This investigation is concerned with the problem of determining the variation of test achievement obtained by students enrolled on a MWF and a TTh schedule. The purpose of the study is to determine if either schedule is superior. The Ss were students enrolled in an Introductory Psychology course at North Texas State University. A t test was administered to the experimental data. The experimental hypothesis of an expected higher test achievement by students enrolled in the TTh schedule was rejected. It was concluded that test achievement for this study was not affected by scheduling.

The goal of this thesis was to design and implement a graphical tool for visualization and editing of schedules which would provide a function for automatic repairing of violated constraints in the schedule. The resulting application called a Gantt Viewer is integrated to the FlowOpt project that represents a complex solution for modeling workflows, creation of schedules from them and analysis of these schedules. The application has been developed with the focus on intuitiveness of the user interface and performance during the management of large schedules. It enables the user to visualize extended manufacturing schedules thanks to the cooperation with other modules of the FlowOpt project. Moreover, the Gantt Viewer incorporates a repair tool exploiting a new Repair-DTP algorithm which is both introduced and demonstrated in this work.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Todd W. Easton / Westside High School (WHS) of Omaha, Nebraska utilizes a novel scheduling system called Modular scheduling. This system offers numerous advantages over the standard school day in terms of student learning and faculty development. Modular Scheduling allows teachers to design the structure of their own classes by adjusting the frequency, duration and location of each of their daily lessons. Additionally, teachers are able combine their classes with those of other teachers and team-teach. Modular scheduling also allows for open periods in both students’ and teachers’ schedules. During this time, students are able to complete school work or seek supplemental instruction with a teacher who is also free. Teachers are able to use their open mods to plan, meet in teams and help students who have fallen behind. Currently, a semester’s class schedules are constructed over the course of a seven week period by a full-time employee using a computer program developed in FORTRAN®. The process is extremely tedious and labor intensive which has led to considerable wasted time, cost and frustration. This thesis presents a novel scheduling program called the SMART Scheduler that is able to do in seconds what previously took weeks to accomplish. Once parameters have been input, The SMART Scheduler is able to create cohesive class schedules within a modular environment in less than 6 seconds. The research presented describes the steps that were taken in developing the SMART Scheduler as well as computational results of its implementation using actual data provided by WHS. The goal of this research is to enable WHS and other schools to efficiently and effectively utilize modular scheduling to positively affect student learning.

O objetivo foi investigar como a natureza do reforçador afeta o comportamento humano em FI após diferentes histórias de reforço. Universitários foram expostos inicialmente a um de três programas de reforço: FR 40, DRL 20 s ou FI 10 s por três sessões de 15 minutos cada. As contingências de reforço foram programadas com o software ProgRef e a conseqüência para a resposta de pressionar um botão era pontos. Para alguns participantes os pontos eram trocados por fotocópias (Condição 1), para outros os pontos eram trocados por dinheiro (Condição 2), enquanto para outros os pontos não eram trocados por nada (Condição 3). Subseqüentemente, os participantes com história de FR e DRL foram expostos a um programa de reforço em FI 10 s e os participantes submetidos inicialmente ao FI 10 s tiveram o parâmetro do FI alterado para 5, 20 ou 30 s, por três sessões de 15 minutos cada. Os participantes da Condição 3-Pontos, expostos a histórias de responder em FR ou DRL, foram submetidos a cinco sessões de Extinção após as sessões de FI. Os participantes expostos ao FR apresentaram um padrão de responder em taxa alta e constante independentemente do tipo de reforçador utilizado. Quando a contingência mudou de FR para FI a taxa de respostas permaneceu alta para os participantes das Condições 1-Fotocópia e Condição 2-Dinheiro, mas diminuiu para a maioria dos participantes da Condição 3-Pontos. Os participantes expostos inicialmente ao DRL apresentaram um responder em taxa baixa tanto sob a contingência de DRL quanto sob a de FI subseqüente, independentemente da condição de reforço. Apesar desse efeito de persistência comportamental, houve uma diminuição no IRT quando a contingência mudou, o que sugere que o responder era controlado também pela contingência de FI presente. O tipo de reforçador empregado parece ter afetado a probabilidade de que os participantes expostos inicialmente a um programa de reforço em FI 10 s exibissem uma taxa de respostas alta (participantes da Condição 2-Dinheiro) ou baixa (participantes da Condição 