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Problem Importance
The students academic success largely depends on their behavior, which is determined not only by the environment but also by psychologic states. Autism spectrum disorder (ASD) is a developmental disease that is marked by communication and social functioning deficits. As reported by the Centers for Disease Control and Prevention (CDC) and the Health Resources and Services Administration (HRSA), the rate of ASD tends to increase: while 1.2% children had this disorder in 2007, 1 out of 50 children (2%) have the associated symptoms in 2012 (McCurdy & Cole, 2014). The majority of children with ASD are likely to engage in off-task behaviors, showing aggression, self-injury, and other disruptions.
The variability with which students present their symptoms requires the use of special methods to diminish their challenging behaviors. While some of them can speak in full sentences, others fail to react to interventions (Fiske et al., 2015).
In particular, inappropriate talking, incorrect posture, and inattention to teacher instruction are the key off-task behaviors that can be noted in students with ASD. The strategy of token economy implies special positive rewards and praise when the expected behavior is achieved (Carnett et al., 2014). Considering that children are especially sensitive to support, the use of the token economy should be explored in detail to determine its potential impact on reducing off-task actions.
Effectiveness of Token Economy in Autism
The review of the academic evidence demonstrates that the authors consider the identified problem form different perspectives. One of the most widespread approaches focuses on the perseverative interest of applying the token economy to students with ASD. The study by Carnett et al. (2014) explores the case of a 7-year-old male student, comparing the traditional token system with the one based on the interest. The mentioned authors reveal that both methods are effective, yet the former shows more significant results. The importance of this article lies in the practical implementation of the advantages discovered during the experiment.
Namely, the puzzle pieces were used as tokens to engage the student. The role of the tangible tokens is also studied by Fiske et al. (2015), who state that two participants responded with a low level of interest to the use of tokens. However, they note that the back-up reinforcement identification frequency seems to be the decisive factor.
The peer support intervention can be regarded as one of the most promising reinforcement factors that are used in inclusive classrooms. McCurdy and Cole (2014) assume that peer-mediated intervention (PMI) can decrease off-task behaviors and positively impact work completion. The hypotheses suggested by these authors are confirmed in their article based on the multiple-baseline design study. These results are consistent with the opinion of the National Professional Development Center on Autism Spectrum Disorders since the paramount goal pursued in the assistance to such children is communication promotion.
Among the motives for involving peers, there is their availability in the classroom and natural impact on children with ASD (McCurdy & Cole, 2014). In addition, peers can help their classmates in a timely manner, which saves a teachers time. The underlying reason for using PMI is that peers contribute to prompting appropriate behaviors that can be effectively learned by the students with autism.
Self-monitoring is another intervention related to token economy, which implies that the students with autism can be taught to observe their behavior and stay focused on a given task. According to Davis et al. (2014), who study the factor of reinforcement, the tangible support for token economy is the only working method. The group of participants that was offered reinforcement plus self-monitoring techniques reduced off-task behaviors.
These findings rationally assume that the education of children with autism should be accompanied by additional strategies to help them in concentrating on a single task. McCurdy and Cole (2014) agree with the statements provided by Davis et al. (2014), emphasizing that self-monitoring is a successful strategy to control ones behaviors. It should be stressed that the previous literature also confirms the recent findings as stated by McCurdy and Cole (2014), there were 24 empirical studies published by 2011.
Further review of the recent evidence shows that the self-monitoring procedure not only reduces off-task behavior but also promotes on-task attitudes. The stereotyped and challenging behavior tends to be replaced by repetitive actions in highly functioning students with autism and symptoms of attention deficit hyperactivity disorder (ADHD) (Stasolla et al., 2017). Most importantly, the happiness indices increased in the participants, which points to the fact that their stimulus to learn is likely to grow as well.
The authors replicated the results of their study in the course of the rehabilitation program that involved 72 students as raters. The study outcomes mean that student engagement can be achieved in terms of applying the theory of covert self-evaluation. This study can be regarded as the landmark one since it sets the role of self-management, which is of great importance for every specialist working in this field of endeavor.
Among other methods of token economy that beneficially impacts the behaviors of students with ASD, it is possible to note the effectiveness of break card intervention. Babin, McLaughlin, Derby, Weber, and Cartmell (2016) provide the review of the break card with without token economy use and conclude that various additional strategies can be useful. For example, one of the interventions allowed students to choose a break time at a convenient time, while the other one integrated the token system with the break cards. The authors suggest that the mentioned interventions are beneficial to encourage students with ASD to complete challenging tasks.
In turn, Jessel, Ingvarsson, Whipple, and Kirk (2017) explore the momentary differential reinforcement, such as supervisions and tokens given in case of the successful work completion. The fact that the participant preserved the compliance with the tasks demonstrates the positive impact of such an approach. Even when the number of checks was decreased from one in every 30 seconds to one in every five minutes, the student remained on task.
While the majority of the studies investigate the tangible reinforcement, intangible token economy seems to be lacking appropriate attention. McCurdy and Cole (2014) uncover one of the methods of the intangible token system, presenting the functions of a Class DoJo. This website is designed to specifically meet the needs of children with autism via behavior tools and intangible tokens. This integrated platform allows teachers to look for the relevant tasks based on the positive feedback, which can be implemented in the classroom settings. This decision is consistent with the overall technologic advancement agenda that is declared in the education sector. One may state that more research in the field of intangible tokens is to be conducted to clarify its benefits and challenges.
References
Babin, H., McLaughlin, T. F., Derby, K. M., Weber, K. P., & Cartmell, H. (2016). An examination of a break card intervention with and without a token economy for a child with autism. World Wide Journal of Multidisciplinary Research and Development, 2(1), 1-5.
Carnett, A., Raulston, T., Lang, R., Tostanoski, A., Lee, A., Sigafoos, J., & Machalicek, W. (2014). Effects of a perseverative interest-based token economy on challenging and on-task behavior in a child with autism. Journal of Behavioral Education, 23(3), 368-377.
Davis, T. N., Dacus, S., Bankhead, J., Haupert, M., Fuentes, L., Zoch, T.,& Lang, R. (2014). A comparison of self-monitoring with and without reinforcement to improve on-task classroom behavior. Journal of School Counseling, 12(12), 12-35.
Fiske, K. E., Isenhower, R. W., Bamond, M. J., Delmolino, L., Sloman, K. N., & LaRue, R. H. (2015). Assessing the value of token reinforcement for individuals with autism. Journal of Applied Behavior Analysis, 48(2), 448-453.
Jessel, J., Ingvarsson, E. T., Whipple, R., & Kirk, H. (2017). Increasing ontask behavior of an adolescent with autism using momentary differential reinforcement. Behavioral Interventions, 32(3), 248-254.
McCurdy, E. E., & Cole, C. L. (2014). Use of a peer support intervention for promoting academic engagement of students with autism in general education settings. Journal of Autism and Developmental Disorders, 44(4), 883-893.
Stasolla, F., Caffò, A. O., Perilli, V., Boccasini, A., Damiani, R., Albano, V., & Albano, A. (2017). Comparing self-monitoring and differential reinforcement of an alternative behavior to promote on-task behavior by three children with cerebral palsy: a pilot study. Life Span and Disability, 20(1), 63-92.
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