some negative side effects associated with the application of group-oriented contingencies, including students (a) sabotaging the group’s effort to earn the reward, (b) giving up because they feel they cannot meet criteria, (c) working to criteria instead of doing their best work, and (d) applying themselves to some assignments but not other assignments.

Figure 2 depicts examples of rewards and criteria elements that were developed by combining strategies from two studies. Popkin and Skinner (2003) randomly selected rewards, numerical criteria, and target behaviors; Scott et al. (2017) randomly selected numerical criteria and scale. Figure 2 depicts numerous rewards that could be included in a pool of rewards from which a teacher could randomly select. Additionally, Figure 2 provides numerous examples of different criteria elements (i.e., target behavior, numerical criterion, and the criterion scale). Including one item from each element list can allow teachers to develop different criteria that can then serve as the criteria pool.

Figure 2

Examples of supplemental-rewards target behaviors, numerical criteria, and criteria scales that could be included in a supplemental interdependent group-oriented bonus reward with unknown, randomly selected components

When applying this SI-GOBR, the reward and criteria would be randomly selected and not communicated to students. Thus, although students would know that they could earn a reward based on their academic performance, they would not know which specific reward they could earn that day. Additionally, students would not know the specific criteria elements that would be used to determine if they earned the reward.

How to Implement SI-GOBRs With Unknown, Randomly Selected Components

At the beginning of the day, with the class seated, Mrs. Burkhaut makes a few announcements and then reaches into a brown lunch bag with the pool of rewards slips, selects a slip, reads it to herself, and places it into an envelope. Next, she does the same thing with another bag that contains criteria. The randomly selected reward is 3 minutes of extra recess, and the randomly selected criterion is Table 1 average (scale) of 91% or higher (numerical criterion) on the spelling assignment (target behavior) (see Figure 3). Today the class has a spelling test scheduled. Thus, all members of the class will receive 3 minutes of extra recess time if the average test score of the four students who sit at Table 1 meets or exceeds 90%. If there is a reason a randomly selected reward cannot be delivered (e.g., the game students earned the chance to play is broken), the teacher can randomly select a different award. Similarly, if the criterion slip indicates a target behavior where there is no assignment scheduled, a different criterion slip can be selected. After selecting slips and placing them in an envelope, Mrs. Burkhaut posts the envelope high up on her bulletin board.

Beginning the day with the drawing reminds the students that they could earn a bonus reward contingent upon their academic performance; however, with this procedure, they do not know which reward they could earn, the target behavior on which they will be judged, or the performance criterion (numerical criterion and scale) against which their performance will be evaluated.

Figure 3

Materials required for randomizing a supplemental interdependent group-oriented bonus reward

Mrs. Burkhaut administers the spelling test at approximately 10:00 a.m. She makes time to score the four students’ tests who are assigned to Table 1 and calculates their average before 2:00 p.m. At an appointed time (e.g., end of school day), she walks to the front of the room being the only person who knows the reward and the criterion. She opens the envelope and lets the students know that the criterion was based on Table 1’s spelling performance and that Table 1 did well enough so that the entire class earned the reward, which is 3 minutes of extra recess. Mrs. Burkhaut and the students clap and congratulate Table 1 as she announces that tomorrow, the class will receive 3 minutes of extra morning recess.

In this example, two characteristics of performance feedback are noteworthy. The teacher did not provide the numerical criterion, as this would have provided all students with information about the academic performance of a small group of classmates. Also, the teacher announced the unknown, randomly selected table. If the students did not earn the reward, they should not be told which reward they failed to earn, whose performance the criterion was based on, or the numerical criterion or how the randomly selected group scored (Skinner et al., 2004). Instead, they should be told that they will have an opportunity to earn a bonus reward tomorrow and that they should continue to try to do their best on academic assignments and exams (VanMaaren et al., 2020).

“If the students did not earn the reward, they should not be told which reward they failed to earn, whose performance the criterion was based on, or the numerical criterion or how the randomly selected group scored.

