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Learning a Skill With the Expectation of Teaching It Impairs the Skill's Execution Under Psychological Pressure

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When practicing a motor skill, learners who are expecting to teach it to another person exhibit superior gains in skill execution and declarative knowledge. Since skills acquired with large gains in declarative knowledge are highly susceptible to decrement under psychological pressure, it is possible the advantage of expecting to teach is lost when performing the learned skill under pressure. To test this hypothesis, we had 40 participants practice golf putting with the expectation of teaching (teach group) and 42 participants practice with the expectation of being tested (test group). The next day, all participants performed low- and high-pressure posttests. The teach group outperformed the test group under low pressure but not high pressure, where the teach group’s performance declined to that of the test group. Further, the teach group reported using more declarative knowledge during the posttests than the test group, but declarative knowledge use did not mediate the performance decline from low- to high-pressure posttest. Taken together, results suggest expecting to teach benefits skill learning, but this advantage is lost when performing the skill under high pressure. However, whether skill breakdown under high pressure is caused by an increase in declarative knowledge use remains an open question.
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PUBLISHED IN JOURNAL OF EXPERIMENTAL PSYCHOLOGY: APPLIED (DOI:
10.1037/xap0000191)
Learning a skill with the expectation of teaching it impairs the skill’s execution under
psychological pressure
Marcos Daoua, b,*, Zach Hutchisona, Mariane Bacelara, Jence A. Rhoadsa, Keith R. Lohsec, and
Matthew W. Millera
*To Whom Correspondence Should Be Addressed
a School of Kinesiology, Auburn University
301 Wire Road
Auburn University, Alabama, USA 36849
mzd0046@auburn.edu (MD); zzh0026@auburn.edu (ZH); mzf0029@auburn.edu (MB);
jar0072@auburn.edu (JAR); mwm0024@auburn.edu (MWM)
b CAPES Foundation
Ministry of Education of Brazil
Brasilia – DF 70040-020, Brazil
c Department of Health, Kinesiology, and Recreation; Department of Physical Therapy and
Athletic Training, University of Utah
Keith.Lohse@health.utah.edu (KRL)
Word Count: 6214
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Abstract 1
When practicing a motor skill, learners who are expecting to teach it to another person exhibit 2
superior gains in skill execution and declarative knowledge. Since skills acquired with large 3
gains in declarative knowledge are highly susceptible to decrement under psychological pressure, 4
it is possible the advantage of expecting to teach is lost when performing the learned skill under 5
pressure. To test this hypothesis, we had 40 participants practice golf putting with the 6
expectation of teaching (teach group) and 42 participants practice with the expectation of being 7
tested (test group). The next day, all participants performed low and high pressure posttests. The 8
teach group outperformed the test group under low pressure, but not high pressure, where the 9
teach group’s performance declined to that of the test group. Further, the teach group reported 10
using more declarative knowledge during the posttests than the test group, but declarative 11
knowledge use did not mediate the performance decline from low to high pressure posttest. 12
Taken together, results suggest expecting to teach benefits skill learning, but this advantage is 13
lost when performing the skill under high pressure. However, whether skill breakdown under 14
high pressure is caused by an increase in declarative knowledge use remains an open question. 15
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Public Significance Statement: This study suggests practicing a motor skill with the 17
expectation of teaching it enhances skill learning. However, this improved capability for skill 18
performance is not manifested when the skill is performed under psychological pressure. Thus, it 19
is recommended that people practice skills with the expectation of teaching them and take 20
measures to prevent choking under pressure. 21
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Keywords: Motor learning; Expecting to teach; Reinvestment Theory; Choking under pressure 23
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The acquisition of motor skills is crucial to human behavior, and relies heavily on the 24
accrual of procedural knowledge and somewhat on the accumulation of declarative knowledge 25
(see Rosenbaum, Carlson, & Gilmore (2001) for review). Determining practical ways to improve 26
motor skill acquisition is crucial to enhancing behavior. Recent studies suggest that practicing 27
and studying a motor skill with the expectation of teaching it enhances learning in comparison to 28
practicing and studying with the expectation of being tested. Specifically, expecting to teach 29
improves skill accuracy and precision, suggesting enhanced procedural knowledge, while also 30
increasing the ability to recall key concepts related to the skill, indicating greater declarative 31
knowledge (Daou, Buchanan, Lindsey, Lohse, & Miller, 2016; Daou, Lohse, & Miller, 2016; 32
Daou, Lohse, & Miller, 2018). A few different mechanisms potentially underlying the expecting 33
to teach effect have been investigated. It was initially thought that motivation and pressure would 34
explain the effect. This followed from the reasoning that expecting to teach should cause a 35
learner to recognize that their own learning might affect another person’s learning, thereby 36
increasing their drive and pressure to learn. Heightened motivation and pressure while practicing 37
and studying, in turn, could yield psychological and physiological states adaptive for learning. 38
However, neither motivation nor pressure were found to differ as a function of expecting to teach 39
(Daou, Buchanan, et al, 2016; Daou, Lohse et al., 2016; Daou, Lohse et al., 2018). 40
Turning from these affective-motivational mechanisms, Daou, Lohse et al. (2016) 41
examined whether enhanced information processing during practice and studying could explain 42
the expecting to teach effect. The authors reasoned that expecting to teach may cause a learner to 43
process more information about the skill they are practicing and studying, knowing that they will 44
have to transmit this information to another person, and that greater information processing 45
should improve learning. The authors used the amount of time spent in motor preparation before 46
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each practice trial as a proxy for information processing and observed that motor preparation 47
time was lengthened by expecting to teach and predicted learning (although not when controlling 48
for whether participants expected to teach). In a follow-up experiment, Daou, Lohse et al. (2018) 49
employed electroencephalography (EEG) to examine cerebral cortical dynamics during the final 50
3-s of motor preparation before each practice trial and did not observe any effects of expecting to 51
teach. In summary, expecting to teach appears to improve motor learning, possibly by increasing 52
the duration of information processing during motor preparation, but not by altering cortical 53
dynamics during the final seconds of preparation. 54
In addition to enhancing procedural knowledge (improved skill accuracy and precision), 55
expecting to teach enhances declarative knowledge (explicit facts) about the skill (Daou, 56
Buchanan et al., 2016; Daou, Lohse et al., 2016; Daou, Lohse et al., 2018) (interestingly, Daou, 57
Buchanan et al. (2016) reported that declarative knowledge did not predict improved skill 58
accuracy or precision). The increase in declarative knowledge may be caused by expecting to 59
teach prompting learners to attend to explicit facts that they can disseminate to another person. 60
This increase in declarative knowledge raises the possibility that the expecting to teach benefit to 61
skill accuracy and precision may be eliminated when a learner is asked to perform the acquired 62
skill under certain conditions, in particular under psychological pressure. This follows because 63
motor skills acquired concomitant to large gains in declarative knowledge are more susceptible 64
to decrement under psychological pressure than skills learned relatively implicitly (Hardy, 65
