CREATING SINGLE‐SUBJECT DESIGN GRAPHS IN MICROSOFT EXCEL™ 2007

Over 10 years have passed since the publication of Carr and Burkholder's (1998) technical article on how to construct single‐subject graphs using Microsoft Excel. Over the course of the past decade, the Excel program has undergone a series of revisions that make the Carr and Burkholder paper somewhat difficult to follow with newer versions. The present article provides task analyses for constructing various types of commonly used single‐subject design graphs in Microsoft Excel 2007. The task analyses were evaluated using a between‐subjects design that compared the graphing skills of 22 behavior‐analytic graduate students using Excel 2007 and either the Carr and Burkholder or newly developed task analyses. Results indicate that the new task analyses yielded more accurate and faster graph construction than the Carr and Burkholder instructions.     

On the link between mind wandering and task performance over time

Here we test the hypothesis that fluctuations in subjective reports of mind wandering over time-on-task are associated with fluctuations in performance over time-on-task. In Study 1, we employed a singleton search task and found that performance did not differ prior to on- and off-task reports, nor did individual differences in mind wandering predict differences in performance (so-called standard analytic methods). Importantly however, we find that fluctuations in mind wandering over time are strongly associated with fluctuations in behavior. In Study 2, we provide a replication of the relation between mind wandering and performance over time found in Study 1, using a Flanker interference task. These data indicate (1) a tight coupling between mind wandering and performance over time and (2) that a temporal-analytic approach can reveal effects of mind wandering on performance in tasks where standard analyses fail to do so. The theoretical and methodological implications of these findings are discussed.     

USING MICROSOFT OFFICE EXCEL® 2007 TO CONDUCT GENERALIZED MATCHING ANALYSES

The generalized matching equation is a robust and empirically supported means of analyzing relations between reinforcement and behavior. Unfortunately, no simple task analysis is available to behavior analysts interested in using the matching equation to evaluate data in clinical or applied settings. This technical article presents a task analysis for the use of Microsoft Excel to analyze and plot the generalized matching equation. Using a data‐based case example and a step‐by‐step guide for completing the analysis, these instructions are intended to promote the use of quantitative analyses by researchers with little to no experience in quantitative analyses or the matching law.     

Self-efficacy expectations and coping with career-related events

The process of self-efficacy expectation development, coping with a difficult task, and task performance is examined using a path analytic framework. A model of this process is examined with a job interview task as a way of assessing the generalizability of self-efficacy theory to career-related behavior. Results show that self-efficacy expectation theory generalizes to a career-related task, and that emotion-focused coping mediates the relationship between self-efficacy expectations and perceived performance, but not performance as assessed by the interviewer. The importance of self-efficacy expectations and emotion-focused coping as mediating the relationship of perceived past performance and pretask anxiety with subsequent behavior and outcomes is discussed.     

Recoding low-level simulator data into a record of meaningful task performance: The integrated task modeling environment (ITME)

The Integrated Task Modeling Environment (ITME) is a user-friendly software tool that has been developed to automatically recode low-level data into an empirical record of meaningful task performance. The present research investigated and validated the performance of the ITME software package by conducting complex simulation missions and comparing the task analyses produced by ITME with taskanalyses produced by experienced video analysts. A very high interrater reliability (> or = .94) existed between experienced video analysts and the ITME for the task analyses produced for each mission. The mean session time:analysis time ratio was 1:24 using video analysis techniques and 1:5 using the ITME. It was concluded that the ITME produced task analyses that were as reliable as those produced by experienced video analysts, and significantly reduced the time cost associated with these analyses.     

Comparing self‐directed methods for training staff to create graphs using Graphpad Prism

An important skill for behavior analysts is creating graphs that clearly convey outcomes and conform to publication conventions. GraphPad Prism is software designed for creating scientific graphs, but no prior research has empirically evaluated training graphing skills using Prism. Two effective training methods are enhanced written instructions (EWI) and video modeling with voiceover instructions (VMVO), but no single‐subject studies have compared the effects of these methods. In this study, we compared the efficacy and social validity of EWI and VMVO for training staff to create graphs using Prism. A single‐subject design was employed to compare the effects of the methods on the individual performance of 11 graduate students. EWI and VMVO were both found to be effective, and more participants chose to use EWI.     

