■
> d<-read.csv("data2.csv")
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
Warning message:
package ‘dplyr’ was built under R version 3.3.3
> dg<-group_by(d,region,gender,condition)
> score<-summarize(dg,n=n(),mean=mean(score),sd=sd(score))
> score
Source: local data frame [16 x 6]
Groups: region, gender [?]
region gender condition n mean sd
<fctr> <fctr> <fctr> <int> <dbl> <dbl>
1 East female A 14 52.92857 5.876476
2 East female B 7 61.00000 6.403124
3 East female C 13 71.38462 7.555776
4 East female D 10 79.90000 11.666190
5 East male A 6 58.33333 11.039324
6 East male B 13 60.92308 7.365025
7 East male C 7 68.14286 12.266874
8 East male D 10 82.10000 7.445356
9 West female A 8 57.37500 11.807231
10 West female B 10 59.60000 11.834038
11 West female C 9 60.33333 12.649111
12 West female D 9 59.22222 7.446103
13 West male A 12 62.25000 10.771385
14 West male B 10 55.90000 12.653063
15 West male C 11 61.72727 18.461262
16 West male D 11 59.45455 6.408801
> EG<-subset(score,region=="East")
> library(ggplot2)
> eg<-ggplot(EG)
> eg+
+ geom_bar(aes(x=gender,y=mean,fill=condition),
+ stat="identity",
+ position="dodge")+
+ geom_errorbar(aes(x=gender,
+ ymin=mean-sd/sqrt(n),
+ ymax=mean+sd/sqrt(n),
+ group=gender),
+ width=0.25,
+ position=position_dodge(0.9))
※1
> egb<-ggplot(EG,aes(x=condition,y=mean,fill=gender))+
+ geom_bar(position="dodge",stat="identity")+
+ geom_errorbar(aes(ymin=mean-sd/sqrt(n),ymax=mean+sd/sqrt(n)),
+ position=position_dodge(0.9),width=0.25)
> egb
> ggsave("egb")
Error: Unknown graphics device ''
※2
> WG<-subset(score,region=="West")
> wg<-ggplot(WG)
> wgb<-ggplot(WG,aes(x=condition,y=mean,fill=gender))+
+ geom_bar(position="dodge",stat="identity")+
+ geom_errorbar(aes(ymin=mean-sd/sqrt(n),ymax=mean+sd/sqrt(n)),
+ position=position_dodge(0.9),width=0.25)
> wgb
> wgb
■
> d<-read.csv("data2.csv")
> dg<-group_by(d,religion,gender,conndition)
Error: could not find function "group_by"
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
Warning message:
package ‘dplyr’ was built under R version 3.3.3
> dg<-group_by(d,religion,gender)
Error in resolve_vars(new_groups, tbl_vars(.data)) :
unknown variable to group by : religion
> d
id region condition gender score
1 s01 East A female 46
2 s02 East A female 49
3 s03 East A female 51
4 s04 East A female 52
5 s05 East A female 55
6 s06 East A male 60
7 s07 East A male 50
8 s08 East A female 51
9 s09 East A male 77
10 s10 East A female 48
11 s11 East A male 64
12 s12 East A female 61
13 s13 East A female 44
14 s14 East A female 63
15 s15 East A female 63
16 s16 East A male 50
17 s17 East A female 53
18 s18 East A female 53
19 s19 East A female 52
20 s20 East A male 49
21 s21 East B female 57
22 s22 East B female 72
23 s23 East B male 65
24 s24 East B male 64
25 s25 East B female 56
26 s26 East B female 63
27 s27 East B female 61
28 s28 East B male 54
29 s29 East B male 55
30 s30 East B male 55
31 s31 East B male 58
32 s32 East B male 71
33 s33 East B male 69
34 s34 East B male 53
35 s35 East B female 53
36 s36 East B male 74
37 s37 East B male 58
38 s38 East B female 65
39 s39 East B male 64
40 s40 East B male 52
41 s41 East C female 77
42 s42 East C female 61
43 s43 East C male 76
44 s44 East C female 65
45 s45 East C female 77
46 s46 East C male 85
47 s47 East C male 65