Effects of SI-GOBRs With Randomly Selected Components

Researchers have evaluated the effects of SI-GOBRs with contingency components unknown and randomly selected. Researchers have used SI-GOBRs with unknown, randomly selected components to reduce inappropriate classroom behavior (Kelshaw-Levering et al., 2000; Murphy et al., 2007) and enhance on-task behavior (Heering & Wilder, 2006; Jacquett et al., 2020). SI-GOBRs with randomly selected components have also been used to encourage prosocial behaviors by reinforcing students’ reports of classmates’ performance of recently taught social skills (Wright et al., 2019). Finally, researchers have used SI-GOBRs with randomly selected components to enhance students’ performance on a variety of in-class academic assignments, including language arts and spelling (Popkin & Skinner, 2003), writing (McCurdy et al., 2008), reading (Sharp & Skinner, 2004), math (Scott et al., 2017), and social studies (Jacquett et al., 2020). Researchers have also used SI-GOBRs to enhance students’ homework assignment performance (Aloisio, 2006; Zibreg Hargis et al., 2016).

In many studies of SI-GOBRs with unknown, randomly selected components, researchers have reported classwide data (e.g., Heering & Wilder, 2006; Jacquett et al., 2020; Zibreg Hargis et al., 2016). In the two studies that served as the basis for the example depicted in Figures 2 and 3, researchers also provided percentage correct data at the individual student level (Popkin & Skinner, 2003; Scott et al., 2017). Data from these two studies provide evidence regarding the effectiveness of SI-GOBRs with randomly selected components on low-performing students.

Scott et al. (2017) developed, installed, and evaluated two SI-GOBRs in a second-grade classroom. During typical classroom procedures, each student who scored over 90% on their in-class math assignment earned extra free time. Unfortunately, several students rarely, if ever, earned this reward as they consistently scored below 70%. A SI-GOBR was installed in which all members of the class received a small piece of candy when they met a randomly selected, group-oriented criterion for performance on in-class math assignments. Thus, the reward (i.e., candy) and target behavior (i.e., math assignment performance) were known and fixed, but the numerical criterion was unknown and randomly selected. Additionally, under one condition, the students were told that the reward would be based on the class average (known scale). However, under the other condition, the reward was based on an unknown, randomly selected table’s (four students per table) average performance (unknown scale).

“Again, those with the lowest performance during typical classroom procedures showed the greatest increases.

Scott et al. (2017) found that the class average percentage correct increased from 64.0% to 83.4% after the SI-GOBRs were installed and that the increases were almost identical across the known class-average SI-GOBR and the unknown, randomly-selected-table SI-GOBR. Across both SI-GOBRs, the largest increases were in the lowest-performing students. The five students who were scoring below 60% increased their math performance by an average of 39.4% after the SI-GOBR was added. Those scoring 60% to 69% showed the next greatest increases (22.0%). Even the students who consistently scored above 90% and had little room to improve increased their performance by an average of 4.3%.

Popkin and Skinner (2003) evaluated the effects of a SI-GOBR in a self-contained classroom serving five students with emotional-behavioral disorders (EBD) who each received different assignments. The classroom teacher was concerned that the students were performing poorly because the material may have been too difficult (e.g., a skill deficit or a mismatch between prerequisite skills and assignment demands). In this class, numerous individual contingencies were applied that were designed to enhance each student’s learning and other desired behaviors while decreasing undesired behaviors. In this study, the SI-GOBR rewards and numerical criteria were always unknown and randomly selected. The scale was known and always based on the class-average performance. The target behaviors varied. First, the students knew the target behavior was their performance on spelling. After a few weeks, math performance was added to the criteria pool. Following a few more weeks, language arts was added. Thus, in the final phase of the study, each student entered the classroom knowing that they could earn a reward for their academic performance on spelling, math, or language arts. However, they did not know what reward they could earn, what target behavior (spelling, math, or language arts) would be used to determine if they won a reward, or what numerical criteria they had to meet to earn a reward.

