ISSN 0439-755X
CN 11-1911/B

心理学报 ›› 2017, Vol. 49 ›› Issue (8): 1022-1030.doi: 10.3724/SP.J.1041.2017.01022

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朱祖德1;  段懿行2;  王穗苹2   

  1.  (1江苏师范大学语言科学与艺术学院; 江苏省语言与认知神经科学重点实验室; 语言能力协同创新中心, 徐州 221009) (2华南师范大学心理学院, 广州 510631)
  • 收稿日期:2015-12-24 出版日期:2017-08-25 发布日期:2017-06-25
  • 通讯作者: 朱祖德, E-mail: E-mail: E-mail:
  • 基金资助:

 The baseline fluid intelligence modulated the transfer effect from working memory to fluid intelligence

 ZHU Zude1; DUAN Yixing2; WANG Suiping2   

  1.  (1 School of Linguistic Sciences and Arts, Jiangsu Normal University, Xuzhou 221009, China) (2 School of Psychology, South China Normal University, Guangzhou 510631, China)
  • Received:2015-12-24 Online:2017-08-25 Published:2017-06-25
  • Contact: ZHU Zude, E-mail: E-mail: E-mail:
  • Supported by:

摘要:   本研究考察了流体智力基线水平对工作记忆训练迁移效果的影响。采用前后测设计, 以视觉和听觉双任务n-back作为工作记忆训练任务, 对训练组进行为期一个月的训练; 积极对照组采用阅读任务进行训练。结果发现积极控制组的流体智力水平在基线与后测之间无显著变化; 而训练组流体智力水平在后测时与基线相比有显著提高, 且工作记忆训练提升量越大的个体其流体智力改善越大。说明认知训练有效迁移到了流体智力水平的改善上。我们还发现流体智力基线水平调节了工作记忆训练对流体智力水平的迁移, 即工作记忆训练提升量越大, 流体智力改善值越大, 对于那些流体智力基线水平较高的人来说, 工作记忆训练对流体智力改善的效果更大。流体智力基线水平、工作记忆训练提升量及两者的乘积共同影响了流体智力改善值。这一结果表明个体差异如流体智力基线水平可以调节工作记忆训练对流体智力水平的迁移。

关键词:  工作记忆训练, 流体智力, 个体差异, 迁移效应

Abstract:  While some previous studies have found significant transfer effect from working memory to fluid intelligence, other studies have failed. The discrepancy may due to individual difference. One type of individual differences is the working memory training improvement. It was found that, transfer effect was found only in subjects who showed significant training improvement. Another type of individual differences is the cognitive ability at baseline, such as baseline fluid intelligence. It remains unclear how such individual differences modulate transfer effect in working memory training. Specifically, the aim of the present study was to investigate how the individual fluid intelligence at baseline modulates the working memory transfer effect. In total, 40 college students were recruited and randomly assigned into active control group (N = 19, 8 males/ 11 females) and training group (N = 21, 9 males /12 females). The training group was asked to complete a dual n-back task. The participants were asked to perform the training 25 minutes a day, 5 days per week in four weeks. The dual n-back task was computerized, in which participants were required to determine if the stimulus position and voice in the current trial were the same as that in the previous n-1 trial. The n was adaptively changed according to the participants’ performances. Meanwhile, the active control group received a scientific knowledge reading training. To make sure the participants’ engaged in the task, the reading material was different for each time. The training time setting in the active control group was the same as that in the training group. All participants were tested by the Raven’s Standard Progressive Matrices (RSPM) before and after the training. In order to avoid the impact of repeated measures, the RSPM were divided into two parallel tests and were counterbalanced across groups and test sessions. The training group showed significant improvement in the dual n-back task, with an average maximum n = 4.86 and mean improved n = 2.51 after 20 days training. In addition, the results have revealed three key findings. First, we found significant group by test session interaction. Specifically, while the RSPM scores were comparable across test sessions in the active control group, the score of RSPM was significantly improved in the post-test than the baseline in the training group. Secondly, to reveal the potential interaction between baseline intelligence and training score improvement on the transfer effect, comparison of moderators was performed by using hierarchy regression. The results revealed that, intelligence improvement was positively correlated with working memory training improvement and negatively correlated with baseline intelligence performance. Additionally, the interaction term of training improvement and baseline intelligence performance positively correlated with intelligence gain. The interaction suggests that, a person can gain the best if he/she showed highest baseline intelligence performance and highest working memory training improvement. In summary, the current study confirmed that working memory training can improve fluid intelligence. More importantly, the results demonstrated that individual difference, i.e. the baseline level of the fluid intelligence in the current project, has modulated the transfer effect from working memory training to fluid intelligence. The results thus suggested that, future studies should pay more attention on individual difference, to reveal the trainability or transfer gain variance across participants.

Key words:  working memory training, fluid intelligence, individual difference, transfer effect