Improving junior high students’ thinking and creative abilities with an executive function training program

Accepted Manuscript Title: Improving Junior High Students’ Thinking and Creative Abilities with an Executive Function Training Program Authors: Wei-Lun Lin, Yi-Ling Shih, Sheng-Wei Wang, Yu-Wen Tang PII: DOI: Reference:

S1871-1871(18)30113-5 https://doi.org/10.1016/j.tsc.2018.06.007 TSC 518

To appear in:

Thinking Skills and Creativity

Received date: Revised date: Accepted date:

11-4-2018 21-6-2018 23-6-2018

Please cite this article as: Lin W-Lun, Shih Y-Ling, Wang S-Wei, Tang YWen, Improving Junior High Students’ Thinking and Creative Abilities with an Executive Function Training Program, Thinking Skills and Creativity (2018), https://doi.org/10.1016/j.tsc.2018.06.007 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

1

Improving Junior High Students’ Thinking and Creative Abilities with an Executive Function Training Program

U

SC R

Department of Psychology, Fo Guang University, Yilan, Taiwan

IP T

Wei-Lun Lin*, Yi-Ling Shih, Sheng-Wei Wang, Yu-Wen Tang

A

N

Corresponding author:

ED

Department of Psychology

M

* Wei-Lun, Lin

Fo Guang University, Taiwan

PT

No.160, Linwei Rd., Jiaosi Shiang, Yilan County, 26247, Taiwan

CC E

E-mail: [email protected] TEL: +886-3-9871000 ext. 27115

A

Fax: +886-3-9875530

2 Highlights   

Adolescents’ EFs are trained with a self-designed application system Participants perform reading aloud and arithmetic calculations for 20 sessions The training effectively improves adolescents’ thinking and creativity abilities

IP T

Abstract Executive functions (EFs) are closely related to thinking and creativity. Recent studies that

SC R

trained the elderly and other adults by reading aloud and performing arithmetic calculations

show their ability to enhance EFs. The present study adopts this program with a self-designed

U

application system on adolescents whose EF capabilities are in a period of extreme

A

N

development and explores its meta-transfer effects to improve adolescents’ thinking and

M

creative abilities. Thirty-eight junior high students were randomly assigned to the training

ED

and the active control group. After completing pretests on EFs, thinking, and creativity, the training group proceeded with reading aloud and arithmetic calculation activities, while the

PT

control group played the game Tetris for 20 15-minute sessions. The ANCOVAs on the

CC E

posttest performance indicated that the participants in the training group outperformed their control group peers on the thinking and creativity measures. These results demonstrate the

A

trainability and easy application of the program and its effectiveness on improving adolescents’ higher cognition. Keywords: executive function training, thinking, creativity, adolescence, reading and arithmetic calculations.

3

1. Introduction In the face of this rapidly changing era, the 21st-century 4C skills, which consist of creativity, critical thinking, communication, and collaboration, are crucial for the young

IP T

generation (Trilling & Fadel, 2009). Among these, creativity and critical thinking (i.e., a broad term of thinking; West, Toplak, & Stanovich, 2008) are two cognitive components

SC R

where creativity is humanity’s highest mental capacity to improve lives (Guilford, 1967) and thinking is related to important real-world problem solving in every domain (West et al.,

U

2008). How can we help students to enhance their thinking and creative abilities through the

A

N

education they acquire at school? Past studies that were dedicated to creativity or thinking

M

interventions mostly focused on environmental shaping (e.g., Antonietti, 2000; Dineen &

ED

Niu, 2008) or specific skill training (Benedek, Fink, & Neubauer, 2006; Dyson et al., 2016; Prowse, Turner, & Thompson, 2009). The present study aimed to inspect this issue from basic

PT

cognitive function intervention; that is, to improve junior high students’ thinking and creative

CC E

abilities by an executive function training program. 1.1. Executive functions in relation to thinking and creativity

A

Executive functions (EFs) are the basis of human information processing and comprise

the attentional control mechanism that fosters complex functions and behaviors involved in initiating, monitoring, planning, and engaging in goal-directed behaviors (Scibinetti, Tocci, & Pesce, 2011; Seiferth, Thienel, & Kirchner, 2007). Three basic components of EFs are

4

identified as “updating,” or to update and monitor mental representations in working memory to replace old, irrelevant information by new, relevant information; “shifting,” or to flexibly switch between multiple tasks, operations, or mental sets (Monsell, 1996); and “inhibition,”

IP T

or to deliberately control or suppress prepotent responses (Miyake & Friedman, 2012; Miyake, Friedman, Emerson, Witzki, & Howerter, 2000). These abilities are located in

SC R

human beings’ prefrontal cortex (Niendam et al., 2012; Ward, 2015). For example,

neuropsychological studies on patients who have experienced frontal lobe damage reveal

U

deficits in EF tasks, such as Tower of Hanoi problem that involves updating and the

A

N

Wisconsin Card Sorting Task (WCST) that involves shifting and inhibition (Miyake et al.,

M

2000). In addition, cognitive and neurophysiological evidence reveals that EF capabilities

ED

(and also the prefrontal cortex) continue to develop significantly throughout childhood and adolescence until young adulthood (Best & Miller, 2010).

PT

Theories and accumulating evidence have shown close relationships between EFs and

CC E

thinking performances. In dual-process theories (Evans & Stanovich, 2013; Sloman, 1996; Stanovich, 2011; Stanovich & West, 2000), theorists propose that humans possess two

A

alternative process types while performing a thinking task such as reasoning, problem solving, and decision making. Type 1 is assumed to process information in an intuitive and associative manner without capacity limits, while Type 2 involves reflective, analytical, and logical processes in which execution relied on cognitive resources. For instance, in a

5

syllogism problem, reasoners could judge the conclusion’s true or false status by the believability of its statement (Type 1 processing) and, hence, conduct the belief bias effect (Evans, 2003) or produce the normative answer by considering the logical relations in the

IP T

premises and conclusion (Type 2 processing). According to dual-process theories, whether reasoners operate Type 1 or Type 2

SC R

processing modes depends on their cognitive resources or EF capabilities (Evans &

Stanovich, 2013; Gilhooly & Fioratou, 2009). This notion gains empirical support from

U

significant relationships found between EFs and thinking performance in syllogisms (De

A

N

Neys, 2006; Handley, Capon, Beveridge, Dennis, & Evans, 2004), conditional reasoning (De

M

Neys, 2006), analogical reasoning (Waltz, Lau, Grewal, & Holyoak, 2000), rule discovery

ED

(Lin & Lien, 2013), problem solving (Gilhooly & Fioratou, 2009), decision making (Toplak, West, & Stanovich, 2011), and critical thinking (West et al., 2008). In Toplak, West, and

PT

Stanovich’s study (2014), students were recruited according to grade level (Grade 2-3, Grade

CC E

4-5, and Grade 6-9) to perform rational thinking tasks from heuristics and biases research tradition (denominator neglect, belief bias syllogisms, base rate sensitivity, resistance to

A

framing and otherside thinking task) and assessed their EFs performance. The working memory task (Gottardo, Stanovich, & Siegel, 1996) was used to measure updating, the Trail Making Test (TMT; Reitan, 1958) was used to measure shifting, and the Stroop Task (Stroop, 1935) was used to measure inhibition. The results revealed that the EF composite score was

