Omiyakita_Elementary_School_Only Students who Marked less than 13 in the Pre-test (N=59)
2023-11-05
#Import data #Only Students who Marked less than 13 in the Pre-test (N=59)
read.csv("pre_test_less_than_13.csv") ## ID username feedback ITS pre_test_type post_test_type class
## 1 4 goniku effort 12 B A 1
## 2 28 yescola effort 12 A B 1
## 3 43 gotako effort 12 B A 2
## 4 101 yesimo effort 12 A B 3
## 5 103 yesnigiri effort 12 A B 3
## 6 20 okfugu performance 12 B A 1
## 7 53 niceunagi performance 12 A B 2
## 8 57 okkaki performance 12 B A 2
## 9 30 yesmiso effort 12 A B 1
## 10 31 yesniku effort 12 A B 1
## 11 45 goyuba effort 12 B A 2
## 12 77 goocha effort 12 B A 3
## 13 105 yessake effort 12 A B 3
## 14 48 nicekaki performance 12 A B 2
## 15 62 okunagi performance 12 B A 2
## 16 63 okyuba performance 12 B A 2
## 17 87 nicesake performance 12 A B 3
## 18 33 yessushi effort 12 A B 1
## 19 40 goonigiri effort 12 B A 2
## 20 74 goimo effort 12 B A 3
## 21 21 okmiso performance 12 B A 1
## 22 26 oktofu performance 12 B A 1
## 23 50 niceramen performance 12 A B 2
## 24 56 okika performance 12 B A 2
## 25 58 okonigiri performance 12 B A 2
## 26 96 oksake performance 12 B A 3
## 27 8 gotofu effort 10 B A 1
## 28 76 gonigiri effort 12 B A 3
## 29 27 okudon performance 12 B A 1
## 30 29 yesfugu effort 12 A B 1
## 31 39 gokaki effort 12 B A 2
## 32 100 yesice effort 12 A B 3
## 33 10 nicecola performance 11 A B 1
## 34 12 nicemiso performance 12 A B 1
## 35 69 yessakana effort 12 A B 2
## 36 75 gonabe effort 12 B A 3
## 37 15 nicesushi performance 12 A B 1
## 38 49 niceonigiri performance 12 A B 2
## 39 91 okice performance 12 B A 3
## 40 102 yesnabe effort 12 A B 3
## 41 44 gounagi effort 12 B A 2
## 42 79 gosomen effort 12 B A 3
## 43 23 oksoba performance 12 B A 1
## 44 46 nicegyoza performance 12 A B 2
## 45 93 oknabe performance 12 B A 3
## 46 5 gosoba effort 12 B A 1
## 47 34 yestamago effort 12 A B 1
## 48 7 gotamago effort 12 B A 1
## 49 35 yestofu effort 12 A B 1
## 50 37 gogyoza effort 12 B A 2
## 51 16 nicetamago performance 12 A B 1
## 52 25 oktamago performance 12 B A 1
## 53 54 niceyuba performance 12 A B 2
## 54 82 niceice performance 12 A B 3
## 55 41 goramen effort 12 B A 2
## 56 52 nicetako performance 12 A B 2
## 57 83 niceimo performance 12 A B 3
## 58 106 yessomen effort 12 A B 3
## 59 13 niceniku performance 12 A B 1
## PreTest_Total_Score PostTest_Total_Score Post_Pre Intrinsic_Value
## 1 13 12 -1 10
## 2 13 14 1 11
## 3 13 13 0 12
## 4 13 13 0 11
## 5 13 13 0 13
## 6 13 13 0 13
## 7 13 12 -1 13
## 8 13 14 1 13
## 9 12 14 2 14
## 10 12 11 -1 8
## 11 12 12 0 13
## 12 12 10 -2 15
## 13 12 14 2 15
## 14 12 13 1 15
## 15 12 12 0 7
## 16 12 6 -6 11
## 17 12 12 0 12
## 18 11 11 0 15
## 19 11 12 1 13
## 20 11 3 -8 5
## 21 11 14 3 12
## 22 11 14 3 7
## 23 11 13 2 7
## 24 11 13 2 14
## 25 11 10 -1 9
## 26 11 13 2 11
## 27 10 8 -2 13
## 28 10 12 2 13
## 29 10 12 2 12
## 30 