Algorithmic analysis of relational learning processes in instructional technology: Some implications for basic, translational, and applied research.

A few noteworthy exceptions notwithstanding, quantitative analyses of relational learning are most often simple descriptive measures of study outcomes. For example, studies of stimulus equivalence have made much progress using measures such as percentage consistent with equivalence relations, discrimination ratio, and response latency. Although procedures may have ad hoc variations, they remain fairly similar across studies.

Teaching Stimulus-Stimulus Relations to Minimally Verbal Individuals: Reflections on Technology and Future Directions.

This paper discusses recent methodological approaches and investigations that are aimed at developing reliable behavioral technology for teaching stimulus-stimulus relations to individuals who are minimally verbal and show protracted difficulty in acquiring such relations. The paper has both empirical and theoretical content. The empirical component presents recent data concerning the possibility of generating rapid relational learning in individuals who do not initially show it.

High-probability stimulus control topographies with delayed S+ onset in a simultaneous discrimination procedure.

Experimenters and teachers use discrimination learning procedures to encourage reliable attending to stimulus differences defined as relevant for their purposes. Put another way, the goal of discrimination training is to establish high-probability stimulus control topographies that are coherent with experimenter or teacher specifications. The present research was conducted to investigate a novel procedure for encouraging stimulus control topography coherence.