6

significantly correlated to all five thinking domains and was the most powerful predictor to thinking performance across different grade levels. The relationships between EFs and creativity were also demonstrated. In a review by

IP T

Dietrich and Kanso (2010), 64 cognitive neuroscience studies using different neuroimaging techniques to inspect the localization of different creativity performances showed that all

SC R

converge in the prefrontal region where EFs originate (Ward, 2015). In another study

(Benedek, Jauk, Sommer, Arendasy, & Neubauer, 2014), researchers used the nonverbal 2-

U

back (Schelling, Schuri, & Arendasy, 2011) and the Stroop Task (Stroop, 1935) to assess

A

N

participants’ updating and inhibition abilities. Participants’ divergent thinking performance

M

was measured by two alternate use tasks (to list uses for a tin and for a car tire) and two

ED

instance tasks (to list instances that can be round and can be used for speedy travel). The results showed that divergent thinking performance was significantly predicted by these two

PT

EF components. Studies that used the working memory task to assess updating (Gilhooly &

CC E

Fioratou, 2009; Gilhooly & Murphy, 2005; Lin & Lien, 2013) and the switching task (Dreisbach & Goschke, 2004) to assess shifting (Lin, Tsai, Lin, & Chen, 2014) revealed

A

significant correlations with insight problem-solving performances. In addition, Storm and Angello (2010) used the retrieval-induced forgetting task (Anderson, Bjork, & Bjork, 1994) to assess participants’ inhibition ability and found that participants high in inhibition could better resist dominant associations and performed more correctly in the Remote Associates

7

Test (RAT) to find an associative concept among three concepts (Mednick & Mednick, 1967). The above results revealed the important role of EFs in thinking and creativity. 1.2. Executive Function Training

IP T

Given the importance of EFs in thinking and creativity, whether we could improve ones’ thinking and creative abilities by enhancing their EFs is a feasible investigation. According to

SC R

the work of Enriquez-Geppert, Huster, and Herrmann (2013), EF training programs are divided into neuroscientific and behavioral categories. In the neuroscientific training

U

category, neuro stimulation on the prefrontal cortex by transcranial magnetic stimulation

A

N

(TMS) or a neurofeedback procedure (e.g., providing feedback on participants’ optimal brain

M

wave patterns, says, peak alpha frequency 10-11 Hz; Angelakis, Stathopoulou, Frymiare,

ED

Green, Lubar, & Kounios, 2007) were often utilized. Although its rationale was based on neural plasticity to fundamentally change prefrontal activities or structures, as well as its

PT

effectiveness in improving EF task performance, neuroscientific training is considered to be

CC E

difficult in widespread application. On the other hand, past behavioral training mostly focused on a training-specific EF task. For example, researchers had participants practice on

A

the number-letter task (Rogers & Monsell, 1995) for shifting ability training (Minear & Shah, 2008) and the stop signal task (Logan, 1994) for inhibition ability training (Thorell, Lindqvist, Bergman Nutley, Bohlin, & Klingberg, 2009). Significant improvements were found on the same tasks in posttests. However, far transfer effects (improvements on another

8

EF skill) or meta-cognitive transfer effects (improvements in other higher cognition or everyday behaviors) were not evident. Recently, the positive impact of physical training on cognition was widely addressed. For instance, studies have shown improvements on the

IP T

Stroop task after aerobic exercise (Chang & Etnier, 2009; Sibley, Etnier, & Le Masurier, 2006) and on visual-spatial memory after 18 running sessions (Stroth, Hille, Spitzer, &

SC R

Reinhardt, 2009). However, meta-analysis shows a small effect size of physical training (Karr, Areshenkoff, Rast, & Garcia-Barrera, 2014; Nouchi & Kawashima, 2014).

U

Based on the results of functional magnetic resonance imaging (fMRI) scanning,

A

N

research indicated that reading aloud and simple arithmetic calculation activities could largely

M

increase prefrontal activation (Kawashima et al., 2004; Miura et al., 2003). Researchers

ED

reasoned that reading aloud activity is accomplished by a combination of several cognitive processes including the recognition of visually presented words, conversion to phonological

PT

representation from the graphic representation of words, analysis of the meaning of words,

CC E

and control over pronunciation. The processes of solving arithmetic problems involve recognition of visually presented numbers, arithmetic operations, and control of hand

A

movements. Both tasks involve the controlled, monitoring, and planning natures of EFs (Uchida & Kawashima, 2008). According to the “use it or lose it” principle, researchers trained the elderly (Nouchi et al., 2012) and young adults (Nouchi et al., 2013) with reading aloud and simple arithmetic calculation tasks for 15 minutes per day, at least 5 days per week,

9

for 4 weeks. The EF capibilities of the elderly were assessed before and after the tasks with the Frontal Assessment Battery at bedside (FAB, Dubois, Slachevsky, Litvan, & Pillon, 2000), which includes six subtests that pertain to conceptualization, mental flexibility,

IP T

programming, sensitivity to interference, inhibitory control, and environmental autonomy. They were also asked to perform the TMT (Reitan, 1958) for assessing shifting abilities. The

SC R

EF capabilities of young adults were assessed pre- and posttest with cognitive tasks; for

example, the WCST for shifting, the Stroop task for inhibition, and the operation span task

U

(Turner & Engel, 1989) for updating. Cognitive tasks other than EFs were also measured,

A

N

including attention and short-term memory. The results showed significant EF improvement

M

in the experimental group in comparison to the active control group (where participants

ED

played Tetris instead), but not in attention and short-term memory performance. These results demonstrated the practicability characteristic and far transfer effect of reading aloud and

PT

arithmetic calculation training. In addition, the effect sizes of this training were larger in

CC E

comparison to other cognitive and physical training processes (Nouchi & Kawashima, 2014). 1.3. Research Aims

A

Given that EFs are the basis for human beings’ higher cognition (e.g., Scibinetti et al.,

2011), their close relationships with thinking and creative performance (e.g., Evans & Stanovich, 2013, Dietrich & Kanso, 2010), and the effectiveness of reading aloud and arithmetic calculation activities for improving EFs (Nouchi et al., 2012; Nouchi et al., 2013),

10

the present study aimed to adopt this training program to investigate its effectiveness on enhancing junior high students’ EF, thinking, and creative abilities. The present study is more innovative than previous studies in two aspects. First, in previous research on EF training,

IP T

meta-cognitive transfer effects were seldom investigated. However, meta-cognitive transfer effect is one of the most important criteria for the assessment of trainings (Enriquez-Geppert

SC R

et al., 2013). The present study inspected whether the effects of reading aloud and arithmetic calculation training could transfer into other domains of higher cognition (i.e., thinking and

U

creativity), which are closely related to EFs. Second, previous studies investigated the

A

N

relations of EFs with thinking and with creative abilities, or conducted EFs intervention

M

research mostly among university students or other adults who were recruited as participants.

ED

Adolescents were seldom addressed. As mentioned above, cognitive and neurophysiological evidence reveals that EFs (and also the prefrontal cortex) continue to mature throughout

PT

childhood and adolescence and until young adulthood (Best & Miller, 2010). Junior high

CC E

students are in the middle of this development. Assisting them with better development is indisputably meaningful and important.

