Edited by: Guido P. H. Band, Leiden University, Netherlands
Reviewed by: Dietsje Jolles, Stanford University, USA; Pier Prins, University of Amsterdam, Netherlands
*Correspondence: Zuowei Wang, Combined Program in Education and Psychology, University of Michigan, 610 E. University Ave., Room 1400-J, Ann Arbor, MI 48109, USA e-mail:
This article was submitted to the journal Frontiers in Human Neuroscience.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Cognitive training studies yield wildly inconsistent results. One dimension on which studies vary is the scheduling of training sessions (Morrison and Chein,
Working memory is the cognitive system that actively maintains and processes information for human problem solving (Miyake and Shah,
The significance of working memory training is largely dependent on the potential transfer effects to other untrained situations. Due to the various transfer effects identified by previous studies, some researchers view working memory training as promising for general cognition enhancement (see the review by Morrison and Chein,
Efforts have been taken to investigate factors that affect successful training and transfer. Three broad classes of factors are likely relevant: individual characteristics of participants receiving training, the nature of the training task, and conditions of training. Individual characteristics that affect training and transfer may include initial ability of participants, the underlying source of any deficits in working memory performance, and motivational factors. Research in our laboratory has found, for example, that individuals who believe that intelligence is a malleable construct are more likely to benefit from training than those who believe intelligence is fixed (Jaeggi et al.,
The nature of the training task(s), of course, will also influence what types of transfer might be found. In a classic review of training and transfer, Schmidt and Bjork (
A third class of factors that affect the effectiveness of cognitive training is the dosage or sheer amount of training (Jaeggi et al.,
Shebilske et al. (
There are many theoretical explanations for the spacing effect, most of which are not mutually exclusive. Spaced learning is consistent with rational models of memory that assume memory is adaptive (Anderson and Schooler,
In summary, the spacing effect in memory may shed light on the understanding of similar effects in cognitive training. However, cognitive training also has some unique features. The increase in the capacity and speed of cognitive processing cannot be treated similarly as the acquisition of new knowledge. For example, the spacing effect in cognitive training may also show different patterns than that in memory: the spacing effect in memory tasks may be a result of more covert rehearsal, whereas in skill acquisition (such as motor behavior), it is likely to be related to “effort, work, reactive inhibition, or fatigue” (Adams,
Currently, we are not aware that any working memory training studies have systematically varied the schedule under which individuals are trained to investigate the effect of training on outcome. A potential spacing effect in working memory training has both theoretical significance and important practical implications. Theoretically, a systematic investigation of the spacing effect in working memory training may help clarify the mixed findings in the current working memory training literature. Studies have revealed different effect size in training gains and training transfers, which could be a result of uncontrolled training schedule. In practice, an optimized training schedule may produce stronger and broader training gains in a shorter time, which cuts the training cost and allows more people to benefit from it.
In the current study, we investigated the effect of different training schedules on the outcome of working memory training in 5th grade classes in Muling, China. We used the same intervention that was originally used in Zhao et al. (
Based on the body of research on spacing, memory, and skill acquisition, we predicted that training schedule would have a substantial impact on working memory training gain and transfer. Specifically, we predicted that the group(s) with the most spacing of training would improve most on the training task and furthermore show the most transfer. In addition to this primary goal, we wished to replicate the results of other studies that have trained memory updating and found transfer to fluid intelligence in children (Jaeggi et al.,
A total of 115 5th grade students (10–11 years old) from Muling Shiyan Elementary School (Muling, China) were recruited to participate in the study. Before the training, they were told that upon finishing the training they would receive different gifts based on their performance in the training, including school bags, fountain pens and lockable notebooks. Twenty subjects were unable to strictly follow their assigned training schedule, or were absent during the pre-test or post-test thus dropped out from the study, resulting of 95 valid subjects in the data analysis (52 female). There was no group difference on the dropout rate, ×2 (4,
Participants were randomly assigned into one of the four training groups or an active control group. All the four training groups received the same total amount of training: 20 sessions of training with 60 trials for an average of 20 min per session. The training was spread across 2, 5, 10, or 20 days. The control group stayed with their teachers in their classrooms (after school) for 20 min each day for 20 days and received instruction focused primarily on math. The gender distribution in the five groups was: 20 Days—9 female 11 male; 10 Days—11 female 9 male; 5 Days—12 female 8 male; 2 Days—10 female 5 male; control group—10 female 10 male.