9 11 2 8
## 31 9 4 -5 15
## 32 9 6 -3 9
## 33 9 11 2 13
## 34 9 9 0 11
## 35 8 11 3 5
## 36 8 6 -2 10
## 37 8 8 0 11
## 38 8 11 3 15
## 39 8 12 4 12
## 40 7 2 -5 12
## 41 5 8 3 8
## 42 5 10 5 8
## 43 5 9 4 14
## 44 5 2 -3 10
## 45 5 8 3 13
## 46 4 6 2 6
## 47 4 3 -1 6
## 48 3 9 6 10
## 49 3 10 7 9
## 50 3 3 0 6
## 51 3 3 0 9
## 52 3 4 1 7
## 53 3 12 9 7
## 54 3 1 -2 4
## 55 2 1 -1 11
## 56 2 3 1 8
## 57 2 13 11 3
## 58 1 0 -1 6
## 59 1 14 13 14
## Self.regulation Self.efficacy Test_anxiety Survey_Total_Score
## 1 16 13 8 47
## 2 16 11 4 42
## 3 11 16 10 49
## 4 11 16 14 52
## 5 16 16 15 60
## 6 18 19 17 67
## 7 14 18 16 61
## 8 19 18 10 60
## 9 20 19 16 69
## 10 13 12 8 41
## 11 13 20 20 66
## 12 15 13 7 50
## 13 14 18 18 65
## 14 16 18 15 64
## 15 14 12 7 40
## 16 13 12 17 53
## 17 19 15 8 54
## 18 16 17 13 61
## 19 19 17 5 54
## 20 10 6 6 27
## 21 15 12 12 51
## 22 14 11 13 45
## 23 14 8 7 36
## 24 18 20 14 66
## 25 14 12 9 44
## 26 11 13 11 46
## 27 16 17 15 61
## 28 16 15 12 56
## 29 14 11 12 49
## 30 11 9 15 43
## 31 18 14 12 59
## 32 8 7 12 36
## 33 18 16 15 62
## 34 15 15 16 57
## 35 15 11 7 38
## 36 11 9 14 44
## 37 15 15 4 45
## 38 17 16 17 65
## 39 14 17 14 57
## 40 18 17 15 62
## 41 11 12 8 39
## 42 14 7 7 36
## 43 13 11 5 43
## 44 16 11 4 41
## 45 17 15 16 61
## 46 11 12 7 36
## 47 12 11 7 36
## 48 15 12 9 46
## 49 13 14 14 50
## 50 15 6 4 31
## 51 13 10 8 40
## 52 14 13 9 43
## 53 13 12 13 45
## 54 17 11 4 36
## 55 16 16 4 47
## 56 7 5 5 25
## 57 11 4 5 23
## 58 9 9 9 33
## 59 17 17 15 63read.csv("pre_test_less_than_13_effort.csv") ## ID username feedback ITS pre_test_type post_test_type class
## 1 4 goniku effort 12 B A 1
## 2 28 yescola effort 12 A B 1
## 3 43 gotako effort 12 B A 2
## 4 101 yesimo effort 12 A B 3
## 5 103 yesnigiri effort 12 A B 3
## 6 30 yesmiso effort 12 A B 1
## 7 31 yesniku effort 12 A B 1
## 8 45 goyuba effort 12 B A 2
## 9 77 goocha effort 12 B A 3
## 10 105 yessake effort 12 A B 3
## 11 33 yessushi effort 12 A B 1
## 12 40 goonigiri effort 12 B A 2
## 13 74 goimo effort 12 B A 3
## 14 8 gotofu effort 10 B A 1
## 15 76 gonigiri effort 12 B A 3
## 16 29 yesfugu effort 12 A B 1
## 17 39 gokaki effort 12 B A 2
## 18 100 yesice effort 12 A B 3
## 19 69 yessakana effort 12 A B 2
## 20 75 gonabe effort 12 B A 3
## 21 102 yesnabe effort 12 A B 3
## 22 44 gounagi effort 12 B A 2
## 23 79 gosomen effort 12 B A 3
## 24 5 gosoba effort 12 B A 1
## 25 34 yestamago effort 12 A B 1
## 26 7 gotamago effort 12 B A 1
## 27 35 yestofu effort 12 A B 1
## 28 37 gogyoza effort 12 B A 2
## 29 41 goramen effort 12 B A 2
## 30 106 yessomen effort 12 A B 3
## PreTest_Total_Score PostTest_Total_Score Post_Pre Intrinsic_Value
## 1 13 12 -1 10
## 2 13 14 1 11
## 3 13 13 0 12
## 4 13 13 0 11
## 5 13 13 0 13
## 6 12 14 2 14
## 7 12 11 -1 8
## 8 12 12 0 13
## 9 12 10 -2 15
## 10 12 14 2 15
## 11 11 11 0 15
## 12 11 12 1 13
## 13 11 3 -8 5
## 14 10 8 -2 13
## 15 10 12 2 