A

2. Methods

2.1. Participants and General Procedure Fifty students (mean age = 13.41 years, SD = 0.54 years, age range = 13–15; 58% girls) from a junior high school in Yilan county, Taiwan, participated in the study after obtaining

11

full consent from each student’s parents and the student himself or herself (the study was approved by the Research Ethics Committee of the National Taiwan University). According to the “Improvement Edition of New Occupational Prestige and Socioeconomic Scores for

IP T

Taiwan,” (Hwang, 2008), the general socioeconomic status and academic standard in Yilan county is at the second level out of five, with the fifth level for the highest (Chiu, 2012). This

SC R

excludes our sample from the possible ceiling effect.

All participants were pretested on their EF, thinking, and creative abilities in a group

U

administration. The pretest took about one hour. Thirty-eight students decided to continue the

A

N

following trainings and posttest sessions. They drew lots to be randomly assigned into the

M

training group (mean age = 13.44 years, SD = 0.51 years; 63.16% girls) and the control group

ED

(mean age = 13.44 years, SD = 0.62 years; 52.63% girls), 19 in each group. The training lasted for four weeks, five days a week (from Monday to Friday), and 15 minutes per session.

PT

The participants in the training group performed the reading aloud and arithmetic calculation

CC E

activities and participants in the control group played Tetris (Nouchi et al., 2012; Nouchi et al., 2013) in small group administration in the school computer room. In order to prevent

A

distraction, all participants performed the activities while wearing ear phones for noise cancelling. The posttest, which was a duplicate form of the tests (except for the EF inventory), was lastly administered to assess the participants’ EF, thinking, and creative abilities, as in the pretest. After the whole procedure, the participants were debriefed and

12

received gifts for participation. 2.2. Test Materials 2.2.1. EF assessments

IP T

In consideration of the practicability of administration in the actual educational field, the present study adopted the Chinese Executive Function Index for junior high students (CEFI-J,

SC R

Yu & Lin, 2018) to assess students’ self-reported EF. The CEFI-J was translated from the

Executive Function Index (EFI; Spinella, 2005) and was validated with over 500 junior high

U

students in Taiwan. There were 15 items on the CEFI-J. The factor analysis results indicated

A

N

three elements: strategic actions (e.g., “I will use strategies or methods to remember things”),

M

organization and planning (e.g., “It is hard for me to do two things at the same time”-

ED

reversed), and impulse control (e.g., “I often cuss or use bad language”-reversed). The participants answered each item with 5-point Likert scale that ranged from 1 (strongly

PT

disagree) to 5 (strongly agree). The averages of the three components were further summed

CC E

into a composite EF index. The internal consistency reliability of the CEFI-J is .77, and the one-month test-retest reliability is .80. It also possesses good criterion-related validity. The

A

completion of the assessment was about 5 minutes. 2.2.2. Thinking tasks Critical thinking, which refers to the ability to draw inferences from evidence, make reflective judgments, use strategies for solving problems, evaluate evidence, and make

13

arguments independent of one’s prior beliefs and opinions (Baron, 2000; Facione, 2007; Norris & Ennis, 1989; Sternberg, 2003), serves as a broad term for rational thinking (West et al., 2008). The Watson Glaser Critical Thinking Assessment (WGCT, Watson & Glaser, 1980)

IP T

was developed by these definitions and was widely used in critical thinking assessment (West et al., 2008). The present study adopted the modified Chinese version of WGCT -The critical

SC R

thinking test-level I (details described below)- to assess participants’ critical thinking abilities.

U

The present study additionally adopted the Chinese Syllogism Reasoning Task (Liu,

A

N

2007) to measure the participants’ thinking abilities. The decontextualization demand of

M

syllogism is also one component of critical thinking (West et al., 2008) and, as mentioned

ED

above, the performance on syllogism problems could depict Type 1 and Type 2 processing,

2013).

PT

whereas the latter is indicative of EFs involvement (e.g., Evans, 2003; Evans & Stanovich,

CC E

The critical thinking test-level I (CTT-I). The CTT-I was modified from WGCT to suit to Taiwan students from Grade 5 to Grade 12 (Yeh, 2003). It includes five subtests: inference,

A

recognition of assumptions, deduction, interpretation, and evaluation of arguments. Each test item generally consists of a series of statements about which the validity of conclusions must be judged. The CTT-I established good reliability and validity results and were adopted in many studies in Taiwan (e.g., Chang, Li, Chen, & Chiu, 2015; Lin, 2017). Form A and form

14

B (10 items in each) were used for pre- and posttests in the present study. The correctness of items was summed as an index. The time limit of the test was 10 minutes. The Chinese syllogism reasoning task. This task was designed by Handley et al. (2004)

IP T

and included 24 syllogism problems. There were 16 thematic problems (conclusion believable/conclusion unbelievable) and 8 neutral problems. In thematic problems where

SC R

conclusion believability and logical correctness are in conflict, the logically correct responses

of these problems were proved to be the proper index for rational thinking ability because this

U

index depicted reasoners’ ability to avoid belief bias and, hence, the processing of the Type 2

A

N

process (Handley et al., 2004). For example, a problem with an unbelievable conclusion, but

M

a logically correct “yes” answer, would be: Premises: “All teachers read books. People who

ED

can read books are astronauts.”/Conclusion: “Are teachers astronauts?” A problem with a believable conclusion, but a logically correct “no” answer, would be: “Babies are older than

PT

elementary students. Elementary students are older than adults.”/Conclusion: “Are adults

CC E

older than babies?” The logical correctness of each problem was verified by the participants and summed as an index. Form A and form B were used for the pre- and posttest. The

A

completion of the task was about 20 minutes. 2.2.3. Creativity tests Benedek and Neubauer (2013) claimed that a representative set of commonly used creativity indicators should be considered when assessing creativity (see also Kaufman,

15

Plucker, & Baer, 2008). The present study adopted two widely used creativity tests to measure the participants’ creative abilities: the unusual uses test and the RAT. The unusual uses test. It was indicated that the unusual uses test possessed the best

IP T

psychometric properties among divergent thinking assessments (Silvia et al., 2008). The present study adopted the unusual uses for a newspaper test (Hsu, Chen, & Chiu, 2012) as the

SC R

pretest and the unusual uses for chopsticks test (the verbal subtest of the Chinese Version of the Creative Thinking Test, CVCTT; Wu, 1998) as the posttest. The participants were asked

U

to generate as many novel, unusual uses for each object for 5 minutes in the former and 10

A

N

minutes in the latter, according to each test’s standard administration manual. Both tests have

M

established stable reliability and validity results. The fluency, flexibility, and originality

ED

scores for each test were scored by two independent raters. All of the interrater reliability results in the present study were above .97.

PT

The Chinese word remote associates test (CWRAT). The CWRAT (Huang, Chen, &

CC E

Liu, 2012) was developed in accordance with Mednick’s definition (1962) of creativity as remote association ability and the RAT (Mednick & Mednick, 1967). There were 30 problems

A

in this test; each problem consisted of three words (for example, Newton, wax, red). The participants had to answer by providing a correct word that was associated with all three problem words (for example, apple). The test has established good reliability and validity results in Taiwan. A time limit was set for 15 minutes, and the total correctness was recorded.

