Other articles in this special issue describe state-of-the-art measurement and instructional methodologies that use the tools of precision teaching and specific strategies that have evolved in its application with particular learner populations. The present author has participated in this work from the early 1970's and can cite examples of successful instruction using these methods with learners that span the range from students suffering from severe developmental disabilities in now-defunct institutions to 21st century corporate training with senior sales executives and customer service personnel. Rather than focusing on one or more populations, or on the specific instructional strategies associated with them, the purpose of this article is two-fold: 1) to describe a framework originally articulated in the 1970's for the evolution of precision teaching and "fluency-based instruction" (Binder, 1978, 1993) that provides a larger context for understanding other contributions in this field, and 2) to illustrate the elements of that framework with examples of measurement and instructional strategies from a range of different populations. Particularly at this time, when many of our colleagues in behavior analysis have not made contact with the work that led to precision teaching, or with early publications that emerged from that work, it seems worthwhile to establish a broader understanding of what precision teaching and its derivatives have brought to our field, and why. A Framework for Evolving Instructional Technology In the late 1960's and early 1970's, precision teaching involved a small and vibrant community of dedicated Skinnerian behavior analysts, led by Ogden Lindsley, Eric Haughton, and a handful of their colleagues and students. Lindsley (1964,1972) was committed to bringing the power of Skinner's "method of free operant conditioning" into the field of education, and this commitment drove the research and development of the time. It was the most pristine translation among behavioral educators and applied behavior analysts of Skinner's methodology and discoveries into education because it preserved without compromise Skinner's sensitive measure of behavior ("response strength"), rate of response or behavior frequency As the impact of measuring response rates in instructional procedures with freely emitted behavior became clear (Lindsley, 1992), precision | teachers saw that discrete trial procedures coupled with percentage correct evaluation had the effect of leaving behind what Skinner (Evans, 1968) and others considered to be his most important contribution. With under the influence of Eric Haughton, who referred to "performance blocks" of various kinds that prevent acceleration of learned behavior, Binder (1978) framed the evolution of instructional methods in precision teaching as a process of removing "ceilings" that obstruct the acceleration of behavior toward useful levels of performance supported by natural contingencies. Four Kinds
本期特刊的其他文章描述了使用精确教学工具的最先进的测量和教学方法，以及在特定学习者群体的应用中发展起来的具体策略。作者从20世纪70年代初就参与了这项工作，他可以举出一些成功的例子，用这些方法对学习者进行指导，从现在已经倒闭的机构中患有严重发育障碍的学生到21世纪的高级销售主管和客户服务人员的企业培训。本文的目的不是关注一个或多个人群，也不是关注与他们相关的具体教学策略，而是有两个方面:1)描述最初在20世纪70年代为精确教学和“基于流利的教学”的演变而提出的框架(Binder, 1978, 1993)，该框架为理解该领域的其他贡献提供了更大的背景;2)用一系列不同人群的测量和教学策略的例子来说明该框架的要素。特别是在这个时候，当我们在行为分析领域的许多同事还没有接触到导致精确教学的工作，或者从这项工作中出现的早期出版物时，似乎有必要建立一个更广泛的理解，即精确教学及其衍生物给我们的领域带来了什么，以及为什么。在20世纪60年代末和70年代初，精确教学涉及到一个由Ogden Lindsley, Eric Haughton以及他们的一些同事和学生领导的专注于斯金纳行为分析的小而充满活力的社区。Lindsley(1964,1972)致力于将斯金纳的“自由操作性条件反射法”的力量引入教育领域，这一承诺推动了当时的研究和发展。这是行为教育者和应用行为分析师对斯金纳的方法论和发现的最原始的翻译，因为它保留了斯金纳对行为的敏感测量(“反应强度”)，反应率或行为频率。随着测量反应率对自由释放行为的教学过程的影响变得清晰起来(Lindsley, 1992)。教师们看到，离散的试验程序加上正确率评估的效果，使斯金纳(Evans, 1968)等人认为是他最重要的贡献。在埃里克·霍顿(Eric Haughton)提到的各种阻碍习得行为加速的“表现障碍”的影响下，宾德(1978)将精确教学中教学方法的演变框定为一个去除阻碍行为加速到由自然偶然因素支持的有用表现水平的“天花板”的过程。阻碍技能发展的四种天花板这四种天花板最初是在20世纪70年代命名的，它提供了一个框架，用于理解在教学环境中使用反应率测量如何导致一种新的教学技术的发展。天花板是:1。测量定义的天花板程序限制(也叫教师限制)赤字上限。当宾德和他的同事在B.H.巴雷特的实验室教室(巴雷特，1977)拆除每一个天花板时，下一个天花板在标准的加速图上显示为一条平坦的数据线，超过这条线学生的表现就不会加速。随着每个天花板的出现，对材料、程序和行为的改变的需求变得清晰起来。本节的其余部分将使用来自不同人群的示例来描述每个上限，以说明推动更有效和高效的性能开发策略演变的基本原则。…
{"title":"Building fluent performance: Measuring response rate and multiplying response opportunities.","authors":"C. Binder","doi":"10.1037/H0100702","DOIUrl":"https://doi.org/10.1037/H0100702","url":null,"abstract":"Other articles in this special issue describe state-of-the-art measurement and instructional methodologies that use the tools of precision teaching and specific strategies that have evolved in its application with particular learner populations. The present author has participated in this work from the early 1970's and can cite examples of successful instruction using these methods with learners that span the range from students suffering from severe developmental disabilities in now-defunct institutions to 21st century corporate training with senior sales executives and customer service personnel. Rather than focusing on one or more populations, or on the specific instructional strategies associated with them, the purpose of this article is two-fold: 1) to describe a framework originally articulated in the 1970's for the evolution of precision teaching and \"fluency-based instruction\" (Binder, 1978, 1993) that provides a larger context for understanding other contributions in this field, and 2) to illustrate the elements of that framework with examples of measurement and instructional strategies from a range of different populations. Particularly at this time, when many of our colleagues in behavior analysis have not made contact with the work that led to precision teaching, or with early publications that emerged from that work, it seems worthwhile to establish a broader understanding of what precision teaching and its derivatives have brought to our field, and why. A Framework for Evolving Instructional Technology In the late 1960's and early 1970's, precision teaching involved a small and vibrant community of dedicated Skinnerian behavior analysts, led by Ogden Lindsley, Eric Haughton, and a handful of their colleagues and students. Lindsley (1964,1972) was committed to bringing the power of Skinner's \"method of free operant conditioning\" into the field of education, and this commitment drove the research and development of the time. It was the most pristine translation among behavioral educators and applied behavior analysts of Skinner's methodology and discoveries into education because it preserved without compromise Skinner's sensitive measure of behavior (\"response strength\"), rate of response or behavior frequency As the impact of measuring response rates in instructional procedures with freely emitted behavior became clear (Lindsley, 1992), precision | teachers saw that discrete trial procedures coupled with percentage correct evaluation had the effect of leaving behind what Skinner (Evans, 1968) and others considered to be his most important contribution. With under the influence of Eric Haughton, who referred to \"performance blocks\" of various kinds that prevent acceleration of learned behavior, Binder (1978) framed the evolution of instructional methods in precision teaching as a process of removing \"ceilings\" that obstruct the acceleration of behavior toward useful levels of performance supported by natural contingencies. Four Kinds","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"11 1","pages":"214-225"},"PeriodicalIF":0.0,"publicationDate":"2010-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58474428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