Before and after training, participants were all tested on a measure of fluid intelligence, the Raven's Standard Progressive matrices test. We compared pre-test to post-test improvements in the five groups (four training and one control) to assess transfer.
We used two forms of the “running span” task for the training (Zhao et al.,
Each session consisted of participants performing one set of animal and one set of grid trials. Each set consisted of 30 trial sequences that were divided into six blocks of five trials each. Within each block, if subjects provided the correct response for three or more trials, the presentation time of each stimulus in the next block would decrease by 100 ms, thus making the task more difficult. If participants got fewer than three trials correct, the presentation time of each stimulus would increase by 100 ms, which made the next block easier. For both the Animal and the Grid tasks, the starting presentation time was 850 ms for the 20, 5, and 2 days groups. The starting presentation time for the 10 days group was about 1000 ms for the Animal task and 950 ms for the Grid task (this was due to a computer error: the recovery mode of the training computers wasn't turned off and the 10 days group started from where the 20 days group left after their first session).
We decided that subjects' performance on the training tasks could be reflected by the presentation time of the stimulus. To track their training performance, we calculated the averaged presentation time for each session (both Animal and Grid), and named this measure as “presentation time” for that set of the session hereafter. To encourage children to try their best on the training tasks, correct response on each trial would earn them one point, which was shown by adding one smiley face to a feedback chart which was located at the bottom of the screen. The total points (smiley faces) could be used to trade for different gifts (school bags, fountain pens and lockable notebooks) after the training. More detailed descriptions of the training tasks can be found in Zhao et al. (
When the 20 days training group received the daily training, the active control group remained in their classroom and worked with their math teachers. They received extra math exercises from a 5th grade mathematics workbook for 20 min every day. Students first worked on problems from the workbook, and then the teacher checked their answers and provided further instruction when necessary. Some example problems the students practiced include: solving equations with one variable, calculating the area of different shapes that required them to divide the shapes into regular shapes with known formulas for area calculation, word problems (e.g., calculating the distance of moving objects, sometimes requiring the use of equations) etc. No rewards were provided for the control group.
The Raven's Standard Progressive Matrices (SPM) was used to evaluate the transfer effect of the training, following the design of a number of working memory training studies (e.g., Jaeggi et al.,
All children in the training groups were given one half of the SPM (even or odd items) as a pre-test before they started the training. Whether they received odd or even items at pre-test was counterbalanced. Children in all the groups were given the pre-test within the same 3 days prior to the training on the 20 days group. Thus, the distance between pre-test and post-test for all groups was approximately the same.
During the training, each training session consisted of one set of Animal task and one set of Grid task. Children in the 20 days group received one session every day after school, which took about 15–25 min. Children in the 10 days group received one session during the 2-h-long noon recess (for 15–25 min) and another session after school (another 15–25 min). Children in the 5 days group received two sessions during the noon recess (i.e., 30–50 min) and another two sessions after school (an additional 30–50 min). Children in the 2 days group received the training after the semester, and they finished the 20 total sessions within 2 days (approximately 10 sessions per day for a total of 150–250 min each day with rest and lunch breaks). For the 5 Days and 2 Days group, children were given a 5–10 min rest after approximately every 30–40 min of training. In all the groups, the very first training session was used as a practice session in which children were allowed to stop and ask questions. Thus, training data for the first session was not recorded and not included in the analysis.
After the training, children were given the alternate version of the SPM as a post-test. For the 5 and 2 days group, the SPM was administered the day following training completion to prevent decreased performance due to training fatigue. We were mindful about keeping the time interval between the pre-test and post-test the same for all the five groups. However, due to scheduling difficulties this interval for the 5 and 2 Days group was about 1 week longer.
Children in all the groups strictly adhered to their training schedule. Before weekends or holidays, we made arrangements with all the parents to make sure their children would come to school for the training. Three children in the 20 Days group and 2 in the 10 Days group who lived too far to get to the school received the training at home with the experimenter overseeing their training using remote desktop.
Children in none of the groups were given any information about how the Raven's pre- and post-tests may be related to training/math learning. Before working on the Raven's tests, they were just told that they were to work on some puzzles. Children in all the four training groups were motivated to earn more points by correctly recalling animals/grid locations during the training for better reward; children in the control group were motivated to learn math because they were to receive a math test after the 20 days.