Mullen, & Jones, 1996; Koedijker, Oudejans, & Beek, 2007; Lam, Maxwell, & Masters, 2009a, 66
2009b; Liao & Masters, 2001; Masters, 1992). That is, when one accumulates a large number of 67
explicit facts about how to perform the skill they are learning, they are more likely to perform it 68
relatively poorly under psychological stress than if they had accrued a smaller number of facts 69
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while learning the skill. 70
The phenomenon that motor skills acquired with large gains in declarative knowledge are 71
highly susceptible to deterioration under pressure is consistent with Reinvestment Theory 72
(Masters & Maxwell, 2008). This theory contends that dispositional and situational factors, such 73
as psychological pressure, trigger individuals to use declarative knowledge acquired earlier in 74
learning to attempt to consciously monitor and control practiced movements. This focus of 75
attention on movement, paradoxically, impairs performance (Wulf & Su, 2007), likely due to 76
inefficient muscle activation as well as invariable and uncorrelated effector movement (Lohse, 77
Jones, Healy, & Sherwood, 2014; Lohse & Sherwood, 2012; Lohse, Sherwood, & Healy, 2010; 78
Lohse, Sherwood, & Healy, 2011). Crucially, learners who accrue more declarative knowledge 79
during skill practice are more likely to exhibit performance decrement under pressure, because 80
they have more declarative knowledge to reinvest’ in motor control. Notably, Reinvestment 81
Theory is similar to other with explanations describing motor skill decrement under high 82
psychological pressure (choking under pressure). Specifically, ‘explicit monitoring’ theories of 83
choking argue that pressure causes individuals to closely attend to their movements, 84
consequently worsening performance on motor skills largely relying on procedural knowledge 85
(Baumeister, 1984; DeCaro, Thomas, Albert, & Beilock, 2011). 86
In light of Reinvestment Theory, the aim of the present study was to investigate whether 87
the learning benefit of expecting to teach is eliminated when the acquired skill is performed 88
under high pressure. It was predicted that participants who practice and study with the 89
expectation of teaching would exhibit superior learning (skill retention, as indicated by posttest 90
performance), but that this advantage would be moderated by the condition under which learning 91
was assessed. Specifically, participants who expected to teach were hypothesized to exhibit 92
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superior performance on a low pressure posttest, but not on a high pressure posttest, due to a 93
decrease in performance (choking) under high pressure. Further, it was predicted that this 94
choking effect would be mediated by the amount of declarative knowledge participants used 95
during posttests, which was hypothesized to be higher for those expecting to teach and correlated 96
with the magnitude of choking. 97
Methods 98
Prior to beginning data collection, the experimental design and analyses were registered 99
and made public on AsPredicted.org (https://aspredicted.org/zb44r.pdf). 100
Participants 101
Eighty-two right-handed young adults (56 females), ages between 18 and 27 years (Mage 102
= 20.8 years, SD = 1.14 years), participated in the study after consenting to a protocol approved 103
by the Auburn University Institutional Review Board (#16-484 EP 1612). Participants were 104
recruited from university courses and by word-of-mouth, and were compensated with course 105
credit. In addition, the five best performers during the high pressure posttest received between 106
$10 (fifth place) and $50 (first place) (see more details in Posttest section). Sample size was 107
determined with an a priori power calculation providing 95% power (α = .05) to detect a 108
moderate-sized (η2p = .09) Between-Subject x Within-Subject interaction (groups = 2; 109
measurements = 3; nonsphericity correction = 1). 110
Task 111
All participants used a standard (89 cm), right-handed golf putter to putt a standard golf 112
ball from a starting position indicated by a 5 cm line painted in white washable paint on an 113
artificial grass surface to a target cross (+) comprised of two 10.8 cm lines painted in white 114
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washable paint and located 300 cm away from the starting position. Participants’ objective was 115
to make the ball stop as close to the center of the target as possible. 116
Procedure 117
All participants completed the experiment individually. After consenting to the 118
experiment, participants completed a demographic questionnaire asking their age, sex, and 119
putting experience (anything from miniature golf to playing 18 holes on a standard golf course) 120
over their lifetime and within the past year. Then, participants put a physiological monitoring 121
device around their chest (BioHarness 3.0, Zephyr Technology, Annapolis, MD) in order to get 122
used to wearing it, which they would be asked to do the following day as well. 123
Pretest. After completing the demographic questionnaire, participants performed the 124
pretest phase, which consisted of one block of ten putts. 125
Practice. After pretest, participants were quasi-randomly assigned to teach or test group. 126
Quasi-randomization was based on pretest accuracy score (distance from target). Specifically, 127
participants' pretest accuracy placed them in one of three categories (< 24 cm, 24 - 49 cm, > 49 128
cm), within which they were randomly assigned to the teach group or test group. (Category range 129
was based on pilot data [N = 12]). After quasi-randomization, the expecting to teach/expecting to 130
test manipulation occurred. Participants in the teach group were told, “Tomorrow you will teach 131
another participant how to putt,” and participants in the test group were told, “Tomorrow you 132
will be tested on your putting skills.” Next, participants completed the practice phase. First, 133
participants studied a golf putting instruction booklet for 2 min. The booklet consisted of written 134
and pictorial descriptions of proper putting technique, as described by an expert golfer (for 135
booklet, see Daou, Buchanan et al. [2016]). Next, participants performed six blocks of ten putts, 136
taking a 1 min break between each block (participants sat in a chair during the breaks). When 137
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participants stopped practicing, they completed the Intrinsic Motivation Inventory (Ryan, 1982) 138
for possible exploratory analyses related to motivation and pressure during practice. 139
Posttests (Low Pressure and High Pressure). One day after completing pretest and 140
practice, participants returned to complete the experiment. Participants in the teach group were 141
told, “The participant who you were going to teach did not show up today, so you will actually 142
be tested on your putting instead.” Then, participants put on the Bioharness, which was used to 143
provide a physiological measure of anxiety (heart rate) during the posttests. Next, they 144
completed low pressure and high pressure tests in counterbalanced order. For the low pressure 145
test, the experimenter told participants, “In this set of ten putts, your goal is to make the ball stop 146
as close to the center of the target as possible. Please, try to do the best you can.” For the high 147
pressure test, the experimenter told participants, “In the next set of ten putts, you will be 148
recorded and critically analyzed by a golf expert who will give you a grade.” The experimenter 149
took an iPad pro 9.7 (240 x 169 x 6.1 mm) from a cabinet and affixed it to the edge of a 73 cm 150
high table, approximately 45° to the right and 225 cm in front of participants. The iPad’s screen 151
faced participants so that they could see themselves being recorded. After the iPad was set-up, 152
the experimenter told participants, “The combination of the golf expert grade and your 153
performance during this set will allow you to compete against the rest of the participants for the 154
1st prize of $50, 2nd prize of $40, 3rd prize of $30, 4th prize of $20, and 5th prize of $10. In 155
summary, you will be putting for money.” As the experimenter explained the rewards, he took an 156
envelope from a cabinet, pulled money from it, and displayed the potential monetary rewards to 157
participants, after which he placed the money on a 91 cm high countertop, approximately 30° to 158