One of the difficulties faced by instructors of courses on the psychology of learning is to develop laboratory projects that effectively recreate the methods used in actual research. The traditional steady-state research methodology used with pigeons or rats does not readily lend itself to classroom investigation because of the extensive timeframe involved, the difficulty in procuring the necessary equipment, and problems with finding an appropriate housing arrangement for the subjects. Zuriff (2005) recommended that instructors use laboratory exercises that recreate the "golden oldies" of past behavior-analytic research, that is, classic experiments that illustrate basic learning processes. Among the numerous advantages of this approach is that laboratory exercises of this kind can be conducted with commercially available computer simulations of animal behavior if live animals are unavailable (e.g., Graf, 1995; Venneman & Knowles, 2005). The laboratory project described here is intended to help instructors create a laboratory project involving original data collection from live subjects. In brief, human participants are used in lieu of nonhumans. Also, the project does not require extensive investigations of single individuals; rather comparisons can be between-groups. The topic of the laboratory project is stimulus generalization and peak shift, an area that qualifies as both a "golden oldie" (cf. Ghirlanda & Enquist, 2003; Honig & Urcuioli, 1981) and the subject of ongoing research and theory development (e.g., Blanco, Santamaria, Chamizo, & Rodrigo, 2006; Derenne, Breitstein, & Cicha, 2008; Ghirlanda & Enquist, 2007; Lynn, Cnaani, & Papaj, 2005; Martindale, 2006; McLaren & Mackintosh, 2002; Spetch, Cheng, & Clifford, 2004). In the traditional method of measuring stimulus generalization, participants first receive generalization training followed by a generalization test. During training one stimulus (S+) is presented repeatedly and responses in its presence are reinforced. During testing, a variety of related stimuli are shown and stimulus generalization is measured as responses to stimuli other than S+. The graphical depiction of response frequency to each stimulus constitutes a generalization gradient. The generalization gradient is usually symmetrical in shape with the modal response or "peak" of the gradient directed to the S+. If participants receive discrimination training instead, responses to the S+ are reinforced while responses to a second stimulus (S-) are not. This procedure often produces an asymmetrical generalization gradient, with the gradient displaced away from S+ and towards stimuli on the opposite end of the stimulus dimension from S-. Peak shift describes displacement in the modal response; if the mean response is displaced but the modal response is not, then the term area shift may be used (Rilling, 1977). Research on stimulus generalizationn and peak shift has used both humans and nonhumans. When nonhumans are used, the
{"title":"A Computer-Based Laboratory Project for the Study of Stimulus Generalization and Peak Shift.","authors":"A. Derenne, Eevett Loshek","doi":"10.1037/H0100679","DOIUrl":"https://doi.org/10.1037/H0100679","url":null,"abstract":"One of the difficulties faced by instructors of courses on the psychology of learning is to develop laboratory projects that effectively recreate the methods used in actual research. The traditional steady-state research methodology used with pigeons or rats does not readily lend itself to classroom investigation because of the extensive timeframe involved, the difficulty in procuring the necessary equipment, and problems with finding an appropriate housing arrangement for the subjects. Zuriff (2005) recommended that instructors use laboratory exercises that recreate the \"golden oldies\" of past behavior-analytic research, that is, classic experiments that illustrate basic learning processes. Among the numerous advantages of this approach is that laboratory exercises of this kind can be conducted with commercially available computer simulations of animal behavior if live animals are unavailable (e.g., Graf, 1995; Venneman & Knowles, 2005). The laboratory project described here is intended to help instructors create a laboratory project involving original data collection from live subjects. In brief, human participants are used in lieu of nonhumans. Also, the project does not require extensive investigations of single individuals; rather comparisons can be between-groups. The topic of the laboratory project is stimulus generalization and peak shift, an area that qualifies as both a \"golden oldie\" (cf. Ghirlanda & Enquist, 2003; Honig & Urcuioli, 1981) and the subject of ongoing research and theory development (e.g., Blanco, Santamaria, Chamizo, & Rodrigo, 2006; Derenne, Breitstein, & Cicha, 2008; Ghirlanda & Enquist, 2007; Lynn, Cnaani, & Papaj, 2005; Martindale, 2006; McLaren & Mackintosh, 2002; Spetch, Cheng, & Clifford, 2004). In the traditional method of measuring stimulus generalization, participants first receive generalization training followed by a generalization test. During training one stimulus (S+) is presented repeatedly and responses in its presence are reinforced. During testing, a variety of related stimuli are shown and stimulus generalization is measured as responses to stimuli other than S+. The graphical depiction of response frequency to each stimulus constitutes a generalization gradient. The generalization gradient is usually symmetrical in shape with the modal response or \"peak\" of the gradient directed to the S+. If participants receive discrimination training instead, responses to the S+ are reinforced while responses to a second stimulus (S-) are not. This procedure often produces an asymmetrical generalization gradient, with the gradient displaced away from S+ and towards stimuli on the opposite end of the stimulus dimension from S-. Peak shift describes displacement in the modal response; if the mean response is displaced but the modal response is not, then the term area shift may be used (Rilling, 1977). Research on stimulus generalizationn and peak shift has used both humans and nonhumans. When nonhumans are used, the","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"13 1","pages":"391-397"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58473411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is believed that 3 to 5% of children in the United States meet the current diagnostic criteria for attention deficit hyperactivity disorder (ADHD), making it one of the most prevalent disorders in the school-age population (American Psychiatric Association, 2000). A diagnosis of ADHD requires the person to display the disorder's symptoms before the age of 7 and impairments must be manifested in two or more settings (e.g., neighborhood, home, school). Additionally, diagnosed ADHD symptoms must cause significant impairments in academic, social, and occupational functioning, which are not better accounted for by any other disorder. Children and adults who have ADHD display certain degrees of overactivity, impulsivity, and inattention in various situations (Root and Resnick, 2003). Neef, Mace, and Shade (1993) operationally defined impulsivity in basic and applied behavioral research as choices between concurrently available response alternatives that produce smaller reinforcers rather than larger delayed reinforcers. Conversely, self-control is defined as choices that yield relatively greater gains at a later point in time. ADHD, like other disruptive behavior disorders of childhood, is connected with low self-control skills (Strayhorn, 2002). Impulsivity is related to self-control deficiencies, which often involve a failure to think about the consequences of actions. Barkley (1997) suggests that children with ADHD tend to be less able to delay gratification and resist temptations and that the essential concern in ADHD is a deficit involving response inhibition. Neef et al. (2005) showed that the choices of children with ADHD are principally influenced by reinforcer immediacy and quality and least by rate and effort. Previous studies that attempted to increase self-control focused on two types of interventions. The first involved interventions that progressively increased the delay to a larger reinforcer (Dixon & Holcomb, 2000). These authors presented a choice between an immediate smaller reinforcer and a larger delayed reinforcer to two groups of dually diagnosed adults. They showed that this progressive delay increased self-control among the participants. The second type of intervention used to increase self-control extends the previous method of Dixon and Cummings (2001). It involves requiring the participant to be engaged in an activity during his or her wait time. Children were more successful in working for delayed rewards when they were asked to direct their attention away from the intervention (Strayhorn, 2002). Binder, Dixon, and Ghezzi (2000) suggested that the type of activity that the participants engage in was not critical to their ability to demonstrate self-control. The mere requirement of an intervening activity is as effective in decreasing impulsivity as requiring a rule describing the contingencies. Neef et al. (2001) showed that a combination of progressive wait times and concurrent activities in increasing self-control can p
