The analysis of classroom talk: Methods and methodologies

This article describes methods for analysing classroom talk, comparing their strengths and weaknesses. Both quantitative and qualitative methods are described and assessed for their strengths and weaknesses, with a discussion of the mixed use of such methods. It is acknowledged that particular methods are often embedded in particular methodologies, which are based on specific theories of social action, research paradigms, and disciplines; and so a comparison is made of two contemporary methodologies, linguistic ethnography, and sociocultural research. The article concludes with some comments on the current state of development of this field of research and on ways that it might usefully progress.     

Reflexively mindblind: Using theory of mind to interpret behavior requires effortful attention

People commonly interpret others’ behavior in terms of the actors’ underlying beliefs, knowledge, or other mental states, thereby using their “theory of mind.” Two experiments suggest that using one’s theory of mind is a relatively effortful process. In both experiments, people reflexively used their own knowledge and beliefs to follow a speaker’s instruction, but only effortfully used their theory of mind to take into account a speaker’s intention to interpret those instructions. In Experiment 1, people with lower working memory capacity were less effective than people with larger working memory capacity in applying their theory of mind to interpret behavior. In Experiment 2, an attention-demanding secondary task reduced people’s ability to apply their theory of mind. People appear to be reflexively mindblind, interpreting behavior in terms of the actor’s mental states only to the extent that they have the cognitive resources to do so.     

Relating different perspectives on how outcomes of behavior influence behavior

Many researchers have tackled the question of how behavior is influenced by its outcomes. Some have adopted a nonmechanistic (functional) perspective that attempts to describe the influence of outcomes on behavior. Others have adopted a mechanistic (cognitive) perspective that attempts to explain the influence of outcomes on behavior. Orthogonal to this distinction, some have focused on the influence of outcomes that a behavior had in the past, whereas others also consider the influence of outcomes that a behavior might have in the future. In this article, we relate these different perspectives with the goal of reducing misunderstandings and fostering collaborations between researchers who adopt different perspectives on the common question of how behavior is influenced by its outcomes.     

Positive behavior support and applied behavior analysis

This article reviews the origins and characteristics of the positive behavior support (PBS) movement and examines those features in the context of the field of applied behavior analysis (ABA). We raise a number of concerns about PBS as an approach to delivery of behavioral services and its impact on how ABA is viewed by those in human services. We also consider the features of PBS that have facilitated its broad dissemination and how ABA might benefit from emulating certain practices of the PBS movement.     

Research on individual differences requires correlational analysis,not ANOVA

The data of Welsh and Baucom (1977) have been reanalyzed using correlational analysis for the complete distributions in place of the analysis of variance of extreme groups. The analysis reveals a number of statistically significant correlations between composites of M-F scales and several measures of intelligence, but these are trival in size. Also the sign of the correlations depends directly on which M-F scales are selected to form composites. One can obtain a correlation between either masculinity and intelligence or femininity and intelligence depending on whether the supposed trait is measured from scales formed from the Adjective Check List or from a combination of the MMPI and the SVIB.     

Countercontrol in behavior analysis

Countercontrol is a functional class of behavior that is part of Skinner's analysis of social behavior. Countercontrol refers to behavioral episodes comprised of socially mediated aversive controlling conditions and escape or avoidance responses that do not reinforce, and perhaps even punish, controllers' responses. This paper suggests that neglect of countercontrol in modern behavior analysis is unfortunate because the concept applies to interpersonal and social relations the fundamental operant principle that human behavior is both controlled and controlling-humans are not passive and inflexible. Countercontrol is addressed here in terms of conceptual status, contemporary developments in behavior analysis, its importance in a behavior-analytic approach to freedom and cultural design, applications, and research. The main conclusion is that Skinner's formulation of counter-control is scientifically supported and worthy of increased prominence in behavior analysis.     