48 s48 East C female 63
49 s49 East C male 49
50 s50 East C female 69
51 s51 East C female 63
52 s52 East C female 64
53 s53 East C male 78
54 s54 East C female 79
55 s55 East C female 76
56 s56 East C female 84
57 s57 East C male 60
58 s58 East C female 73
59 s59 East C male 64
60 s60 East C female 77
61 s61 East D male 97
62 s62 East D male 69
63 s63 East D female 73
64 s64 East D female 65
65 s65 East D female 85
66 s66 East D male 88
67 s67 East D male 85
68 s68 East D female 81
69 s69 East D female 82
70 s70 East D female 62
71 s71 East D female 96
72 s72 East D female 96
73 s73 East D male 78
74 s74 East D male 79
75 s75 East D male 78
76 s76 East D male 83
77 s77 East D female 73
78 s78 East D female 86
79 s79 East D male 85
80 s80 East D male 79
81 s81 West A male 65
82 s82 West A female 62
83 s83 West A male 70
84 s84 West A male 52
85 s85 West A male 36
86 s86 West A male 57
87 s87 West A female 78
88 s88 West A male 59
89 s89 West A male 74
90 s90 West A male 71
91 s91 West A male 72
92 s92 West A female 63
93 s93 West A female 55
94 s94 West A male 60
95 s95 West A female 62
96 s96 West A female 50
97 s97 West A male 70
98 s98 West A female 38
99 s99 West A female 51
100 s100 West A male 61
101 s101 West B male 62
102 s102 West B male 56
103 s103 West B male 59
104 s104 West B female 51
105 s105 West B female 54
106 s106 West B female 56
107 s107 West B female 71
108 s108 West B male 40
109 s109 West B male 73
110 s110 West B female 66
111 s111 West B male 53
112 s112 West B male 71
113 s113 West B female 77
114 s114 West B female 67
115 s115 West B male 52
116 s116 West B male 61
117 s117 West B female 48
118 s118 West B male 32
119 s119 West B female 39
120 s120 West B female 67
121 s121 West C female 60
122 s122 West C female 71
123 s123 West C female 63
124 s124 West C female 60
125 s125 West C male 82
126 s126 West C male 84
127 s127 West C male 77
128 s128 West C female 43
129 s129 West C female 64
130 s130 West C male 51
131 s131 West C female 82
132 s132 West C male 64
133 s133 West C female 41
134 s134 West C male 58
135 s135 West C male 35
136 s136 West C male 76
137 s137 West C male 74
138 s138 West C male 35
139 s139 West C male 43
140 s140 West C female 59
141 s141 West D male 63
142 s142 West D male 55
143 s143 West D female 61
144 s144 West D male 62
145 s145 West D male 68
146 s146 West D male 56
147 s147 West D male 66
148 s148 West D female 57
149 s149 West D male 55
150 s150 West D male 52
151 s151 West D female 65
152 s152 West D female 57
153 s153 West D male 69
154 s154 West D male 57
155 s155 West D female 62
156 s156 West D female 55
157 s157 West D male 51
158 s158 West D female 54
159 s159 West D female 48
160 s160 West D female 74
> dg<-group_by(d,region,gender)
> score<-summarize(dg,n=n(),mean=mean(score),sd=sd(score))
> score
Source: local data frame [4 x 5]
Groups: region [?]
region gender n mean sd
<fctr> <fctr> <int> <dbl> <dbl>
1 East female 44 65.79545 13.18840
2 East male 36 67.77778 12.93966
3 West female 36 59.19444 10.68997
4 West male 44 59.97727 12.57626
> dgg<=group_by(d,region,gender,condition)
Error: object 'dgg' not found
> dgg<-group_by(d,region,gender,condition)
> score1<-summarize(dgg,n=n(),mean=mean(score),sd=sd(score))
> score1
Source: local data frame [16 x 6]
Groups: region, gender [?]