13
## 16 9 11 2 8
## 17 9 4 -5 15
## 18 9 6 -3 9
## 19 8 11 3 5
## 20 8 6 -2 10
## 21 7 2 -5 12
## 22 5 8 3 8
## 23 5 10 5 8
## 24 4 6 2 6
## 25 4 3 -1 6
## 26 3 9 6 10
## 27 3 10 7 9
## 28 3 3 0 6
## 29 2 1 -1 11
## 30 1 0 -1 6
## Self.regulation Self.efficacy Test_anxiety Survey_Total_Score
## 1 16 13 8 47
## 2 16 11 4 42
## 3 11 16 10 49
## 4 11 16 14 52
## 5 16 16 15 60
## 6 20 19 16 69
## 7 13 12 8 41
## 8 13 20 20 66
## 9 15 13 7 50
## 10 14 18 18 65
## 11 16 17 13 61
## 12 19 17 5 54
## 13 10 6 6 27
## 14 16 17 15 61
## 15 16 15 12 56
## 16 11 9 15 43
## 17 18 14 12 59
## 18 8 7 12 36
## 19 15 11 7 38
## 20 11 9 14 44
## 21 18 17 15 62
## 22 11 12 8 39
## 23 14 7 7 36
## 24 11 12 7 36
## 25 12 11 7 36
## 26 15 12 9 46
## 27 13 14 14 50
## 28 15 6 4 31
## 29 16 16 4 47
## 30 9 9 9 33read.csv("pre_test_less_than_13_performance.csv") ## ID username feedback ITS pre_test_type post_test_type class
## 1 20 okfugu performance 12 B A 1
## 2 53 niceunagi performance 12 A B 2
## 3 57 okkaki performance 12 B A 2
## 4 48 nicekaki performance 12 A B 2
## 5 62 okunagi performance 12 B A 2
## 6 63 okyuba performance 12 B A 2
## 7 87 nicesake performance 12 A B 3
## 8 21 okmiso performance 12 B A 1
## 9 26 oktofu performance 12 B A 1
## 10 50 niceramen performance 12 A B 2
## 11 56 okika performance 12 B A 2
## 12 58 okonigiri performance 12 B A 2
## 13 96 oksake performance 12 B A 3
## 14 27 okudon performance 12 B A 1
## 15 10 nicecola performance 11 A B 1
## 16 12 nicemiso performance 12 A B 1
## 17 15 nicesushi performance 12 A B 1
## 18 49 niceonigiri performance 12 A B 2
## 19 91 okice performance 12 B A 3
## 20 23 oksoba performance 12 B A 1
## 21 46 nicegyoza performance 12 A B 2
## 22 93 oknabe performance 12 B A 3
## 23 16 nicetamago performance 12 A B 1
## 24 25 oktamago performance 12 B A 1
## 25 54 niceyuba performance 12 A B 2
## 26 82 niceice performance 12 A B 3
## 27 52 nicetako performance 12 A B 2
## 28 83 niceimo performance 12 A B 3
## 29 13 niceniku performance 12 A B 1
## PreTest_Total_Score PostTest_Total_Score Post_Pre Intrinsic_Value
## 1 13 13 0 13
## 2 13 12 -1 13
## 3 13 14 1 13
## 4 12 13 1 15
## 5 12 12 0 7
## 6 12 6 -6 11
## 7 12 12 0 12
## 8 11 14 3 12
## 9 11 14 3 7
## 10 11 13 2 7
## 11 11 13 2 14
## 12 11 10 -1 9
## 13 11 13 2 11
## 14 10 12 2 12
## 15 9 11 2 13
## 16 9 9 0 11
## 17 8 8 0 11
## 18 8 11 3 15
## 19 8 12 4 12
## 20 5 9 4 14
## 21 5 2 -3 10
## 22 5 8 3 13
## 23 3 3 0 9
## 24 3 4 1 7
## 25 3 12 9 7
## 26 3 1 -2 4
## 27 2 3 1 8
## 28 2 13 11 3
## 29 1 14 13 14
## Self.regulation Self.efficacy Test_anxiety Survey_Total_Score
## 1 18 19 17 67
## 2 14 18 16 61
## 3 19 18 10 60
## 4 16 18 15 64
## 5 14 12 7 40
## 6 13 12 17 53
## 7 19 15 8 54
## 8 15 12 12 51
## 9 14 11 13 45
## 10 14 8 7 36
## 11 18 20 14 66
## 12 14 12 9 44
## 13 11 13 11 46
## 14 14 11 12 49
## 15 18 16 15 62
## 16 15 15 16 57
## 17 15 15 4 45
## 18 17 16 17 65
## 19 14 17 