3-Pontos). O tipo de reforçador empregado parece ter afetado também o padrão de responder dos participantes quando a parâmetro do FI mudou de 10 para 5, 20 ou 30 segundos. O padrão de responder da maioria dos participantes das Condições 1 e 3 (Fotocópia e Pontos, respectivamente) mudou quando o parâmetro do FI foi alterado, enquanto que o padrão dos participantes da Condição 2-Dinheiro permaneceu o mesmo. Quando a contingência de reforço dos participantes da Condição 3-Pontos foi alterada de FI para extinção houve uma mudança no padrão comportamental tanto dos participantes que tinham história de responder sob FR quanto daqueles com história de responder em DRL. Tomados em conjunto os resultados sugerem que: (a) o comportamento dos participantes foi controlado tanto pela história de reforço quanto pelas contingências presentes; (b) a natureza do reforçador empregado pode favorecer o responder em taxa alta e constante sob FI – tanto após exposição a uma contingência de FR quanto quando o FI é programado desde o início (i.e., sem história experimental prévia a nenhuma outra contingência de reforço). Os resultados do presente estudo assemelham-se àqueles obtidos em outros estudos com organismos humanos e não-humanos respondendo sob programas de reforço e sugerem que as diferenças entre o comportamento de humanos e não-humanos sob programas de reforço podem ser atribuídas tanto à história de condicionamento quanto a diferenças de procedimento entre os estudos com humanos e não-humanos. Os resultados também sugerem que a natureza do reforçador é uma variável importante para modular os efeitos da história experimental sobre o comportamento de seres humanos. / In the present study it was investigated how the nature of reinforcer affects the human behavior on FI reinforcement schedule under different histories of reinforcement. College students were initially exposed to one of three reinforcement schedules: FR 40, DRL 20 s or FI 10 s for 15 minutes each. A computer software, ProgRef, was used to program contingencies of reinforcement. So, if the subject gave a click on the left button of mouse, a number correspondent to the number of reinforced response pop out on the monitor screen. That number was equivalent to points, and some students could exchange their points for photocopies (Condition 1), other for money (Condition 2), and other could not exchange for anything (Condition 3). Later, students whose behaviors have been reinforced in FR and DRL schedules (histories) went to a FI 10 s reinforcement schedule and the ones who had already been exposed to the FI 10 s had their FI parameter altered to 5, 20 or 30 s during three sessions of 15 min each. Before being exposed to histories of responding in FR or DRL, Condition 3-Points participants were exposed to five Extinction sessions after being exposed to FI 10 s sessions. All students exposed to FR had high rates of responding, independently of the nature of reinforcer. When the contingencies changed from FR to FI, response rates remained high in the Conditions 1 and 2 (Photocopies and Money), but it deeply decreased in the Condition 3. Students exposed to DRL history presented a low rate of response under both DRL and FI contingencies, independently of the nature of reinforcement. Despite this behavioral persistence effect, the IRT decreased when contingency changed from DRL 20 s to FI 10 s. This suggests that the pattern responding was also under controlling of contingency of reinforcement current. The nature of reinforcer affected the students’ behavior in FI 10 s even then had no previous experimental history. A high rates of responses was produced by students in the Condition 2-Money while a low rates of responses was produced by most students in the Condition 3-Points. The nature of reinforcer also influenced the students’ behaviors pattern as FI value changed from 10 to 5, 20 or 30 s. Results show that students’ behaviors pattern changed as FI value was altered as in the sequence before in the Conditions 1 and 3. However, it did not change at the same way as FI value was altered in the Condition 2. As contingencies of reinforcement, in the Condition 3, were altered from FI to extinction schedules, subjects’ behaviors under FR and DRL schedules showed a different pattern. Taken as a whole the results suggests that: first, participants’ behavior seemed to be controlled either by reinforcement history or by contingency of reinforcement; Second, the nature of reinforcement may be produced both high and low rates of response under FI – both after FR contingency exposure and when FI is programmed from the beginning (i.e., with no previous experimental history to no other reinforcement contingency). The results of the present study are in agreement to most those studies carried out with human and non-human responding under reinforcement schedules and suggest that the discrepancies between the behavior of humans and non-humans on schedules of reinforcement maybe attributed to both conditioning history and procedural differences between human and non-human research procedures. Also, the results here presented suggest that the nature of reinforcer is an important variable to modulate the effects of experimental history on the human behaviors.