region gender condition n mean sd
<fctr> <fctr> <fctr> <int> <dbl> <dbl>
1 East female A 14 52.92857 5.876476
2 East female B 7 61.00000 6.403124
3 East female C 13 71.38462 7.555776
4 East female D 10 79.90000 11.666190
5 East male A 6 58.33333 11.039324
6 East male B 13 60.92308 7.365025
7 East male C 7 68.14286 12.266874
8 East male D 10 82.10000 7.445356
9 West female A 8 57.37500 11.807231
10 West female B 10 59.60000 11.834038
11 West female C 9 60.33333 12.649111
12 West female D 9 59.22222 7.446103
13 West male A 12 62.25000 10.771385
14 West male B 10 55.90000 12.653063
15 West male C 11 61.72727 18.461262
16 West male D 11 59.45455 6.408801
> G<-ggplot(score)
Error: could not find function "ggplot"
> library(ggplot2)
> G<-ggplot(score)
> G+
+ geom_bar(aes(x=region,y=mean,fill=gender),
+ stat="identity",
+ position="dodge")
> G+
+ geom_bar(aes(x=region,y=mean,fill=gender),
+ stat="identity",
+ position="dodge")
> J<-G+
+ geom_bar(aes(x=region,y=mean,fill=gender),
+ stat="identity",
+ position="dodge")
> G+
+ geom_bar(aes(x=condition,y=mean,fill=gender),
+ stat="identity",
+ position="dodge")
Error in eval(expr, envir, enclos) : object 'condition' not found
>
■
撫でられ始めてすぐ、自分はすぐラバーハンド錯覚が生じた。模型の手を撫でられている間は、実際に撫でられているという触覚、感覚がラバーハンドの位置に存在している、今見ている景色のそこに存在しているという風に感じた。初めはラバーハンドと自分の手の形を同じにしようとしていたが、錯覚が生じて以降、ラバーハンドと自分の手の形を変えることを試みた。具体的にはラバーハンドの中指、薬指が少しだけ浮いていたが、自分の中指、薬指は地面に付けようとした。すると、確かに自分の指は動いているはずなのに今見ているラバーハンドのほう手は動かないということが強く不自然に感じ、少し気分が悪くなってしまった。これより、自分にはかなり強い錯覚が起こっていたのだと予想される。ただ、ペンで刺されそうになった時は咄嗟に避けようとはならず、ペンで刺された時に「なぜビジュアル的には自分の手が刺されているのに感覚的には刺されている感覚がないのだろう」という印象だった。その後、2度目の試行ではついたてを外して実験を行った。そうしたところ、1度目より錯覚は弱まった。具体的に言うと、中指より右側の指を撫でられている時は錯覚が起こらず、中指より左の指を撫でられている時は錯覚が生じた。これは、左側にラバーハンド、右側に自分の手が位置していることに関係しているのかもしれないと考えられた。
■
> install.packages("dplyr")
Installing package into ‘M:/Documents/R/win-library/3.3’
(as ‘lib’ is unspecified)
--- Please select a CRAN mirror for use in this session ---
trying URL 'https://cran.ism.ac.jp/bin/windows/contrib/3.3/dplyr_0.5.0.zip'
Content type 'application/zip' length 2557234 bytes (2.4 MB)
downloaded 2.4 MB
package ‘dplyr’ successfully unpacked and MD5 sums checked
The downloaded binary packages are in
C:\Users\a0155441\AppData\Local\Temp\RtmpekFbx7\downloaded_packages
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
Warning message:
package ‘dplyr’ was built under R version 3.3.3
> pass<-dplyr::filter(d,grade!="D")
Error in filter_(.data, .dots = lazyeval::lazy_dots(...)) :
object 'd' not found
Error in file(file, "rt") : cannot open the connection
In addition: Warning message:
In file(file, "rt") :
cannot open file 'dataa1.csv': No such file or directory
> d
id class gender score1 score2 grade
1 a001 A female 50 59 C
2 a002 A female 53 70 A
3 a003 A male 46 57 C
4 a004 A female 59 67 A
5 a005 A male 51 66 B
6 a006 A male 47 64 B
7 a007 A male 55 53 C
8 a008 A male 66 66 A