据信，美国有3%到5%的儿童符合目前的注意缺陷多动障碍(ADHD)的诊断标准，使其成为学龄人口中最普遍的疾病之一(美国精神病学协会，2000)。ADHD的诊断要求患者在7岁之前表现出该障碍的症状，并且必须在两个或两个以上的环境中表现出缺陷(例如，社区，家庭，学校)。此外，被诊断为多动症的症状必须在学业、社交和职业功能上造成重大损害，这是其他任何疾病都无法更好地解释的。患有多动症的儿童和成人在各种情况下都会表现出一定程度的过度活跃、冲动和注意力不集中(Root and Resnick, 2003)。Neef, Mace和Shade(1993)在基础和应用行为研究中将冲动性定义为在同时可用的反应选项中做出选择，这些选项产生较小的强化而不是较大的延迟强化。相反，自我控制被定义为在稍后的时间点产生相对更大收益的选择。ADHD和其他儿童破坏性行为障碍一样，与自我控制能力低下有关(Strayhorn, 2002)。冲动与自我控制缺陷有关，这通常涉及到不考虑行为的后果。Barkley(1997)认为ADHD儿童延迟满足和抵制诱惑的能力较差，ADHD的主要问题是反应抑制的缺陷。Neef et al.(2005)表明ADHD儿童的选择主要受强化物的即时性和质量的影响，而受强化物的速度和努力的影响最小。之前试图提高自我控制能力的研究主要集中在两种干预措施上。第一种干预措施是逐步增加对更大强化物的延迟(Dixon & Holcomb, 2000)。这些作者向两组双重诊断的成年人提出了在即时较小的强化物和较大的延迟强化物之间的选择。他们发现，这种渐进式延迟提高了参与者的自制力。第二种用于增强自我控制的干预是对Dixon和Cummings(2001)先前方法的扩展。它要求参与者在他或她的等待时间内从事一项活动。当孩子们被要求将他们的注意力从干预中转移出来时，他们在争取延迟奖励方面更成功(Strayhorn, 2002)。Binder, Dixon和Ghezzi(2000)认为，参与者参与的活动类型对他们展示自我控制的能力并不重要。在减少冲动性方面，仅仅要求一种干预活动与要求一条描述偶然性的规则一样有效。Neef et al.(2001)表明，渐进式等待时间和并发活动在提高自我控制方面的结合可以在未经训练的强化因素维度上产生转移。然而，他们没有提供关于自我控制训练的普遍性或在参与者的典型环境中的效果的信息。本研究的目的是评估在参与者的典型环境中渐进式延迟和渐进式延迟联合并行活动的自我控制训练过程。所有参与者均为居住在治疗性寄养中心的非裔美国男性。理查德(11岁)和鲍勃(10岁)住在宾夕法尼亚州费城的市区，而文森特(14岁)住在费城郊外的郊区。理查德服用Straterra(40毫克/天)治疗多动症。文森特和鲍勃在研究过程中是免费用药的。所有的实验都在参与者的家中或家外的休闲区进行。．..
{"title":"Assessing Self-Control Training in Children with Attention Deficit Hyperactivity Disorder.","authors":"Christopher L. Bloh","doi":"10.1037/H0100676","DOIUrl":"https://doi.org/10.1037/H0100676","url":null,"abstract":"It is believed that 3 to 5% of children in the United States meet the current diagnostic criteria for attention deficit hyperactivity disorder (ADHD), making it one of the most prevalent disorders in the school-age population (American Psychiatric Association, 2000). A diagnosis of ADHD requires the person to display the disorder's symptoms before the age of 7 and impairments must be manifested in two or more settings (e.g., neighborhood, home, school). Additionally, diagnosed ADHD symptoms must cause significant impairments in academic, social, and occupational functioning, which are not better accounted for by any other disorder. Children and adults who have ADHD display certain degrees of overactivity, impulsivity, and inattention in various situations (Root and Resnick, 2003). Neef, Mace, and Shade (1993) operationally defined impulsivity in basic and applied behavioral research as choices between concurrently available response alternatives that produce smaller reinforcers rather than larger delayed reinforcers. Conversely, self-control is defined as choices that yield relatively greater gains at a later point in time. ADHD, like other disruptive behavior disorders of childhood, is connected with low self-control skills (Strayhorn, 2002). Impulsivity is related to self-control deficiencies, which often involve a failure to think about the consequences of actions. Barkley (1997) suggests that children with ADHD tend to be less able to delay gratification and resist temptations and that the essential concern in ADHD is a deficit involving response inhibition. Neef et al. (2005) showed that the choices of children with ADHD are principally influenced by reinforcer immediacy and quality and least by rate and effort. Previous studies that attempted to increase self-control focused on two types of interventions. The first involved interventions that progressively increased the delay to a larger reinforcer (Dixon & Holcomb, 2000). These authors presented a choice between an immediate smaller reinforcer and a larger delayed reinforcer to two groups of dually diagnosed adults. They showed that this progressive delay increased self-control among the participants. The second type of intervention used to increase self-control extends the previous method of Dixon and Cummings (2001). It involves requiring the participant to be engaged in an activity during his or her wait time. Children were more successful in working for delayed rewards when they were asked to direct their attention away from the intervention (Strayhorn, 2002). Binder, Dixon, and Ghezzi (2000) suggested that the type of activity that the participants engage in was not critical to their ability to demonstrate self-control. The mere requirement of an intervening activity is as effective in decreasing impulsivity as requiring a rule describing the contingencies. Neef et al. (2001) showed that a combination of progressive wait times and concurrent activities in increasing self-control can p","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"10 1","pages":"357-363"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58473130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cheryl J. Davis, Michele D. Brock, K. McNulty, Mary L. Rosswurm, B. Bruneau, Thomas Zane
The preferences of individuals with developmental disabilities have been studied since Ferrari and Harris (1981) investigated the reinforcing properties, limits, and motivating potentials of sensory stimuli among children with autism. Over the past twenty-eight years, research has improved preference assessment methods and enabled practitioners to more accurately assess preference. Graff and Ciccone (2002) defined preference assessments as those methods that ... "... effectively identify functional reinforcers for individuals with developmental disabilities" (p. 85). Penrod, Wallace, and Dyer (2008) wrote that "preference assessments produce a relative ranking of stimulus preferences that is based on the relative amount of time with which the stimuli were manipulated or the number of times one stimulus was chosen relative to other stimuli" (p.177). Accurately identifying the preferences of individuals with severe disabilities is essential to their skill acquisition and personal well-being. According to Parsons and Reid (1990), although the need to make choices is essential to one's well-being, persons with developmental disabilities do not receive as many opportunities to make choices when compared to their typical counterparts. The identification of preferred items and activities that may serve as reinforcers for these individuals is critical when developing programming that will be the most effective at increasing desired skills while reducing challenging behaviors. Many different methods have been utilized and developed to assess preference. Variations across methods comprise three major factors : (1) how the stimuli are presented to the individual in order for a preference to be demonstrated, (2) the nature of the stimuli being presented, and (3) whether or not the individual has access to the selected item immediately upon selection. With regard to how stimuli are presented during a preference assessment, there are distinctly different procedures, including parent or caregiver surveys (questionnaires about what the individual likes), single stimulus presentation (when one item is presented at a time and engagement time is measured, Pace, Ivancic, Edwards, Iwata, & Page, 1985), multiple stimulus presentation with or without replacement (an array of items is presented and the participant selects one of the items, which is either replaced or removed from further presentations; e.g., Windsor, Piche, & Locke, 1994), and forced choice presentations (two items are presented at a time, all items are paired against each other as described by Fisher, Piazza, Bowman , Hagopian, Owens, & Slevin, 1992). When considering what type of stimuli are used in these assessments, some researchers have used actual items, while others have used pictures of actual items and/or verbal presentation. Lastly, in some preference studies, researchers have given the individual access to the selected item and other researchers prevented such access. Research has shown there
自法拉利和哈里斯(Ferrari and Harris, 1981)研究自闭症儿童感官刺激的强化特性、限制和激发潜能以来，对发育障碍个体的偏好进行了研究。在过去的28年里，研究改进了偏好评估方法，使从业者能够更准确地评估偏好。Graff和Ciccone(2002)将偏好评估定义为……“…有效地识别发育障碍个体的功能强化因素”(第85页)。Penrod, Wallace和Dyer(2008)写道，“偏好评估产生了刺激偏好的相对排名，这是基于刺激被操纵的相对时间量，或者一个刺激相对于其他刺激被选择的次数”(第177页)。准确识别严重残疾个体的偏好对他们的技能习得和个人福祉至关重要。根据Parsons和Reid(1990)的观点，尽管做出选择的需要对一个人的幸福至关重要，但与典型的同龄人相比，发育性残疾人士没有那么多的机会做出选择。在制定最有效地提高期望技能同时减少挑战性行为的计划时，识别可能作为这些个体强化物的首选项目和活动是至关重要的。许多不同的方法被用来评估偏好。方法之间的差异包括三个主要因素:(1)如何将刺激呈现给个体以证明偏好，(2)所呈现的刺激的性质，以及(3)个体是否在选择后立即获得所选项目。关于在偏好评估过程中如何呈现刺激，有明显不同的程序，包括父母或照顾者调查(关于个人喜好的问卷)，单一刺激呈现(当一次呈现一个项目并测量参与时间，Pace, Ivancic, Edwards, Iwata， & Page, 1985)，有或没有替代的多重刺激呈现(呈现一系列项目，参与者选择其中一个项目)。在以后的演示中被替换或删除;例如，Windsor, Piche， & Locke, 1994)，以及强制选择展示(一次展示两个项目，所有项目相互配对，如Fisher, Piazza, Bowman, Hagopian, Owens， & Slevin, 1992)。当考虑在这些评估中使用什么类型的刺激时，一些研究人员使用实际物品，而另一些研究人员使用实际物品的图片和/或口头陈述。最后，在一些偏好研究中，研究人员允许个人访问所选项目，而其他研究人员阻止这种访问。研究表明，没有最好的方法。Conyers, Doole, Vause, Harapiak, Yu, and Martin (2002);deVries, Yu, Sakko, Wirth, Walters, Marion和Martin (2005);Schwartzman, Yu, and Martin(2003)比较了实际项目、图片和口头强迫选择的呈现方法。这些研究结果表明，评估两项选择的视觉辨别、与样本匹配的视觉辨别和两项选择的听觉-视觉组合辨别等基本辨别技能可用于预测不同呈现方法的有效性。他们得出结论，在偏好评估中使用的刺激模式需要与参与者的辨别技能相匹配。Cohen-Almeida, Graff和Ahearn(2000)比较了使用实际项目的评估和使用口头陈述的评估。两项评估发现，6名参与者中有4人有相似的高偏好项目。．．．