Introduction to the Special Issue: The Influence of Cultural and Linguistic Variables on Student Behavior and Academic Performance

Although focus on linguistic and cultural variables in education has been a priority at the federal level, few empirical papers reporting experimental analyses of the influence of these variables have been published. The goal of this special issue is to highlight recent experimental analyses of cultural or linguistic variables on student behavior or academic performance and to illustrate the challenges in translating an applied behavior analytic approach across languages and cultures. The special issue is comprised of studies that address three issues relevant to behavioral education: (1) comparative effects of providing academic instruction or addressing challenging behavior of children with intellectual and developmental disorders in English or their home language of Spanish, (2) delivering effective instructional practices with students from diverse racial and cultural groups, and (3) considerations regarding the translation of applied behavior analysis in education for adoption in a different language and culture.     

The influence of alcohol and loud music on analytic and holistic processing

The influence of alcohol and loud music on analytic versus holistic processing was examined in classification, concept learning, and embedded figures tasks. In the classification task, loud music reduced analytic responding by individuals who had consumed alcohol and increased analytic responding by individuals who had received placebo drinks. Alcohol also decreased the speed with which individuals were able to generate analytic responses in the classification task and decreased analytic performance on the embedded figures test. Alcohol slowed the rate of learning in the concept-learning task but did not lead to less analytic responding in that task. The results are consistent with the idea that alcohol slows the rate of information processing, particularly in tasks requiring visual analysis of stimuli.     

Comparing instructor-led,video-model,and no-instruction control tutorials for creating single-subject graphs in Microsoft Excel: A systematic replication and extension

Visual inspection of single-subject data is the primary method for behavior analysts to interpret the effect of an independent variable on a dependent variable; however, there is no consensus on the most suitable method for teaching graph construction for single-subject designs. We systematically replicated and extended Tyner and Fienup (2015) using a repeated-measures between-subjects design to compare the effects of instructor-led, video-model, and no-instruction control tutorials on the graphing performance of 81 master's students with some reported Microsoft Excel experience. Our mixed-design analysis revealed a statistically significant main effect of pretest, tutorial, and posttest submissions for each tutorial group and a nonsignificant main effect of tutorial group. Tutorial group significantly interacted with submissions, suggesting that both instructor-led and video-model tutorials may be superior to providing graduate students with a written list of graphing conventions (i.e., control condition). Finally, training influenced performance on an untrained graph type (multielement) for all tutorial groups.     

A Meta-Analytic Investigation of the Relationship Between State Affect,Discrete Emotions,and Job Performance

The relationship between affect and job performance has been the topic of previous meta-analytic investigations. However, these studies have been limited by their focus on only one form of affect, trait dimensional affect, or failure to differentiate between various forms of affect, such as state affect and emotions. The present study extends past research by meta-analytically examining the association between state dimensional affect and discrete emotions and three dimensions of job performance, task performance, organizational citizenship behavior, and counterproductive work behavior. In addition, we examined subgroup differences according to the temporal consistency of performance and affect measurement, and we reviewed studies that assessed the affect–performance link using within-person analyses in the context of experience sampling designs.     

A primer for using multilevel models to meta-analyze single case design data with AB phases

Meta-analytic methods provide a way to synthesize data across treatment evaluation studies. However, these well-accepted methods are infrequent with behavior analytic studies. Multilevel models may be a promising method to meta-analyze single-case data. This technical article provides a primer for how to conduct a multilevel model with single-case designs with AB phases using data from the differential-reinforcement-of-low-rate behavior literature. We provide details, recommendations, and considerations for searching for appropriate studies, organizing the data, and conducting the analyses. All data sets are available to allow the reader to follow along with this primer. The purpose of this technical article is to minimally equip behavior analysts to complete a meta-analysis that will summarize a current state of affairs as it relates to the science of behavior analysis and its practice. Moreover, we aim to demonstrate the value of analyses of this sort for behavior analysis.