A token point economy was established at a residential facility for adolescent boys adjudicated either pre-delinquent or delinquent. Points were awarded for positive target behaviors and points subtracted from target behaviors defined as negative. Points earned could be exchanged for such bac1up reinforcers as off-campus activities, snacks, telephone calls, etc. Results indicated a vast improvement on contingent behaviors such as fighting, foul language, destruction of property, behavior in the classroom, and cottages. In addition, there was an indication of improvement in more global areas such as attitudes and communication. The overall running of the residential program appeared smoother. The token point economy facilitated an improvement of the more traditional types of ongoing therapy. It offered a common reference point of what was expected of the resident's behavior.

Thesis (M.A.)--West Virginia University, 1999. / Title from document title page. Document formatted into pages; contains [vi], 101 p. : ill. (some col.) Includes abstract. Includes bibliographical references (p. 54-64).

Thesis (M.S.)--University of North Texas, Dec., 2008. / Title from title page display. Includes bibliographical references.

Theses (Ed.S.)--Marshall University, 2002. / Title from document title page. Includes abstract. Document formatted into pages: contains v, 37 p. Bibliography: p. 28-33.

abstract: ABSTRACT The purpose of this study was to investigate the effects of E Bucks, a simulated classroom economy (a token economy system), in business classes on students' grades, absences, and tardiness. The study compared these variables in classes using E Bucks to those in similar classes before E Bucks was initiated. The following research questions were addressed: (a) How did the mean term grades in business classes that included E Bucks compare to those in similar classes prior to the E Bucks implementation? (b) How did the mean number of student absences in business classes that included E Bucks compare to those in similar classes prior to the E Bucks implementation? (c) How did the mean number of student tardies in business classes that included E Bucks compare to those in similar classes prior to the E Bucks implementation? Four teachers in 3 high schools in Phoenix, Arizona, participated in the study that included 22 sections of business classes with a total of 568 students. All participating teachers implemented the token economy voluntarily, although some implemented the program more consistently than others. All of the teachers administered district-aligned assessments with the same terms/occasions throughout the district. Archival data (term grades, attendance, and tardies) from 3 years of business, technology, and marketing courses were collected and analyzed. The results of 4 analyses of variance examining the dependent variables of grades, absences, and tardies were mixed. The results demonstrated significance for some but not all of the teachers' classes on all 3 dependent variables. In 1 of the 4 analyses 2 teachers had approached significant increases in grades when students were "paid" for grades. The same two teachers had nonsignificant decreases in the mean number of student absences during the grading period students were "paid" for grades. Recommendations included studying a larger number of students and measuring the impact of gender and socioeconomic status on the effects of the E Bucks simulation. / Dissertation/Thesis / Ed.D. Educational Leadership and Policy Studies 2010

The current studies evaluated variables affecting sharing exhibited by children with autism spectrum disorder. The first study evaluated the effects of manipulating item preference on the level of assistance needed to exhibit sharing behavior for four children with autism. Item preference affected two participants' percentage of independent sharing. Preference did not have as clear of an effect for another participant. However, sharing a more preferred item required more assistance (e.g., vocal prompts) to share. The fourth participant's percentage of independent sharing was not influenced by preference, and his independent sharing behavior was similar across item preference. The second study assessed the effectiveness of a token reinforcement procedure as an intervention for increasing independent sharing of high-preferred items for the two participants who did not independently share high-preferred items during study one. Independent sharing increased for both participants when the token procedure was in place and returned to baseline levels when it was removed.

AN ABSTRACT OF THE DISSERTATION OFMarty D. Price, for the Doctor of Philosophy degree in Psychology, presented on November 13, 2024, at Southern Illinois University Carbondale. TITLE: USING A HYPOTHETICAL PURCHASE TASK TO INFORM THE SELECTION OF TERMINAL REINFORCERS IN A TOKEN ECONOMY MAJOR PROFESSOR: Dr. Eric Jacobs Token economies are among the most used techniques in applied behavior analysis across a variety of locations and diagnoses. However, most of the research in token economies is targeted at the economy and how it functions, and little attention is paid to the methods for backup reinforcer selection. Often simple interviews or standard preference assessments are used to determine which items are selected, with the values assigned to those items arbitrarily selected by the clinician. Methods within behavioral economics can be used to address this oversight, specifically hypothetical purchasing tasks and demand curve analysis. For this study, four participants with intellectual and/or developmental disabilities will be asked to complete two experiments using hypothetical purchasing tasks, the first with fixed incomes and variable prices and the second with variable incomes and fixed prices. A third experiment will introduce a simulated token economy by introducing a work component necessary to earn tokens to spend on backup reinforcers. Therefore, the purpose of the proposed research is to assess the efficacy of using hypothetical purchasing to inform the creation of a token economy for the treatment of behavioral problems in individuals with intellectual or developmental disabilities.Keywords: hypothetical purchasing, token economy, developmental disabilities, assessment