{"title":"Efficiency of Forced Choice Preference Assessment: Comparing Multiple Presentation Techniques.","authors":"Cheryl J. Davis, Michele D. Brock, K. McNulty, Mary L. Rosswurm, B. Bruneau, Thomas Zane","doi":"10.1037/H0100682","DOIUrl":"https://doi.org/10.1037/H0100682","url":null,"abstract":"The preferences of individuals with developmental disabilities have been studied since Ferrari and Harris (1981) investigated the reinforcing properties, limits, and motivating potentials of sensory stimuli among children with autism. Over the past twenty-eight years, research has improved preference assessment methods and enabled practitioners to more accurately assess preference. Graff and Ciccone (2002) defined preference assessments as those methods that ... \"... effectively identify functional reinforcers for individuals with developmental disabilities\" (p. 85). Penrod, Wallace, and Dyer (2008) wrote that \"preference assessments produce a relative ranking of stimulus preferences that is based on the relative amount of time with which the stimuli were manipulated or the number of times one stimulus was chosen relative to other stimuli\" (p.177). Accurately identifying the preferences of individuals with severe disabilities is essential to their skill acquisition and personal well-being. According to Parsons and Reid (1990), although the need to make choices is essential to one's well-being, persons with developmental disabilities do not receive as many opportunities to make choices when compared to their typical counterparts. The identification of preferred items and activities that may serve as reinforcers for these individuals is critical when developing programming that will be the most effective at increasing desired skills while reducing challenging behaviors. Many different methods have been utilized and developed to assess preference. Variations across methods comprise three major factors : (1) how the stimuli are presented to the individual in order for a preference to be demonstrated, (2) the nature of the stimuli being presented, and (3) whether or not the individual has access to the selected item immediately upon selection. With regard to how stimuli are presented during a preference assessment, there are distinctly different procedures, including parent or caregiver surveys (questionnaires about what the individual likes), single stimulus presentation (when one item is presented at a time and engagement time is measured, Pace, Ivancic, Edwards, Iwata, & Page, 1985), multiple stimulus presentation with or without replacement (an array of items is presented and the participant selects one of the items, which is either replaced or removed from further presentations; e.g., Windsor, Piche, & Locke, 1994), and forced choice presentations (two items are presented at a time, all items are paired against each other as described by Fisher, Piazza, Bowman , Hagopian, Owens, & Slevin, 1992). When considering what type of stimuli are used in these assessments, some researchers have used actual items, while others have used pictures of actual items and/or verbal presentation. Lastly, in some preference studies, researchers have given the individual access to the selected item and other researchers prevented such access. Research has shown there","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"10 1","pages":"440-455"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58473500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Operant conditioning represents a unique data language that describes the lawfulness of behavior as derived from the cumulative record over time of consistent correlations between the universally observed or 'public' form or topography of behavior and its consequences. Operant conditioning procedures are based upon methodological principles, wherein reliable behavioral consistencies or 'laws' are derived using a data language that precisely maps to the universally agreed upon facts of behavior. As a form of methodological behaviorism (Pavlovian or classical conditioning is another example), the experimental methodology of operant conditioning directly measures and manipulates only publicly observable behavior. Grasping, walking, talking, etc. are operant behaviors because they are correlated with or are 'reinforced' by specific discrete outcomes. Because these behaviors uniformly engage a specific organelle of the body, namely the striated musculature, a common presumption is that operant conditioning primarily reflects the conditioning of these muscles. Of course, convulsions, startle reactions, etc. do involve the striated musculature and can be mediated by neurological rather than purely cognitive causes, but in general muscular activity is guided by its functionality as consciously perceived. It is commonly assumed that if striated muscles are activated, they are publically observed, and hence may be subsumed entire under an operant analysis. Yet only a fraction of striated muscular activity is observable publicly or privately. That is, the musculature may be activated yet not result in publicly observable responses, and neither may it be consciously or privately perceived by the individual. Ironically, the private activity of the musculature has long been made public through resolving instrumentalities (e.g., SCR, EMG) but rarely if ever has an operant analysis been employed to explain this behavior. Rather, tension has generally been construed to be an artifact of autonomic arousal that is elicited due to psycho-social 'demand'. This interpretation regards muscular tension as subsumed under different motivational principles that do not incorporate contingency, such as the reflexive or S-R responses entailed by a fight or flight response, stress reaction, etc. (Marmot & Wilkinson, 2006). In this case, inferred mediating processes take the place of observed correlations between behavior and environmental events. However, this conclusion may remain uncontested not because the relationship between tension and its governing contingencies is disproven, or because the relevant data are unobtainable, but because of a common misinterpretation of the semantics of 'demand'. The purpose of this article is to argue that the same data and data language used to establish the concept that tension is reflexive or is a respondent can be reinterpreted to unequivocally demonstrate that muscular tension is an instrumental or operant behavior. The Striated Muscu
{"title":"Muscular tension: An explanation from a methodological behaviorism.","authors":"Arthur J. Marr","doi":"10.1037/H0100677","DOIUrl":"https://doi.org/10.1037/H0100677","url":null,"abstract":"Operant conditioning represents a unique data language that describes the lawfulness of behavior as derived from the cumulative record over time of consistent correlations between the universally observed or 'public' form or topography of behavior and its consequences. Operant conditioning procedures are based upon methodological principles, wherein reliable behavioral consistencies or 'laws' are derived using a data language that precisely maps to the universally agreed upon facts of behavior. As a form of methodological behaviorism (Pavlovian or classical conditioning is another example), the experimental methodology of operant conditioning directly measures and manipulates only publicly observable behavior. Grasping, walking, talking, etc. are operant behaviors because they are correlated with or are 'reinforced' by specific discrete outcomes. Because these behaviors uniformly engage a specific organelle of the body, namely the striated musculature, a common presumption is that operant conditioning primarily reflects the conditioning of these muscles. Of course, convulsions, startle reactions, etc. do involve the striated musculature and can be mediated by neurological rather than purely cognitive causes, but in general muscular activity is guided by its functionality as consciously perceived. It is commonly assumed that if striated muscles are activated, they are publically observed, and hence may be subsumed entire under an operant analysis. Yet only a fraction of striated muscular activity is observable publicly or privately. That is, the musculature may be activated yet not result in publicly observable responses, and neither may it be consciously or privately perceived by the individual. Ironically, the private activity of the musculature has long been made public through resolving instrumentalities (e.g., SCR, EMG) but rarely if ever has an operant analysis been employed to explain this behavior. Rather, tension has generally been