Zen and behavior analysis

Zen's challenge for behavior analysis is to explain a repertoire that renders analysis itself meaningless-a result following not from scientific or philosophical arguments but rather from a unique verbal history generated by Zen's methods. Untying Zen's verbal knots suggests how meditation's and koans' effects on verbal behavior contribute to Enlightenment and Samādhi. The concept of stimulus singularity is introduced to account for why, within Zen's frame of reference, its methods can be studied but its primary outcomes (e.g., Samādhi and Satori) cannot be described in any conventional sense.     

Contingency and behavior analysis

The concept of contingency is central to theoretical discussions of learned behavior and in the application of learning research to problems of social significance. This paper reviews three aspects of the contingency concept as it has been developed by behavior analysts. The first is the empirical analysis of contingency through experimental studies of both human and nonhuman behavior. The second is the synthesis of experimental studies in theoretical and conceptual frameworks to yield a more general account of contingency and to integrate the concept with other behavioral processes. The third aspect is one of practical considerations in the application of the contingency concept in both laboratory and applied settings.     

What we talk about when we talk about epistemic justification

Stewart Cohen argues that much contemporary epistemological theorizing is hampered by the fact that ‘epistemic justification’ is a term of art (rather than something we all pretheoretically understand) and one that is never given any serious explication in a non-tendentious, theory-neutral way. He suggests that epistemologists are therefore better off theorizing in terms of rationality, rather than in terms of ‘epistemic justification’. Against this, I argue that even if the term ‘epistemic justification’ is not broadly known, the concept it picks out is quite familiar, and partly because it’s a term of art, justification talk is a better vehicle for philosophical theorizing. ‘Rational’ is too unclear for our philosophical purposes, and the fact that ‘epistemic justification’ gets fleshed out by appeal to substantive, controversial theses is no obstacle to its playing the needed role in epistemological theorizing.     

What we talk about when we talk about pediatric suffering

Theoretical Medicine and Bioethics - In this paper I aim to show why pediatric suffering must be understood as a judgment or evaluation, rather than a mental state. To accomplish this task, first I...     

The speciation of behavior analysis

The relationship between the Experimental Analysis of Behavior (EAB) and Applied Behavior Analysis (ABA) has been the subject of several editorials and commentaries in recent years. Various authors have argued that researchers in these two fields (a) have become isolated from each other, (b) face different requirements for survival in their respective fields, and (c) possess different skills to meet those requirements. The present paper provides an allegory for the relationship between EAB and ABA in terms of biological speciation. The conditions that have changed the relationship between EAB and ABA are parallel to those responsible for biological speciation: (a) isolation of some members of a species from the rest of the population, (b) different contingencies of survival for members of the two separate groups, and (c) divergence in the adaptive characteristics displayed by the two groups. When members of two different groups, descendants of common ancestors, no longer are capable of producing viable offspring by interbreeding, the different groups then represent different species. To the extent that members of the EAB group and members of the ABA group interact with each other only trivially, they each represent allegorically different species. Changes in the relationship between EAB and ABA are part of a natural process that takes place in many other sciences, and the course of that process can hardly be reversed by us.     

Multilevel analysis of matching behavior

Multilevel modeling has been considered a promising statistical tool in the field of the experimental analysis of behavior and may serve as a convenient statistical analysis for matching behavior because it structures data in groups (or levels) to account simultaneously for the within‐subject and between‐subject variances. Heretofore, researchers have sometimes pooled data erroneously from different subjects in a single analysis by using average ratios, average response and reinforcer rates, aggregation of subjects, etc. Unfortunately, this leads to loss of information and biased estimations, which can severely undermine generalization of the results. Instead, a multilevel approach is advocated to combine several subjects' matching behavior. A reanalysis of previous data on matching behavior is provided to illustrate the method and point out its advantages. It illustrates that multilevel regression leads to better estimations, is more convenient, and offers more behavioral information. We hope this paper will encourage the use of multilevel modeling in the statistical practices of behavior analysts.