Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.

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10th International Conference; Stockholm, Sweden; 2019

Event Details


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Paper Session #96
Topics in Education
Monday, September 30, 2019
2:00 PM–3:20 PM
Stockholm Waterfront Congress Centre, Level 2, C1
Area: EDC
Instruction Level: Intermediate
Chair: Joanne K. Robbins (Morningside Academy)
 

Project HEAR+T: Implementation of A Social-Emotional Intervention Package to Teach Behavioral Expectations in Early Childhood

Domain: Applied Research
CHARIS WAHMAN (The Ohio State University)
 
Abstract:

With the rising incidence in young children being suspended and expelled from pre-school settings in the United States, on-going examination of evidence-based social/emotional/behavioral interventions is essential. The present study explored the feasibility of a social/emotional/behavioral intervention on teacher and student behavior. Children and teachers were recruited from an inclusive early childhood center in a Midwestern city to participate in this study focused on explicitly teaching behavioral expectations. Using a multiple baseline design across three children, the impact of scripted stories, role plays, and positive reinforcement was examined. Teachers were trained on how to implement the intervention through simple technical assistance meetings, including on-going feedback. A change in behavior was observed for all three target children which resulted in an established functional relation between the intervention package and child adherence to behavioral expectations.

 

Online Learning: The Effect of Synchronous Discussion Sessions in Asynchronous Courses

Domain: Applied Research
Jesslyn Farros (Center for Applied Behavior Analysis (CABA) and Endicott College), Lesley A. Shawler (Endicott College), Ksenia Kravtchenko (Endicott College), BRYAN J. BLAIR (Long Island University)
 
Abstract:

Online learning is extremely prevalent in education. In 2015, close to six million students were taking at least one online learning course, which was 29.7% of all postsecondary students (U.S. Department of Education, National Center for Education Statistics, 2018). In 2017, the Online Learning Consortium reported an almost 4% increase in online learning students in 2015 as compared to the previous two years. Although online learning is becoming more prevalent, there has been little to no research to determine what makes online learning most effective and those that have, either have not compared modalities (i.e., only testing one format) (Sella et al., 2014; Walker and Rehfeldt, 2012) or have focused on another aspect of the learning (i.e., does grading anonymously affect performance) (Lui et al., 2018). Determining the components of online learning that lead to better student outcomes will add to the current literature and improve online learning as a whole. The current study comprises four different experiments that evaluated the effect of synchronous discussion sessions in asynchronous master-level applied behavior analysis courses. Three different applied behavior analysis courses were used and each experiment utilized a slightly different experimental design. The first two focused on the addition of synchronous discussion within an asynchronous course and the last two focused on comparing the effects of synchronous and asynchronous discussion. The primary purpose of these experiments was to determine what forms of discussion (synchronous vs asynchronous) are most effective in asynchronous online courses. (Note: Data is submitted for the first experiment only as the last three are currently in progress.)

 
Analyzing Instructional Content
Domain: Service Delivery
JOANNE K. ROBBINS (Morningside Academy; PEER Intl.)
 
Abstract: Designing instruction begins with the analysis of content and defining objectives. Content analysis is not a statement of subject matter to be learned, but of specific types of instructional relations to be taught and tested. One taxonomy or classification system of educational objectives was created by Tiemann and Markle (1991). The system divides objectives into three primary domains domains: psychomotor, simple cognitive, and complex cognitive. Underlying all learning is an emotional component. This paper will introduce how content can be analyzed to discover the relations to be taught, how testing differs for each type of relation, and how each type of relation requires different types of practice. For example, those relations that fall within the psychomotor domain, which includes basic responses, chains, and kinesthetic repertoires, will require much different teaching and practice approaches than those that fall into the simple cognitive domain or the complex cognitive domain, which includes concepts, principles, and strategies.
 
 

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