When SI-GOBRs were added, the students increased their class-average spelling accuracy from 62.2% to 96.2%, their math accuracy from 66.6% to 86.6%, and their language arts accuracy from 85.7% to 93.3% (Popkin & Skinner, 2003). Again, those with the lowest performance during typical classroom procedures showed the greatest increases. Across spelling, math, and language arts, there were six instances of students scoring below 70% during typical classroom procedures (e.g., letter grades of D or F). In four of those instances, after the SI-GOBR was added, students increased their performance to above 89% (letter grades of A), and in two instances, students increased their performance to between 80% and 89% correct (e.g., letter grades of B). Thus, the material was not too difficult, and the students responded to the opportunity to earn an additional bonus reward by improving their academic performance.

Guidelines for Developing a Pool of Rewards and Criteria

There are numerous options when selecting SI-GOBR rewards and criteria to include in the random selection pool. Criteria subcomponents or elements include target behaviors, numerical criteria, and a scale, which can include class averages, high scores, or scores of a smaller subgroup of the class (Aloisio, 2006; Heering & Wilder, 2006; Scott et al., 2017). Next, both a rationale and guidelines for developing a pool of rewards and criteria are provided (Skinner & Watson, 1997).

Reward Pool

There are several reasons for using unknown, randomly selected rewards drawn from a pool of possible rewards. “Mystery motivator” contingencies employ unknown, group-oriented rewards (Kowalewicz & Coffee, 2014; Rhode et al., 1993; Robichaux & Gresham, 2014). Like a wrapped present, an unknown or mystery reward may be higher quality or more powerful than a known reward (Rhode et al., 1993).

“Like a wrapped present, an unknown or mystery reward may be higher quality or more powerful than a known reward.

The quality of any reward is likely to differ across students. For example, for one student, getting to play a specific game may be a high-quality or powerful reinforcer, whereas getting extra recess may be less powerful. The opposite pattern may occur with another student. The key to any group reward pool is to have some rewards that are high-quality rewards for each student (Skinner & Watson, 2000) and for all students to know which rewards are in the pool. As long as there is a high-quality reward for each student in the pool (although this may be a different reward for Jack than for Olivia), each student may be highly motivated to do their best (Popkin & Skinner, 2003) because there is a chance that their academic performance could be rewarded with a high-quality reinforcer.

Use consequences that are rewarding to everyone

It is unjust to punish students (e.g., deliver aversive stimuli or remove privileges contingent upon behavior) who performed well or behaved appropriately contingent upon their classmates’ performance or behaviors (McCurdy et al., 2018). Doing so can cause students to blame, threaten, or aggress against peers and become uncooperative with teachers who delivered unfair punishment (Heering & Wilder, 2006; Pigott & Heggie, 1986; Romeo, 1998). When SI-GOBRs are applied, rewards should not be punishers for some students. For example, earning the opportunity to play dodgeball may be a high-quality reward for some students but a punisher for others (McCurdy et al., 2020). If playing dodgeball is punishing for some students, these students may sabotage the group’s effort to earn the consequence by intentionally doing poorly and disrupting classmates’ efforts to do well (Skinner et al., 1996).

Use low-stakes rewards

Teachers, administrators, and parents may object to interdependent group-oriented rewards because of a perception that they are not fair (Briesch et al., 2015; VanMaaren et al., 2020; Witt et al., 1984). Students can perform poorly and earn a reward when their classmates do well; conversely, students can perform well and not earn a reward because their classmates performed poorly. Therefore, rewards that may have a meaningful and long-lasting impact on students should not be applied. For example, because letter grades can impact a student’s ability to get into specific classes or their admission to college, teachers may want to avoid assigning grades for group performance (Skinner et al., 2020). Instead, teachers should use rewards that do not have long-lasting meaningful impact, such as music during independent work time, a reinforcer that works well across primary and secondary grades.

