On the Representativeness of Behavior Observation Samples in Classrooms

Tiger, Jeffrey H.; Miller, Sarah; Mevers, Joanna Lomas; Mintz, Joslyn Cynkus; Scheithauer, Mindy; Alvarez, Jessica

doi:10.1002/jaba.39

Cited by 21 publications

(11 citation statements)

References 15 publications

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“…However, a small absolute difference (e.g., when a behavior is recorded as not occurring, or 0, but occurs during 1% of the timeof-interest, resulting in an absolute difference of 1%) may not sufficiently reflect true duration even though the absolute difference would fall on a AE1% absolute accuracy limit. We agree with the views of Tiger et al (2013) that acceptable error is likely to be judged according to the purposes of data collection, and thus we suggest that there are merits to evaluating both absolute and relative errors. Perhaps acceptable error varies with overall behavioral duration (e.g., absolute error of AE5% may be acceptable for behaviors that occur for 50% of the week but not for those that occur for 5% of the week).…”

Section: Discussionsupporting

confidence: 82%

“…Equation 1 calculates the required numbers of observations based on relative error (i.e., error as a percentage of the duration), which results in minute absolute-error margins for behaviors that occur for 10% or less of the week (e.g., when true duration is 1%, AE5% absolute error would result in margins of 0.95% and 1.05%). Tiger et al (2013) suggested that as Mudford et al (1990) reported relative error, small errors in measuring low-duration behaviors were amplified. Tiger et al therefore suggested that reporting absolute error allows for fairer comparisons of errors for high-and low-duration behaviors.…”

Section: Discussionmentioning

confidence: 99%

“…Consideration of representativeness is necessary when planning data collection in applied behavior analysis, because it is usually impractical to measure variables of interest throughout whole times-of-interest. Mudford, Beale, and Singh (1990) and Tiger et al (2013) have conducted studies that evaluated the representativeness of continuous samples. Mudford et al recorded behaviors on a computer in 150-min blocks for each participant, after which the computer was used to extract samples ranging from 15 to 135 min.…”

mentioning

confidence: 99%

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Representativeness of direct observations selected using a work‐sampling equation

Sharp

Mudford

Elliffe

2015

J of App Behav Analysis

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Deciding on appropriate sampling to obtain representative samples of behavior is important but not straightforward, because the relative duration of the target behavior may affect its observation in a given sampling interval. Work-sampling methods, which offer a way to adjust the frequency of sampling according to a priori or ongoing estimates of the behavior to achieve a preselected level of representativeness, may provide a solution. Full-week observations of 7 behaviors were conducted for 3 students with autism spectrum disorder and intellectual disabilities. Work-sampling methods were used to select momentary time samples from the full time-of-interest, which produced representative samples. However, work sampling required impractically high numbers of time samples to obtain representative samples. More practical momentary time samples produced less representative samples, particularly for low-duration behaviors. The utility and limits of work-sampling methods for applied behavior analysis are discussed.

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Section: Discussionsupporting

confidence: 82%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Representativeness of direct observations selected using a work‐sampling equation

Sharp

Mudford

Elliffe

2015

J of App Behav Analysis

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“…When using an Every Fifth PAC method, the data suggest that longer duration observations (e.g., 60 min) do not confer any substantial benefit over shorter duration (e.g., 10 min) observations. These results add to the literature suggesting that shorter duration observations may yield sufficiently representative estimates of behavior (e.g., Tiger et al, 2013).…”

Section: Discussionsupporting

confidence: 75%

The Accuracy of Peer Comparison Observations: A Simulated Analysis

Radley

Dart

Schrieber

et al. 2020

Behavioral Disorders

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Classroom observations are frequently conducted with the purpose of comparing the behavior of a target student to that of other peers within the same classroom. A variety of procedures may be utilized by researchers and practitioners to collect such data; however, little is known of the accuracy of estimates of behavior produced by such procedures relative to continuous behavior recording for the target student, peers sampled as a representation of the class, and the class as a whole. The purpose of the present study was to evaluate the accuracy of estimates of frequently utilized peer comparison observation procedures relative to duration recording. Data were simulated for 4,000 classroom observations, with variations in level of classroom behavior and length of observation being simulated. Results indicated that an Every Fifth interval procedure resulted in the lowest levels of absolute error during single observations for target students, with planned activity checks resulting in the most accurate estimates of class-wide behavior. Despite differences being apparent in level of accuracy of single observations, differences in accuracy across procedures were not apparent when all observations of the same type (i.e., duration, level of classroom behavior, and observation procedure) were compared.

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“…However, the number and length of observations required to obtain data related to the behavior of interest is not easily predicted. For example, Tiger et al () conducted 5‐hr observations of problem behavior exhibited by three children across four consecutive school days. In cases where behavior occurred with low variability, briefer observations (e.g., 10 min) were sufficient for obtaining an accurate sample of behavior.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the accuracy, reliability, efficiency, and acceptability of fast forwarding to score problem behavior

Machado

Luczynski

Hood

2018

J of App Behav Analysis

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Technological advances have allowed professionals to obtain extended recordings of caregiver–client interactions in natural settings, but scoring recorded video at normal speed to identify instances of low‐rate problem behavior is impractical in terms of scoring time. Fast forwarding is a continuous measurement system in which all seconds of an observation are viewed at a speed faster than normal. In Study 1, we evaluated whether three groups of five observers could discriminate problem behavior at three fast‐forwarding speeds across 10‐min observations. We analyzed the efficiency of using fast forwarding compared to continuous scoring, and interobserver agreement across the fast‐forwarding speeds. In Study 2, we compared the accuracy, efficiency, and social acceptability of fast forwarding (3.5x) and momentary time sampling (3.5 s) across 90‐min observations. Results support the use of 3.5x fast forwarding as a viable measurement system of improving the practicality of scoring problem behavior from video.

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On the Representativeness of Behavior Observation Samples in Classrooms

Cited by 21 publications

References 15 publications

Representativeness of direct observations selected using a work‐sampling equation

Representativeness of direct observations selected using a work‐sampling equation

The Accuracy of Peer Comparison Observations: A Simulated Analysis

Evaluation of the accuracy, reliability, efficiency, and acceptability of fast forwarding to score problem behavior

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