9 a009 A male 54 68 B
10 a010 A female 54 67 B
11 a011 A male 59 69 A
12 a012 A male 60 75 A
13 a013 A female 60 68 A
14 a014 A female 61 71 A
15 a015 A female 32 42 D
16 a016 A male 74 70 A
17 a017 A female 48 57 C
18 a018 A male 52 60 B
19 a019 A female 60 73 A
20 a020 A female 52 59 B
21 a021 A female 39 52 D
22 a022 A male 58 67 A
23 a023 A male 48 55 C
24 a024 A male 68 78 A
25 a025 A female 69 76 A
26 a026 A female 61 72 A
27 a027 A female 53 62 B
28 a028 A female 52 68 B
29 a029 A male 35 48 D
30 a030 A female 41 47 D
31 a031 A female 44 51 D
32 a032 A male 47 54 C
33 a033 A male 55 57 B
34 a034 A female 43 61 C
35 a035 A female 48 56 C
36 a036 A male 56 72 A
37 a037 A female 54 63 B
38 a038 A female 65 66 A
39 a039 A male 37 58 D
40 a040 A female 49 55 C
41 a041 A female 59 69 A
42 a042 A male 47 59 C
43 a043 A male 38 49 D
44 a044 A male 31 49 D
45 a045 A female 56 67 A
46 a046 A male 49 55 C
47 a047 A male 52 55 C
48 a048 A male 31 56 D
49 a049 A female 51 55 C
50 a050 A female 49 60 C
51 a051 A male 54 63 B
52 a052 A female 28 36 D
53 a053 A female 53 51 C
54 a054 A female 69 72 A
55 a055 A female 45 55 C
56 a056 A female 51 64 B
57 a057 A male 53 58 B
58 a058 A female 46 56 C
59 a059 A male 55 73 A
60 a060 A female 32 53 D
61 a061 A male 52 50 C
62 a062 A female 53 64 B
63 a063 A male 42 57 D
64 a064 A male 37 44 D
65 a065 A male 34 51 D
66 a066 A male 46 58 C
67 a067 A female 45 54 D
68 a068 A male 35 45 D
69 a069 A female 42 56 D
70 a070 A male 55 68 A
71 a071 A male 30 48 D
72 a072 A male 55 62 B
73 a073 A male 61 61 B
74 a074 A female 42 47 D
75 a075 A male 58 68 A
76 a076 A female 59 69 A
77 a077 A male 43 54 D
78 a078 A female 56 53 C
79 a079 A female 55 66 B
80 a080 A female 56 71 A
81 a081 A female 60 82 A
82 a082 A female 45 57 C
83 a083 A male 30 37 D
84 a084 A female 35 40 D
85 a085 A male 39 51 D
86 a086 A male 38 50 D
87 a087 A male 51 48 D
88 a088 A male 50 59 C
89 a089 A female 48 43 D
90 a090 A male 37 47 D
91 a091 A male 75 71 A
92 a092 A male 53 64 B
93 a093 A female 43 48 D
94 a094 A female 54 60 B
95 a095 A male 56 62 B
96 a096 A female 62 74 A
97 a097 A female 34 49 D
98 a098 A female 49 57 C
99 a099 A female 51 57 C
100 a100 A male 47 59 C
101 b001 B female 58 29 D
102 b002 B male 64 40 C
103 b003 B female 54 51 C
104 b004 B female 50 57 C
105 b005 B male 60 55 B
106 b006 B female 48 38 D
107 b007 B male 55 71 A
108 b008 B male 68 49 B
109 b009 B male 52 52 C
110 b010 B female 72 58 A
111 b011 B male 72 59 A
112 b012 B male 65 49 B
113 b013 B female 59 43 C
114 b014 B male 39 52 D
115 b015 B female 57 49 C
116 b016 B male 63 59 B
117 b017 B male 52 37 D
118 b018 B female 55 64 B
119 b019 B male 50 48 D
120 b020 B male 54 32 D
121 b021 B male 55 57 B
122 b022 B male 61 57 B
123 b023 B female 67 66 A
124 b024 B male 67 54 B
125 b025 B female 48 50 D
126 b026 B female 68 45 B
127 b027 B male 66 45 B