Use unique bonus rewards

Because these are additional or bonus rewards, teachers may want to avoid rewards that they are already using to reinforce individual students’ behaviors or performance (e.g., stickers in Mrs. Burkhaut’s classroom). To make these truly feel like bonus rewards, teachers should consider using some unique, atypical rewards (Skinner et al., 1999). Although doing so may require some creativity, because scarcity breeds demand, considering unique rewards may allow teachers to develop many high-quality, low-stakes, and resource-efficient rewards (McCurdy et al., 2020).

Consider activity rewards

When applying individualized contingencies, teachers often choose tangible rewards (e.g., candy, stickers, small plastic trinkets, school supplies, small edibles) because they can be easily delivered to those who earned them and withheld from those who did not earn the reward. When all members of the group earn rewards, it is easy to deliver activity rewards (Skinner et al., 1999). These activity rewards are often resource efficient (i.e., free) and easy to deliver when all students earn the reward. Examples of atypical activities that are scarce in school include being able to (a) listen to music during independent seat work, (b) have the teachers sing the students a song, (c) eat lunch in the classroom, (d) chew gum, (e) wear hats during class, (f) have the teacher wear a funny hat, (g) have a special T-shirt day, (h) take shoes off for a class, and (i) play games.

Some common activity rewards allow for student choice, enhancing the probability that the activity is reinforcing for everyone. For example, when students earn extra recess time, each can choose to engage in their own preferred behaviors. There are numerous options for activity rewards that can be found with online searches, shared from teacher to teacher, or created by teachers and students. Regardless, if the activity takes little time (e.g., teacher sings a song), does not interfere with teaching and learning (e.g., listening to music during seatwork), and is not something that is typically done in school (e.g., shoes off in class), then it may be a high-quality bonus reward for most students that can be used to enhance academic performance without significantly reducing teaching and learning time (McCurdy et al., 2020).

Ask the students

One way to generate group rewards is to use a suggestion box (Popkin & Skinner, 2003). Provide guidelines for student-suggested rewards, as such rewards should (a) cost little or nothing, (b) take little time away from teaching and learning activities, (c) be enjoyed by everyone, and (d) be consistent with school and society rules and laws (Skinner et al., 2004). Additionally, the reward pool should be varied, with new rewards (including student-suggested rewards) being added and others withdrawn. Regularly adding rewards can enhance the program’s effectiveness by preventing satiation (e.g., reinforcers becoming weaker or lower quality after they are received frequently) and enhancing salience of the contingency (e.g., students’ awareness of the contingency) by reminding students that they can earn rewards for their academic performance every time a reward is added to the pool (Robichaux & Gresham, 2014; Skinner et al., 2009). Finally, because immediate reinforcement is more powerful than delayed reinforcement (Neef et al., 1993), the pool should include some rewards that can be delivered immediately (e.g., a 30-second dance party).

Target Behavior Pool

Criteria include target behaviors, numerical scores, and a scale or how those scores are calculated. As Popkin and Skinner (2003) demonstrated, the target academic behaviors can also be unknown and selected randomly. The primary advantage to randomly selecting academic target behaviors is that this procedure can encourage students to do their best across academic assignments or exams (Skinner & Watson, 2000). For example, students may have a particularly challenging math assignment early in the school day. If they feel that they can no longer earn the reward for their academic performance that day because of their poor performance on this math assignment, they may stop putting forth their best effort on spelling, language arts, and science assignments that come later. However, when target behaviors are unknown and randomly selected, students start each assignment with the possibility that their performance on that assignment could help them earn a reward (Campbell & Skinner, 2004). Thus, the rationale behind using unknown, randomly selected assignments is that it keeps students motivated across assignments (Popkin & Skinner, 2003).