16

Form A and form B were used for pre- and posttest. 2.3. EF Training Materials and Procedure One of the co-authors of the present study is a computer science specialist who

IP T

developed a smartphone-based application with a web-based backend cloud system that provides database support for the reading aloud and arithmetic calculation trainings. The

SC R

application was further transformed into a computer version in order to administrate training in the school computer room. When conducting the activities, each participant’s processes

U

were immediately recorded by the system, including the date, time course, arithmetic

A

N

calculation responses, and voices on reading aloud. Other than a previous study in which the

M

participants recorded most of their activity processes on their own (Nouchi et al., 2012;

ED

Nouchi et al., 2013), our system allows administrators to monitor the response profile of each participant (everyone logged into his/her own account) and collect precise data for further

PT

analyses. In addition, the proposed system was found to effectively improve participants’ EF

CC E

performance among a university sample (Yu, Lin, & Wang, 2017). In each session, the participants in the training group read aloud and performed

A

arithmetic calculations for about seven and half minutes, for a total of 15 minutes, as automatically controlled by the application system. There were three difficulty levels for reading aloud and arithmetic calculation. The participants were determined their own level before training according to school grade in literature and math separately (the easy level:

17

below 60 points on semester grades; the middle level: 60-80 points; the difficult level: above 80 points). This adaptive training procedure could mostly activate prefrontal cortex and pique the participants’ motivation (Uchida & Kawashima, 2008).

IP T

The reading materials came from Aesop’s fables (the easy level), ancient Chinese novels (the middle level), and classical Chinese literature (the difficult level); about 350 words in

SC R

each story. In each story, a sentence was presented on the computer screen, one at a time, and the participants pressed the “NEXT” button with the mouse for the next sentence after

U

completing the former reading. No materials were repeated during 20 training sessions. In

A

N

terms of the arithmetic calculations, the difficulty levels were as follows: 1) the easy level:

M

addition and subtraction on a one-digit number and a two-digit number (e.g., 12+3=?; 24-

ED

6=?), division of two one-digit numbers (e.g., 8/2=?); 2) the middle level: addition and subtraction on two two-digit numbers (e.g., 11+25=?; 62-34=?), multiplication and division

PT

of a two-digit number and a one-digit number (e.g., 25×3=?; 68/4=?); 3) the difficult level:

CC E

addition and subtraction on a two-digit number and a three-digit number (e.g., 135+22=?; 340-15=?), multiplication and division of a three-digit number and a one-digit number (e.g.,

A

221×4=?; 844/2=?). The answers to all the problems were set for positive integers and were no larger than three-digit numbers. The arithmetic problems were generated and provided randomly by the application system within certain difficulty levels, and the number of generated problems and the number of correct answers were shown on the screen. The

18

participants keyed in answers to each problem. The participants in the control group logged into another self-designed website to play Tetris. In this game, participants rotated and moved blocks with various shapes descending

IP T

from the top of the screen to form a complete line at the bottom of the screen. The complete lines would disappear and be scored, while the incomplete lines would pile higher and higher

SC R

until they reached the top of the screen and the game should start over again. According to

Nouchi et al. (2012, 2013), playing Tetris did not affect the participants’ EFs performances

U

and, therefore, was suitable for the chosen activity in the active control group. The

A

N

participants’ performance was also recorded in our website database.

M

After 20 sessions of activities, all of the participants in the training group and the control

ED

group used a 5-point scale that described their feelings about reading aloud and arithmetic calculation activities or playing Tetris in 4 statements (the activity is fun / interesting; when

CC E

3. Results

PT

doing the activity, I am focused / tired).

3.1. The Relationships between EF and Higher Cognition

A

The relationships between the assessed variables from the pretest (n = 50) were first

analyzed to inspect whether the findings from previous studies were evident and replicated in the present study. The correlational analyses (Table 1) show that the three components of CEFI-J (i.e., strategic actions, organization and planning, and impulse control) were

19

correlated with each other (rs = .26 - .43, ps = .071 - .002), and all were significantly correlated with the composite EF index (rs = .66 - .80, ps < .001). These results were consistent with previous findings (Yu & Lin, 2018) and indicated the legitimacy to compute a

IP T

composite score for EF. The relationships between the composite EF index and higher cognitive performances (thinking and creativity) were, therefore, further inspected. The

SC R

results show that the composite EF index was significantly correlated to participants’

performances on critical thinking (r = .31, p = .031) and the fluency index in the unusual uses

U

test (r = .33, p = .018). The composite EFs index exhibited positive relations to performances

A

N

on syllogism (r = .21, p = .147), the CWRAT (r = .11, p = .467), and other indices of

M

divergent thinking (with flexibility: r = .22, p = .132; with originality: r = .24, p = .097).

ED

Although not significant (possibly constrained by the sample size), most correlational values were of medium effect size1, as defined by Cohen (1992). The above results replicated the

PT

past findings that EFs are closely related to thinking (mostly the critical thinking index in the

CC E

present study) and creative (mostly the fluency index in the present study) abilities (e.g.,

A

Evans & Stanovich, 2013, Dietrich & Kanso, 2010).

(Table 1 about here)

An effect size complements statistical hypothesis testing and play an important role in meta-analysis (Kelley & Preacher, 2012). For example, the meta-analysis on the comparative effectiveness of the EF training programs used effect sizes (Karr et al., 2014). Effect sizes were reported here for readers to learn the magnitude of the phenomena and the comparative effectiveness. 1

20

3.2. Analyses on Training Processes The participants’ activity processes during 20 sessions of training and playing Tetris

IP T

were analyzed from the recorded data in our website database. For the training group, two regression analyses on their performances of reading aloud (the numbers of stories completed

SC R

within seven and half minutes per session) and arithmetic calculation (the total correct rates

of arithmetic calculation per session) over the course of 20 training sessions were computed.

U

As shown in Figure 1A, the linear regression on the reading aloud index (Y = 0.044X+ 4.217,

A

N

R2 = 0.73, β = 0.86) was significant (F(1,18) = 48.77, p < .001) and the linear regression on

M

the arithmetic calculation index was marginally significant (Y = 0.001X+ 0.948, R2 = 0.18, β

ED

= 0.42); F(1,18) = 3.95, p = .062). For the active control group (Figure 1B), the regression analysis on game performance (the average scores on Tetris per session) over 20 sessions also

PT

showed a significant linear trend (Y = 0.341X+ 7.878, R2 = 0.91, β = 0.95, F(1,18) = 176.35,

CC E

p < .001). These results indicated that the participants both in the training group and in the

A

active control group could follow instructions to dedicatedly proceed with their activities.

(Figure 1 about here)

The participants’ self-ratings on their feelings toward the assigned activities after 20

21

sessions were compared. The results showed that the training group and the control group did not differ in the extent to which they could focus on the activities (4.00 ± .75 vs. 4.05 ± 1.08, t(32) = -.18, p = .862) or the extent to which they felt tired (2.79 ± 0.79 vs. 2.58 ± 1.12, t(36)

IP T

= .67, p = .507). However, participants in the control group felt that the activities were more interesting and fun (4.47 ± 0.70; 4.26 ± 0.73) in comparison to the participants in the training

SC R

group (3.47 ± 1.12; 3.58 ± 0.90), t(36) = -3.30, p = .002; t(36) = -2.57, p = .015. 3.3. The Effectiveness of the EF Training Program

U

To inspect the effectiveness of the EF training program in the present study, several

A

N

ANCOVAs with performance in the pretest as the covariates, training as the independent

M

variable, and performances in the posttest as the dependent variables were computed. Table 2

ED

shows the participants’ performance in the posttest. The results of analyses revealed that the EF indices on the CEFI-J did not differ between the training (strategic actions: 3.27 ± .52,

PT

organization and planning: 3.09 ± .71, impulse control: 3.12 ± .76, and composite EFs index:

CC E

9.49 ± 1.43) and the control group (strategic actions: 3.40 ± .46, organization and planning: 2.79 ± .83, impulse control: 3.16 ± .67, and composite EFs index: 9.36 ± 1.56), all ps > .100.