The study was reviewed and approved by the Institutional Review Board at the University of Michigan. Informed consent was obtained from all the parents whose children participated in the study. Before each training/testing session, oral assent was also obtained from all the children who participated.
The five groups had similar scores in the Raven's pre-test,
20 Days group | −246 | −2.30 | 0.033 | 19 | −691 | −8.69 | <0.001 | 19 |
10 Days group | −481 | −3.57 | 0.002 | 18 | −722 | −5.12 | <0.001 | 18 |
5 Days group | −124 | −0.675 | 0.507 | 19 | −743 | −11.9 | <0.001 | 19 |
2 Days group | −165 | −1.54 | 0.147 | 14 | −502 | −4.62 | <0.001 | 13 |
Training gain can also be measured by the regression slope of presentation time (defined in Training task) on session number as an indication of the session-by-session processing speed improvement. In both Figures
20 Days Group | −74(32) | −261(47) |
10 Days Group | −156(47) | −247(50) |
5 Days Group | −43(75) | −265(32) |
2 Days Group | −41 (43) | −187(54) |
It should be noted that subjects' accuracy was also tracked. However, due to the nature of the task, subjects' accuracy only improved during the first few sessions and then remained stable. This is because if their accuracy in a given block (five trials), the presentation speed would become faster in the next block.
A Paired-sample
20 Days group | 2.93 | 19 | 0.009 | 1.34 |
10 Days group | 1.27 | 19 | 0.220 | 0.58 |
5 Days group | 0.95 | 19 | 0.355 | 0.44 |
2 Days group | 0.19 | 14 | 0.854 | 0.10 |
0 Days group (Control) | 0.19 | 19 | 0.855 | 0.09 |
Table
To provide further support for the idea that practice on the running span task was directly related to improvement on the transfer measure of fluid intelligence, the SPM, we assessed the relationship between improvement on the training task and the magnitude of the transfer effect. Each subjects' training gain is measured by the averaged session-by-session presentation time decrease (i.e., processing speed increase), which is calculated as the regression slope of each subject's presentation time by the session number. The magnitude of the transfer effect is the score difference between SPM post-test and pre-test. Table
This study assessed the effect of spacing of working memory training on the Raven's SPM. We predicted that spacing of training would affect both training gains as well as transfer, but found that there were no significant differences in training gain (as measured by reaction time) across the groups. Importantly, however, we did find a significant effect of training schedule on
β | ||||
---|---|---|---|---|
Pre-test | 0.279 | 0.078 | 0.349 | <0.001 |
Pre-test | 0.289 | 0.077 | 0.361 | <0.001 |
Training schedule | 0.076 | 0.038 | 0.189 | =0.052 |
20 Days group ( |
−0.465 |
10 Days group ( |
+0.046 |
5 Days group ( |
−0.015 |
2 Days group ( |
−0.135 |
We can draw two main conclusions from this study. First, training schedule has a significant impact on transfer of training. Second, the transfer effect of the 20-day group replicated results of a recent study that used the identical training and transfer tasks (Zhao et al.,
One question that arises is why this study and some others find far transfer effects whereas others do not. As discussed above, our study had several features associated with successful training studies: we tested children and not adults (Morrison and Chein,
Interestingly, our study found that training task improvements, at least in the group that received training across 20 days, was correlated with improvement in the transfer task. This result is consistent with the Jaeggi et al. (
As the first study that we are aware of that explores the spacing effect in working memory training, the current study has some limitations that need to be addressed by future research. First, the four different training schedules we used did not fully represent the schedule variation of the current training studies. According to Morrison and Chein (
In conclusion, this study demonstrated that training schedule has substantial impact on transfer of training. More research that investigates the moderators of training may help shed light on the debate of whether working memory training leads to broader cognitive improvement.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The study was supported by the Rackham Graduate Student Research Grant awarded to Zuowei Wang. The authors thank Yanmei Ma, Yong Feng (school principals), Xiaoxia Xie, Changyan Liu, Xueqiang Liu, and Hongli Li and all other teachers at Muling Shiyan Elementary School for helping make arrangement with the data collection. The authors also thank all the students and parents for participating in the study.