14 57
## 20 13 11 5 43
## 21 16 11 4 41
## 22 17 15 16 61
## 23 13 10 8 40
## 24 14 13 9 43
## 25 13 12 13 45
## 26 17 11 4 36
## 27 7 5 5 25
## 28 11 4 5 23
## 29 17 17 15 63read.csv("pre_test_less_than_13_value.csv") ## ID feedback ITS class PreTest_Total_Score PostTest_Total_Score Post_Pre
## 1 4 1 12 1 13 12 -1
## 2 28 1 12 1 13 14 1
## 3 43 1 12 2 13 13 0
## 4 101 1 12 3 13 13 0
## 5 103 1 12 3 13 13 0
## 6 20 2 12 1 13 13 0
## 7 53 2 12 2 13 12 -1
## 8 57 2 12 2 13 14 1
## 9 30 1 12 1 12 14 2
## 10 31 1 12 1 12 11 -1
## 11 45 1 12 2 12 12 0
## 12 77 1 12 3 12 10 -2
## 13 105 1 12 3 12 14 2
## 14 48 2 12 2 12 13 1
## 15 62 2 12 2 12 12 0
## 16 63 2 12 2 12 6 -6
## 17 87 2 12 3 12 12 0
## 18 33 1 12 1 11 11 0
## 19 40 1 12 2 11 12 1
## 20 74 1 12 3 11 3 -8
## 21 21 2 12 1 11 14 3
## 22 26 2 12 1 11 14 3
## 23 50 2 12 2 11 13 2
## 24 56 2 12 2 11 13 2
## 25 58 2 12 2 11 10 -1
## 26 96 2 12 3 11 13 2
## 27 8 1 10 1 10 8 -2
## 28 76 1 12 3 10 12 2
## 29 27 2 12 1 10 12 2
## 30 29 1 12 1 9 11 2
## 31 39 1 12 2 9 4 -5
## 32 100 1 12 3 9 6 -3
## 33 10 2 11 1 9 11 2
## 34 12 2 12 1 9 9 0
## 35 69 1 12 2 8 11 3
## 36 75 1 12 3 8 6 -2
## 37 15 2 12 1 8 8 0
## 38 49 2 12 2 8 11 3
## 39 91 2 12 3 8 12 4
## 40 102 1 12 3 7 2 -5
## 41 44 1 12 2 5 8 3
## 42 79 1 12 3 5 10 5
## 43 23 2 12 1 5 9 4
## 44 46 2 12 2 5 2 -3
## 45 93 2 12 3 5 8 3
## 46 5 1 12 1 4 6 2
## 47 34 1 12 1 4 3 -1
## 48 7 1 12 1 3 9 6
## 49 35 1 12 1 3 10 7
## 50 37 1 12 2 3 3 0
## 51 16 2 12 1 3 3 0
## 52 25 2 12 1 3 4 1
## 53 54 2 12 2 3 12 9
## 54 82 2 12 3 3 1 -2
## 55 41 1 12 2 2 1 -1
## 56 52 2 12 2 2 3 1
## 57 83 2 12 3 2 13 11
## 58 106 1 12 3 1 0 -1
## 59 13 2 12 1 1 14 13
## Intrinsic_Value Self.regulation Self.efficacy Test_anxiety
## 1 10 16 13 8
## 2 11 16 11 4
## 3 12 11 16 10
## 4 11 11 16 14
## 5 13 16 16 15
## 6 13 18 19 17
## 7 13 14 18 16
## 8 13 19 18 10
## 9 14 20 19 16
## 10 8 13 12 8
## 11 13 13 20 20
## 12 15 15 13 7
## 13 15 14 18 18
## 14 15 16 18 15
## 15 7 14 12 7
## 16 11 13 12 17
## 17 12 19 15 8
## 18 15 16 17 13
## 19 13 19 17 5
## 20 5 10 6 6
## 21 12 15 12 12
## 22 7 14 11 13
## 23 7 14 8 7
## 24 14 18 20 14
## 25 9 14 12 9
## 26 11 11 13 11
## 27 13 16 17 15
## 28 13 16 15 12
## 29 12 14 11 12
## 30 8 11 9 15
## 31 15 18 14 12
## 32 9 8 7 12
## 33 13 18 16 15
## 34 11 15 15 16
## 35 5 15 11 7
## 36 10 11 9 14
## 37 11 15 15 4
## 38 15 17 16 17
## 39 12 14 17 14
## 40 12 18 17 15
## 41 8 11 12 8
## 42 8 14 7 7
## 43 14 13 11 5
## 44 10 16 11 4
## 45 13 17 15 16
## 46 6 11 12 7
## 47 6 12 11 7
## 48 10 15 12 9
## 49 9 13 14 14
## 50 6 15 6 4
## 51 9 13 10 8
## 52 7 14 13 9
## 53 7 13 12 13
## 54 4 17 11 4
## 55 11 16 16 4
## 56 8 7 5 5
## 57 3 11 4 5
## 58 6 9 9 9
## 59 14 17 17 15
## Survey_Total_Score
## 1 47
## 2 42
## 3 49
## 4 52
## 5 60
## 6 67
## 7 61
## 8 60
## 9 69
## 10 41
## 11 66
## 12 50
## 13 65
## 14 64
## 15 40
## 16 53
## 17 54
## 18 61
## 19 54
## 20 27
## 21 51
## 22 