A

However, the participants in the training group performed significantly better than the participants in the control group on the syllogism task (9.63 ± 3.55 vs. 6.55 ± 2.87, F(1,35) = 4.19, p = .048, η2 = .107) and the CWRAT (12.63 ± 4.68 vs. 7.89 ± 4.63, F(1,35) = 4.47, p = .042, η2 = .113). Their performances were also better than those in the control group on the

22

CTT-I (5.37 ± 1.89 vs. 4.16 ± 1.61, F(1,35) = 3.89, p = .057, η2 = .100) and the fluency and the flexibility indices of the unusual uses test (9.26 ± 5.70 vs. 6.47 ± 3.79, F(1,35) = 3.81, p = .059, η2 = .098; 6.26 ± 3.03 vs. 4.63 ± 1.95, F(1,35) = 3.21, p = .082, η2 = .084) to a

IP T

marginally significant level, but all were of median to large effect sizes. The above results showed that after 20 sessions of reading aloud and arithmetic calculation trainings, the

SC R

participants’ outperformed the participants in the control group in terms of critical thinking,

U

syllogism reasoning, and creative performance.

M

A

N

(Table 2 about here)

ED

4. Discussion

Based on previous theories and findings that pertain to the close relationships between

PT

EFs and higher cognition (e.g., Evans & Stanovich, 2013, Dietrich & Kanso, 2010) and the

CC E

applicability of EF training (e.g., Enriquez-Geppert et al., 2013; Nouchi et al., 2012; Nouchi et al., 2013), the present study adopted the reading aloud and arithmetic calculation training

A

program to investigate its meta-transfer effects on junior high students’ thinking and creative abilities. The design of the present study is also consistent with the proposed criteria for assessing trainings in the random assignment of participants and the use of an active control group (Enriquez-Geppert et al., 2013; Nouchi & Kawashima, 2014). In addition, the present

23

study targeted at the adolescent population, which has been seldom investigated in the past yet the development of EFs and the prefrontal cortex are rapid and important during this period of life (Best & Miller, 2010). Our pretest results patterned the previous findings,

IP T

indicating the appropriateness of measures that we applied. The analyses on participants’ activity processes showed that they improved in the practiced activities, indicating the

SC R

trainability of this procedure. Most importantly, the ANCOVAs analyses showed that the participants in the training group gained significant or marginally significant better

U

performance on the CTT-I, the syllogism task, the CWRAT, and the unusual uses test after

A

N

training in comparison to the control group. All of the analyses were of medium to large

M

effect sizes, demonstrating the effectiveness of reading aloud and arithmetic calculation EF

ED

training on enhancing junior high students’ thinking and creative abilities. Although with better performance on thinking and creativity tasks, the participants’ self-

PT

assessments on the CEFI-J in the training group were not significantly different from those in

CC E

the control group. In the CEFI-J, the participants rated the extent of whether certain behavior described themselves in a 5-point scale. It is possible that this constrained range of responses

A

could not sensitively reflect on the mild change of pre- and posttest behaviors within a onemonth training period. In addition, the researchers indicated the distinction between typical performance versus optimal / maximal performance (Ackerman & Kanfer, 2004; Toplak et al., 2011). The self-reported behavioral rating assessed the former, where no overt

24

instructions to maximize performance were given, in contrast to the cognitive tasks (e.g., the tasks used in Nouchi et al., 2013). Empirical evidence showed that the typical performance ratings and the maximal performance measures were only mildly correlated (Duckworth,

IP T

2009; Toplak, West, & Stanovich, 2013). For example, the correlation between the CEFI-J and the plus-minus task (measuring for shifting ability, Miyake et al., 2000) was .17 (Yu &

SC R

Lin, 2018). Future studies might consider adopting the cognitive tasks to measure EFs in

accordance with the practicability of administration in the real-field educational environment.

U

However, the feedback of class teachers in the present study revealed certain qualitative

A

N

improvements of students in the training group on some EF-related behaviors. For example,

M

some passive students became enthusiastic about handing in assignments on time; a few

ED

students who had often verbally or physically insulted classmates in the past became more polite and well behaved; and one quiet student with mild Tourette’s syndrome started to ask

PT

questions in class. These observations might contribute to the effectiveness of the EF training.

CC E

As shown in the analyses, participants in the training group rated the reading aloud and arithmetic calculation activity to be less interesting and fun than the participants’ ratings on

A

Tetris in the control group. These results might indicate the decrease of motivation for the training. However, the participants in the training group continued to improve on their reading aloud and arithmetic calculation performance, as shown in the regression analyses, and they outperformed the thinking and creativity measures on the posttest. In the study

25

inspecting a university sample with the same application system (Yu, Lin, & Wang, 2017), participants rated their feelings toward the reading aloud and arithmetic calculation activity (concentration, interest, and tired) in the middle and end of the training sessions. There were

IP T

no differences between two time-point assessments. It is possible that for junior high students to enhance their interest toward the training activity, a more colorful and fascinating interface

SC R

of the application system (more like a game instead of an exam) is needed. Giving bonuses

(e.g., small gifts) to commend improvements during each training session (e.g., Angelakis et

U

al., 2007) is another practical method. These manipulations might further boost the

A

N

effectiveness of the training program. Future studies could address this issue.

M

Aside from thinking and creativity, recent studies also demonstrated the positive

ED

correlations between EFs and students’ academic achievements. For instance, researchers adopted TMT to measure adolescents’ shifting ability and found that it was positively

PT

correlated with their mathematic grades (Valiente-Barroso & García-García, 2012).

CC E

Researchers used the operation span task to measure the updating function in elementary school students and found that it could positively predict students’ English, mathematic, and

A

science class performances (St. Clair-Thompson & Gathercole, 2006). Best and colleagues (Best, Miller, & Naglieri, 2011) examined students between the ages of 5 to 17 to evaluate their complex EF skills (subtests that involve planning and monitoring from the Cognitive Assessment System, CAS; Naglieri & Das, 1997) and found a steady strength of correlations

26

with students’ math and reading achievements across all ages. In addition, EFs were found to be related to individuals’ positive psychological characteristics, such as gratitude, satisfaction of life, forgiveness, optimism, and hope (Kruger, 2011; Pronk, Karremans, Overbeek,

IP T

Vermulst, & Wigboldus, 2010). EFs also exhibited close relationships to emotional regulation in adults (Carvalho & Ready, 2010; Whitmer & Gotlib, 2013) and in children and adolescents

SC R

(Best, Miller, & Jones, 2009). Moreover, researchers found that psychological maturity (e.g., encompassing self-reliance) was significantly correlated to adolescents’ EF performance

U

(Galambos, MacDonald, Naphtali, Cohen, & de Frias, 2005). Given the effectiveness of

A

N

reading aloud and arithmetic calculation EF training program on thinking and creative

M

abilities found in the present study, whether this program could enhance students’ academic

ED

achievements and social-emotional functions will be interesting and merit further investigations.

