Educators need evidence-based practices to assist students with disabilities in meeting increasingly rigorous standards in mathematics. Students with autism spectrum disorder (ASD) are increasingly expected to demonstrate learning of basic and advanced mathematical concepts. This review identifies math intervention studies involving children and adolescents with ASD and describes participant characteristics, methodological features, interventions, target behaviors, and related outcomes. Included studies met the design standards of the What Works Clearinghouse (2014). Studies focused on functional and computational skills for students with a comorbid diagnosis of intellectual disability (ID). Visual analysis confirmed a functional relation between evaluated interventions and mathematics outcomes in 71% of cases. Interventions generally yielded moderate to large effect sizes. Large confidence intervals were obtained across effects. More high-quality research including students with higher-functioning ASD is required to fully address the needs of this population.

Social skills interventions designed to increase pro-social interactions for individuals with autism spectrum disorders are critical, but the relative effectiveness of these interventions is not well understood. More than 250 single-case design studies in 113 articles were reviewed and described in terms of participants, settings, arrangements, implementers, social partners, target behaviors, and treatment components. Differential success rates are reported, given the variation in study and participant characteristics (e.g., implementers, treatment components, participant age). Environmental arrangement, social skills training, and prompting were highly successful, and peer training, priming, and video-based interventions were less successful. More evidence is needed, particularly research including older individuals and utilizing indigenous implementers and typical social partners.

Replication is a critical aspect of scientific inquiry that presents a variety of challenges to researchers, even under the best of conditions. We conducted a review of replication rates in special education journals similar to the review conducted by Makel et al. in this issue. Unknowingly conducting independent reviews allowed for an unexpected opportunity to examine how two teams of researchers attempted to replicate a previously published study and explore similarities and differences between the outcomes. In our review, we identified 70 replication studies published between 1997 and 2013, indicating that 0.41% of published articles in special education journals are replication studies. Similar to findings reported by Makel et al., our review indicates that most replications are successful and that successful replications are more likely when author overlap occurs. Although there are similar patterns in the two data sets, an examination of exact agreement on article inclusion revealed an agreement rate of 15.2%. Possible explanations for the discrepancy and implications for future directions are provided.

Background: Shortages in qualified supervision and other resources prevent education personnel from rehearsing effective practices. Interactive simulations, although increasingly used in education, frequently require instructor management. Automated simulations rarely engage trainees in skills related to practice (eg, speech). Objective: We evaluated the capability of delivering behavioral skills training through an automated virtual reality (VR) simulation using artificial intelligence to improve the implementation of a nondirective mathematical questioning strategy. Methods: We recruited and randomly assigned 30 college-aged participants to equivalent treatment (ie, lecture, modeling, and VR; 15/30, 50%) and control groups (ie, lecture and modeling only; 15/30, 50%). The participants were blind to treatment conditions. Sessions and assessments were conducted face to face and involved the use of VR for assessment regardless of the condition. Lessons concerned the use of a nondirective mathematical questioning strategy in instances where a simulated student provided correct or incorrect answers to word problems. The measures included observed and automated assessments of participant performance and subjective assessments of participant confidence. The participants completed the pretest, posttest, and maintenance probes each week over the course of 3 weeks. Results: A mixed ANOVA revealed significant main effects of time (F2,27=124.154; P<.001; ηp2=0.816) and treatment (F1,28=19.281; P<.001; ηp2=0.408) as well as an interaction effect (F2,28=8.429; P<.001; ηp2=0.231) for the average percentage of steps in the questioning procedure. Posttest scores for the intervention group (mean 88%, SD 22.62%) exceeded those of the control group (mean 63.33%, SD 22.64%), with t28=3.653, P<.001, and Cohen d=1.334. Maintenance scores indicated a positive effect of the intervention (mean 83.33%, SD 24.40%) relative to the control (mean 54.67%, SD 15.98%), t28=3.807, P<.001, Cohen d=1.39. A Mann-Whitney U test indicated that the treatment groups’ self-ratings of confidence (mean 2.41, SD 0.51) were higher than those of the control group (mean 2.04, SD 0.52), U=64, P=.04, r=0.137. Conclusions: The results demonstrate the potential of artificial intelligence-augmented VR to deliver effective, evidence-based training with limited instructor management. Additional work is needed to demonstrate the cascading effect of training on authentic practice and to encompass a wider range of skills.