construed to be an artifact of autonomic arousal that is elicited due to psycho-social 'demand'. This interpretation regards muscular tension as subsumed under different motivational principles that do not incorporate contingency, such as the reflexive or S-R responses entailed by a fight or flight response, stress reaction, etc. (Marmot & Wilkinson, 2006). In this case, inferred mediating processes take the place of observed correlations between behavior and environmental events. However, this conclusion may remain uncontested not because the relationship between tension and its governing contingencies is disproven, or because the relevant data are unobtainable, but because of a common misinterpretation of the semantics of 'demand'. The purpose of this article is to argue that the same data and data language used to establish the concept that tension is reflexive or is a respondent can be reinterpreted to unequivocally demonstrate that muscular tension is an instrumental or operant behavior. The Striated Muscu","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"35 1","pages":"364-380"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58473222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Teaching techniques based on behavior analysis have been available for over 50 years as for example Skinner discussed the strategies for teaching in the classroom (Skinner, 1954). Later techniques such as programmed instruction (Holland & Skinner, 1961), precision teaching (Lindsley, 1964), direct instruction (Engelmann & Carnine, 1982), and PSI or the Keller-plan (Keller, 1968) have been used. However, there has been a decline in the use of such procedures (Lamal, 1984). Some years ago a type of strategy of peer learning or interteaching was described in the behavior analytic literature (Boyce & Hineline, 2002) as ".... mutually probing, mutually informing conversation between two people" (Boyce & Hineline, 2002p. 220). Interteaching is based on principles from the different strategies mentioned above and the main points are: (1) Students have to read the text beforehand, (2) Questions from the text are prepared by the instructor, (3) Students discuss the questions in pairs for 30-45 min, (4) An interteach record is filled out by the students whereby they write down the questions that are difficult, and (5) The instructor prepares a lecture based on the interteach records. Three studies have shown that interteaching is more effective than traditional instructions at improving students learning outcome (Saville & Zinn, 2006, 2009; Saville, Zinn, & Elliot, 2005). Saville et al. (2005) found that students did better on quizzes after interteaching than traditional lectures, reading alone or control. Saville and Zinn (2006) also found that after interteaching students did better on the exams and that students preferred interteaching. However, there have been relatively few reports on the effect of interteaching, so the purpose of the current study was to expand the knowledge by comparing the effect of interteaching with traditional lectures in a group of undergraduate students. Method Participants Sixty-nine undergraduate students from two different classes participated in the current study. Two-thirds of the participants were females and the average age for the whole group of participants was 30 years. The participants were students studying on a bachelor program in social welfare. They were recruited through ads in the class. The classes were not mandatory. Design A pre- post-test design was used. One group of the participants was exposed to interteaching as the first condition and traditional lectures as the second condition. The other group was exposed to the conditions in the reversed order. Procedure Traditional lectures. The lectures were based on previously known learning objectives. The students had the curriculum and some recommended texts. Each lecture lasted for approximately 3-4 hours with 15 minutes breaks. The second author was the instructor Interteaching. The sequence started with a short introductory lecture, maximum 45 minutes, followed by an interteaching sequence of 1-2 hours and finally a lecture of 45 minutes based on the resul
{"title":"On the Effectiveness of Interteaching.","authors":"E. Arntzen, Kari Høium","doi":"10.1037/H0100698","DOIUrl":"https://doi.org/10.1037/H0100698","url":null,"abstract":"Teaching techniques based on behavior analysis have been available for over 50 years as for example Skinner discussed the strategies for teaching in the classroom (Skinner, 1954). Later techniques such as programmed instruction (Holland & Skinner, 1961), precision teaching (Lindsley, 1964), direct instruction (Engelmann & Carnine, 1982), and PSI or the Keller-plan (Keller, 1968) have been used. However, there has been a decline in the use of such procedures (Lamal, 1984). Some years ago a type of strategy of peer learning or interteaching was described in the behavior analytic literature (Boyce & Hineline, 2002) as \".... mutually probing, mutually informing conversation between two people\" (Boyce & Hineline, 2002p. 220). Interteaching is based on principles from the different strategies mentioned above and the main points are: (1) Students have to read the text beforehand, (2) Questions from the text are prepared by the instructor, (3) Students discuss the questions in pairs for 30-45 min, (4) An interteach record is filled out by the students whereby they write down the questions that are difficult, and (5) The instructor prepares a lecture based on the interteach records. Three studies have shown that interteaching is more effective than traditional instructions at improving students learning outcome (Saville & Zinn, 2006, 2009; Saville, Zinn, & Elliot, 2005). Saville et al. (2005) found that students did better on quizzes after interteaching than traditional lectures, reading alone or control. Saville and Zinn (2006) also found that after interteaching students did better on the exams and that students preferred interteaching. However, there have been relatively few reports on the effect of interteaching, so the purpose of the current study was to expand the knowledge by comparing the effect of interteaching with traditional lectures in a group of undergraduate students. Method Participants Sixty-nine undergraduate students from two different classes participated in the current study. Two-thirds of the participants were females and the average age for the whole group of participants was 30 years. The participants were students studying on a bachelor program in social welfare. They were recruited through ads in the class. The classes were not mandatory. Design A pre- post-test design was used. One group of the participants was exposed to interteaching as the first condition and traditional lectures as the second condition. The other group was exposed to the conditions in the reversed order. Procedure Traditional lectures. The lectures were based on previously known learning objectives. The students had the curriculum and some recommended texts. Each lecture lasted for approximately 3-4 hours with 15 minutes breaks. The second author was the instructor Interteaching. The sequence started with a short introductory lecture, maximum 45 minutes, followed by an interteaching sequence of 1-2 hours and finally a lecture of 45 minutes based on the resul","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"11 1","pages":"155-160"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58474410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Weiss, Eliza Delpizzo-Cheng, R. LaRue, Kimberly N. Sloman