45
## 23 36
## 24 66
## 25 44
## 26 46
## 27 61
## 28 56
## 29 49
## 30 43
## 31 59
## 32 36
## 33 62
## 34 57
## 35 38
## 36 44
## 37 45
## 38 65
## 39 57
## 40 62
## 41 39
## 42 36
## 43 43
## 44 41
## 45 61
## 46 36
## 47 36
## 48 46
## 49 50
## 50 31
## 51 40
## 52 43
## 53 45
## 54 36
## 55 47
## 56 25
## 57 23
## 58 33
## 59 63setwd("/Users/satoushintarou/Desktop/Master thesis/大宮北小/Data") #Directory
datapt13<-read.csv("pre_test_less_than_13.csv")
datapt13e<-read.csv("pre_test_less_than_13_effort.csv")
datapt13p<-read.csv("pre_test_less_than_13_performance.csv")
datapt13v<-read.csv("pre_test_less_than_13_value.csv")#Students who Marked less than 13 in the Pre-test（N=59）
#Pre-Test = score "13" N=59
read.csv("R.csv") #All students N=65## ID username feedback ITS pre_test_type post_test_type class
## 1 1 gocola effort 12 B A 1
## 2 4 goniku effort 12 B A 1
## 3 5 gosoba effort 12 B A 1
## 4 7 gotamago effort 12 B A 1
## 5 8 gotofu effort 10 B A 1
## 6 28 yescola effort 12 A B 1
## 7 29 yesfugu effort 12 A B 1
## 8 30 yesmiso effort 12 A B 1
## 9 31 yesniku effort 12 A B 1
## 10 33 yessushi effort 12 A B 1
## 11 34 yestamago effort 12 A B 1
## 12 35 yestofu effort 12 A B 1
## 13 37 gogyoza effort 12 B A 2
## 14 38 goika effort 12 B A 2
## 15 39 gokaki effort 12 B A 2
## 16 40 goonigiri effort 12 B A 2
## 17 41 goramen effort 12 B A 2
## 18 42 gosakana effort 12 B A 2
## 19 43 gotako effort 12 B A 2
## 20 44 gounagi effort 12 B A 2
## 21 45 goyuba effort 12 B A 2
## 22 69 yessakana effort 12 A B 2
## 23 74 goimo effort 12 B A 3
## 24 75 gonabe effort 12 B A 3
## 25 76 gonigiri effort 12 B A 3
## 26 77 goocha effort 12 B A 3
## 27 79 gosomen effort 12 B A 3
## 28 100 yesice effort 12 A B 3
## 29 101 yesimo effort 12 A B 3
## 30 102 yesnabe effort 12 A B 3
## 31 103 yesnigiri effort 12 A B 3
## 32 105 yessake effort 12 A B 3
## 33 106 yessomen effort 12 A B 3
## 34 107 yestaiyaki effort 12 A B 3
## 35 10 nicecola performance 11 A B 1
## 36 12 nicemiso performance 12 A B 1
## 37 13 niceniku performance 12 A B 1
## 38 15 nicesushi performance 12 A B 1
## 39 16 nicetamago performance 12 A B 1
## 40 20 okfugu performance 12 B A 1
## 41 21 okmiso performance 12 B A 1
## 42 23 oksoba performance 12 B A 1
## 43 25 oktamago performance 12 B A 1
## 44 26 oktofu performance 12 B A 1
## 45 27 okudon performance 12 B A 1
## 46 46 nicegyoza performance 12 A B 2
## 47 48 nicekaki performance 12 A B 2
## 48 49 niceonigiri performance 12 A B 2
## 49 50 niceramen performance 12 A B 2
## 50 51 nicesakana performance 12 A B 2
## 51 52 nicetako performance 12 A B 2
## 52 53 niceunagi performance 12 A B 2
## 53 54 niceyuba performance 12 A B 2
## 54 56 okika performance 12 B A 2
## 55 57 okkaki performance 12 B A 2
## 56 58 okonigiri performance 12 B A 2
## 57 62 okunagi performance 12 B A 2
## 58 63 okyuba performance 12 B A 2
## 59 82 niceice performance 12 A B 3
## 60 83 niceimo performance 12 A B 