O objetivo foi investigar como a natureza do reforçador afeta o comportamento humano em FI após diferentes histórias de reforço. Universitários foram expostos inicialmente a um de três programas de reforço: FR 40, DRL 20 s ou FI 10 s por três sessões de 15 minutos cada. As contingências de reforço foram programadas com o software ProgRef e a conseqüência para a resposta de pressionar um botão era pontos. Para alguns participantes os pontos eram trocados por fotocópias (Condição 1), para outros os pontos eram trocados por dinheiro (Condição 2), enquanto para outros os pontos não eram trocados por nada (Condição 3). Subseqüentemente, os participantes com história de FR e DRL foram expostos a um programa de reforço em FI 10 s e os participantes submetidos inicialmente ao FI 10 s tiveram o parâmetro do FI alterado para 5, 20 ou 30 s, por três sessões de 15 minutos cada. Os participantes da Condição 3-Pontos, expostos a histórias de responder em FR ou DRL, foram submetidos a cinco sessões de Extinção após as sessões de FI. Os participantes expostos ao FR apresentaram um padrão de responder em taxa alta e constante independentemente do tipo de reforçador utilizado. Quando a contingência mudou de FR para FI a taxa de respostas permaneceu alta para os participantes das Condições 1-Fotocópia e Condição 2-Dinheiro, mas diminuiu para a maioria dos participantes da Condição 3-Pontos. Os participantes expostos inicialmente ao DRL apresentaram um responder em taxa baixa tanto sob a contingência de DRL quanto sob a de FI subseqüente, independentemente da condição de reforço. Apesar desse efeito de persistência comportamental, houve uma diminuição no IRT quando a contingência mudou, o que sugere que o responder era controlado também pela contingência de FI presente. O tipo de reforçador empregado parece ter afetado a probabilidade de que os participantes expostos inicialmente a um programa de reforço em FI 10 s exibissem uma taxa de respostas alta (participantes da Condição 2-Dinheiro) ou baixa (participantes da Condição 3-Pontos). O tipo de reforçador empregado parece ter afetado também o padrão de responder dos participantes quando a parâmetro do FI mudou de 10 para 5, 20 ou 30 segundos. O padrão de responder da maioria dos participantes das Condições 1 e 3 (Fotocópia e Pontos, respectivamente) mudou quando o parâmetro do FI foi alterado, enquanto que o padrão dos participantes da Condição 2-Dinheiro permaneceu o mesmo. Quando a contingência de reforço dos participantes da Condição 3-Pontos foi alterada de FI para extinção houve uma mudança no padrão comportamental tanto dos participantes que tinham história de responder sob FR quanto daqueles com história de responder em DRL. Tomados em conjunto os resultados sugerem que: (a) o comportamento dos participantes foi controlado tanto pela história de reforço quanto pelas contingências presentes; (b) a natureza do reforçador empregado pode favorecer o responder em taxa alta e constante sob FI – tanto após exposição a uma contingência de FR quanto quando o FI é programado desde o início (i.e., sem história experimental prévia a nenhuma outra contingência de reforço). Os resultados do presente estudo assemelham-se àqueles obtidos em outros estudos com organismos humanos e não-humanos respondendo sob programas de reforço e sugerem que as diferenças entre o comportamento de humanos e não-humanos sob programas de reforço podem ser atribuídas tanto à história de condicionamento quanto a diferenças de procedimento entre os estudos com humanos e não-humanos. Os resultados também sugerem que a natureza do reforçador é uma variável importante para modular os efeitos da história experimental sobre o comportamento de seres humanos. / In the present study it was investigated how the nature of reinforcer affects the human behavior on FI reinforcement schedule under different histories of reinforcement. College students were initially exposed to one of three reinforcement schedules: FR 40, DRL 20 s or FI 10 s for 15 minutes each. A computer software, ProgRef, was used to program contingencies of reinforcement. So, if the subject gave a click on the left button of mouse, a number correspondent to the number of reinforced response pop out on the monitor screen. That number was equivalent to points, and some students could exchange their points for photocopies (Condition 1), other for money (Condition 2), and other could not exchange for anything (Condition 