the left and 100 cm in front of participants. Our pressure manipulation involved two types of 159
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pressure revealed to elicit choking in previous studies: performance-contingent outcomes and 160
monitoring by others (e.g., DeCaro et al., 2011). 161
After each pressure manipulation (but before actually starting each posttest), participants 162
completed the Revised Competitive State Anxiety Inventory-2 (Cox, Martens, & Russell, 2003) 163
in order to determine manipulation efficacy. The Revised Competitive State Anxiety Inventory-2 164
is frequently used to assess anxiety in motor skill studies (Allsop & Gray, 2014; Elliot, Polman, 165
& Taylor, 2014; Kinrade, Jackson, & Ashford, 2015; Kuan, Morris, Kueh, & Terry, 2018; 166
Mullen, Jones, Oliver, & Hardy, 2016) and possesses good psychometric properties (Cox et al., 167
2003). The cognitive and somatic anxiety subscales were of interest, since the pressure 168
manipulation was intended to modulate anxiety (nonetheless, participants did complete the self-169
confidence subscale as well) (Jackson, Ashford, & Norsworthy, 2006). The cognitive and 170
somatic anxiety subscale items ask participants to report how much they are currently feeling 171
various indicators of anxiety. All responses were made by reporting a number between 0 and 100 172
on a scale with “not at all” corresponding to 0, followed by “somewhat”, then “moderately so”, 173
and finally “very much so”, which corresponded to 100. 174
After finishing posttests, participants completed a free recall test to measure declarative 175
knowledge use. Specifically, participants were asked to report, in as much detail as possible, any 176
rules, methods, or techniques they recalled using to putt during the posttests. This type of free 177
recall test is frequently used to assess declarative knowledge in motor skill studies (Daou, 178
Buchanan et al., 2016; Daou, Lohse et al., 2016; Daou, Lohse et al., 2018; Maxwell, Masters, & 179
Eves, 2000; Maxwell, Masters, Kerr, & Weedon, 2001; Zhu, Poolton, Wilson, Maxwell, & 180
Masters, 2011). 181
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Next, participants completed the Movement Specific Reinvestment Scale (Masters, Eves, 182
& Maxwell, 2005). The Movement Specific Reinvestment Scale is frequently used to examine 183
individual tendencies to reinvest in motor control (Huffman, Horslen, Carpenter, & Adkin, 2009; 184
Kal, van der Kamp, Houdijk, Groet, Bennekom, & Sherder, 2015; Klämpfl, Lobinger, & Raab, 185
2013; Malhorta, Poolton, Wilson, Ngo, & Masters, 2012; Vine, Moore, Cooke, Ring, & Wilson, 186
2013) and possesses good psychometric properties (Masters et al., 2005). The Movement 187
Specific Reinvestment Scale consists of the conscious motor processing and movement self-188
consciousness subscales, which ask participants to indicate how strongly they agree with 189
statements related to their tendency to attempt to control their movements and monitor their 190
movements, respectively. Participants respond on a 6-point scale anchored by strongly disagree 191
and strongly agree. Movement Specific Reinvestment Scale data was used to explore whether 192
individual tendencies toward reinvestment would significantly moderate any effects of expecting 193
to teach on choking under pressure. 194
Next, participants completed the shortened operation span task, which indexes working 195
memory capacity (Foster et al., 2014). Operation span task data were intended to be used to 196
examine whether individual differences in working memory capacity would significantly 197
moderate any effects of expecting to teach on choking, given that working memory capacity is 198
associated with one’s likelihood of choking. Interestingly, whether high working memory 199
capacity increases or decreases the likelihood of choking is debatable (Beilock & Carr, 2005; 200
Wood, Vine, & Wilson, 2016). Unfortunately, problems with operation span task data collection 201
led to removal of this data. Finally, participants were debriefed regarding the purpose of the 202
study and dismissed. 203
Data Processing 204
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Self-reported anxiety and heart rate. Good reliability was found among Revised 205
Competitive State Anxiety Inventory-2 subscale items reported prior to the low pressure 206
(cognitive anxiety Chronbach’s α = .781; somatic anxiety Chronbach’s α = .798) and high 207
pressure posttest (cognitive anxiety Chronbach’s α = .846; somatic anxiety Chronbach’s α = 208
.899). Thus, items were averaged within each subscale for each posttest. Next, the cognitive and 209
anxiety subscales were averaged together separately for each posttest, since the subscales were 210
strongly correlated for each posttest (low pressure: r = .549, p < .001; high pressure: r = .588, p < 211
.001). Thus, there was one self-reported anxiety score for the low pressure posttest and one score 212
for the high pressure posttest. 213
Bioharness data was extracted and analyzed using Omnisense software (Zephyr 214
Technology, Annapolis, MD). Specifically, heart rate was averaged from the time participants 215
were read test instructions until they completed the test for the low and high pressure posttest. 216
Bioharness data was not successfully recorded for six participants. 217
Putting. Putting accuracy was indexed by recording radial error as recommended by 218
Hancock, Butler, and Fischman (1995):   = (2+ 2)1/2, where x and y represent 219
the magnitude of error along the respective axes (i.e., how far away from the target cross the ball 220
stopped in the horizontal and vertical directions). Precision was indexed by recording bivariate 221
variable error as recommended by Hancock et al.:    =222
{(1
)[( )2
=1 + ( )2]}1/2, where k = trials in a block and c = centroid along the 223
given axis (x or y) for that block. Radial error and bivariate variable error were calculated over 224
pretest (10 putts) to get a baseline skill level, as well as for each of the six blocks (6 x 10 putts) 225
of the practice phase to get an assessment of improvement in performance. To assess motor 226
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learning and choking under pressure, radial error and bivariate variable error were calculated for 227
the low and high pressure posttests. 228
Free recall. Three indices of declarative knowledge use were extracted from participants’ 229
responses on the free recall test. (One participants’ free recall data was lost.) First, ‘all concepts’ 230
referred to the number of statements about a concept (rule) (e.g., “I held my left hand over above 231
my right”), ignoring statements irrelevant to technical performance (e.g., “I was told to putt ten 232
times to the target”). Second, ‘key concepts’ referred to the four most important rules in the golf 233
putting instruction booklet: (1) establish proper grip, (2) place the putter head behind the ball and 234
take a hip-width stance, (3) place the eyes directly over the ball by hinging from the hips, and (4) 235
stroke the ball without breaking the wrists (Daou, Buchanan et al., 2016). Third, hypothesis 236
testing referred to statements indicating that the participant had tested hypotheses related to their 237
putting stroke (e.g., “I adjusted the swing path of the putter after each missed ball” or “I tried to 238
keep my head still throughout my putting stroke”). That is, hypothesis testing statements were 239
those that indicated the participant made a prediction about the relationship between their putting 240
movement and putt outcome (Maxwell et al., 2001). We ignored retrospective statements (e.g., “I 241
held my left hand above my right” or “My feet were shoulder width apart”) that may not have 242
been used or thought about while putting, and we also ignored statements irrelevant to technical 243
performance. Two researchers blind to participants’ group assignment scored the declarative 244
knowledge use measures. Next, their scores were correlated to examine interrater consistency. 245
The correlation coefficients were strong and significant: all concepts (r = .788, p < .001), key 246
concepts (r = .685, p < .001), and hypothesis testing (r = .815, p < .001). Thus, the raters’ scores 247
for each measure were averaged. The hypothesis testing score was of greatest interest, as it has 248
been most closely linked with reinvestment (Maxwell et al., 2001). 249
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Movement Specific Reinvestment Scale. Good reliability was found among movement 250