3
## 61 87 nicesake performance 12 A B 3
## 62 91 okice performance 12 B A 3
## 63 93 oknabe performance 12 B A 3
## 64 96 oksake performance 12 B A 3
## 65 98 oktaiyaki performance 12 B A 3
## PreTest_Total_Score PostTest_Total_Score Post_Pre Intrinsic_Value
## 1 14 14 0 15
## 2 13 12 -1 10
## 3 4 6 2 6
## 4 3 9 6 10
## 5 10 8 -2 13
## 6 13 14 1 11
## 7 9 11 2 8
## 8 12 14 2 14
## 9 12 11 -1 8
## 10 11 11 0 15
## 11 4 3 -1 6
## 12 3 10 7 9
## 13 3 3 0 6
## 14 14 14 0 15
## 15 9 4 -5 15
## 16 11 12 1 13
## 17 2 1 -1 11
## 18 14 14 0 14
## 19 13 13 0 12
## 20 5 8 3 8
## 21 12 12 0 13
## 22 8 11 3 5
## 23 11 3 -8 5
## 24 8 6 -2 10
## 25 10 12 2 13
## 26 12 10 -2 15
## 27 5 10 5 8
## 28 9 6 -3 9
## 29 13 13 0 11
## 30 7 2 -5 12
## 31 13 13 0 13
## 32 12 14 2 15
## 33 1 0 -1 6
## 34 14 13 -1 12
## 35 9 11 2 13
## 36 9 9 0 11
## 37 1 14 13 14
## 38 8 8 0 11
## 39 3 3 0 9
## 40 13 13 0 13
## 41 11 14 3 12
## 42 5 9 4 14
## 43 3 4 1 7
## 44 11 14 3 7
## 45 10 12 2 12
## 46 5 2 -3 10
## 47 12 13 1 15
## 48 8 11 3 15
## 49 11 13 2 7
## 50 14 14 0 11
## 51 2 3 1 8
## 52 13 12 -1 13
## 53 3 12 9 7
## 54 11 13 2 14
## 55 13 14 1 13
## 56 11 10 -1 9
## 57 12 12 0 7
## 58 12 6 -6 11
## 59 3 1 -2 4
## 60 2 13 11 3
## 61 12 12 0 12
## 62 8 12 4 12
## 63 5 8 3 13
## 64 11 13 2 11
## 65 14 14 0 8
## Self.regulation Self.efficacy Test_anxiety Survey_Total_Score
## 1 19 20 14 68
## 2 16 13 8 47
## 3 11 12 7 36
## 4 15 12 9 46
## 5 16 17 15 61
## 6 16 11 4 42
## 7 11 9 15 43
## 8 20 19 16 69
## 9 13 12 8 41
## 10 16 17 13 61
## 11 12 11 7 36
## 12 13 14 14 50
## 13 15 6 4 31
## 14 20 20 6 61
## 15 18 14 12 59
## 16 19 17 5 54
## 17 16 16 4 47
## 18 18 20 17 69
## 19 11 16 10 49
## 20 11 12 8 39
## 21 13 20 20 66
## 22 15 11 7 38
## 23 10 6 6 27
## 24 11 9 14 44
## 25 16 15 12 56
## 26 15 13 7 50
## 27 14 7 7 36
## 28 8 7 12 36
## 29 11 16 14 52
## 30 18 17 15 62
## 31 16 16 15 60
## 32 14 18 18 65
## 33 9 9 9 33
## 34 16 18 17 63
## 35 18 16 15 62
## 36 15 15 16 57
## 37 17 17 15 63
## 38 15 15 4 45
## 39 13 10 8 40
## 40 18 19 17 67
## 41 15 12 12 51
## 42 13 11 5 43
## 43 14 13 9 43
## 44 14 11 13 45
## 45 14 11 12 49
## 46 16 11 4 41
## 47 16 18 15 64
## 48 17 16 17 65
## 49 14 8 7 36
## 50 16 17 13 57
## 51 7 5 5 25
## 52 14 18 16 61
## 53 13 12 13 45
## 54 18 20 14 66
## 55 19 18 10 60
## 56 14 12 9 44
## 57 14 12 7 40
## 58 13 12 17 53
## 59 17 11 4 36
## 60 11 4 5 23
## 61 19 15 8 54
## 62 14 17 14 57
## 63 17 15 16 61
## 64 11 13 11 46
## 65 7 5 8 28data<-read.csv("R.csv")
sum(data$PreTest_Total_Score < 14) #Pre-test score 0-13/14 (exclude:score 14 students)## [1] 59#Demographic
#Students who Marked less than 13 in the Pre-test（N=59）
table(datapt13$feedback)##
## effort performance
## 30 29#Analysis 13 #Compare Pre- vs. Post-Test #Students who Marked less than 13 in the Pre-test（N=59）
#Comment:This result is the same as all students (N=65) and middle/low level students (N=42), Analysis1,7.