128 b028 B female 63 52 B
129 b029 B male 63 52 B
130 b030 B female 52 55 C
131 b031 B female 70 57 A
132 b032 B male 65 48 B
133 b033 B female 55 41 D
134 b034 B female 49 48 D
135 b035 B male 72 31 C
136 b036 B female 55 36 D
137 b037 B female 75 61 A
138 b038 B female 48 50 D
139 b039 B male 82 64 A
140 b040 B female 60 41 C
141 b041 B male 47 43 D
142 b042 B female 61 53 B
143 b043 B male 59 59 B
144 b044 B male 75 53 A
145 b045 B female 47 46 D
146 b046 B male 53 43 D
147 b047 B male 54 59 B
148 b048 B female 70 52 B
149 b049 B female 65 44 C
150 b050 B female 47 58 C
151 b051 B male 28 32 D
152 b052 B female 47 43 D
153 b053 B female 57 55 B
154 b054 B female 60 57 B
155 b055 B female 58 63 B
156 b056 B male 63 52 B
157 b057 B male 72 54 A
158 b058 B female 61 63 A
159 b059 B female 71 59 A
160 b060 B female 79 30 C
161 b061 B male 67 58 A
162 b062 B female 61 47 C
163 b063 B female 57 46 C
164 b064 B female 70 34 C
165 b065 B male 57 66 A
166 b066 B female 63 56 B
167 b067 B male 59 34 D
168 b068 B male 46 51 D
169 b069 B female 64 53 B
170 b070 B female 70 59 A
171 b071 B female 64 53 B
172 b072 B female 74 51 A
173 b073 B female 45 57 C
174 b074 B male 64 48 B
175 b075 B male 68 48 B
176 b076 B male 69 35 C
177 b077 B male 48 62 B
178 b078 B male 73 56 A
179 b079 B male 72 60 A
180 b080 B male 52 41 D
181 b081 B female 56 43 D
182 b082 B female 78 44 B
183 b083 B male 58 43 C
184 b084 B female 70 35 C
185 b085 B male 58 66 A
186 b086 B female 60 62 B
187 b087 B female 39 49 D
188 b088 B male 47 41 D
189 b089 B male 59 58 B
190 b090 B male 57 46 C
191 b091 B male 53 47 C
192 b092 B female 66 65 A
193 b093 B female 57 46 C
194 b094 B male 66 57 A
195 b095 B female 63 41 C
196 b096 B male 64 73 A
197 b097 B male 47 65 B
198 b098 B male 65 44 C
199 b099 B male 61 62 A
200 b100 B male 67 78 A
> pass<-dplyr::filter(d,grade!="D")
> pass
id class gender score1 score2 grade
1 a001 A female 50 59 C
2 a002 A female 53 70 A
3 a003 A male 46 57 C
4 a004 A female 59 67 A
5 a005 A male 51 66 B
6 a006 A male 47 64 B
7 a007 A male 55 53 C
8 a008 A male 66 66 A
9 a009 A male 54 68 B
10 a010 A female 54 67 B
11 a011 A male 59 69 A
12 a012 A male 60 75 A
13 a013 A female 60 68 A
14 a014 A female 61 71 A
15 a016 A male 74 70 A
16 a017 A female 48 57 C
17 a018 A male 52 60 B
18 a019 A female 60 73 A
19 a020 A female 52 59 B
20 a022 A male 58 67 A
21 a023 A male 48 55 C
22 a024 A male 68 78 A
23 a025 A female 69 76 A
24 a026 A female 61 72 A
25 a027 A female 53 62 B
26 a028 A female 52 68 B
27 a032 A male 47 54 C
28 a033 A male 55 57 B
29 a034 A female 43 61 C
30 a035 A female 48 56 C
31 a036 A male 56 72 A
32 a037 A female 54 63 B
33 a038 A female 65 66 A
34 a040 A female 49 55 C
35 a041 A female 59 69 A
36 a042 A male 47 59 C
37 a045 A female 56 67 A
38 a046 A male 49 55 C
39 a047 A male 52 55 C
40 a049 A female 51 55 C
41 a050 A female 49 60 C
42 a051 A male 54 63 B