self-consciousness items (Chronbach’s α = .813), but not among conscious motor processing 251
items (Chronbach’s α = .573). Importantly, good reliability was found when all items were 252
considered (Chronbach’s α = .750), so all items were summed into a single score (Malhorta et 253
al., 2012). 254
Statistical Analysis 255
To assess heart rate and self-reported anxiety, 2 (Group: teach/test) x 2 (Posttest: low 256
pressure/high pressure) ANOVAs were conducted. (We planned to conduct paired-sample t-tests, 257
but switched to ANOVAs in accord with the suggestions of two anonymous reviewers.) To 258
assess practice performance, 2 (Group) x 6 (Practice Block: 1/2/3/4/5/6) ANCOVAs were 259
conducted for radial error and bivariate variable error, with pretest radial error and bivariate 260
variable error serving as the respective covariate. Prior to analysis, we conducted Mauchly’s test 261
for sphericity and the Greenhouse-Geisser correction was applied when sphericity was violated. 262
To assess motor learning, 2 (Group) x 2 (Posttest) mixed-factor ANCOVAs (with repeated 263
measures on the second factor) were conducted for radial error and bivariate variable error, with 264
pretest radial error and bivariate variable error serving as the respective covariate. To examine 265
reinvestment scores, we conducted linear mixed effect regressions for radial error and bivariate 266
variable error with fixed effects of pretest radial error and bivariate variable error, group, 267
posttest, reinvestment score, and interactions between the last three factors. The models also 268
included participant as a random effect. Independent sample t-tests (group) were conducted for 269
free recall scores. 270
Results 271
Descriptive Data 272
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Table 1 shows descriptive data for each group. 273
274
Table 1. Descriptive data for each group. 275 276
Descriptive Data by Group
Test (n = 42; 32 females)
Teach (n = 40; 24 females)
M
95% CI
95% CI
Age (Years)
20.9
20.5 – 21.3
20.4 – 21.4
Lifetime Putting Experiencea
1.24
0.97 – 1.51
1.03 – 1.57
Past-Year Putting Experiencea
0.405
0.245 – 0.565
0.280 – 0.620
Low Pressure Self-Reported Anxiety
10.1
6.90 – 10.1
11.3 – 18.9
High Pressure Self-Reported Anxiety
20.3
15.3 – 25.3
19.0 – 30.2
Low Pressure Heart Rate (beats/min)
87.6
83.8 – 91.4
89.2 – 95.6
High Pressure Heart Rate (beats/min)
89.4
85.6 – 93.2
91.1 – 97.9
Free Recall All Concepts
5.76
5.09 – 6.43
6.37 – 7.70
Free Recall Key Concepts
1.88
1.61 – 2.15
1.92 – 2.42
Free Recall Hypothesis Testing
0.357
0.087 – 0.627
0.103 – 0.563
Reinvestment Score
30.0
27.9 – 32.1
28.7 – 33.3
a 0 = Never putted; 1= Putted 1 – 10 times; 2 = Putted 11 – 20 times; 3 = Putted 21 – 30 times 277 278 Self-Reported Anxiety and Heart Rate 279
There was a significant main effect of posttest for self-reported anxiety (F(1, 80) = 53.5, 280
p < .001, η2p = .401), such that anxiety was greater preceding the high pressure posttest in 281
comparison to the low pressure posttest (see Table 1). There was no main effect of group (F(1, 282
80) = 2.46, p = .121, η2p = .030) nor was there a Group x Posttest interaction (F(1, 80) = 0.071, p 283
= .791, η2p = .001). There was a significant main effect of posttest for heart rate (F(1, 74) = 21.6, 284
p < .001, η2p = .226), such that heart rate was elevated preceding the high pressure posttest in 285
comparison to the low pressure posttest (see Table 1). There was no main effect of group (F(1, 286
74) = 3.75, p = .057, η2p = .048)1 nor was there a Group x Posttest interaction (F(1, 74) = 0.097, 287
1 The main effect of group approaching conventional significance appears to be due to teach group participants
randomly having higher heart rate than test group participants, because teach participants also exhibited higher heart
rate at pretest (teach: M = 92.1, CI = 88.1 96.1 beats/min vs. test: M = 86.3, CI = 82.2 90.4 beats/min). Crucially,
pretest occurred prior to the expecting to teach/test manipulation. Finally, neither low pressure heart rate, high
15
p = .756, η2p = .001). Self-reported anxiety and heart rate results suggest the psychological 288
pressure manipulation was effective. 289
Practice Performance and Motor Learning 290 291
The left panel of Figure 1 shows accuracy (radial error) for the groups across study 292
phases. For practice radial error, no main effect of group (F(1, 79) = 2.06, p = .155, η2p = .025) 293
or block (F(4.27, 338) = 1.03, p = .397, η2p = .013, ɛ = .855) was observed nor was a Group x 294
Block interaction revealed (F(4.27, 338) = 1.229, p = .298, η2p = .015, ɛ = .855), controlling for 295
pretest radial error. The right panel of Figure 1 shows precision (bivariate variable error) for the 296
groups across all study phases. For practice bivariate variable error, no main effect of group (F(1, 297
79) = 2.45, p = .121, η2p = .030) or block (F(4.32, 341) = 1.32, p = .259, η2p = .016, ɛ = .864) was 298
observed nor was a Group x Block interaction revealed (F(4.27, 338) = 1.229, p = .298, η2p = 299
.015, ɛ = .864), controlling for pretest bivariate variable error. These results are consistent with 300
past experiments showing expecting to teach does not improve performance while practicing the 301
skill (Daou, Buchanan et al., 2016; Daou, Lohse et al., 2016; Daou, Lohse et al., 2018). 302
For posttest radial error, a main effect of group was observed (F(1, 79) = 4.34, p = .041, 303
η2p = .052), but a main effect of posttest was not (F(1, 79) = 1.31, p = .256, η2p = .016), 304
controlling for pretest radial error. Importantly, the predicted Group x Posttest interaction 305
approached our alpha level (F(1, 79) = 3.82, p = .054, η2p = .046), controlling for pretest radial 306
error2, 3. Thus, we conducted univariate (group) ANCOVAs for each posttest, controlling for 307
pressure heart rate, nor low pressure high pressure Δheart rate predicted low pressure radial error, high pressure
radial error, or low pressure high pressure Δradial error (ps ≥ .098), controlling for pretest radial error and group.
2 It is worth noting that the Group x Posttest interaction is significant when not controlling for pretest radial error
(F(1, 79) = 4.35, p = .040, η2p = .052), which would be justifiable given that participants were quasi-randomly
assigned to groups based on pretest radial error.
3 Adding a between-subjects factor of posttest order (low pressure posttest first/high pressure posttest first) to the
ANCOVA reveals: posttest order does not have a main effect on posttest radial error (F(1, 72) = 0.840, p = .362, η2p
= .012); Group x Posttest Order does not affect posttest radial error (F(1, 72) = 0.974, p = .327, η2p = .013); Posttest
16
pretest radial error. The group effect was significant for the low pressure posttest, with the teach 308
group exhibiting superior accuracy (F(1, 79) = 10.6, p = .002, η2p = .119). This result is 309
consistent with prior experiments and indicates expecting to teach enhances motor learning as 310
measured by accuracy (Daou, Buchanan et al., 2016; Daou, Lohse et al., 2016; Daou, Lohse et 311
al., 2018). Importantly, the group effect was not significant for the high pressure posttest, with 312
the teach and test groups exhibiting similar accuracy (F(1, 79) = 0.235, p = .630, η2p = .003). 313
Crucially, the reason for this is revealed by paired sample t-tests demonstrating that teach group 314
was significantly less accurate under high pressure relative to low pressure (t(39) = 2.31, p = 315
.026, d = 0.449), whereas test group’s accuracy exhibited a non-significant improvement (t(41) = 316
0.627, p = .534, d = 0.102). That is, expecting to teach enhanced motor learning as measured by 317
accuracy, but this advantage was eliminated under high pressure, due to a choking effect 318
exhibited by participants who had practiced with the expectation of teaching. 319
For posttest bivariate variable error, there was no main effect of group (F(1, 79) = 3.04, p 320
= .085, η2p = .003) or posttest (F(1, 79) = 0.581, p = .448, η2p = .007), nor was there a Group x 321
Posttest interaction (F(1, 79) = 2.26, p = .137, η2p = .028), controlling for pretest bivariate 322
variable error. Exploratory analyses for bivariate variable error are presented in supplementary 323
online material. These analyses mirror those performed for radial error and exhibit fairly similar 324
results. 325
x Posttest Order does not affect posttest radial error (F(1, 72) = 1.18, p = .282, η2p = .016); and Group x Posttest x
Posttest Order does not affect posttest radial error (F(1, 72) = 0.150, p = .700, η2p = .002).