#T-test
#Pre-test and Post-test
#p-value = 0.03972
t.test(datapt13$PreTest_Total_Score, datapt13$PostTest_Total_Score, paired=TRUE)##
## Paired t-test
##
## data: datapt13$PreTest_Total_Score and datapt13$PostTest_Total_Score
## t = -2.1041, df = 58, p-value = 0.03972
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## -1.91828025 -0.04782144
## sample estimates:
## mean difference
## -0.9830508#Analysis 14 #Compare Pre-Test / Effort vs. Performance Group #Compare Post-Test / Effort vs. Performance Group #Students who Marked less than 13 in the Pre-test（N=59）
#Comment:"Post-test between the effort and performance group"（p-value = 0.2334）. This is the same result as all students (N=65), Analysis 2. However, it shows the significant difference in the case of middle and low level students, Analysis8.
#T-test
#Pre-test between the effort and performance group
#p-value = 0.6792
var.test(datapt13e$PreTest_Total_Score,datapt13p$PreTest_Total_Score)##
## F test to compare two variances
##
## data: datapt13e$PreTest_Total_Score and datapt13p$PreTest_Total_Score
## F = 0.95916, num df = 29, denom df = 28, p-value = 0.9104
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.4522781 2.0240482
## sample estimates:
## ratio of variances
## 0.9591591t.test(PreTest_Total_Score ~ feedback, var.equal=T,data = datapt13)##
## Two Sample t-test
##
## data: PreTest_Total_Score by feedback
## t = 0.41568, df = 57, p-value = 0.6792
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -1.632225 2.487397
## sample estimates:
## mean in group effort mean in group performance
## 8.600000 8.172414#T-test
#Post-test between the effort and performance group
#p-value = 0.2334
var.test(datapt13e$PostTest_Total_Score,datapt13p$PostTest_Total_Score)##
## F test to compare two variances
##
## data: datapt13e$PostTest_Total_Score and datapt13p$PostTest_Total_Score
## F = 1.1438, num df = 29, denom df = 28, p-value = 0.7241
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.5393426 2.4136819
## sample estimates:
## ratio of variances
## 1.143799t.test(PostTest_Total_Score ~ feedback, var.equal=T,data = datapt13)##
## Two Sample t-test
##
## data: PostTest_Total_Score by feedback
## t = -1.2045, df = 57, p-value = 0.2334
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -3.464323 0.862024
## sample estimates:
## mean in group effort mean in group performance
## 8.733333 10.034483#Analysis 15 #Compare Test Score Increase (増加量) / Effort vs. Performance Group #Students who Marked less than 13 in the Pre-test（N=59）
#Comment:This result is the same as all students (N=65), Analysis3,9.
#T-test
#Post_Pre[(Post_Test_Total_Score)ー(Pre_Test_Total_Score)] between the effort and performance group
#p-value = 0.0638
var.test(datapt13$Post_Pre,datapt13$Post_Pre)##
## F test to compare two variances
##
## data: datapt13$Post_Pre and datapt13$Post_Pre
## F = 1, num df = 58, denom df = 58, p-value = 1
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.5946366 1.6816995
## sample estimates:
## ratio of variances
## 1t.test(Post_Pre ~ feedback,var.equal=T,data = datapt13)##
## Two Sample t-test
##
## data: Post_Pre by feedback
## t = -1.8904, df = 57, p-value = 0.0638
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -3.5599761 0.1025048
## sample estimates:
## mean in group effort mean in group performance
## 0.1333333 1.8620690#Analysis 16 #Regression Model #Students who Marked less than 13 in the Pre-test（N=59）
#Comment:???