43 a053 A female 53 51 C
44 a054 A female 69 72 A
45 a055 A female 45 55 C
46 a056 A female 51 64 B
47 a057 A male 53 58 B
48 a058 A female 46 56 C
49 a059 A male 55 73 A
50 a061 A male 52 50 C
51 a062 A female 53 64 B
52 a066 A male 46 58 C
53 a070 A male 55 68 A
54 a072 A male 55 62 B
55 a073 A male 61 61 B
56 a075 A male 58 68 A
57 a076 A female 59 69 A
58 a078 A female 56 53 C
59 a079 A female 55 66 B
60 a080 A female 56 71 A
61 a081 A female 60 82 A
62 a082 A female 45 57 C
63 a088 A male 50 59 C
64 a091 A male 75 71 A
65 a092 A male 53 64 B
66 a094 A female 54 60 B
67 a095 A male 56 62 B
68 a096 A female 62 74 A
69 a098 A female 49 57 C
70 a099 A female 51 57 C
71 a100 A male 47 59 C
72 b002 B male 64 40 C
73 b003 B female 54 51 C
74 b004 B female 50 57 C
75 b005 B male 60 55 B
76 b007 B male 55 71 A
77 b008 B male 68 49 B
78 b009 B male 52 52 C
79 b010 B female 72 58 A
80 b011 B male 72 59 A
81 b012 B male 65 49 B
82 b013 B female 59 43 C
83 b015 B female 57 49 C
84 b016 B male 63 59 B
85 b018 B female 55 64 B
86 b021 B male 55 57 B
87 b022 B male 61 57 B
88 b023 B female 67 66 A
89 b024 B male 67 54 B
90 b026 B female 68 45 B
91 b027 B male 66 45 B
92 b028 B female 63 52 B
93 b029 B male 63 52 B
94 b030 B female 52 55 C
95 b031 B female 70 57 A
96 b032 B male 65 48 B
97 b035 B male 72 31 C
98 b037 B female 75 61 A
99 b039 B male 82 64 A
100 b040 B female 60 41 C
101 b042 B female 61 53 B
102 b043 B male 59 59 B
103 b044 B male 75 53 A
104 b047 B male 54 59 B
105 b048 B female 70 52 B
106 b049 B female 65 44 C
107 b050 B female 47 58 C
108 b053 B female 57 55 B
109 b054 B female 60 57 B
110 b055 B female 58 63 B
111 b056 B male 63 52 B
112 b057 B male 72 54 A
113 b058 B female 61 63 A
114 b059 B female 71 59 A
115 b060 B female 79 30 C
116 b061 B male 67 58 A
117 b062 B female 61 47 C
118 b063 B female 57 46 C
119 b064 B female 70 34 C
120 b065 B male 57 66 A
121 b066 B female 63 56 B
122 b069 B female 64 53 B
123 b070 B female 70 59 A
124 b071 B female 64 53 B
125 b072 B female 74 51 A
126 b073 B female 45 57 C
127 b074 B male 64 48 B
128 b075 B male 68 48 B
129 b076 B male 69 35 C
130 b077 B male 48 62 B
131 b078 B male 73 56 A
132 b079 B male 72 60 A
133 b082 B female 78 44 B
134 b083 B male 58 43 C
135 b084 B female 70 35 C
136 b085 B male 58 66 A
137 b086 B female 60 62 B
138 b089 B male 59 58 B
139 b090 B male 57 46 C
140 b091 B male 53 47 C
141 b092 B female 66 65 A
142 b093 B female 57 46 C
143 b094 B male 66 57 A
144 b095 B female 63 41 C
145 b096 B male 64 73 A
146 b097 B male 47 65 B
147 b098 B male 65 44 C
148 b099 B male 61 62 A
149 b100 B male 67 78 A
> pass_g<-grop_by(pass,class,gender)
Error: could not find function "grop_by"
> pass_g<-group_by(pass,class,gender)
> pass_s2<-summarize(pass_g,n=n(),mean=mean(score2),sd=sd(score2))
> pass_s2
Source: local data frame [4 x 5]
Groups: class [?]