17
326
Figure 1. Putting accuracy (left panel) and precision (right panel) as a function of study phase and group. Lower 327
radial error and bivariate variable error indicate superior accuracy and precision, respectively. All error bars 328
represent 95% CIs. Generally, teach and test group exhibited similar accuracy and precision during pretest and 329
practice. Conversely, teach group tended to show superior accuracy under low pressure posttest, but not under high 330
pressure posttest, wherein teach group’s accuracy declined (teach group choked under pressure). 331
332
Movement Specific Reinvestment Scale 333
The linear mixed effect regression for radial error failed to reveal a significant 334
Reinvestment Score x Group (p = .426), Reinvestment Score x Posttest (p = .880), or 335
Reinvestment Score x Group x Posttest interaction (p = .900). Notably, the main effect of 336
reinvestment score approached conventional significance (p = .0503), with lower reinvestment 337
scores predicting lower radial error (see Table 2 and Figure 2). Further, the main effect of group 338
(p = .022) and the Group x Posttest interaction (p = .039) become more reliable when accounting 339
for reinvestment score. Thus, an individual’s tendency to reinvest does not moderate the effect of 340
expecting to teach on motor learning or choking under pressure, as measured by accuracy. 341
18
However, accounting for an individual’s tendency to reinvest does strengthen these effects, as 342
one’s disposition to reinvest tends to explain individual differences in accuracy. 343
344
Table 2. Parameters for linear mixed effect regression predicting posttest radial error and including reinvestment 345
score as a predictor. 346
Linear Mixed Effect Regression Predicting Posttest Radial Errora
Fixed-Effect
Beta
SE
df
t-value
p-value
Intercept
40.0
1.24
82
32.3
< .001
Pretest Radial Errorb
0.138
0.050
82
2.74
.007
Groupc
-2.91
1.25
82
-2.33
.022
Posttestd
1.14
0.925
82
1.23
.223
Reinvestment Scoreb
0.348
0.175
82
1.99
.050
Groupc x Posttestd
1.94
0.925
82
2.10
.039
Groupc x Reinvestment Scoreb
-0.140
0.175
82
-0.800
.426
Posttestd x Reinvestment Scoreb
0.020
0.131
82
0.152
.880
Groupc x Posttestd x Reinvestment Scoreb
-0.017
0.131
82
-0.127
.900
a Model included a random effect of participant. Model fit and random effect statistics are included in 347
supplementary online material (Table S1). 348
b Factor is mean centered 349
cContrast coded (test = -1, teach = 1) 350
dContrast coded (low pressure = -1, high pressure = 1) 351
352
353
354
19
Figure 2. High pressure (left) and low pressure (right) posttest putting accuracy as a function of group and 355
reinvestment score. Lower radial error indicates superior accuracy and higher Movement Specific Reinvestment 356
Scale scores indicate a greater disposition to reinvestment in motor control. Participants with higher reinvestment 357
scores tended to exhibit poorer accuracy. 358
359
Free Recall 360
A significant effect of group was demonstrated for all concepts, with teach group 361
exhibiting superior recall (t(79) = 2.58, p = .012, d = 0.573). However, no significant effects 362
were observed for key concepts (t(79) = 1.49, p = .141, d = 0.332) or hypothesis testing (t(79) = 363
0.150, p = .881, d = 0.070). Thus, results suggest expecting to teach increased declarative 364
knowledge use during posttests, but not hypothesis testing. 365
Mediation of Low Pressure High Pressure Posttest Performance Change by Free Recall 366
Thus far, results have generally shown that participants who expected to teach exhibited 367
superior motor learning, but that this benefit is eliminated under high pressure, because these 368
participants choked under pressure. Additionally, results have demonstrated that these 369
participants self-reported more declarative knowledge about the task. However, it is unknown 370
whether the amount of declarative knowledge explains the choking effect exhibited by 371
participants who expected to teach. To address this question, we conducted a mediation analysis 372
using linear regressions (Barron & Kenny, 1986). Specifically, we considered group as the 373
independent variable, all concepts (the free recall variable that differed between groups) as the 374
mediator variable, and the low pressure – high pressure posttest difference for radial error 375
(Δradial error) as the dependent variable. (Lower Δradial error indicates great choking under 376
pressure.) Figure 3 depicts the mediation. First, group (coded as test = -1 and teach = 1) was 377
shown to predict Δradial error (Path C: βunstandardized = -3.90 cm, p = .040). Next, group was 378
20
shown to predict all concepts (Path A: βunstandardized = 0.632, p = .012). However, all concepts 379
failed to predict Δradial error (Path B: βunstandardized = 0.640 cm, p = .453), and group still 380
predicted Δradial error when adding all concepts to the regression (Path C': βunstandardized = -4.42 381
cm, p = .026). This result suggests declarative knowledge use, as measured by free recall of all 382
concepts, does not explain the choking effect exhibited by participants who expected to teach. 383
384
385
Figure 3. Mediation model testing whether the teach group’s greater declarative knowledge use (Path A), as 386
measured by all concepts recalled, explains their increased choking under pressure (Path C), reflected by greater 387
change from low pressure to high pressure posttest accuracy. Declarative knowledge use did not explain the 388
relationship between group assignment (teach/test) and choking under pressure. Specifically, declarative knowledge 389
use did not predict choking under pressure (Path B), and group assignment still predicted choking under pressure, 390
even when accounting for declarative knowledge use (Path C'). 391
392
Discussion 393
21
The aim of the present study was to investigate whether the learning benefit of expecting 394
to teach is eliminated when the acquired skill is performed under high pressure. A Group x 395
Posttest interaction approached conventional significance. As predicted, teach group participants 396
generally exhibited superior accuracy on a low pressure posttest relative to test group 397
participants, but this group difference was not present on a high pressure posttest. Importantly 398
and as predicted, the failure of the teach group to outperform the test group under high pressure 399
was due to the teach group’s accuracy significantly decreasing from low pressure to high 400
pressure posttest, which did not occur for the test group. That is, the teach group choked under 401
pressure, but the test group did not. It was predicted that the cause of the choking effect would be 402
the teach group’s greater use of declarative knowledge than the test group, but results do not 403
support this hypothesis. In particular, although the teach group did recall using more skill 404
concepts while performing posttests, the number of skill concepts did not predict choking under 405
pressure (decrease in accuracy from low pressure to high pressure posttest). 406
Present results are consistent with prior experiments revealing that expecting to teach 407
enhances motor learning in comparison to expecting to test (Daou, Buchanan et al., 2016; Daou, 408
Lohse et al., 2016; Daou et al., 2018). Specifically, expecting to teach improved skill accuracy, 409
suggesting enhanced procedural knowledge. Thus, the present experiments adds to the growing 410
body of evidence that practicing and studying a motor skill with the expectation of teaching it 411
enhances learning. However, it is important to note that past experiments assessed golf putting 412
like the present study. Therefore, future investigations may attempt to replicate the expecting to 413
teach effect with other discrete aiming skills or more dissimilar skills (e.g., continuous skills, 414
such as swimming). 415
Previous experiments have revealed participants who expect to teach can recall more skill 416
22
concepts than participants who expect to test, indicating expecting to teach enhances declarative 417
knowledge (Daou, Buchanan et al., 2016; Daou, Lohse et al., 2016; Daou, Lohse et al., 2018). 418
Notably, Reinvestment Theory posits that learners who have more declarative knowledge are at 419
increased risk of choking under pressure, because they may reinvest their knowledge in motor 420
control (Masters & Maxwell, 2008). Thus, present results showing participants who expected to 421
teach reported using more rules, methods, and/or techniques during posttests and choked under 422
pressure are consistent with prior expecting to teach experiments and Reinvestment Theory. 423
However, the result that expecting to teach increased the use of declarative knowledge 424
coincident to choking under pressure does not demonstrate the increase in knowledge use caused 425
choking. Indeed, declarative knowledge use, as measured by free recall of concepts used for 426
putting, did not predict choking under pressure. Thus, it is possible there is an alternative 427
explanation for why expecting to teach caused choking, but such an explanation is unapparent to 428
us. Rather, it is possible free recall is an imprecise measure of declarative knowledge use and, 429
therefore, may poorly predict choking. Specifically, measuring declarative knowledge use with 430
free recall assumes participants are aware of their thoughts during performance, which may be a 431
poor assumption given that individuals may mind-wander during motor performance (Kam et al., 432
2012). Indeed, it is notable that Reinvestment Theory experiments report increases in declarative 433
knowledge use coincident to choking, but have not shown knowledge use predicts choking 434
(Hardy et al., 1996; Koedijker et al., 2007; Lam et al., 2009a, 2009b; Liao & Masters, 2001; 435
Masters, 1992). To improve the precision of measuring declarative knowledge use during 436
performance, researchers may employ ‘online’ measurement techniques, such as EEG measures 437
of neural activation in verbal-analytic brain regions and networking between these regions and 438
motor planning regions (e.g., Buszard, Farrow, Zhu, & Masters, 2016; Deeny, Hillman, Janelle, 439
23
& Hatfield, 2003; Dyke et al., 2014; Zhu et al., 2010; Zhu, Poolton, Wilson, Hu et al., 2011; Zhu 440
et al., 2011). 441
Besides using an imprecise measure of declarative knowledge use, other limitations of 442
the present experiment should be noted. First, although results concerning the effect of expecting 443
to teach on motor learning (e.g., accuracy for the low pressure posttest) were moderately strong 444
in terms of effect size and p-value, results concerning the effects of expecting to teach on 445
choking (e.g., Group x Posttest interaction) tended to be weak. Notably, accounting for 446
participants’ inclination to reinvest in their movement (reinvestment score) strengthened the 447
effect of expecting to teach on choking (and motor learning). Further, reinvestment score tended 448
to predict accuracy, with greater propensity toward reinvestment associated with poorer 449
accuracy. Thus, the present results highlight the value of employing the Movement Specific 450
Reinvestment Scale score to reduce between-subjects variability in motor learning and 451
performance research. Unfortunately, due to problems with operation span task data collection, 452
we were unable to account for working memory capacity, which could have further accounted 453
for between-subjects variability in the effects of expecting to teach on choking (Beilock & Carr, 454