Parents of children with autism, as well as numerous practitioners, are bombarded with potential treatment options for the individuals for whom they care. These treatments include biological interventions, such as psychotropic medications, specialized diets, and highly experimental procedures, such as chelation or hyperbaric oxygen therapy. In addition, several non-biological interventions have emerged that have little or no empirical support. Examples of these include Relationship Development Interventions and DIR/Floortime (Greenspan, 1992; Greenspan & Wieder, 1998; Wieder & Greenspan, 2001) and facilitated communication (e.g., Eberlin, McConnachie, Ibel, & Volpe, 1993; Simpson & Myles, 1994). The majority of parents of children with autism pursue a combination of medical and educational treatments. Most individuals with autism receive some combination of empirically verified and experimental treatments. The intervention with the most support is Applied Behavior Analysis (ABA; e.g., Matson, Bernavidez, Compton, Paclawskyj, & Baglio, 1996; New York State Department of Health, 1999; Rosenwasser & Axelrod, 2001). ABA has been recognized by the Surgeon General of the United States as the treatment of choice for autism in the mental health report for children: "Thirty years of research demonstrated the efficacy of applied behavioral methods in reducing inappropriate behavior and in increasing communication, learning, and appropriate social behavior" (U.S. Department of Health and Human Services, 1999). However, even within the discipline of ABA, there is confusion about definitions of terms and about approaches to the intervention process. This paper will explore the emergence of two disciplines within the field of behavioral intervention, both of which have considerable empirical support: Applied Behavior Analysis (ABA) and Positive Behavior Support (PBS). PBS is generally considered to be an extension of ABA. However, in recent years, practitioners have fought over the current status of PBS. While some people consider PBS to be an extension of ABA, others consider PBS to be a separate science. While theorists squabbling about the current status of PBS may not be of interest to most consumers or practitioners, there are potential dangerous consequences of having a fractured discipline. These include rampant consumer confusion, divisiveness within the professional community, and dilution of the strength of the field in advancing broader goals. What follows is a brief discussion of ABA and PBS, a discussion about what these disciplines have in common, why the divergence of the science may be problematic, and suggestions for how to address these issues. Applied Behavior Analysis Behavior analysis is a field in psychology dedicated to the study of behavior and the natural events and causes of behavior. Behavior analysis differs from other areas of psychology in that behavior is the subject matter, rather than an index of some underlying cause or state
{"title":"ABA and PBS: The Dangers in Creating Artificial Dichotomies in Behavioral Intervention.","authors":"M. Weiss, Eliza Delpizzo-Cheng, R. LaRue, Kimberly N. Sloman","doi":"10.1037/H0100681","DOIUrl":"https://doi.org/10.1037/H0100681","url":null,"abstract":"Parents of children with autism, as well as numerous practitioners, are bombarded with potential treatment options for the individuals for whom they care. These treatments include biological interventions, such as psychotropic medications, specialized diets, and highly experimental procedures, such as chelation or hyperbaric oxygen therapy. In addition, several non-biological interventions have emerged that have little or no empirical support. Examples of these include Relationship Development Interventions and DIR/Floortime (Greenspan, 1992; Greenspan & Wieder, 1998; Wieder & Greenspan, 2001) and facilitated communication (e.g., Eberlin, McConnachie, Ibel, & Volpe, 1993; Simpson & Myles, 1994). The majority of parents of children with autism pursue a combination of medical and educational treatments. Most individuals with autism receive some combination of empirically verified and experimental treatments. The intervention with the most support is Applied Behavior Analysis (ABA; e.g., Matson, Bernavidez, Compton, Paclawskyj, & Baglio, 1996; New York State Department of Health, 1999; Rosenwasser & Axelrod, 2001). ABA has been recognized by the Surgeon General of the United States as the treatment of choice for autism in the mental health report for children: \"Thirty years of research demonstrated the efficacy of applied behavioral methods in reducing inappropriate behavior and in increasing communication, learning, and appropriate social behavior\" (U.S. Department of Health and Human Services, 1999). However, even within the discipline of ABA, there is confusion about definitions of terms and about approaches to the intervention process. This paper will explore the emergence of two disciplines within the field of behavioral intervention, both of which have considerable empirical support: Applied Behavior Analysis (ABA) and Positive Behavior Support (PBS). PBS is generally considered to be an extension of ABA. However, in recent years, practitioners have fought over the current status of PBS. While some people consider PBS to be an extension of ABA, others consider PBS to be a separate science. While theorists squabbling about the current status of PBS may not be of interest to most consumers or practitioners, there are potential dangerous consequences of having a fractured discipline. These include rampant consumer confusion, divisiveness within the professional community, and dilution of the strength of the field in advancing broader goals. What follows is a brief discussion of ABA and PBS, a discussion about what these disciplines have in common, why the divergence of the science may be problematic, and suggestions for how to address these issues. Applied Behavior Analysis Behavior analysis is a field in psychology dedicated to the study of behavior and the natural events and causes of behavior. Behavior analysis differs from other areas of psychology in that behavior is the subject matter, rather than an index of some underlying cause or state ","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"10 1","pages":"428-439"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58473483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A note about the interviews from the editors: The use of Skinner's Verbal Behavior (VB) classification system has been increasingly applied to learners with autism. We asked several of the best known behavior analysts to answer some key questions regarding this practice, the state of research regarding the advantages of this approach, and the confusion that exists regarding the application of VB to this population of learners. We structured the responses to follow each question separately, indicating the responder in each case. At the end of the interviews, you will find relevant references from each responder. We are very grateful to Dr. Mark Sundberg, Dr. Barbara Esch, Dr. John Esch, and Dr. Andrew Bondy for their thoughtful and wise replies. 1. Can you briefly explain the relevance of Skinner's analysis of verbal behavior to intervention for children with autism? Bondy Skinner's analysis provides a guide for teachers and professionals, as well as parents, to determine factors that relate to the control of language. When we teach any skill, I must know the controlling conditions currently in place- where we are now- and the controlling conditions I aim for by the end of the lesson- where we are going. Skinner reminds us to always consider the ABCs of behavior and not to become 'blinded' by the behavior in isolation. Esch and Esch First, it's important to recognize that the advantages of Skinner's analysis of verbal behavior (1957) aren't limited to just those individuals with a diagnosis of autism. The analysis is widely applicable to any language behavior, whether typical or atypical, developmentally appropriate or developmentally delayed, regardless of age, diagnosis, or etiology of condition. Skinner's analysis made it clear that language responses occur, not in isolation, but within a context of ongoing environmental events (i.e., antecedents and consequences). Responses that occur within particular contexts are said to have different functions. As Iwata and colleagues (1982/1994; also see Hanley, Iwata, & McCord, 2003; Lerman et al., 2005) and many other researchers (see Sautter & LeBlanc for a review, 2006) have shown, a functional analysis of behavior is critical to informing intervention. If responses are weak, wrong, or otherwise somehow deficient, an analysis of the contexts in which they occur can help us determine what to do. That is, we can identify the stimuli that currently evoke and maintain behavior (or those that currently fail to do so) and we can compare this information to the stimuli that should control these, or other, responses that we want to develop. Then we can use behavioral procedures (e.g., prompting, fading, differential reinforcement) to eliminate errors by establishing desired language skills (or other skills) under appropriate stimulus control. Without this analysis, we run the risk of recommending interventions that may be ineffective at best, or detrimental at worst. For children with a diagnosis of autism, S