Target unobservable or private behaviors

With SI-GOBRs, because students’ fates are intertwined (Slavin, 1991), when public or observable behaviors are targeted, students may observe and monitor classmates’ behavior. When the class does not earn a reward, these observations may cause some students to blame classmates for causing them to fail to earn the reward (Heering & Wilder, 2006; Romeo, 1998). This may be more likely to occur when rewards are delivered contingent upon lower levels of disruptive behavior (McCurdy et al., 2020; Pigott & Heggie, 1986). If the behavior is disruptive, it gets classmates’ attention and allows them to identify who to blame. In their attempts to prevent classmates from engaging in these disruptive behaviors, students may threaten peers with aversive consequences if they engage in these public behaviors (Pigott & Heggie, 1986; Romeo, 1998). Another reason to avoid targeting these unwanted behaviors is that it can be very time-consuming for teachers to measure these behaviors.

“If students struggled in one area early in the day (e.g., math), they were still motivated to apply themselves in other areas (spelling and language arts) because they did not know which target behavior would be selected as the criterion for earning a reward.

Target academic performance

There are several reasons teachers should consider targeting academic performance on exams, in-class assignments, and homework (Skinner et al., 2009). Building academic proficiency is of primary importance; thus, it is appropriate to reinforce behaviors that enhance academic proficiency. Teachers often score students’ academic performance; thus, there is less additional work in determining if a class met a criterion (Scott et al., 2017). Finally, academic performance is often private and teachers do not share academic performance indicators (e.g., scores) with classmates; thus, students may be less likely to blame classmates when the class fails to earn a reward (Skinner et al., 2020).

Target something every day

Scott et al. (2017) targeted math performance for several reasons. The primary reason was that the teacher had concerns that failure to perform math assignments to the best of their ability was having an adverse effect on some students’ learning and skill development. Also, students had math assignments each day; therefore, targeting academic performance allowed SI-GOBRs to be built into daily routines. By supplementing typical classroom procedures with a daily SI-GOBR, all students entered the school each day knowing that they could earn an additional bonus reward, potentially enhancing students’ attitudes towards school, teachers, and learning (Skinner et al., 2004).

Add target behaviors to the pool

Although targeting multiple academic tasks simultaneously may prove effective, there are reasons why teachers may want to start with one academic target behavior and then sequentially add target behaviors (see Popkin & Skinner, 2003). One strategy is to begin with academic assignments that students are more likely to be successful with and then introduce other tasks to the criteria pool that may prove more challenging. In this way, a teacher can gradually increase the amount of work targeted by the SI-GOBR (i.e., shaping), enhancing the amount of motivated academic performance students obtain for the same rewards (Alberto & Troutman, 2012; Stokes & Baer, 1977).

Popkin and Skinner (2003) targeted spelling first because the teacher was fairly certain that all students in the classroom had the prerequisite skills to write letters in sequence. The teacher was correct, and the students consistently earned rewards for their spelling performance. This early success (i.e., priming the pump) likely served to motivate students, who actually received rewards for their academic performance (Alberto & Troutman, 2012). Next, the teacher targeted spelling and math using unknown, random selection. Finally, the teacher targeted spelling, math, and language arts using unknown, randomly selected target behaviors. In this final phase, performance was enhanced across all three academic targets, using the same rewards that initially targeted only spelling. Additionally, if students struggled in one area early in the day (e.g., math), they were still motivated to apply themselves in other areas (spelling and language arts) because they did not know which target behavior would be selected as the criterion for earning a reward (Campbell & Skinner, 2004).

Numerical Criteria

Behavioral science has not progressed to the point that allows for teachers to identify a single best “Goldilocks” numerical criterion (e.g., 90% correct), which is a criterion that is not so high that they cannot reach it and not so low that they do not do their best (Skinner et al., 2020). If the criterion is too high, students may lose their motivation to try to meet it. If it is too low, students may work to meet the criterion, as opposed to doing their best. Like all behaviors, academic performance is variable (Skinner et al., 2020). Thus, setting a numerical criterion that maximizes any student’s performance across assignments is challenging. Setting one for an entire class may be even more challenging (Skinner et al., 2009). To motivate students to perform their best, teachers can apply unknown, randomly selected numerical criteria (Jacquett et al., 2020).