2005; Wood et al., 2016). 455
Determining practical ways to enhance people’s learning while they study and practice 456
motor skills is crucial to improving behavior. Present results add to a growing body of evidence 457
that having learners study or practice with the expectation of teaching is one means to 458
improvement. (Importantly, it is likely that eventually having learners actually teach another 459
person (in addition to expecting to teach) further enhances learning (Fiorella & Mayer, 2014, 460
Experiment 2.) Although present results suggest the enhancement imparted by expecting to teach 461
may be eliminated when a learner is required to perform under high psychological pressure, it is 462
24
crucial to note that present results suggest expecting to teach does not cause learners to perform 463
worse under high pressure than learners who studied and practiced with the expectation of 464
testing. Rather, high pressure brought learners who expected to teach back to the level of those 465
who expected to test. Thus, having learners study and practice with the expectation of teaching is 466
still preferable over having them study and practice with the expectation of testing, especially 467
considering the strong and reliable effect of the expecting to teach effect on motor learning in 468
comparison to the weak effect of expecting to teach on choking. 469
Future research should explore means by which the expecting to teach benefit can be 470
preserved when learners must perform under high pressure. Present results are inconclusive as to 471
whether the elimination of the expecting to teach advantage was caused by relatively large 472
accruals of declarative knowledge. Even so, it is advisable to investigate whether having learners 473
study and practice in ways likely to promote implicit learning (minimize gains in declarative 474
knowledge) while expecting to teach can prevent choking under pressure by learners who study 475
and practice with the expectation of teaching. There are multiple techniques to encourage 476
implicit learning, including providing instructions in the form of analogies (Lam et al., 2009a, 477
2009b; Liao & Masters, 2001; Masters, Poolton, Maxwell, & Raab, 2008) and minimizing errors 478
during practice (Orrell, Eves, & Masters, 2006; Poolton, Masters, & Maxwell, 2005; Zhu et al.., 479
2011), and these techniques should be considered in conjunction with having learners expect to 480
teach. 481
Another way to alter the practice environment so that learners may train with the 482
expectation of teaching and avoid choking under pressure might be to expose learners to 483
performance pressure during practice. This may inoculate learners from experiencing 484
psychological stress in high stakes environments (Mace & Carroll, 1986), thus preserving the 485
25
benefits gained by practicing with the expectation of teaching. For example, learners could 486
practice with the expectation of teaching as well as perform practice tests with performance-487
contingent outcomes and close monitoring by others. 488
Implicit learning and stress inoculation both involve physical practice, but instructors 489
may also have learners engage in mental practice/skills training to reduce their likelihood of 490
experiencing anxiety in high stakes environments, thus reducing the probability of choking under 491
pressure. Mental practice/skills training techniques could involve imagery and meditation 492
(Benson, 2000; Hill, Hanton, Matthews, & Fleming, 2011), and these techniques could be 493
implemented along with practicing with the expectation of teaching. 494
The aforementioned means to preserving the expecting to teach benefit under pressure are 495
implemented outside of performance (e.g., while learners are practicing); however, instructors 496
should also apply methods to minimize choking while learners are performing (when pressure is 497
occurring). For example, instructors could have learners engage in hemispheric-specific priming 498
just prior to performing under pressure. This priming can be done by repeatedly squeezing a soft 499
ball in one’s left hand (in the case of right-handed individuals) for 30 s (Beckmann, Gröpel, & 500
Ehrlenspiel, 2013). Additionally, instructors should take measures to reduce anxiety when 501
learners are performing skills in high stakes situations. This could be done by having learners 502
engage in arousal reduction practices, such as progressive relaxation (Jacobson, 1938; Ӧst, 503
1988). 504
In conclusion, it is recommended that learners practice with the expectation of teaching. 505
Further, learners should also engage in physical and mental training techniques likely to prevent 506
choking under pressure. Finally, methods to reduce choking under pressure should be 507
implemented while learners are performing in high stakes environments. 508
26
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... Although Daou and colleagues have replicated the expecting to teach effect, they have shown that it may have limits, such as operating under low pressure situations, but not high pressure post-test situations (Daou, Hutchison, et al., 2019). Moreover, in recent experimentation, which used a 2x2 factorial design consisting of instruction set (Teach/Test) and motor preparation time (limited/unlimited), expecting to teach did not increase motor preparation time nor did it generate the motor learning advantages previously demonstrated . ...
... To date, the benefits for motor learning associated with expecting to teach has only been found in one research laboratory, and that laboratory has produced both significant expecting to teach effects (Daou, Hutchison, et al., 2019;Daou, Buchanan, et al., 2016) and null effects Rhoads et al., 2019). Lohse et al. (2016) have encouraged motor learning researchers to conduct replications stating that the replication of results in a different research laboratory greatly improves the precision of effect estimates (see also Open Science Collaboration (2015)). ...
... Beyond the direct replication, a secondary purpose was to explore other mechanisms that may be at play in the expecting to teach effect. Daou and colleagues had focused their efforts on possible affectivemotivational mechanisms, as well as motor preparatory mechanisms that may occur during the acquisition phase (Daou, Hutchison, et al., 2019;Daou, Buchanan, et al., 2016). Throughout their series of experiments, however, there has been little support for either of these mechanisms. ...
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While research has identified several practice variables that purportedly enhance motor learning, recent replication failures highlight the importance of conducting high-powered, pre-registered replications. The "expecting to teach" phenomenon was first reported in the motor learning literature by Daou and colleagues and suggested learners benefit from practicing with the understanding they will later need to teach the skill. The extant data have been mixed but generally positive. While expecting to teach has been shown to enhance motor learning of a golf putt, the mechanisms linked with this benefit are yet to be determined. As such, this study sought to replicate the expecting to teach effect and to extend those findings by exploring participants’ thought processes. Participants (N = 76) were randomly assigned to one of two groups in which they were told that they were learning a golf putt in order to 1) be tested on the skill or 2) teach the skill to another individual. On Day 1, participants completed pre-test putts, a pre-acquisition intrinsic motivation inventory (IMI), a 2-minute study of an instructional booklet, 50 practice putts and a post-acquisition IMI. During practice, participants were also afforded opportunities to continue studying the booklet and to complete additional putts. Participants returned 24 hours later to complete a retention, a transfer (50-cm longer golf-putt), and a free recall test, as well as a post-study survey to reveal thoughts they engaged in after practice but before (or during) the retention test. Similar to Daou et al., no significant differences were found with study time, number of acquisition putts, or motivation. However, golf-putting performance during retention resulted in no differences for radial error, g = -0.13 (95% C.I. [-0.55, 0.29]), between the two groups and no differences were shown for the recall test. The present study fails to replicate the benefits reported in the original experiments.
... However, motivation and anxiety have nothing to do with the benefit of learning with the expectation to teach, but due to the improvement of declarative knowledge during this new method the recall of key skill-related concepts was improved. This group of researchers in several studies indicated benefits of learning by expecting to teach compared to other test groups [6][7][8][9]. However, some studies have shown that learning by expecting to teach will not be effective in situations under high psychological pressure. ...
... However, some studies have shown that learning by expecting to teach will not be effective in situations under high psychological pressure. For example, Daou et al. [7] in another study examined the effectiveness of learning by expecting to teach in stressful situations. They sought to examine whether the advantage created by the expectation to teach is sustainable in certain situations, such as high psychological pressure, and concluded that the motor skill learning efficacy deteriorated in the situations when people practice in a group with expectation to teach. ...
... Since this method enhances the learner's declarative knowledge in accordance with the reinvestment theory [12], it causes a decline in performance in certain situations such as stress and high psychological pressure. Of course, this decline in performance is manifested in a way that they perform similarly to someone who has practiced the skill without expecting to teach [7]. Given that this research topic in the field of motor learning is relatively new, there are still many ambiguities in this area. ...
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Introduction and purpose. Recently, some motor behavior researchers have introduced the learning method that indicates expecting to teach to others improves motor learning in adults. The purpose of the present study is to examine the effect of expecting to teach to the others on the learning of a golf-putting task in children. Method and Material. Participants consisted of 24 children (all males; Mage= 9.58; SD=0.50 years) who were randomly assigned into two experimental groups. Participants in the group of expecting to teach to the others were instructed as follows: "given that you have to teach golf putt to some people the day after the acquisition phase, you have the opportunity to practice this skill carefully today and tomorrow". Participants in the group of expecting to be tested received the following instructions; "you have the opportunity to practice this skill carefully today and tomorrow expecting to be tested in this skill". Results. The results showed that the children in the group of expecting to teach to the others had better accuracy scores relative to children in the group of expecting to be tested in retention phase (p ≤ 0.05). Conclusion. The findings of this study suggest that promoting the expectation to teach to others would improve motor learning in children.