{"title":"Questions on verbal behavior and its application to individuals with autism: An interview with the experts.","authors":"A. Bondy, Barbara E. Esch, J. Esch, M. Sundberg","doi":"10.1037/H0100700","DOIUrl":"https://doi.org/10.1037/H0100700","url":null,"abstract":"A note about the interviews from the editors: The use of Skinner's Verbal Behavior (VB) classification system has been increasingly applied to learners with autism. We asked several of the best known behavior analysts to answer some key questions regarding this practice, the state of research regarding the advantages of this approach, and the confusion that exists regarding the application of VB to this population of learners. We structured the responses to follow each question separately, indicating the responder in each case. At the end of the interviews, you will find relevant references from each responder. We are very grateful to Dr. Mark Sundberg, Dr. Barbara Esch, Dr. John Esch, and Dr. Andrew Bondy for their thoughtful and wise replies. 1. Can you briefly explain the relevance of Skinner's analysis of verbal behavior to intervention for children with autism? Bondy Skinner's analysis provides a guide for teachers and professionals, as well as parents, to determine factors that relate to the control of language. When we teach any skill, I must know the controlling conditions currently in place- where we are now- and the controlling conditions I aim for by the end of the lesson- where we are going. Skinner reminds us to always consider the ABCs of behavior and not to become 'blinded' by the behavior in isolation. Esch and Esch First, it's important to recognize that the advantages of Skinner's analysis of verbal behavior (1957) aren't limited to just those individuals with a diagnosis of autism. The analysis is widely applicable to any language behavior, whether typical or atypical, developmentally appropriate or developmentally delayed, regardless of age, diagnosis, or etiology of condition. Skinner's analysis made it clear that language responses occur, not in isolation, but within a context of ongoing environmental events (i.e., antecedents and consequences). Responses that occur within particular contexts are said to have different functions. As Iwata and colleagues (1982/1994; also see Hanley, Iwata, & McCord, 2003; Lerman et al., 2005) and many other researchers (see Sautter & LeBlanc for a review, 2006) have shown, a functional analysis of behavior is critical to informing intervention. If responses are weak, wrong, or otherwise somehow deficient, an analysis of the contexts in which they occur can help us determine what to do. That is, we can identify the stimuli that currently evoke and maintain behavior (or those that currently fail to do so) and we can compare this information to the stimuli that should control these, or other, responses that we want to develop. Then we can use behavioral procedures (e.g., prompting, fading, differential reinforcement) to eliminate errors by establishing desired language skills (or other skills) under appropriate stimulus control. Without this analysis, we run the risk of recommending interventions that may be ineffective at best, or detrimental at worst. For children with a diagnosis of autism, S","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"11 1","pages":"186-205"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58474419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The active treatment ingredient in any operant-based behavior change procedure is the provision of some form of consequence made contingent upon a target response (see Skinner, 1953; 1957). Whether in the form of an edible, a praise statement, or the simple provision of data regarding one's performance, the science of operant behavior dictates that this consequential feedback will impact future instances of behavior in some capacity--either increasing or decreasing the likelihood that this behavior is emitted again in the future. Moreover, this notion is echoes that of Skinner's eloquently worded description in Science and Human Behavior (1953, pg. 59), that "The consequences of behavior may "feed back" into the organism. When they do so, they may change the probability that the behavior which produced them will occur again." Perhaps more importantly, the scheduling of such consequential feedback has proven to be paramount in the kinds of behavioral patterns subsequently observed (see Ferster & Skinner, 1957). Whether by design or act of nature, feedback schedules--similar to other consequential schedules, such as reinforcement or punishment--come as either interval- or ratio-based forms. Intervalbased schedules deliver feedback contingent upon the first occurrence of some target response after some pre-specified passage of time (e.g., a child reinforced for his/her first correct response after 5-min). However, ratio-based schedules dictate that the target response must occur a pre-specified number of times before it is provided feedback. (e.g., a child is reinforced after he/she emits five correct responses). As such, interval-based schedules typically produce lower response rates, relative to ratio-based schedules (see Ferster & Skinner, 1957). This is in part due to the fact that during ratio-based schedules, the responding organism is to some extent able to govern the rate of feedback through his/her own behavior since the feedback is directly contingent upon response rate. In addition, all feedback schedules, whether interval- or ratio-based, feature an additional requirement characteristic. Namely, as either being fixed (i.e., after a static number of required responses; e.g., a child is reinforced after every fifth correct response) or variable (i.e., after a dynamic number of required responses which averages to some specified value; e.g., on average, a child's behavior is reinforced for approximately every five correct responses) contingencies. Like interval- and ratio-schedules, fixed- and variable-schedules have specific behavioral patterns associated with their schedule type. Specifically, fixed-schedules tend to produce pauses in responding after the delivery of feedback, while variable-schedules tend to produce steady response rates despite instances of feedback delivery (see Ferster & Skinner, 1957). This phenomenon likely occurs because organisms may more accurately predict feedback delivery in fixed-schedules, but remain persiste
{"title":"Generating Randomized Schedules for Direct Observations in Microsoft[R] Office Excel[R]","authors":"Richard L. Azulay, Derek D. Reed","doi":"10.1037/H0100675","DOIUrl":"https://doi.org/10.1037/H0100675","url":null,"abstract":"The active treatment ingredient in any operant-based behavior change procedure is the provision of some form of consequence made contingent upon a target response (see Skinner, 1953; 1957). Whether in the form of an edible, a praise statement, or the simple provision of data regarding one's performance, the science of operant behavior dictates that this consequential feedback will impact future instances of behavior in some capacity--either increasing or decreasing the likelihood that this behavior is emitted again in the future. Moreover, this notion is echoes that of Skinner's eloquently worded description in Science and Human Behavior (1953, pg. 59), that \"The consequences of behavior may \"feed back\" into the organism. When they do so, they may change the probability that the behavior which produced them will occur again.\" Perhaps more importantly, the scheduling of such consequential feedback has proven to be paramount in the kinds of behavioral patterns subsequently observed (see Ferster & Skinner, 1957). Whether by design or act of nature, feedback schedules--similar to other consequential schedules, such as reinforcement or punishment--come as either interval- or ratio-based forms. Intervalbased schedules deliver feedback contingent upon the first occurrence of some target response after some pre-specified passage of time (e.g., a child reinforced for his/her first correct response after 5-min). However, ratio-based schedules dictate that the target response must occur a pre-specified number of times before it is provided feedback. (e.g., a child is reinforced after he/she emits five correct responses). As such, interval-based schedules typically produce lower response rates, relative to ratio-based schedules (see Ferster & Skinner, 1957). This is in part due to the fact that during ratio-based schedules, the responding organism is to some extent able to govern the rate of feedback through his/her own behavior since the feedback is directly contingent upon response rate. In addition, all feedback schedules, whether interval- or ratio-based, feature an additional requirement characteristic. Namely, as either being fixed (i.e., after a static