This poster presents development and pilot-testing of an electronic survey evaluating behavior analysts perceptions and use of Evidence-Based Practices (EBPs). Demographic information, ratings of quality indicators (Horner et al 2005) in evaluating and choosing behavior interventions, and resources identifying EBPs were assessed. Fourteen graduate trainees in a behavior analysis certification program were participants. Test-retest intra-rater agreement was assessed approximately 2 weeks apart and varied considerably across survey items. Overall exact agreement was 71 % while agreement within 1 rating point was 91 %. The most highly rated quality indicators were clear descriptions of baseline and intervention conditions, measures of inter-observer agreement, and repeated measures of target behaviors. Lowest rated were group experimental designs, statistical analyses, and numbers of participants. Surprisingly, multiple studies with 20+ participants, integrated intervention packages, and written intervention manuals were not as highly rated. Most frequently reported EBP sources were professional society websites, university courses, practitioner journals, and professional peer-reviewed journals. Least frequently reported were webinars by private entities, non-peer-reviewed journals, and government websites (e.g., What Works Clearing House). Participants identified time constraints, difficulty finding research relevant to their current situation and technical rather than practical nature of research as impediments to keeping current with EBPs

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A company, Unanimous AI, has created a software platform that allows individuals to come together as a group or a human swarm to make decisions. These human swarms amplify the decision-making capabilities of both the individuals and the group. One way Unanimous AI increases the swarm’s collective decision-making capabilities is by limiting the swarm to more informed individuals on the given topic. The previous way Unanimous AI selected users to enter the swarm was improved upon by a new methodology that is detailed in this study. This new methodology implements a new type of survey that collects data that is more indicative of a user’s knowledge on the subject than the previous survey. This study also identifies better metrics for predicting each user’s performance when predicting Major League Baseball game outcomes throughout a given week. This study demonstrates that the new machine learning models and data extraction schemes are approximately 12% more accurate than the currently implemented methods at predicting user performance. Finally, this study shows how predicting a user’s performance based purely on their inputs can increase the average performance of a group by limiting the group to the top predicted performers. This study shows that by limiting the group to the top predicted performers across five different weeks of MLB predictions, the average group performance was increased up to 5.5%, making this a superior method.

Orientador: Ana Claudia Moreira Almeida-Verdu / Resumo: O programa sistemático e informatizado de ensino Aprendendo a Ler e a Escrever em Pequenos Passos® (ALEPP®), foi criado com base no paradigma das relações de equivalência. Sua finalidade é estabelecer repertório básico de leitura e escrita com diferentes níveis de complexidade, cuja eficiência tem sido replicada em diferentes centros de pesquisa. As intervenções em situações aplicadas e em populações com diferentes características de diagnóstico apontam sua efetividade, atendendo um amplo número de diagnósticos e necessidades especiais de ensino. O Estudo 1 trata-se de uma revisão de literatura, rastreando as diferentes versões do programa e sua evolução, desde a apresentação impressa até a apresentação informatizada e online atual. Os resultados apontam que o ALEPP® em seus diferentes módulos, tem potencial para ensinar repertórios de leitura e escrita em diferentes contextos. Enquanto lacuna verificou-se que apesar de seu potencial, o ALEPP® não tem sido utilizado em larga escala nas escolas, exceto para pesquisas do INCT/ECCE (Instituto Nacional de Ciência e Tecnologia sobre Comportamento, Cognição e Ensino). O Estudo 2 refere-se a uma pesquisa aplicada, com o objetivo de verificar a eficácia do Módulo 1 do software ALEPP® em crianças com diferentes diagnósticos e condições de aprendizagem, que frequentaram uma sala de recursos de uma Escola Pública Municipal de Ensino Fundamental, com queixas de atraso na aquisição de repertórios de leitura e escrita. Os resultados aponta... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The systematic and computerized teaching program Learning to Read and Write in Small Steps® (ALEPP®), created based on the paradigm of equivalence relations. It´s goal a basic repertoire of reading and writing with different levels of complexity, the efficiency of which has been replicated in different research centers. Tests in applied situations and in variations with different diagnostic characteristics point to its effectiveness, meeting a wide number of diagnoses and special teaching needs. Study 1 deals with a literature review, tracking how different versions of the program and their evolution, from a printed presentation to a current computerized presentation. The results pointed out for ALEPP®, in its different modules, have the potential to reproduce reading and writing repertoires in different contexts. While the gap was verified, despite its potential, ALEPP® was not used on a large scale in schools, except for INCT research. Study 2 refers to applied research, with the objective of verifying Module 1 of the ALEPP® ® software in children with different diagnoses and learning conditions, frequent in a resource room of the Municipal Public School of Elementary Education, with complaints of delay in the acquisition of reading and writing repertoires. The results show that, despite the initial diversified impact, the participants managed to finish two teaching units, reaching a percentage above 80% in reading and dictation post-tests. This data indicates that the ALEP... (Complete abstract click electronic access below) / Doutor