... As many skills must be performed in high-stakes environments, such as sports competition, it is crucial to determine practice conditions that enhance learning and preserve learning benefits under psychological pressure. Recently, Daou, Hutchison, et al. (2019) revealed that practicing a motor skill with the expectation of teaching it to another person loses its benefit when the learned skill is performed under psychological pressure. Therefore, the purpose of the present study is to determine whether the expecting to teach approach can be modified to preserve its learning advantage, and, in so doing, shed light on the mechanisms underlying the loss of the benefit under psychological pressure. ...
... Daou, Buchanan, Lindsey, Lohse, and Miller (2016) conducted the first investigation into whether expecting to teach enhances learning of motor skills, which rely more heavily on procedural knowledge than academic information does (Rosenbaum, Carlson, & Gilmore, 2001). Daou, Buchanan et al. observed having learners practice and study a motor skill with the expectation of teaching it to another person enhanced skill learning in comparison to having learners practice and study a skill with the expectation of being tested, and this effect has been replicated several times (Daou, Hutchison et al., 2019;Daou, Lohse, & Miller, 2016;Daou, Lohse, & Miller, 2018;Daou, Rhoads, Jacobs, Lohse, & Miller, 2019). Although research has failed to reveal the mechanisms underlying the learning benefit of expecting to teach, studies have consistently shown that the learning advantage occurs concomitant to large gains in declarative knowledge about the learned skill (Daou, Buchanan et al., 2016;Daou et al., 2018;Daou, Hutchison et al., 2019;Daou, Lohse et al., 2016;. ...
... Daou, Buchanan et al. observed having learners practice and study a motor skill with the expectation of teaching it to another person enhanced skill learning in comparison to having learners practice and study a skill with the expectation of being tested, and this effect has been replicated several times (Daou, Hutchison et al., 2019;Daou, Lohse, & Miller, 2016;Daou, Lohse, & Miller, 2018;Daou, Rhoads, Jacobs, Lohse, & Miller, 2019). Although research has failed to reveal the mechanisms underlying the learning benefit of expecting to teach, studies have consistently shown that the learning advantage occurs concomitant to large gains in declarative knowledge about the learned skill (Daou, Buchanan et al., 2016;Daou et al., 2018;Daou, Hutchison et al., 2019;Daou, Lohse et al., 2016;. As motor skills acquired with large gains in declarative knowledge are highly susceptible to decrement under psychological pressure (Lam, Maxwell, & Masters, 2009a, 2009bHardy, Mullen, & Jones, 1996;Koedijker, Oudejans, & Beek, 2007;Liao & Masters, 2001;Masters, 1992), it was unsurprising that Daou, Hutchison, et al. (2019) revealed that the expecting to teach benefit vanished under psychological pressure, due to participants who practiced with the expectation of teaching 'choking' in a high-pressure posttest. ...
Article
Objective: Having learners practice a motor skill with the expectation of teaching it (versus an expectation of being tested on it) has been revealed to enhance skill learning. However, this improvement in skill performance is lost when the skill must be performed under psychological pressure due to 'choking under pressure.' The present study will investigate whether this choking effect is caused by an accrual of declarative knowledge during skill practice and could be prevented if a technique (analogy instructions) to minimize the accrual of declarative knowledge during practice is employed. Design: We will use a 2 (Expectation: teach/test) x 2 (Instruction: analogy/explicit) x 2 (Posttest: high-pressure/low-pressure) mixed-factor design, with repeated measures on the last factor. Methods: A minimum of 148 participants will be quasi-randomly assigned (based on sex) to one of four groups. Participants in the teach/analogy and teach/explicit groups will practice golf putting with the expectation of teaching putting to another participant, and analogy instructions or explicit instructions, respectively. Participants in the test/analogy and test/explicit groups will practice golf putting with the expectation of being tested on their putting, and analogy instructions or explicit instructions, respectively. The next day all participants will complete low- and high-pressure putting posttests, with their putting accuracy serving as the dependent variable.
... Usually, fear resulted from a previous traumatic experience or an attempt to protect themselves from an injury [32]. It is observed that children, when entering the water, choose to enter on foot or hold their nose to dive. ...
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The playful training method shows positive effects on sports learning, thus the aim of the present study was to compare the effect of two different swimming learning programs. In an 8-week intervention with a training frequency of three times per week, 23 healthy primary school-aged novice swimmers (13 boys, 10 girls) aged 9.0 ± 0.9 participated. They were split into control (CG) and alternative (AG) groups and evaluated on skills (Start, Sink), backstroke (BK) and breaststroke (BR) technique, performance (Skills time, Kicks Time), and salivary cortisol concentration. According to the results, "Start" had a greater percentage of success in AG, at the first (CG = 9.1% vs. AG = 58.3%, p = 0.027) and third (CG = 63.6% vs. AG = 100%, p = 0.037) measurement. Additionally, greater scores were found in technique for AG in both BK (p = 0.009, η 2 = 0.283) and BR (p = 0.020, η 2 = 0.231). Salivary cortisol concentration was decreased for both groups (p < 0.001) and greater in CG at the second measurement (p < 0.001). The alternative swimming learning program was found to be more efficient or equally effective, compared with the standardized method in-water skills, swimming technique and performance, and in salivary cortisol concentration.
... Prior to the pilot study, we chose to assign seven raffle tickets for choosing the correct target in order to approximately equate the number of raffle tickets that would be earned through the action selection and action execution tasks. Specifically, we used data from previous golf putting experiments in our lab (e.g., Daou, Lohse, & Miller, 2018;Daou et al., 2019) to determine that participants were likely to earn an average of five to six raffle tickets per putt, and we assumed that participants would get close to 75% of the action selection trials correct, giving them an average of 5 to 6 raffle tickets on each trial of the action selection task. 5 After being assigned to their respective condition, participants followed the same protocol as in the pilot study. ...
Article
It is unknown whether rewards improve the capability to select appropriate targets for one’s movement (action selection) and/or the movement itself (action execution). Thus, we devised an experimental task wherein participants categorized a complex visual stimulus to determine toward which one of two targets to execute an action (putt a golf ball) on each trial under one of three conditions: reward, punishment, or neutral. After practicing the task under their assigned condition, participants performed an immediate, 24-hr, and 7-day post-test. Results revealed participants putted to the correct target more frequently during the post-tests than the first practice block, and putted more accurately during the post-tests than a pretest. However, the condition in which participants practiced did not moderate post-test performance (for either task component). Additionally, motivation scores explained action selection and action execution for the immediate posttest performance but not long-term retention, suggesting that motivation might be related to immediate performance, but not long-term learning. Further, the present task may be useful for researchers studying action selection and execution, since the task yielded learning effects that could be moderated by factors of interest.
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Motor learning encompasses a broad set of phenomena that requires a diverse set of experimental paradigms. However, excessive variation in tasks across studies creates fragmentation that can adversely affect the collective advancement of knowledge. Here, we show that motor learning studies tend toward extreme fragmentation in the choice of tasks, with almost no overlap between task paradigms across studies. We argue that this extreme level of task fragmentation poses serious theoretical and methodological barriers to advancing the field. To address these barriers, we propose the need for developing common ‘model’ task paradigms which could be widely used across labs. Combined with the open sharing of methods and data, we suggest that these model task paradigms could be an important step in increasing the robustness of the motor learning literature and facilitate the cumulative process of science.
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Aim: One of the topics of interest to researchers in motor behavior is to examine the different effects of attention strategies on motor behavior and brain activity.The purpose of this study is to investigate the role of attention instructions on alpha and theta wave variations and the accuracy of dart throwing. Methodology: For this purpose, 20 male students in dart beginner (age range 19-22 years old) were volunteered among the students of Mazandaran University. At first, the participants performed ten attempts in the baseline (No attention instructions). Then, as a counterbalance, 20 trials were performed in both the external and internal attention strategies. In all trials, the alpha and teta brain wave of the subjects were record used for biofeedback device and the radial error was used to measure accuracy in throwing darts. The data measured by In-group variance analysis with repeated measurements at a significance level of 0.05. Result: The results showed that the external attention strategy, in comparison with the internal attention strategy, increased the accuracy of the dart throw (P=0.0001), increased alpha wavelength (P=0.01) and theta wave reduction (P=0.01). Conclusions: These findings showed, the need to use from Instructions attention, Particular attention of external, In target skill task at beginner level; Therefore, it is suggested that coaches use an external attention strategy to improve the accuracy and intelligence of the brain in beginners.