3). Later, students whose behaviors have been reinforced in FR and DRL schedules (histories) went to a FI 10 s reinforcement schedule and the ones who had already been exposed to the FI 10 s had their FI parameter altered to 5, 20 or 30 s during three sessions of 15 min each. Before being exposed to histories of responding in FR or DRL, Condition 3-Points participants were exposed to five Extinction sessions after being exposed to FI 10 s sessions. All students exposed to FR had high rates of responding, independently of the nature of reinforcer. When the contingencies changed from FR to FI, response rates remained high in the Conditions 1 and 2 (Photocopies and Money), but it deeply decreased in the Condition 3. Students exposed to DRL history presented a low rate of response under both DRL and FI contingencies, independently of the nature of reinforcement. Despite this behavioral persistence effect, the IRT decreased when contingency changed from DRL 20 s to FI 10 s. This suggests that the pattern responding was also under controlling of contingency of reinforcement current. The nature of reinforcer affected the students’ behavior in FI 10 s even then had no previous experimental history. A high rates of responses was produced by students in the Condition 2-Money while a low rates of responses was produced by most students in the Condition 3-Points. The nature of reinforcer also influenced the students’ behaviors pattern as FI value changed from 10 to 5, 20 or 30 s. Results show that students’ behaviors pattern changed as FI value was altered as in the sequence before in the Conditions 1 and 3. However, it did not change at the same way as FI value was altered in the Condition 2. As contingencies of reinforcement, in the Condition 3, were altered from FI to extinction schedules, subjects’ behaviors under FR and DRL schedules showed a different pattern. Taken as a whole the results suggests that: first, participants’ behavior seemed to be controlled either by reinforcement history or by contingency of reinforcement; Second, the nature of reinforcement may be produced both high and low rates of response under FI – both after FR contingency exposure and when FI is programmed from the beginning (i.e., with no previous experimental history to no other reinforcement contingency). The results of the present study are in agreement to most those studies carried out with human and non-human responding under reinforcement schedules and suggest that the discrepancies between the behavior of humans and non-humans on schedules of reinforcement maybe attributed to both conditioning history and procedural differences between human and non-human research procedures. Also, the results here presented suggest that the nature of reinforcer is an important variable to modulate the effects of experimental history on the human behaviors.

Amish communities have persistently low childhood immunization rates. Prior to this study, reasons for low rates had not been clearly identified. Researchers have speculated that access to health care, religious factors, and fear might be reasons that Amish parents refuse childhood immunizations, but more empirical evidence was warranted.The purpose of this study was to gather that empirical evidence regarding the knowledge, attitudes, opinions, and beliefs of Amish parents residing in Ashtabula County Ohio, an additional purpose was to examine how these factors influence timely immunizations of Amish children. The theoretical framework was the PEN-3-Cultural Model, focusing on cultural influences, beliefs, and experiences in health behavior of individuals in a community. The development of a 20 question survey was guided by 4 research questions designed to evaluate any differences in Amish parents' decision to defer recommended childhood immunizations. Multivariate analysis of variance was used to evaluate the 4 research questions based on the 84 individual surveys received. Results revealed a significant link between knowledge, beliefs, and opinions toward immunization and immunization adherence. Results also revealed that age and gender had no effect on the relationship between knowledge, beliefs, attitudes, and opinions toward immunization adherence. This study contributes to positive social change by educating parents of Amish children as to why it is important to receive timely childhood immunizations; thereby, keeping their children safe from vaccine-preventable diseases.