class gender n mean sd
<fctr> <fctr> <int> <dbl> <dbl>
1 A female 38 63.92105 7.316703
2 A male 33 62.90909 6.929843
3 B female 38 52.15789 8.918630
4 B male 40 54.77500 9.754650
■
1.問題・目的
心理学において“学習”という言葉は、「経験の結果として生じる、行動の比較的永続的な変容」を意味する。つまり、練習によってあるスキルが向上するのは経験によって比較的永続的な行動の変化が起こされたものであり、そのような過程を心理学では学習の過程とよぶ。
学習は多様な形で後の学習に影響を与える。一般に選考する学習が後の学習に影響することを「学習の転移」とよぶ。転移には、学習を促進させる影響をもつ「正の転移」と、干渉的に影響を与える「負の転移」がある。また、学習の転移の一例として、身体の一方の側の器官、たとえば右手を用いた学習を行うと、それがその後に行われるもう一方の側の器官、たとえば左手を用いた学習に作用する「両側性転移」というものがある。
今回の実習では鏡映描写の学習過程において、「両側性転移」が生じるかどうかを検討した。鏡映描写は、鏡を用いることで視覚の視野の上下が反転する、被験者にとって親しみのない状況を作り出し、反転状況で描かれたコースをなぞる課題である。まず、鏡映描写を複数回行うことによって学習が成立するのかどうかを調べた。学習が成立した場合、描写にかかる時間や、経路逸脱回数が減少すると考えられる。次に、先に鏡映描写を複数回行った手と異なる手で鏡映描写を行うことで、両側正転移が生じるのかどうかを検証した。「正の転移」が生じれば異なる手での試行についてかかった時間や経路逸脱回数は減少し、逆に「負の転移」が生じれば描写にかかる時間や経路逸脱回数は増加すると考えられる。これらの予想が実験結果よりどの程度当てはまるかによって鏡映描写における両側性転移と学習の関係性が決まる。よって仮説としては、「鏡映描写における両側性転移は完全な正の転移である」、「鏡映描写における両側性転移は不完全な正の転移である」、「鏡映描写における両側性転移は起こらない」「鏡映描写における両側性転移は負の転移である」の4段階が挙げられる。
2.方法
実験参加者:大学生24人(男性16人、女性8人、平均年齢20.2歳)が実験に参加した。被験者は、利き手のみ学習条件群と非利き手学習条件群、統制群の3群にそれぞれ8人ずつ分けられた。これらの群を前から順にA群、B群、C群と名付ける。
器具:星形図形の描写用紙、1人につき15枚、鏡映描写装置、ストップウォッチを実験に用いた。
手続き課題は鏡に映った星形図形のコースをなぞって描写することであった。実験参加者には、描写はできるだけ速く正確に行うこと、描写開始後は鉛筆の先を図形から離さないことなどが教示された。どの群の実験参加者もまず利き手で鉛筆をもって図形描写を2試行連続で行った。その後、条件ごとに、A群では第1~15試行まで全て利き手で、B群では第1・2・13~15試行は利き手で、3~12試行は非利き手で、C群では第1・2試行を利き手で行った後、第3~12試行で一定時間の休憩を挟み、第13~15試行を利き手で行った。1試行は、閉眼状態で待機中の被験者が持つ鉛筆の先を、実験者が描写開始地点に誘導する尾頃から始まった。次に、実験者の合図と共に被験者は開眼して鏡映描写を開始した。実験者は描写完了にかかった時間と、図形のコースからの逸脱回数を計測した。
3.結果
グラフ1.試行数と経過時間
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問2
> bm<-subset(d,gender=="male")
> summary(bm$score2)
Min. 1st Qu. Median Mean 3rd Qu. Max.
31.00 48.00 55.50 55.13 62.00 78.00
> bf<-subset(d,gender=="female")
> summary(bf$score2)
Min. 1st Qu. Median Mean 3rd Qu. Max.
29.00 47.75 55.50 55.02 63.00 82.00
>
bm、bfについて箱ひげ図を描いた場合、それぞれの箱の長さは第一四分位数と第三四分位数との差で求められる。
∴(bfの箱の長さ)=63.00-47.75>(bmの箱の長さ)=62.00-48.00
より、bf、つまり女子について箱ひげ図を描いたときのほうが箱の長さは長い。
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Data1classAscore2
階級 |
階級値 |
度数 |
相対度数 |
累積相対度数 |
|
35-40 |
37.5 |
3 |
0.03 |
0.03 |
|
40-45 |
42.5 |
4 |
0.04 |
0.07 |
|
45-50 |
47.5 |
12 |
0.12 |
0.19 |
|
50-55 |
52.5 |
17 |
0.17 |
0.36 |
|
55-60 |
57.5 |
22 |
0.22 |
0.58 |
|
60-65 |
62.5 |
11 |
0.11 |
0.69 |
|
65-70 |
67.5 |
18 |
0.18 |
0.87 |
|
70-75 |
72.5 |
10 |
0.1 |
0.97 |
|
75-80 |
77.5 |
2 |
0.02 |
0.99 |
|
80-85 |
82.5 |
1 |
0.01 |
1 |
Data1classBscore2
階級 |
階級値 |
度数 |
相対度数 |
累積相対度数 |
|
25-30 |
27.5 |
2 |
0.02 |
0.02 |
|
30-35 |
32.5 |
7 |
0.07 |
0.09 |
|
35-40 |
37.5 |
4 |
0.04 |
0.13 |
|
40-45 |
42.5 47.5 |
16 |
0.16 |
0.29 |
|
45-50 |
17 |
0.17 |
0.46 |
||
50-55 |
52.5 |
18 |
0.18 |
0.64 |
|
55-60 |
57.5 |
20 |
0.2 |
0.84 |
|
60-65 |
62.5 |
10 |
0.1 |
0.94 |
|
65-70 |
67.5 |
3 |
0.03 |
0.97 |
|
70-75 |
72.5 |
2 |
0.02 |
0.99 |
|
75-80 |
77.5 |
1 |
0.01 |
1 |