Children with autism have deficits in social interactions and verbal and nonverbal communication and engagement in rigid and repetitive activities and/or interests (ASA, 2008). A joint attention (JA) repertoire has been identified as a behavioral cusp for later social development and thus, JA deficits serve as an early indicator for diagnosis of autism spectrum disorder (Vismara & Lyons, 2007; Whalen & Schbreibman, 2003). A JA repertoire consists of both responses to- and initiations for-bids for coordinated attention. Previous research has shown teaching strategies such as pivotal response and discrete trial training for joint attention skills to be effective (Vismara & Lyons, 2007; Whalen & Schreibman, 2003). The purpose of the current study was to evaluate a mixture of pivotal response and discrete trial training as an intervention method for training joint attention behaviors with children diagnosed with autism spectrum disorder in a home setting. In addition, this study evaluated the effects of interspersing targets during training and incorporated generalization probes to assess JA initiations in the form of shifting eye gaze and pointing. Lastly this study examined a parent training procedure to determine if it would promote maintenance after skill acquisition. Results show that all targets were acquired when taught simultaneously. The results show that 2 of the 3 participants made JA initiations during probes throughout intervention. Lastly, the results indicated that parent training did not help maintain JA responding for participant one.

Animal Assisted Therapy (AAT) has become a popular intervention for the health and behavioral community as evidenced by media attention. The research that has been done on AAT has been mostly qualitative and anecdotal. The current study adds to the literature on AAT by collecting quantitative data on AAT. A multiple baseline design across three participants was used to evaluate the independent reading duration under a baseline condition (no dog present) and a non-contingent access to dog condition (which simulated how dog therapy is typically conducted). If reading did not increase during the non-contingent dog condition, a contingent access to the dog condition was implemented to determine if the participants would engage in increased reading duration to earn access to the dog. In this study, noncontingent access to the therapy dog resulted in increased reading duration for two of the participants. One participant showed variable results in the noncontingent phase and required the introduction of the contingent dog phase, which resulted in increases in reading duration.

The purpose of this study was to add to the existing body of research supporting the efficacy of ACT in improving performance and psychological challenges athletes experience. Three collegiate women’s basketball players participated in the current study in a multiple baseline design across participants. Two of the three subjects received the ACT only condition and individualized ACT plus mindfulness (IACT+M) treatment conditions. Subject three entered the IACT+M condition directly following baseline. Free throws, Mikan drill and three-ball dribbling where the three skills being assessed as well as psychological flexibility using two the assessment tools. The results suggest that brief ACT interventions may be useful for improving practice performance for collegiate basketball players. Participant one had an average increase for free throws by M=12.9%, a M=5% increase in the Mikan drill, and M=3.3% increase in the three-ball drill. Participant two had an average increase of M=7.3% for free throws, M=1.8% increase in the Mikan drill and M=0.4% increase in the three-ball drill. Participant three had an average increase of M=13% for free throws, 1.8% increase in the Mikan drill and a M=2% increase in the three-ball drill.

Caregivers' evaluation of evidence-based behavioral interventions may differ dependent upon the type of language used to describe the intervention. We administered a survey to 24 parents of children with autism to assess social validity measures of behavioral interventions described in one of three communication styles: technical, conversational, and conversational with intended outcome. Participants were presented with a description of two behavior-reduction and two behavior-acquisition interventions. Overall, interventions described in conversational with intended outcome style received the highest social validity ratings, while interventions described in the technical style received the lowest ratings. Moreover, behavior-acquisition interventions were rated significantly higher than behavior-reduction interventions when described in either conversational or conversational with intended outcome style. The current study supports the requirements of the Behavior Analyst Certification Board's Compliance Code that behavior analysts should inform the client/consumer of the treatment/interventions in an understandable language. Findings are also discussed in terms of verbal communities.

In the last decade, socially assistive robots have been used in therapeutic treatments for individuals diagnosed with Autism Spectrum Disorders (ASDs). Preliminary studies have demonstrated positive results using the Penguin for Autism Behavioral Intervention (PABI) developed by the AIM Lab at WPI to assist individuals diagnosed with ASDs in Applied Behavioral Analysis (ABA) therapy treatments. In recent years, power-efficient embedded AI computing devices have emerged as a powerful technology by reducing the complexity of the hardware platforms while providing support for parallel models of computation. This new hardware architecture seems to be an important step in the improvement of socially assistive robots in ABA therapy. In this thesis, we explore the use of a power-efficient embedded AI computing device and pre-trained deep learning models to improve PABI’s performance. Five main contributions are made in this work. First, a robot-enhanced ABA therapy framework is designed. Second, a multilayer pattern software architecture for a robot-enhanced ABA therapy framework is explored. Third, a multifactorial experiment is completed in order to benchmark the performance of three popular deep learning frameworks over the AI computing device. Experimental results demonstrate that some deep learning frameworks utilize the resources of GPU power while others utilize the multicore ARM-CPU system of the device for its parallel model of computation. Fourth, the robustness of state-of-the-art pre-trained deep learning models for feature extraction is analyzed and contrasted with the previous approach used by PABI. Experimental results indicate that pre-trained deep learning models overcome the traditional approaches in some fields; however, combining different pre-trained models in a process reduces its accuracy. Fifth, a patient-tracking algorithm based on an identity verification approach is developed to improve the autonomy, usability, and interactions of patients with the robot. Experimental results show that the developed algorithm has the potential to perform as well as the previous algorithm used by PABI based on a deep learning classifier approach.