Use a range of numerical criteria

Skinner and Watson (1997) suggested developing a pool of criteria—some difficult, some easier—and randomly selecting a criterion. The key is not to let students know which criterion was selected. When students know how well they have to do, they may only work to the criterion (Cashwell et al., 2001). However, when they do not know how well they have to do, they are more likely do their best.

Popkin and Skinner (2003) wrote the following criteria on slips of paper: one slip with “25%,” three with “50%,” three with “70%,” four with “80%,” four with “85%,” five with “90%,” five with “95%,” and five with “100%.” When Scott et al. (2017) developed their SI-GOBR, they used the same criteria. Although both Scott et al. and Popkin and Skinner provided evidence that the SI-GOBRs were effective, this was not caused by having the “best numerical criteria” in the criteria pool. These researchers included a range of numerical criteria, and it is important to understand the rationale for including such a range of criteria. Numerical criteria should include some that are slightly higher than the current average, because gradual improvements may be the best students can do. Some numerical criteria should be much higher, as teachers may underestimate how well students can do when their motivation is enhanced (see Popkin & Skinner, 2003). Finally, there are reasons why it is appropriate to include some numerical criteria lower than the current typical performance (Campbell & Skinner, 2004). Academic performance may be impacted by the varying difficulty of the material being covered, disruptions that may impact students’ learning, and numerous other factors. Having the opportunity to continue to earn rewards, even though material is very difficult, may prevent students from giving up on the tasks that require their best effort.

Alter the numerical criteria pool

As teachers gain a better understanding of student performance after the SI-GOBR is installed, they can alter the pool. For example, if students are rarely earning rewards, teachers could replace some high-criterion slips of paper with some lower-criterion slips of paper. Alternatively, if students are consistently earning rewards, a shaping procedure could be used as teachers replace lower-criterion slips with higher-criterion slips (Skinner et al., 2004).

Prime the pump

Teachers should never rig the criterion selection process so that the group loses. However, to enhance motivation and student buy-in, when first implementing the contingency, teachers may want to rig it so the students earn their reward. For example, teachers could appear to randomly select a criterion but purposefully select a very low numerical criterion (see Sharp & Skinner, 2004). Earning a reward early on is likely to motivate the students to keep working hard to earn additional rewards (Scott et al., 2017).

Criteria Scale: How Criteria Are Calculated

As with numerical criteria, there are numerous ways to scale or calculate criteria. Although class averages may be the most common (Little et al., 2015), others have used criteria based on the number of desired responses meeting a cumulative criterion, the percentage of students who met a criterion, the group’s highest score, the lowest score from the group, and the average score of a randomly selected subgroup of students (Aloisio, 2006; Cashwell et al., 2001; Kirkpatrick et al., 2019; Skinner, 2008). Which scale is selected may depend upon goal or context. For example, Kirkpatrick et al. (2019) based their criteria on the number of different students who were reported to have engaged in a prosocial behavior. They selected this scale, rather than the total number of instances of prosocial behavior, because they were concerned that students would continually report the behavior of the same student(s) (e.g., popular students who engaged in high rates of prosocial behavior) while failing to report the prosocial behaviors of less popular students.