number of required responses; e.g., a child is reinforced after every fifth correct response) or variable (i.e., after a dynamic number of required responses which averages to some specified value; e.g., on average, a child's behavior is reinforced for approximately every five correct responses) contingencies. Like interval- and ratio-schedules, fixed- and variable-schedules have specific behavioral patterns associated with their schedule type. Specifically, fixed-schedules tend to produce pauses in responding after the delivery of feedback, while variable-schedules tend to produce steady response rates despite instances of feedback delivery (see Ferster & Skinner, 1957). This phenomenon likely occurs because organisms may more accurately predict feedback delivery in fixed-schedules, but remain persiste","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"34 1","pages":"349-356"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58473048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction In educational settings, it is desired that all students know the value of knowledge and skills and are intrinsically motivated to learn, but it is rarely the case. Therefore, teachers in school settings often have to employ extrinsic reinforcers to motivate students to learn. After the frequent use of reinforcement on good school performance, it can be expected that the act of learning will become a conditioned response, and after the teacher applies intermittent reinforcement or the student acquires natural consequence of success in education or carrier, it is hoped that the learning can become intrinsically motivated with less extrinsic reinforcement. Reinforcement can be classified into four kinds: (a) positive reinforcement (giving positive reinforcer), (b) punishment (giving negative reinforcer), (c) punishment (withdrawing positive reinforcer), and (d) negative reinforcement (withdrawing negative reinforcer). The present study concentrated mostly on the comparison of the effectiveness of positive reinforcers including edible foods, tangible objects, activities, and tokens. Less attention is paid to the effectiveness of negative (aversive) reinforcers, but the mean effect sizes of punishment were presented for the purpose of comparison. There have been many studies reporting success in the use of primary reinforcers to modify the behavior of participants (e.g., Forness, Kavale, Blum, and Lloyd, 1997; Kern, Ringdahl, Hilt, and Sterling-Turner, 2001; Osborne, 1969; and Williams, Koegel, and Egel, 1981). Cameron and Pierce (1994) conducted a meta-analysis to address the issue of whether extrinsic reinforcement is harmful to the intrinsic motivation and found that rewards given for task completion or for quality of performance are not detrimental to intrinsic motivation. According to the principle of behavior modification, in order to expect a desirable behavior to happen in the future, three conditions must be fulfilled as follows: a discriminative stimulus must be present; there must be a contingency for reinforcement of the target behavior, and the reinforcer must be able to satisfy the need of the individual. Researchers in behavior analysis have paid more attention to the third condition recently. Neef and Lutz (2001) found that the effect of more preferred reinforcers was higher than that of less preferred reinforcers. The results of Pace, Ivancic, Edwards, Iwata, and Page's (1985) study confirmed that the success of reinforcement depends on the selection of suitable reinforcement schedules and contingencies. Glynn (1970) found that the effect of self-determined and experimenter-determined token intervention on the learning of history and geography material was superior to that of chance-determined and no-token interventions. It may be alternatively hypothesized that the effect size of an intervention would be larger when the reinforcer can better meet the needs of the participant and serve as a mechanism to increase his or h
在教育环境中，人们希望所有的学生都知道知识和技能的价值，并有内在的动力去学习，但这种情况很少发生。因此，教师在学校设置往往不得不采用外部强化激励学生学习。在对良好学习表现进行频繁强化后，可以预期学习行为将成为条件反应，在教师进行间歇性强化或学生获得教育成功或载体的自然结果后，希望学习成为内在动机，减少外在强化。强化可分为四种:(a)正强化(给予正强化)，(b)惩罚(给予负强化)，(c)惩罚(撤回正强化)，(d)负强化(撤回负强化)。本研究主要集中在食用食物、有形物品、活动和标记物等正向强化物的有效性比较上。对负强化(厌恶强化)的有效性关注较少，但为了进行比较，我们给出了惩罚的平均效应量。有许多研究报告成功地使用初级强化物来改变参与者的行为(例如，Forness, Kavale, Blum, and Lloyd, 1997;Kern, Ringdahl, Hilt, and Sterling-Turner, 2001;奥斯本1969;和Williams, Koegel, and Egel, 1981)。Cameron和Pierce(1994)进行了一项元分析，以解决外部强化是否对内在动机有害的问题，并发现对任务完成或绩效质量的奖励对内在动机并不有害。根据行为修正原理，为了期望未来发生理想的行为，必须满足以下三个条件:必须存在判别刺激;目标行为的强化必须有偶然性，强化者必须能够满足个体的需要。最近，行为分析的研究者们更加关注第三种情况。Neef和Lutz(2001)发现偏好强化物较多的效应高于偏好强化物较少的效应。Pace、Ivancic、Edwards、Iwata和Page(1985)的研究结果证实，强化的成功取决于选择合适的强化计划和偶发性。Glynn(1970)发现，自我决定的和实验者决定的象征性干预对历史地理资料学习的效果优于机会决定的和无象征性干预。另一种假设是，当强化物能够更好地满足被试的需求，并作为一种增加被试动机的机制时，干预的效应量就会更大。用于衡量不同强化剂有效性的工具是超过基线阶段(PEM)方法中位数的数据点百分比(Ma, 2006)。迄今为止，最广泛使用的测量单例实验设计效应大小的方法是由马斯特罗皮里和斯克鲁格斯(1985-1986)提出的非重叠数据百分比(PND)方法。PEM方法的优缺点及其相对于PND方法的优越性已经被Ma(2006)讨论过，并得到Gao和Ma(2006)的经验证实;陈、马(2007);Ma(2009)和Preston and Carter(2009)。因此，决定采用PEM方法来比较行为矫正领域中使用的不同强化物的相对有效性。通过计算机辅助检索相关数据库，包括EBSCOhost、ERIC和ProQuest，获得本综合研究中分析的强化剂影响的单例实验研究。．..
{"title":"Comparison of the Relative Effectiveness of Different Kinds of Reinforcers: A PEM Approach.","authors":"Hsen-Hsing Ma","doi":"10.1037/H0100680","DOIUrl":"https://doi.org/10.1037/H0100680","url":null,"abstract":"Introduction In educational settings, it is desired that all students know the value of knowledge and skills and are intrinsically motivated to learn, but it is rarely the case. Therefore, teachers in school settings often have to employ extrinsic reinforcers to motivate students to learn. After the frequent use of reinforcement on good school performance, it can be expected that the act of learning will become a conditioned response, and after the teacher applies intermittent reinforcement or the student acquires natural consequence of success in education or carrier, it is hoped that the learning can become intrinsically motivated with less extrinsic reinforcement. Reinforcement can be classified into four kinds: (a) positive reinforcement (giving positive reinforcer), (b) punishment (giving negative reinforcer), (c) punishment (withdrawing positive reinforcer), and (d) negative reinforcement (withdrawing negative reinforcer). The present study concentrated mostly on the comparison of the effectiveness of positive reinforcers including edible foods, tangible objects, activities, and tokens. Less attention is paid to the effectiveness of negative (aversive) reinforcers, but the mean effect sizes of punishment were presented for the purpose of comparison. There have been many studies reporting success in the use of primary reinforcers to modify the behavior of participants (e.g., Forness, Kavale, Blum, and Lloyd, 1997; Kern, Ringdahl, Hilt, and Sterling-Turner, 2001; Osborne, 1969; and Williams, Koegel, and Egel, 1981). Cameron and Pierce (1994) conducted a meta-analysis to address the issue of whether extrinsic reinforcement is harmful to the intrinsic motivation and found that rewards given for task completion or for quality of performance are not detrimental to intrinsic motivation. According to the principle of behavior modification, in order to expect a desirable behavior to happen in the future, three conditions must be fulfilled as follows: a discriminative stimulus must be present; there must be a contingency for reinforcement of the target behavior, and the reinforcer must be able to satisfy the need of the individual. Researchers in behavior analysis have paid more attention to the third condition recently. Neef and Lutz (2001) found that the effect of more preferred reinforcers was higher than that of less preferred reinforcers. The results of Pace, Ivancic, Edwards, Iwata, and Page's (1985) study confirmed that the success of reinforcement depends on the selection of suitable reinforcement schedules and contingencies. Glynn (1970) found that the effect of self-determined and experimenter-determined token intervention on the learning of history and geography material was superior to that of chance-determined and no-token interventions. It may be alternatively hypothesized that the effect size of an intervention would be larger when the reinforcer can better meet the needs of the participant and serve as a mechanism to increase his or h","PeriodicalId":88717,"journal":{"name":"The behavior analyst today","volume":"10 1","pages":"398-427"},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58473438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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