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The etiological significance of neurological disorders in autism is debated, but it is clear that they complicate support provision and clinical management, and can have negative impact on outcomes. This systematic review and meta-analysis explored the full range of co-occurring neurological disorders in autism. We estimated the odds of having neurological complications compared to the general population and other neurodevelopmental conditions, as well as the overall prevalence of different neurological disorders. Seventy-nine articles were eligible for the systematic review, including 28 case-control studies, 43 prevalence studies, and 8 cohort studies. Findings were heterogeneous across studies. Overall, autistic individuals were significantly more likely than the general population to exhibit epilepsy, macrocephaly, hydrocephalus, cerebral palsy, migraine/headache, and congenital abnormalities of the nervous system, with prevalence estimates ranging from 1.1% (0%-3.3%; hydrocephalus) to 14.2% (11.3%-17.2%; epilepsy). Epilepsy was also more common in autism than in attention-deficit/hyperactivity disorder (odds ratio [95% confidence interval] = 4.06 [2.81-5.88]). Findings indicate that awareness of neurological disorders and neurological check-ups are indicated in autism to ensure adequate physical health care and support. Prospective studies of neurological disorders in children diagnosed with or at risk of autism might further enhance our understanding of causal pathways.

Computer simulation has significant potential as a supplementary tool for effective conceptual-change learning based on the integration of technology and appropriate instructional strategies. This study elucidates misconceptions in learning on diodes and constructs a conceptual-change learning system that incorporates prediction-observation-explanation (POE) and simulation-based learning strategies to explore the effects on correcting misconceptions and improving learning performance. Thirty-four sophomore students majoring in engineering participated in the experiments. The empirical results indicate that the system significantly corrects participants' misconceptions on diodes and improves learning performance. This study shows that conceptual change instructions could correct misconceptions effectively by constructing scenarios that conflict with existing knowledge structures. The results also show that misconceptions on diode models and semiconductor characteristics could be corrected in more than 80% of cases. Conversely, difficulty in correcting misconceptions correlates with the fundamental definition of voltage, circuit analysis, or the interaction between different diode concepts.