PT

In addition to adopting different EF measures and to enhance students’ interest toward

CC E

the training activities as mentioned above, the sample size could be enlarged, more measures on thinking and creativity performances could be explored, and the long-term effect of

A

training could be inspected in the future. For example, Uchida and Kawashima (2008) found that the effects of the reading aloud and arithmetic calculation training for the elderly could last for three to six months on the EF measures after six months of training. The long-term effect of the four-week training and for the adolescents still needs further examination.

27

5. Conclusion In conclusion, the present exploratory study demonstrated a practical and economical method that was aimed at activating junior high students’ prefrontal cortex and enhancing

IP T

their EF capabilities. Although the neurofeedback technique has proven to be useful for the same purpose, it usually requires 15-40 training sessions that range from 30 to 60 minutes per

SC R

session (Marzbani, Marateb, & Mansourian, 2016) and is not suitable for application in the

school educational environment. Moreover, the results of the present study showed that the

U

reading aloud and arithmetic calculation training improved junior high students’ EF-related

A

N

thinking and creative abilities that are deemed as crucial in facing this rapidly changing era

M

(Trilling & Fadel, 2009). Improvements on junior high students’ academic achievements and

ED

social emotional functions as a whole through this EF training program are implicated and are worthy of future investigation.

PT

Acknowledgement

CC E

This research was supported by grants to the corresponding author from the Ministry of Science and Technology of Taiwan (MOST 105-2410-H-431-020).

A

References

Ackerman, P. L., & Kanfer, R. (2004). Cognitive, affective, and conative aspects of adult intellect within a typical and maximal performance framework. In D. Y. Dai & R. J. Sternberg (Eds.), Motivation, emotion, and cognition: Integrative perspectives on

28

intellectual functioning and development (pp. 119-141). Mahwah, NJ: Erlbaum. Anderson, M. C., Bjork, R. A., & Bjork, E. L. (1994). Remembering can cause forgetting: Retrieval dynamics in long-term memory. Journal of Experimental Psychology:

IP T

Learning Memory and Cognition, 20, 1063–1087. Angelakis, E., Stathopoulou, S., Frymiare, J. L., Green, D. L., Lubar, J. F., & Kounios, J.

SC R

(2007). EEG neurofeedback: A brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly. The Clinical Neuropsychologist, 21,

U

110-129.

A

N

Antonietti, A. (2000). Enhancing creative analogies in primary school children. North

M

American Journal of Psychology, 2, 75-84.

University Press.

ED

Baron, J. (2000). Thinking and deciding (3rd ed.). Cambridge, England: Cambridge

PT

Benedek, M., & Neubauer, A. C. (2013). Revisiting Mednick's model on creativity‐related

CC E

differences in associative hierarchies. Evidence for a common path to uncommon thought. The Journal of Creative Behavior, 47, 273-289.

A

Benedek, M., Fink, A., & Neubauer, A. C. (2006). Enhancement of ideational fluency by means of computer-based training. Creativity Research Journal, 18, 317-328.

Benedek, M., Jauk, E., Sommer, M., Arendasy, M., & Neubauer, A. C. (2014). Intelligence, creativity, and cognitive control: The common and differential involvement of executive

29

functions in intelligence and creativity. Intelligence, 46, 73-83. Best, J. R., & Miller, P. H. (2010). A developmental perspective on executive function. Child Development, 81, 1641-1660.

IP T

Best, J. R., Miller, P. H., & Jones, L. L. (2009). Executive functions after age 5: Changes and correlates. Developmental Review, 29, 180-200.

SC R

Best, J. R., Miller, P. H., & Naglieri, J. A. (2011). Relations between executive function and academic achievement from ages 5 to 17 in a large, representative national sample.

U

Learning and Individual Differences, 21, 327-336.

A

N

Carvalho, J. O., & Ready, R. E. (2010). Emotion and executive functioning: The effect of

ED

Neuropsychology, 32, 225-230.

M

normal mood states on fluency tasks. Journal of Clinical and Experimental

Chang, Y. K., & Etnier, J. L. (2009). Exploring the dose-response relationship between

PT

resistance exercise intensity and cognitive function. Journal of Sport and Exercise

CC E

Psychology, 31, 640-656.

Chang, Y., Li, B. D., Chen, H. C., & Chiu, F. C. (2015). Investigating the synergy of critical

A

thinking and creative thinking in the course of integrated activity in Taiwan. Educational Psychology, 35, 341-360.

Chiu, L. M. (2012). The influences of social capital, cultural capital and self-concept on academic achievements of the 5th and 6th graders in Yilan county-Comparison between

30

new immigrant students and natural born students (Unpublished master’s dissertation). Yilan, Taiwan: Fo Guang University. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.

IP T

De Neys, W. (2006). Dual processing in reasoning: Two systems but one reasoner. Psychological Science, 17, 428-433.

SC R

Dietrich, A., & Kanso, R. (2010). A review of EEG, ERP, and neuroimaging studies of creativity and insight. Psychological Bulletin, 136, 822-848.

U

Dineen, R., & Niu, W. (2008). The effectiveness of western creative teaching methods in

A

N

china: An action research project. Psychology of Aesthetics, Creativity, and the Arts, 2,

M

42-52.

ED

Dreisbach, G., & Goschke, T. (2004). How positive affect modulates cognitive control: Reduced perseveration at the cost of increased distractibility. Journal of Experimental

PT

Psychology: Learning, Memory, and Cognition, 30, 343-353.

CC E

Dubois, B., Slachevsky, A., Litvan, I., & Pillon, B. (2000). The FAB: A frontal assessment battery at bedside. Neurology, 55, 1621-1626.

A

Duckworth, A. L. (2009). Over and beyond high-stakes testing. American Psychologist, 64, 279-280.

Dyson, S. B., Chang, Y. L., Chen, H. C., Hsiung, H. Y., Tseng, C. C., & Chang, J. H. (2016). The effect of tabletop role-playing games on the creative potential and emotional

31

creativity of Taiwanese college students. Thinking Skills and Creativity, 19, 88-96. Enriquez-Geppert, S., Huster, R. J., & Herrmann, C. S. (2013). Boosting brain functions: improving executive functions with behavioral training, neurostimulation, and

IP T

neurofeedback. International Journal of Psychophysiology, 88, 1-16. Evans, J. St. B. T. (2003). In two minds: dual-process accounts of reasoning. Trends in

SC R

Cognitive Science, 7, 454-459.

Evans, J. St. B. T., & Stanovich, K. E. (2013). Dual-process theories of higher cognition:

U

Advancing the debate. Perspectives on Psychological Science, 8, 223-241.

A

N

Facione, P. (2007). Critical thinking: What it is and why it counts. Millbrae, CA: Insight

M

Assessment, California Academic Press.

ED

Galambos, N. L., MacDonald, S. W., Naphtali, C., Cohen, A. L., & de Frias, C. M. (2005). Cognitive performance differentiates selected aspects of psychosocial maturity in

PT

adolescence. Developmental Neuropsychology, 28, 473-492.

CC E

Gilhooly, K. J., & Fioratou, E. (2009). Executive functions in insight versus non-insight problem solving: An individual differences approach. Thinking & Reasoning, 15, 355-

A

376.

