Association for Behavior Analysis International

An Individualized Education Program (IEP), by definition, states a student should receive instruction that is tailored to his/her specific needs. The IEP outlines the goals and activities that over the course of a year should lead to measurable progress. What happens when an IEP is implemented in a system that does not support the student? When a systems approach to behavior analysis is used, the student remains at the center of the program yet has interdependent relationships. These relationships are with the instructional staff, supervisory staff, family members, and university students. Instructional gains are made when each component of the system is accountable to the student, and accountability is derived from the application of behavior analytic instruction to each component. Behavior analytic instruction, as it is applied to an educational setting, can lead to measurable gains not only in meeting the student?s IEP goals, but for all components of the system (e.g., student, instructional staff, supervisory staff, and university). In this symposium, each presenter will illustrate how behavior analysis was applied to a component of the system with the goal of creating measurable change.

A behavior analytic school by definition has to include much more than discrete trial instruction. In schools where behavior analysis is used as a systems approach to educating its population the dimensions of Applied Behavior Analysis should be observable across all aspects of the setting. In such settings the power of data should be evident. Student performance, teacher performance as well as supervisory productivity can be measured and evaluated and ultimately changed to better meet the needs of both students and staff. Once gathered and analyzed, data are used to make clinical and administrative changes that lead to progress toward greater learning and improved outcomes for the school. Important aspects in educational services are quantified, thereby becoming variables themselves to be systematically manipulated to improve the performance of the system, in this case the school as a whole. The following presentation will look at the data collected in 2 schools, across one year. The value in these data is what can and has been used to move toward improved outcomes.

esearch has demonstrated that most-to-least (MTL) and least-to-most (LTM) prompting are effective in helping children with Autism Spectrum Disorders acquire a variety of skills. However, when directly compared to one another, the efficiency and efficacy of these prompting procedures have been variable. The inconsistencies in the literature could be due to selecting prompt topographies that do not promote correct responding. To address this, the present study began by assessing different prompt topographies and then compared most-to-least (MTL) and least-to-most (LTM) prompt fading with only prompt topographies that were potent enough to promote corrected responding. The subsequent comparison of prompt fading procedures revealed that MTL prompting was more effective and efficient than LTM prompting for all three participants. Further implications for practice and future research are discussed.

ne of the most crucial elements of an effective behavior analytic program is the promotion of generalization from school to the home and other relevant community settings. A number of researchers have looked at parent training methods in an attempt to identify the most salient factors associated with positive outcomes (Clark et al, 1982; Hudson, 1982; Baker & Brightman, 1984). Given the numerous formats in which parent training is now available, trainings are becoming more readily available to parents. As a result, it is imperative that effective and efficient parent training methods are implemented to improve instructional efficacy as well as manage home and community behavior problems. The purpose of this experiment was to examine the effectiveness of three parent training formats on fidelity of implementation, student behavior change and generalization to the home and community. The independent variable consisted of verbal instructions, verbal instructions plus teaching behavioral principles and verbal instructions plus modeling and structured feedback. The dependent variables included the fidelity of implementation across participants, student behavior change following implementation and generalization to the community. Results are presented in terms of the efficiency of strategy in training, effect on student behavior and generalization within the home and community.