Agility: What It Is, How to Measure It, and How to Use It

Abstract

A positive and expected by-product of a well-programmed instructional sequence is an escalation of learning, where skills are acquired more quickly as teaching goes on. Despite the importance of this effect in behavior analysis and education, techniques for detecting and analyzing it are rarely observed in practice settings. A behavioral approach to this phenomenon is rooted in the term agility, which has persisted in the precision-teaching community as a description of desirable acquisition patterns. Precision teachers have long carried forward a loose definition of agility as “celerating celerations.” Although this definition might succeed in generally orienting practitioners toward the goal of helping people acquire new skills more quickly, its lack of technical specificity has hindered efforts to fully integrate such analyses into practice. In this article, the authors define agility and distinguish it from other concepts common to education and behavior analysis. Further, a tutorial for quantifying and analyzing agility using frequency, celeration, and bounce multipliers is presented in detail. Finally, the practical implications afforded by analyses of agility are delineated.

Using Precision Teaching to Improve Typically Developing Student’s Mathematical Skills Via Teleconferencing

“…Such a learning profile would suggest that students have become agile learners. In other words, they have learned how to learn more effectively and efficiently, which is considered an essential outcome in PT (Meyer et al, 2021 ).…”

Comparison of two video prompting interventions to teach daily living skills to adolescents with autism

“…The segments of the SCC offer accurate illustrations of behavior change over time, display behavior change proportionately, and quantify changes in behavior facilitating a statistical analysis (Pennypacker et al., 2003). The growth of SCC segments in behavioral journals as a method for providing clear visual and quantitative analysis has accelerated (e.g., Barosky et al., 2020; Bulla et al., 2020; Kinney et al., 2020; Kostewicz et al., 2020; Kubina et al., 2016; Meyer et al., 2020; Mrachko et al., 2017; Vostanis et al., 2021). The use of SCC segments meets the call for single‐case research to add quantification, objectivity, and decision rules to the visual analysis (Brossart et al., 2006; Bulté & Onghena, 2012; Lanovaz et al., 2019; Roane et al., 2013; Shaddish, 2014).…”

Deploying Big Data Enablers to Strengthen Supply Chain Agility to Mitigate Bullwhip Effect: An Empirical Study of China’s Electronic Manufacturers

“…Supply chain agility is presented as a means of improving customer responsiveness and addressing market changes [17]. Meyer et al, 2017 pointed out that supply chain agility is an emerging dynamic capability that has been widely accepted as an important aspect of successful supply chain management [68]. Supply chain agility needs to be able to respond to changes in supply and demand, ensure that the company remains competitive and have a shorter life cycle, promote the company's sustainable development, create new products and services, and foster social, environmental, and economic sustainability within the supply chain [69].…”