Gilhooly, K. J., & Murphy, P. (2005). Differentiating insight from non-insight problems. Thinking & Reasoning, 11, 279-302. Gottardo, A., Stanovich, K. E., & Siegel, L. S. (1996). The relationships between

32

phonological sensitivity, syntactic processing, and verbal working memory in the reading performance of third-grade children. Journal of Experimental Child Psychology, 63, 563-582.

IP T

Guilford, J. P. (1967). The nature of human intelligence. New York, NY: McGraw-Hill. Handley, S. J., Capon, A., Beveridge, M., Dennis, I., & Evans, J. St. B. T. (2004). Working

SC R

memory, inhibitory control and the development of children’s reasoning. Thinking and Reasoning, 10, 175-195.

U

Hsu, C. C., Chen, H. C., & Chiu, F. C. (2012). The development of unusual uses of the

A

N

newspapers test. Journal of Chinese Creativity, 3, 33-56.

M

Huang, P. S., Chen, H. C., & Liu, C. H. (2012). The development of Chinese word remote

ED

associates test for college students. Psychological Testing, 59,581-607. Hwang, Y. J. (2008). How to precisely measure occupational status? Construction of the

PT

“Improvement edition of new occupational prestige and socioeconomic scores for

CC E

Taiwan.” NTTU Educational Research Journal, 19, 151-160. Karr, J. E., Areshenkoff, C. N., Rast, P., & Garcia-Barrera, M. A. (2014). An empirical

A

comparison of the therapeutic benefits of physical exercise and cognitive training on the executive functions of older adults: A meta-analysis of controlled trials. Neuropsychology, 28, 829-845.

Kaufman, J.C., Plucker, J.A., & Baer, J. (2008). Essentials of creativity assessment. Hoboken,

33

NJ: Wiley & Sons. Kawashima, R., Taira, M., Okita, K., Inoue, K., Tajima, N., Yoshida, H., ... Fukuda, H. (2004). A functional MRI study of simple arithmetic—a comparison between children

IP T

and adults. Cognitive Brain Research, 18, 225-231. Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological Methods, 17, 137-152.

SC R

Kruger, G. H. J. (2011). Executive functioning and positive psychological characteristics: A replication and extension. Psychological Reports, 108, 477-486.

U

Lin, C. Y. (2017). Threshold effects of creative problem-solving attributes on creativity in the

A

N

math abilities of Taiwanese Upper Elementary Students. Education Research

M

International, 2017, Article ID 4571383, 9 pages.

ED

Lin, W. L., & Lien, Y. W. (2013). The different role of working memory in open-ended versus closed-ended creative problem solving: A dual-process theory account. Creativity

PT

Research Journal, 25, 85-96.

CC E

Lin, W. L., Tsai, P. H., Lin, H. Y., & Chen, H. C. (2014). How does emotion influence different creative performances? The mediating role of cognitive flexibility. Cognition

A

and Emotion, 28, 834-844.

Liu, P. P. (2007). Improving children’s performance in scientific reasoning: The influences of individual’s working memory capacity and cognitive load during practice (Unpublished master’s dissertation). Taipei, Taiwan: National Taiwan University.

34

Logan, G. D. (1994). On the ability to inhibit thought and action: A user’s guide to the stop signal paradigm. In D. Dagenbach & T. H. Carr (Eds.), Inhibitory processes in attention, memory, and language (pp. 189-239). San Diego, CA: Academic Press.

IP T

Marzbani, H., Marateb, H. R., & Mansourian, M. (2016). Neurofeedback: a comprehensive review on system design, methodology and clinical applications. Basic and Clinical

SC R

Neuroscience, 7, 143-158.

Mednick, S. A. (1962). The associative basis of the creative process. Psychological Review,

U

69, 220-232.

A

N

Mednick, S. A., & Mednick, M. T. (1967). Examiner’s manual, remote associates test.

M

Boston, MA: Houghton Mifflin.

ED

Minear, M., & Shah, P. (2008). Training and transfer effects in task switching. Memory & Cognition, 36, 1470-1483.

PT

Miura, N., Iwata, K., Watanabe, J., Sugiura, M., Akitsuki, Y., Sassa, Y., ... Kawashima, R.

CC E

(2003). Cortical activation during reading aloud of long sentences: fMRI study. Neuroreport, 14, 1563-1566.

A

Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions four general conclusions. Current Directions in Psychological Science, 21, 8-14. Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., & Howerter, A. (2000). The

35

unity and diversity of executive functions and their contributions to complex ‘‘frontal lobe’’ tasks: A latent variable analysis. Cognitive Psychology, 41, 49-100. Monsell, S. (1996). Control of mental processes. In V. Bruce (Ed.), Unsolved mysteries of the

IP T

mind: Tutorial essays in cognition (pp. 93-148). Hove, UK: Erlbaum. Naglieri, J. A., & Das, J. P. (1997). Cognitive assessment system. Austin, TX: ProEd.

SC R

Niendam, T. A., Laird, A. R., Ray, K. L., Dean, Y. M., Glahn, D. C., & Carter, C. S. (2012).

Meta-analytic evidence for a superordinate cognitive control network subserving diverse

U

executive functions. Cognitive, Affective, & Behavioral Neuroscience, 12, 241-268.

A

N

Norris, S. P., & Ennis, R. H. (1989). Evaluating critical thinking. Pacific Grove, CA:

M

Midwest.

ED

Nouchi, R., & Kawashima, R. (2014). Improving cognitive function from children to old age: a systematic review of recent smart ageing intervention studies. Advances in

PT

Neuroscience. 2014:235479.

CC E

Nouchi, R., Taki, Y., Takeuchi, H., Hashizume, H., Akitsuki, Y., Shigemune, Y., ... Kawashima, R. (2012). Brain training game improves executive functions and

A

processing speed in the elderly: A randomized controlled trial. PLoS One 7:e29676.

Nouchi, R., Taki, Y., Takeuchi, H., Hashizume, H., Nozawa, T., Kambara, T., ... Kawashima, R. (2013). Brain training game boosts executive functions, working memory and processing speed in the young adults: A randomized controlled trial. PLoS One

36

8:e55518. Pronk, T. M., Karremans, J. C., Overbeek, G., Vermulst, A. A., & Wigboldus, D. H. J. (2010). What it takes to forgive: When and why executive functioning facilitates forgiveness.

IP T

Journal of Personality and Social Psychology, 98, 119-131. Prowse Turner, J. A., & Thompson, V. A. (2009). The role of training, alternative models, and

SC R

logical necessity in determining confidence in syllogistic reasoning. Thinking & Reasoning, 15, 69-100.

A

N

damage. Perceptual and Motor Skills, 8, 271-276.

U

Reitan, R. M. (1958). Validity of the Trail Making Test as an indicator of organic brain

M

Rogers, R. D., & Monsell, S. (1995). Costs of a predictable switch between simple cognitive

ED

tasks. Journal of Experimental Psychology: General, 124, 207-231.

Schufried.

PT

Schellig, D., Schuri, U., & Arendasy, M. (2011). Manual nback nonverbal. Mödling:

CC E

Scibinetti, P., Tocci, N., & Pesce, C. (2011). Motor creativity and creative thinking in children: the diverging role of inhibition. Creativity Research Journal, 23, 262-272.