Previous researchers conducted activity schedule studies and used them on unstructured areas such as the playground. This study investigates the ability of fading procedures on the effects of using activity schedules on the playground. This study displayed that fading procedures can be used and determined based on the level of the individual. The results showed that two participants were able to fade to more portable forms of activity schedules from the typical activity schedule binder. This study provides many possibilities for conducting future research involving the use of fading procedures on activity schedules.

Young children with Autism Spectrum Disorder (ASD) demonstrate behavioral deficits and excesses that can adversely affect their play skills. Teaching children with ASD to use activity schedules with embedded scripts have led to increased appropriate game play with other children with autism and typically developing peers; however, there is sparse research on promoting more dynamic social play in children with ASD. The purpose of this study was to examine the effects of teaching the use of activity schedules with embedded scripts on the sociodramatic play of preschoolers with ASD with their typically developing peers. We also examined the extent to which we could remove scripts and schedule components and continue to observe appropriate sociodramatic play. Two participants with ASD quickly demonstrated high levels of sociodramatic play with their typically developing peers compared to baseline, and an additional participant with ASD demonstrated similar increases with procedural modifications. The participants also continued to show these increased levels after all scripts and nearly all components of the activity schedules were systematically removed, including during 1-and 2-week follow-up sessions. In addition, all participants engaged in additional unscheduled, yet contextually appropriate, sociodramatic play behaviors.

Resistance to extinction of single-schedule performance is negatively related to the reinforcer rate that an organism experienced in the pre-extinction context. This finding opposes the predications of behavioral momentum theory, which states that resistance to change, in general, is positively related to reinforcer rates. The quantitative model of extinction provided by behavioral momentum theory can describe resistance to extinction following single schedules in a post-hoc fashion, and only if the parameters of the model are allowed to vary considerably from those typically derived from multiple- schedule preparations. An application of the principles of Bayesian inference offers an alternative account of extinction performance following single schedules. According to the Bayesian change-detection algorithm, the temporal intervals of non-reinforcement that an organism experiences during extinction are compared to the temporal distribution of reinforcers that the organism experienced during baseline. A transition to extinction is more readily detectable when the previously collected distribution of reinforcers in timeis populated with relatively short intervals (i.e., when more frequent reinforcement was experienced during baseline). The Bayesian change-detection algorithm also suggests that changes in reinforcer rates are more detectable when organisms have temporally proximal experience with frequently changing rates. The current experiment investigated this novel prediction. Pigeons pecked keys for food under schedules of reinforcement that arranged either relatively dynamic reinforcer rates or relatively static rates across conditions. Following each period of reinforcement, resistance to extinction was assessed. Persistence was greater following static contingencies than following dynamic contingencies for the majority of subjects. These data provide support for the Bayesian approach to understanding operant extinction and might serve to extend behavioral momentum theory by offering change detection as an additional mechanism through which extinction occurs.

Four pigeons had discrimination training that required the choice of a left side-key following completion of a fixed-ratio 10 an the center key, and a right side-key response after fixed-ratio 20. Correct choices were reinforced on various fixed-interval, fixed-ratio, random-interval, and random-ratio schedules. When accuracy was examined across quarters of intervals (fixed-interval schedules) or quarters of median interreinforcerrent intervals (fixed-ratio schedules), accuracy was usually laver in the second quarter than in the first, third, or fourth quarters. When accuracy was examined across quarters of ratios (fixed-ratio schedules) or quarters of median number of correct interreinforcement trials (fixed-interval schedules), accuracy increased across quarters. These accuracy patterns did not occur m random-interval or random-ratio schedules. The results indicate that, when choice patterns differed on fixed-interval and fixed-ratio schedules, these differences were due to the methods of data analyses.