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Interteaching is a behavioral teaching method that has demonstrated efficacy in higher education. Of particular interest is the use of a preparation guide (a guided reading assignment), which is designed to promote engagement in the other areas of the interteaching process. The present study compared the use of a preparation guide completed before the start of class with that of a quiz administered at the start of the class. The quiz was hypothesized to serve as a functional alternative to the preparation guide. A total of 38 undergraduate students enrolled in an Introduction to Psychology course participated in this study. The primary dependent measure was student performance on tests following each condition. The analysis revealed no statistically significant difference between the conditions, F(1, 302) = 0.103, p = .748, though qualitative feedback revealed student preference for preparation guides. Future research is necessary to examine the effects of quizzing while addressing the limitations of this study.

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This study compares the effectiveness and efficiency of constant time delay (CTD) and simultaneous prompting (SP) to teach decoding and word reading to four students, 7 to 9 years of age, with intellectual disabilities (ID) in the mild to moderate range. An adapted alternating treatment design was implemented to assess the two methods. The results suggest that both procedures were equally effective. All four students learned to decode and read the instructional words. Maintenance data showed no substantial differences between the two teaching procedures. CTD was more efficient according to two efficiency measures since three students acquired the word sets taught with CTD in fewer sessions and trials. However, SP was more efficient in terms of the number and percentage of errors made and the instructional time needed for all four students. Two students were able to decode and read all or some of the generalization words, while the other two were able to decode a higher percentage of sounds within the words than before the teaching sessions. This study shows that CTD and SP are effective in improving reading skills for students with ID.

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Multiple quantitative methods for single-case experimental design data have been applied to multiple-baseline, withdrawal, and reversal designs. The advanced data analytic techniques historically applied to single-case design data are primarily applicable to designs that involve clear sequential phases such as repeated measurement during baseline and treatment phases, but these techniques may not be valid for alternating treatment design (ATD) data where two or more treatments are rapidly alternated. Some recently proposed data analytic techniques applicable to ATD are reviewed. For ATDs with random assignment of condition ordering, the Edgington's randomization test is one type of inferential statistical technique that can complement descriptive data analytic techniques for comparing data paths and for assessing the consistency of effects across blocks in which different conditions are being compared. In addition, several recently developed graphical representations are presented, alongside the commonly used time series line graph. The quantitative and graphical data analytic techniques are illustrated with two previously published data sets. Apart from discussing the potential advantages provided by each of these data analytic techniques, barriers to applying them are reduced by disseminating open access software to quantify or graph data from ATDs.

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The adapted alternating treatments design is a commonly used experimental design in skill acquisition research. This design allows for the evaluation of two or more independent variables on responding to unique target sets. Equating target sets is necessary to ensure a valid comparison of the independent variables. To date, there is little guidance on best practice when equating target sets and it is unclear how researchers have done so previously. We reviewed the reported methods used to equate target sets in articles published using the adapted alternating treatments design in five behavior-analytic journals. Just over half of the studies published using the adapted alternating treatments design reported any method to equate target sets and the methods varied considerably. Alternative methods, such as random assignment, were prevalent. Considerations for best practice and avenues for future research are discussed.

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Cover-copy-compare (CCC) is a self-managed intervention that relies on modeling, opportunities to respond, and corrective feedback to improve spelling. Refinements to CCC have been investigated to maximize its effectiveness and efficiency. One such refinement is the addition of a sounding-out step (CCC+SO). Because research investigating CCC+SO has yielded inconsistent results, the current study sought to further examine CCC+SO while addressing some of the methodological limitations of previous studies. An alternating-treatments design was used to compare CCC and CCC+SO on the cumulative number of spelling words acquired with three 2nd and 3rd graders. Participants practiced spelling words using CCC and CCC+SO and demonstrated considerable growth in spelling performance from baseline to intervention; however, there was little difference in cumulative spelling words acquired across conditions. Implications for practitioners and researchers, limitations, and future directions are discussed.

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Two common barriers to applying statistical tests to single-case experiments are that single-case data often violate the assumptions of parametric tests and that random assignment is inconsistent with the logic of single-case design. However, in the case of randomization tests applied to single-case experiments with rapidly alternating conditions, neither the statistical assumptions nor the logic of the designs are violated. To examine the utility of randomization tests for single-case data, we collected a sample of published articles including alternating treatments or multielement designs with random or semi-random condition sequences. We extracted data from graphs and used randomization tests to estimate the probability of obtaining results at least as extreme as the results in the experiment by chance alone (i.e., p-value). We compared the distribution of p-values from experimental comparisons that did and did not indicate a functional relation based on visual analysis and evaluated agreement between visual and statistical analysis at several levels of α. Results showed different means, shapes, and spreads for the p-value distributions and substantial agreement between visual and statistical analysis when α = .05, with lower agreement when α was adjusted to preserve family-wise error at .05. Questions remain, however, on the appropriate application and interpretation of randomization tests for single-case designs.

RESUMEN

Alternating treatments designs (ATDs) are single-case experimental designs entailing the rapid alternation of conditions, and the specific sequence of conditions is usually determined at random. The visual analysis of ATD data entails comparing the data paths formed by connecting the measurements from the same condition. Apart from visual analyses, there are at least two quantitative analytical options also comparing data paths. On option is a visual structured criterion (VSC) regarding the number of comparisons for which one conditions has to be superior to the other to consider that the difference is not only due to random fluctuations. Another option, denoted as ALIV (a comparison involving Actual and Linearly Interpolated Values), computes the mean difference between the data paths and uses a randomization test to obtain a p value. In the current study, these two options are compared, along with a binomial test, in the context of simulated data, representing ATDs with a maximum of two consecutive administrations of the same condition and a randomized block design. Both VSC and ALIV control Type I error rates, although these are closer to the nominal 5% for ALIV. In contrast, the binomial test is excessively liberal. In terms of statistical power, ALIV plus a randomization test is superior to VSC. We recommend that applied researchers complement visual analysis with the quantification of the mean difference, as per ALIV, and with a p value whenever the alternation sequence was determined at random. We have extended an already existing website providing the graphical representation and the numerical results.

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