Considerable research has been carried out in the last two decades on the putative benefits of cognitive training on cognitive function and academic achievement. Recent meta-analyses summarizing the extent empirical evidence have resolved the apparent lack of consensus in the field and led to a crystal-clear conclusion: The overall effect of far transfer is null, and there is little to no true variability between the types of cognitive training. Despite these conclusions, the field has maintained an unrealistic optimism about the cognitive and academic benefits of cognitive training, as exemplified by a recent article (Green et al., 2019). We demonstrate that this optimism is due to the field neglecting the results of meta-analyses and largely ignoring the statistical explanation that apparent effects are due to a combination of sampling errors and other artifacts. We discuss recommendations for improving cognitive-training research, focusing on making results publicly available, using computer modeling, and understanding participants’ knowledge and strategies. Given that the available empirical evidence on cognitive training and other fields of research suggests that the likelihood of finding reliable and robust far-transfer effects is low, research efforts should be redirected to near transfer or other methods for improving cognition.

在过去的二十年里，关于认知训练对认知功能和学业成绩的假定好处进行了大量研究。最近的荟萃分析总结了经验证据的程度，解决了该领域明显缺乏共识的问题，并得出了一个非常明确的结论：远距离转移的总体影响为零，认知类型之间几乎没有或没有真正的变异性训练。尽管得出了这些结论，该领域仍对认知训练的认知和学术益处保持不切实际的乐观态度，最近的一篇文章（Green 等人，2019 年）就是例证。我们证明这种乐观是由于该领域忽视了荟萃分析的结果，并且在很大程度上忽略了统计解释，即明显的影响是由于抽样误差和其他人为因素的组合。我们讨论了改进认知训练研究的建议，重点是公开结果、使用计算机建模以及了解参与者的知识和策略。鉴于有关认知训练和其他研究领域的可用经验证据表明，找到可靠且稳健的远迁移效应的可能性很低，因此研究工作应转向近迁移或其他改善认知的方法。使用计算机建模，并了解参与者的知识和策略。鉴于有关认知训练和其他研究领域的可用经验证据表明，找到可靠且稳健的远迁移效应的可能性很低，因此研究工作应转向近迁移或其他改善认知的方法。使用计算机建模，并了解参与者的知识和策略。鉴于有关认知训练和其他研究领域的可用经验证据表明，找到可靠且稳健的远迁移效应的可能性很低，因此研究工作应转向近迁移或其他改善认知的方法。