This study uses ultrasound to image onset velar stop consonant articulation in words. By examining tongue body placement, the extent of velar closure variation across vowel contexts provides for the measurement of anticipatory coarticulation while productions within the same vowel context provide measurement of extent of token-to-token variation. Articulate Assistant Advanced 2.0 software was used to semi-automatically generate midsagittal tongue contours at the initial point of maximum velar closure and was used to fit each contour to a curved spline. Patterns of lingual coarticulation and measures of speech motor stability, based on curve-to-curve distance (Zharkova, Hewlett, & Hardcastle, 2011), are investigated to compare the speech of typically fluent speakers to the speech of people who stutter. Anticipatory coarticulation can be interpreted as a quantitative measure indicating the maturity of the speech motor system and its planning abilities. Token-to-token variability is examined from multiple velar vowel productions within the same vowel context, describing the accuracy of control, or stability, of velar closure gestures. Measures for both speaking groups are examined across the lifespan at stages during speech development, maturation, and aging. Results indicate an overall age effect, interpreted as refinement, with increased speech stability and progressively more segmental (less coarticulated) productions across the lifespan. A tendency toward decreased stability and more coarticulated speech was found for younger people who stutter, but this difference was small and absent among older adults. Outcomes of this study suggest the articulatory maturation trajectories of people who stutter may be delayed, but overall maturation of the speech mechanism is evident by older adulthood for typically fluent speakers and those who stutter. Applications to intervention are discussed in closing.

[pt] Uma das tarefas mais importantes em Processamento de Linguagem Natural é a análise sintática, onde a estrutura de uma sentença é determinada de acordo com uma dada gramática, informando o significado de uma sentença a partir do significado das palavras nela contidas. A Análise Sintática baseada em Gramáticas de Dependência consiste em identificar para cada palavra a outra palavra na sentença que a governa. Assim, a saída de um analisador sintático de dependência é uma árvore onde os nós são as palavras da sentença. Esta estrutura simples, mas rica, é utilizada em uma grande variedade de aplicações, entre elas Sistemas de Pergunta-Resposta, Tradução Automática, Extração de Informação, e Identificação de Papéis Semânticos. Os sistemas estado-da-arte em análise sintática de dependência utilizam modelos baseados em transições ou modelos baseados em grafos. Essa dissertação apresenta uma abordagem por classificação tokena- token para a análise sintática de dependência ao criar um conjunto especial de classes que permitem a correta identificação de uma palavra na sentença. Usando esse conjunto de classes, qualquer algoritmo de classificação pode ser treinado para identificar corretamente a palavra governante de cada palavra na sentença. Além disso, este conjunto de classes permite tratar igualmente relações de dependência projetivas e não-projetivas, evitando abordagens pseudo-projetivas. Para avaliar a sua eficácia, aplicamos o algoritmo Entropy Guided Transformation Learning aos corpora disponibilizados publicamente na tarefa proposta durante a CoNLL 2006. Esses experimentos foram realizados em três corpora de diferentes idiomas: dinamarquês, holandês e português. Para avaliação de desempenho foi utilizada a métrica de Unlabeled Attachment Score. Nossos resultados mostram que os modelos gerados atingem resultados acima da média dos sistemas do CoNLL. Ainda, nossos resultados indicam que a abordagem por classificação token-a-token é uma abordagem promissora para o problema de análise sintática de dependência. / [en] One of the most important tasks in Natural Language Processing is syntactic parsing, where the structure of a sentence is inferred according to a given grammar. Syntactic parsing, thus, tells us how to determine the meaning of the sentence fromthemeaning of the words in it. Syntactic parsing based on dependency grammars is called dependency parsing. The Dependency-based syntactic parsing task consists in identifying a head word for each word in an input sentence. Hence, its output is a rooted tree, where the nodes are the words in the sentence. This simple, yet powerful, structure is used in a great variety of applications, like Question Answering,Machine Translation, Information Extraction and Semantic Role Labeling. State-of-the-art dependency parsing systems use transition-based or graph-based models. This dissertation presents a token classification approach to dependency parsing, by creating a special tagging set that helps to correctly find the head of a token. Using this tagging style, any classification algorithm can be trained to identify the syntactic head of each word in a sentence. In addition, this classification model treats projective and non-projective dependency graphs equally, avoiding pseudo-projective approaches. To evaluate its effectiveness, we apply the Entropy Guided Transformation Learning algorithm to the publicly available corpora from the CoNLL 2006 Shared Task. These computational experiments are performed on three corpora in different languages, namely: Danish, Dutch and Portuguese. We use the Unlabelled Attachment Score as the accuracy metric. Our results show that the generated models are above the average CoNLL system performance. Additionally, these findings also indicate that the token classification approach is a promising one.

The research literature with nonhumans supports findings that token economies are a common component of training programs. The literature suggests that the schedule by which exchange opportunities become available determines the organization of behavioral performances in token economies to a great extent. This study sought to systematically document whether the dynamics observed in basic laboratory procedures will also be observed in a child diagnosed with autism spectrum disorders and whether altering schedules by which the exchange opportunities become available will attenuate these effects. The participant was exposed to two conditions: 1) a fixed token-production schedule (FR1) with a fixed token-exchange schedule (FR5) and 2) a fixed token-production schedule (FR1) with a variable token-exchange schedule (VR5). Results of the current study did not lend themselves to draw definitive conclusions that the patterns of responding observed in this experiment were in fact due to the change in the token exchange schedule.