A

Seiferth, N. Y., Thienel, R. & Kirchner, T. (2007). Exekutive funktionen. In F. Schneider & G. R. Fink (Eds.), Funktionelle MRT in Psychiatrie und Neurologie (pp.265-277). Heidelberg, Berlin: Springer. Sibley, B. A., Etnier, J. L., & Le Masurier, G. C. (2006). Effects of an acute bout of exercise

37

on cognitive aspects of stroop performance. Journal of Sport & Exercise Psychology, 28, 285-299. Silvia, P. J., Winterstein, B. P., Willse, J. T., Barona, C. M., Cram, J. T., Hess, K. I., ... &

IP T

Richard, C. A. (2008). Assessing creativity with divergent thinking tasks: Exploring the reliability and validity of new subjective scoring methods. Psychology of Aesthetics,

SC R

Creativity, and the Arts, 2, 68-85.

Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological

U

Bulletin, 119, 3-22.

A

N

Spinella, M. (2005). Self-rated executive function: Development of the executive function

M

index. International Journal of Neuroscience, 115, 649-667.

ED

St Clair-Thompson, H. L., & Gathercole, S. E. (2006). Executive functions and achievements in school: Shifting, updating, inhibition, and working memory. The Quarterly Journal of

PT

Experimental Psychology, 59, 745-759.

CC E

Stanovich, K. E. (2011). Rationality and the reflective mind. New York, NY: Oxford University Press.

A

Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate. The Behavioral and Brain Science, 23, 645-726.

Sternberg, R. J. (2003). Wisdom, intelligence, and creativity synthesized. Cambridge, England: Cambridge University Press.

38

Storm, B. C., & Angello, G. (2010). Overcoming fixation: Creative problem solving and retrieval-induced forgetting. Psychological Science, 21, 1263-1265. Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of

IP T

Experimental Psychology, 18, 643-662. Stroth, S., Hille, K., Spitzer, M., & Reinhardt, R. (2009). Aerobic endurance exercise benefits

SC R

memory and affect in young adults. Neuropsychological Rehabilitation, 19, 223-243. Thorell, L.B., Lindqvist, S., Bergman Nutley, S., Bohlin, G., & Klingberg, T. (2009).

U

Training and transfer effects of executive functions in preschool children.

A

N

Developmental Science, 12, 106-113.

M

Toplak, M. E., West, R. F., & Stanovich, K. E. (2011). The Cognitive Reflection Test as a

ED

predictor of performance on heuristics-and-biases tasks. Memory & Cognition, 39, 12751289.

PT

Toplak, M. E., West, R. F., & Stanovich, K. E. (2013). Practitioner review: Do performance‐

CC E

based measures and ratings of executive function assess the same construct? Journal of Child Psychology and Psychiatry, 54, 131-143.

A

Toplak, M. E., West, R. F., & Stanovich, K. E. (2014). Assessing miserly information processing: An expansion of the Cognitive Reflection Test. Thinking & Reasoning, 20, 147-168. Trilling, B., & Fadel, C. (2009). 21st century skills: Learning for life in our times. San

39

Francisco, CA: Jossey-Bass. Turner, M. L., & Engle, R. W. (1989). Is working memory capacity task dependent? Journal of Memory and Language, 28, 127-154.

IP T

Uchida, S., & Kawashima, R. (2008). Reading and solving arithmetic problems improves cognitive functions of normal aged people: A randomized controlled study. Age, 30, 21-

SC R

29.

Valiente-Barroso, C., & García-García, E. (2012). Executive function, adolescent

U

development and mathematical competence: Importance of quantitative and qualitative

A

N

analysis in educational psychology. Procedia-Social and Behavioral Sciences, 69, 2193-

M

2200.

ED

Waltz, J. A., Lau, A., Grewal, S. K., & Holyoak, K. J. (2000). The role of working memory in analogical mapping. Memory & Cognition, 28, 1205-1212.

CC E

Press.

PT

Ward, J. (2015). The student’s guide to cognitive neuroscience. New York, NY: Psychology

Watson, G., & Glaser, E. M. (1980). Watson-Glaser Critical Thinking Appraisal. San

A

Antonio, TX: Psychological Corporation.

West, R. F., Toplak, M. E., & Stanovich, K. E. (2008). Heuristics and biases as measures of critical thinking: Associations with cognitive ability and thinking dispositions. Journal of Educational Psychology, 100, 930-941.

40

Whitmer, A. J., & Gotlib, I. H. (2013). An attentional scope model of rumination. Psychological Bulletin, 139, 1036-1061. Wu, C. C. (1998). The Chinese version of creative thinking test. Taipei, Taiwan: Foundation

IP T

for Scholarly Exchange. Yeh, Y. C. (2003). The manual of critical thinking test, level I (CTT-I). Taipei: Psychological

SC R

Publishing.

Yu, S. H., & Lin, W. L. (2018). The development and validation of Chinese Executive

N

A

(CEFI-J). Psychological Testing, 65, 29-67.

U

Function Index-for College students (CEFI-C) and for Junior high school students

M

Yu, S. H., Lin, W. L., & Wang, S. W. (2017). Do some “mental exercises” by yourselves

ED

everywhere: An innovative self-training system for enhancing the executive function.

A

CC E

PT

Manuscript submitted for publication.

41 Table 1 The Correlations between EFs and Higher Cognitive Performance. CEFI-J Thinking SA

OP

IC

Creativity

CT

SR

RAT

FLU

.31*

.21

.11

.33*

FLE

ORI

Strategic actions (SA) and

.31*

planning (OP) .26

Composite EF index

.66** .80** .77**

.22

SC R

.43**

Impulse control (IC)

IP T

Organization

.24

A

CC E

PT

ED

M

A

N

fluency, FLE: flexibility, ORI: originality; **p < .01; *p < .05.

U

Note. CT: critical thinking, SR: syllogism reasoning, RAT: CWART, Chinese Word Remote Associates Test, FLU:

42 Table 2 The ANCOVAs Analyses on the Posttest Performances between the Training and Active Control Group. The Training The Active Result of ANCOVAs Group Control Group Mean

SD

p-value

Effect Size (ƞ2)

9.49

1.43

9.36

1.56

.945

.000

3.27

0.52

3.40

0.46

.401

3.09

0.71

2.79

0.83

3.12

0.76

3.16

0.67

5.37

1.89

4.16

1.61

9.63

3.55

6.55

Organization and

.016

.862

.001

.057

.100

2.87

.048

.107

ED

Creativity

Fluency

CC E

Flexibility

12.63

Originality

4.68

7.89

4.63

.042

.113

9.26

5.70

6.47

3.79

.059

.098

6.26

3.03

4.63

1.95

.082

.084

6.16

7.46

4.63

4.28

.420

.019

PT

CWRAT CVCTT

N

M

Reasoning

A

Syllogism

U

Thinking CTT-I

.020

.463

Planning Impulse Control

IP T

Strategic Actions

SD

SC R

EF Index

Mean

A

Note. CTT-I: Critical Thinking Test-Level I, CWART: Chinese Word Remote Associates Test, CVCTT: Chinese Version of the Creative Thinking Test. We report eta square (ƞ2) as an index of effect size. ƞ2 ≧ .01 is regarded as a small effect, ƞ2 ≧ .06 as a medium effect, and ƞ2 ≧ .14 as a large effect.

43

IP T

A. The training group

A

N

U

SC R

B. The active control group

M

Figure 1 The linear trends of training activity indices over 20 sessions for (A) the training group and (B)

A

CC E

PT

ED

the active control group.