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Measures of working memory capacity (WMC), such as complex span tasks (e.g., operation span), have become some of the most frequently used tasks in cognitive psychology. However, due to the length of time it takes to complete these tasks many researchers trying to draw conclusions about WMC forgo properly administering multiple tasks. But can the complex span tasks be shortened to take less administration time? We address this question by splitting the tasks into three blocks of trials, and analyzing each block's contribution to measuring WMC and predicting fluid intelligence (Gf). We found that all three blocks of trials contributed similarly to the tasks' ability to measure WMC and Gf, and the tasks can therefore be substantially shortened without changing what they measure. In addition, we found that cutting the number of trials by 67 % in a battery of these tasks still accounted for 90 % of the variance in their measurement of Gf. We discuss our findings in light of administering the complex span tasks in a method that can maximize their accuracy in measuring WMC, while minimizing the time taken to administer.
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When well-learned motor skills fail, such as when elderly persons fall or when athletes "choke under pressure," it is assumed that attention is directed toward the execution of the action. Research findings suggest that this controlled execution and subsequent inferior performance depend on a dominant left-hemispheric activation. In a series of 3 experiments, we tested whether increasing right-hemispheric activation by the use of hemisphere-specific priming extenuates motor skill failure. We compared the performances of a sample of experienced athletes in different sports (soccer, tae kwon do, and badminton) in a pressure-free situation with that performed under pressure. As expected, the hemisphere-specific priming extenuated a performance decrease after pressure induction when compared with a control condition. The results suggest that hemisphere-specific priming may prevent motor skill failure. It is argued that this hemispheric priming should be task dependent and can be understood as a functional regulation of the activation in the hemispheres. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
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Attentional processes governing skilled motor behavior were examined in two studies. In Experiment 1, fi eld hockey players performed a dribbling task under single-task, dual-task, and skill-focused conditions under both low and high pressure situations. In Experiment 2, skilled soccer players performed a dribbling task under single-task, skill-focused, and process-goal conditions, again under low and high pressure situations. Results replicated recent fi ndings regarding the detrimental effect of skill-focused attention and the facilitative effect of dual-task conditions on skilled performance. In addition, focusing on movement related process goals was found to adversely affect performance. Support for the predictive validity of the Reinvestment Scale was also found, with high reinvesters displaying greater susceptibility to skill failure under pressure. Results were consistent with explicit monitoring theories of choking and are further discussed in light of the conceptual distinction between explicit monitoring and reinvestment of conscious control.
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The study examined the effect of an evidence-based intervention on choking in golf. It is informed by the work of Hill, Hanton, Matthews and Fleming (2010a) that explored the experiences of elite golfers who either choked or excelled under pressure. The perceptions of elite golf coaches who worked with both 'chokers' and those who excelled, were also considered. It revealed that choking may be alleviated through the use of process goals, cognitive restructuring, imagery, simulated training and a pre/postshot routine. The present study incorporated each strategy into an intervention that was introduced to two professional golfers (aged 22) who choked under pressure regularly. Through an action research framework the impact of the intervention was evaluated over a ten month period via qualitative methods. The results indicated the intervention alleviated the participants' choking episodes and so provides information that can be of use to practitioners working with golfers who choke.
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Objectives: This study assessed whether individual differences in working memory capacity influenced verbal-analytical processes when performing a novel motor skill. Design: Participants performed a tennis-hitting task in two conditions: no pressure and high-pressure. Methods: Eighteen young adults participated in the study. EEG coherence between the T3-F3 and T4-F4 regions in the Beta1 and Alpha2 frequencies was recorded during performance in each condition. Verbal and visuo-spatial working memory capacity were assessed using the Automated Working Memory Assessment. Results: No differences were found between the two conditions for hitting performance and EEG activity. However, across both conditions, verbal and visuo-spatial working memory were significant predictors of EEG coherence between the T3-F3 and T4-F4 regions in the Beta1 and Alpha2 frequencies. Larger verbal working memory capacity was associated with greater coherence while the opposite trend was observed for visuo-spatial working memory capacity. Conclusions: These results indicate that larger verbal working memory capacity is associated with a greater tendency to use explicit processes during motor performance, whereas larger visuo-spatial working memory capacity is associated more with implicit processes. The findings are discussed with relevance to the theory of implicit motor learning.
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The purpose of this study was to use confirmatory factor analysis (CFA) to revise the factor structure of the CSAI-2 using one data set, and then to use CFA to validate the revised structure using a second data set. The first data set (calibration sample) consisted of 503 college-age intramural athletes, and the second (validation sample) consisted of 331 intercollegiate (Division I) and interscholastic athletes. The results of the initial CFA on the calibration sample resulted in a poor fit to the data. Using the Lagrange Multiplier Test (Gamma) as a guide, CSAI-2 items that loaded on more than one factor were sequentially deleted. The resulting 17-item revised CSAI-2 was then subjected to a CFA using the validation data sample. The results of this CFA revealed a good fit of the data to the model (CFI = .95, NNFI = .94, RMSEA = .054). It is suggested that the CSAI-2R instead of the CSAI-2 be used by researchers and practitioners for measuring competitive state anxiety in athletes.
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Landing an aircraft is a complex task that requires effective attentional control in order to be successful. The present study examined how anxiety may influence gaze behavior during the performance of simulated landings. Participants undertook simulated landings in low visibility conditions which required the use of cockpit instruments in order to obtain guidance information. Landings were performed in either anxiety or control conditions, with anxiety being manipulated using a combination of ego-threatening instructions and monetary incentives. Results showed an increase in percentage dwell time towards the outside world in the anxiety conditions. Visual scanning entropy, which is the predictability of visual scanning behavior, showed an increase in the randomness of scanning behavior when anxious. Furthermore, change in scanning randomness from the pre-test to anxiety conditions positively correlated with both the change in cognitive anxiety and change in performance error. These results support the viewpoint that anxiety can negatively affect attentional control.
This review provides an overview of a diverse, temporally distributed, body of literature regarding the effects of conscious attention to movement. An attempt is made to unite the many different views within the literature through Reinvestment Theory (Masters, 1992; Masters, Polman, & Hammond, 1993), which suggests that relatively automated motor processes can be disrupted if they are run using consciously accessed, task-relevant declarative knowledge to control the mechanics of the movements on-line. Reinvestment Theory argues that the propensity for consciousness to control movements on-line is a function of individual personality differences, specific contexts and a broad range of contingent events that can be psychological, physiological, environmental or even mechanical.
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Research on the focus of attention (FOA) in motor control has found a consistent advantage for focusing externally (on the effects of one's actions) compared to focusing internally (on one's body mechanics). However, most of this work has concentrated on movement outcomes, leaving open the question of how external attention changes the movement itself. Somewhat paradoxically, recent research has found that external attention also increases trial-by-trial movement variability. To explain these findings, we propose a theory of attention in motor control, grounded in optimal control theory, wherein variability is minimized along attended aspects of the movement. Internal attention thus reduces variability in individual bodily dimensions (positions and velocities of effectors), whereas external attention minimizes variability in the task outcome. Because the goal of a task defines a dimension in the movement space that is generally oblique to bodily dimensions, external attention should increase correlations among bodily dimensions while allowing their individual variances to grow. The current experiment tests these predictions in a dart-throwing task. External FOA led to more accurate performance and increased variability in the motion of the throwing arm, concomitant with stronger correlations among bodily dimensions (shoulder, elbow, and wrist positions and velocities) in a manner consistent with the task kinematics. These findings indicate a shift in the control policy of the motor system, consistent with the proposed theory. These results suggest an important role of attention as a control parameter in the regulation of the motor system, and more broadly illustrate the importance of cognitive mechanisms in motor behavior. (PsycINFO Database Record (c) 2013 APA, all rights reserved).