Cumulative total responses

Using cumulative criteria that have limited opportunities (e.g., number of math problems the class got correct on today’s assignment) is similar to a class-average score but is influenced by factors such as attendance or number of items assigned each day; thus, average percentage-correct scores are often used. However, cumulative criteria that are not time limited can be based on total responses across school days. This type of scale allows students to make progress toward earning a reward over time, without ever losing the opportunity to earn a reward. When such procedures are used, researchers have depicted, students progress toward their goal (e.g., move an icon up a ladder based on daily performance), and when they reach the cumulative criterion (e.g., top of the ladder 1 week after the SI-GOBRS was initiated), the class receives the reward (e.g., Cashwell et al., 2001; Wright et al., 2019). Providing progress feedback via public postings can reinforce students’ progress toward their goal. The primary weakness associated with such a procedure is that they may occasion a postreinforcement pause or a decrease in student performance immediately after they meet their cumulative criterion and receive their reward (Alberto & Troutman, 2012). Additionally, when they get very close to their goal, they may not perform their best but, rather, work toward the criterion that they have almost met (see Skinner et al., 2000).

Class average

Class-average criteria have many advantages. First, each student’s performance influences whether or not the group meets the criterion, which is consistent with rewards being delivered to all or no students in the class. Thus, this scale may seem fairer than some other scales. However, there are limitations associated with class averages. When the class is large, each student’s performance contributes less and less to the class’s average (Shapiro & Goldberg, 1986). Consequently, some students may not be motivated to perform their best, because their performance has too little influence on whether the group meets the criterion, and they may rely on other students’ efforts to allow them to receive a reward. The second issue is with application. Although teachers may score each student’s academic assignment performance, calculating class averages can be time-consuming, especially with a large class (Scott et al., 2017).

Randomly selected subgroups

When Scott et al. (2017) compared SI-GOBRs with two different scales, class average versus the average of a randomly selected smaller subgroup (i.e., a table of four students), results showed that the two SI-GOBRS with different scales caused almost identical increasing math performance in an elementary school classroom. There were several reasons why Scott et al. recommended using randomly selected small-group (i.e., tables) performance. If students are already placed in subgroups (e.g., tables, science lab groups), then targeting subgroup performance may cause students in the subgroup to encourage each other to perform their best. Also, Scott et al. reported that several students found the intervention more acceptable, perhaps because having the table randomly selected introduced another component that was unknown (McCurdy et al., 2018; Rhode et al., 1993). The teacher indicated that this strategy was more acceptable because it took much less time to score and calculate the average of a smaller group (Scott et al., 2017).

Another advantage to using scales that include the average performance of randomly selected subgroups is that it may occasion social reinforcement. When an unknown, randomly selected smaller group’s performance does not meet criteria, students should not be told which table was randomly selected. However, when the table did earn a reward, teachers can announce which table was selected, which may cause classmates to clap and praise these students. For students who rarely receive reinforcement for their academic performance, this type of peer social reinforcement can be incredibly powerful (Scott et al., 2017).

“Additionally, teachers should encourage students to celebrate their success as this additional social reinforcement may enhance the effectiveness of the SI-GOBRs.

Other Considerations

When introducing SI-GOBRs to the class, teachers should stress that they are giving the students an opportunity to earn extra or bonus rewards based on the class’s academic performance. To enhance the idea that this is a bonus reward, teachers may want to install their SI-GOBRs after a few weeks of school have passed and include unique, low-stakes rewards in their pool of rewards. After installing SI-GOBRs, there are several reasons why teachers should alter components after the system is in place. First, teachers can replace or remove rewards dependent upon student response. For example, if the reward is being able to chew gum and the teacher finds the classroom littered with gum, they can remove this reward from the pool. Alternatively, if the students really seem to enjoy listening to music during independent seat work, the teacher can replace the reward after it has been selected. Also, allowing students to continually suggest rewards may make the entire system more salient and effective (Popkin & Skinner, 2003). Furthermore, students may suggest some powerful, low-stakes rewards that do not reduce time for teaching and learning activities. Finally, altering the criteria pool by including a larger percentage of higher numerical criteria or additional target behaviors can allow teachers to shape academic performance, which may enhance maintenance (Stokes & Baer, 1977).

