Application of the generalized matching law for description of student behavior in the classroom

Matching law and theory have applied implications for classroom instruction and student behavior. The Generalized Matching Law (GML) is examined in this exploratory study to assess its utility for quantitatively describing student behavior in the classroom. Data were collected using computer-based observational software. Time-lag sequential analysis was used to identify specific teacher behaviors following specific student behaviors as estimates of reinforcement. Derived rates of student and teacher behaviors were analyzed in a linear regression of the natural logarithmic form of the GML. On average, the GML described over 70% of the variance in two students' behavior in a first-grade regular education classroom. Discussion addresses the potential utility of the GML for observation and intervention in the classroom.