When the group earns a reward, teachers should not withhold the reward from a student who performed poorly, did not even try, or misbehaved. In some instances, this can be very difficult; however, if teachers expect students to understand and accept that these are different types of rewards (e.g., interdependent group-oriented rewards), they must deliver the reward to all members of the group when criteria are met (Skinner et al., 2009). Additionally, teachers should encourage students to celebrate their success as this additional social reinforcement may enhance the effectiveness of the SI-GOBRs (Alberto & Troutman, 2012).

Because SI-GOBRs are added to existing procedures, teachers must spend additional time administering SI-GOBRs. Also, teachers may have to do more teaching and scoring assignments after applying these contingencies (Popkin & Skinner, 2003). More students ask more questions, request more clarification, and ask for help more frequently (Jacquett et al., 2020), which may require additional teacher time. Because students are more likely to earn a reward when their classmates do well, teachers need to monitor for a particular typical type of cheating—cheating initiated by stronger students who insist that weaker students take their answers (Scott et al., 2017). When detected, the teacher could provide a warning to the class that if cheating occurs, their opportunity to earn a reward could be suspended for that day. Additionally, the teacher could take this opportunity to provide tips to strong-performing students regarding what they could do to help others learn the material (Skinner et al., 2020).

Students may occasionally complain about failing to get a reward when they did well (Heering & Wilder, 2006; VanMaaren et al., 2020). Repeating that this is a group reward and indicating other benefits from their excellent individual work (e.g., benefits from learning, other rewards they receive for their individual performance) may mitigate these complaints (McCurdy et al., 2020). If complaining persists, teachers can let students know that this bonus reward system can be dropped (Andrews & Williams, 1970; VanMaaren et al., 2020). Because this is a bonus reward program, the outcome would be their losing the chance to receive an additional reward. Most students do not want to lose the chance to receive a bonus reward (Skinner et al., 2009). With a randomly selected reward, a student may complain when one of their most preferred rewards is randomly selected on a day they did not attend (Skinner, 2008). This can be addressed by replacing rewards after they are randomly selected. Regardless, students wanting to attend school because it is a place where their academic performance is rewarded is really not much of a problem (McCurdy et al., 2020).

Back to Mrs. Burkhaut

Mrs. Burkhaut has implemented a SI-GOBR with unknown, randomly selected rewards and criteria. Since installing the SI-GOBR, Mrs. Burkhaut has made many changes in the reward and criteria pools. She has added rewards, including student-suggested rewards, and removed some rewards that were problematic (e.g., chewing gum). Additionally, she has added target academic behaviors, and as students showed improved performance, she has replaced some lower numerical criteria with higher criteria. Mrs. Burkhaut is particularly pleased with the large increases in performance from the students who scored the lowest before the SI-GOBR was applied. These students are attending to teacher-led instruction and asking more questions. Additionally, during independent work, some students who never asked for assistance are asking for clarification and additional help while they work.

Although the four or five students who were her primary concern are requesting additional assistance (e.g., additional instruction or clarification) more frequently, such assistance is much easier to provide. When students were not applying themselves, they would sometimes score 30% on assignments. Now that they are motivated, low days are more likely to result in 70% accuracy. Mrs. Burkhaut finds it much more manageable to provide additional instruction for 30% of the assignment as opposed to 60% of the assignment. Although the students occasionally express disappointment when they don’t earn a reward, they are not too upset because they know they could earn a bonus reward tomorrow. The students seem excited about the bonus reward program, and Mrs. Burkhaut is glad to spend her time teaching, encouraging, and rewarding students for their motivated academic performance.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Robert D. Richardson

Robert D. Richardson, Clinical Assistant Professor, Educational Psychology and Counseling; Margaret A. Crewdson, PhD, Candidate, Educational Psychology and Counseling; Christopher H. Skinner, Professor, Educational Psychology and Counseling; Laura S. Wheat, Assistant Professor, Educational Psychology and Counseling; and James A. Martinez, Assistant Professor, Educational Leadership and Policy Studies, University of Tennessee, Knoxville.

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