#y="Post-test", x="Feedback type" and "Pre-test"
model5 <- lm(PostTest_Total_Score ~ feedback*PreTest_Total_Score, data = datapt13)
summary(model5)##
## Call:
## lm(formula = PostTest_Total_Score ~ feedback * PreTest_Total_Score,
## data = datapt13)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.5897 -1.8788 0.6369 1.9103 7.8372
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.0815 1.4601 1.426 0.1596
## feedbackperformance 3.5414 2.0232 1.750 0.0856
## PreTest_Total_Score 0.7735 0.1550 4.990 6.42e-06
## feedbackperformance:PreTest_Total_Score -0.2337 0.2189 -1.068 0.2903
##
## (Intercept)
## feedbackperformance .
## PreTest_Total_Score ***
## feedbackperformance:PreTest_Total_Score
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.263 on 55 degrees of freedom
## Multiple R-squared: 0.4177, Adjusted R-squared: 0.3859
## F-statistic: 13.15 on 3 and 55 DF, p-value: 1.382e-06model6 <- lm(PostTest_Total_Score ~ feedback+PreTest_Total_Score, data = datapt13)
summary(model6)##
## Call:
## lm(formula = PostTest_Total_Score ~ feedback + PreTest_Total_Score,
## data = datapt13)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.3083 -1.9898 0.4537 1.8479 8.6724
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.0896 1.1152 2.770 0.00758 **
## feedbackperformance 1.5818 0.8522 1.856 0.06869 .
## PreTest_Total_Score 0.6562 0.1096 5.990 1.58e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.267 on 56 degrees of freedom
## Multiple R-squared: 0.4056, Adjusted R-squared: 0.3844
## F-statistic: 19.11 on 2 and 56 DF, p-value: 4.719e-07library(ggplot2)
ggplot(datapt13, aes(x = PreTest_Total_Score, y = Post_Pre, col = feedback)) + geom_point() +geom_smooth(method = "lm",se=FALSE)## `geom_smooth()` using formula = 'y ~ x'
#y="Score Increase(増加量)", x="Feedback type" and "Pre-test"
model7 <- lm(Post_Pre ~ feedback*PreTest_Total_Score, data = datapt13)
summary(model7)##
## Call:
## lm(formula = Post_Pre ~ feedback * PreTest_Total_Score, data = datapt13)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.5897 -1.8788 0.6369 1.9103 7.8372
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.0815 1.4601 1.426 0.1596
## feedbackperformance 3.5414 2.0232 1.750 0.0856 .
## PreTest_Total_Score -0.2265 0.1550 -1.461 0.1496
## feedbackperformance:PreTest_Total_Score -0.2337 0.2189 -1.068 0.2903
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.263 on 55 degrees of freedom
## Multiple R-squared: 0.2159, Adjusted R-squared: 0.1732
## F-statistic: 5.049 on 3 and 55 DF, p-value: 0.003676model8 <- lm(Post_Pre ~ feedback+PreTest_Total_Score, data = datapt13)
summary(model8)##
## Call:
## lm(formula = Post_Pre ~ feedback + PreTest_Total_Score, data = datapt13)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.3083 -1.9898 0.4537 1.8479 8.6724
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.0896 1.1152 2.770 0.00758 **
## feedbackperformance 1.5818 0.8522 1.856 0.06869 .
## PreTest_Total_Score -0.3438 0.1096 -3.137 0.00272 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.267 on 56 degrees of freedom
## Multiple R-squared: 0.1997, Adjusted R-squared: 0.1711
## F-statistic: 6.986 on 2 and 56 DF, p-value: 0.001956library(ggplot2)
ggplot(datapt13, aes(x = PreTest_Total_Score, y = PostTest_Total_Score, col = feedback)) + geom_point() +geom_smooth(method = "lm",se=FALSE)## `geom_smooth()` using formula = 'y ~ x'
#Analysis 17 #Compare Math Motivation Score (算数学習への意欲) / Effort vs. Performance Group #Students who Marked less than 13 in the Pre-test（N=59）
#Comment:This result is the same as all students (N=65) and middle/low level students (N=42), Analysis5,11
#T-test
#Math motivation score between the effort and performance group
#p-value = 0.5449
var.test(datapt13e$Survey_Total_Score,datapt13p$Survey_Total_Score)#等分散##
## F test to compare two variances
##
## data: datapt13e$Survey_Total_Score and datapt13p$Survey_Total_Score
## F = 0.92339, num df = 29, denom df = 28, p-value = 0.8313
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.4354137 1.9485759
## sample estimates:
## ratio of variances
## 0.9233941t.test(Survey_Total_Score ~ feedback,var.equal=T,data = datapt13)##
## Two Sample t-test
##
## data: Survey_Total_Score by feedback
## t = -0.60907, df = 57, p-value = 0.5449
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -7.964378 4.249435
## sample estimates:
## mean in group effort mean in group performance
## 47.86667 49.72414#T-test
#Intrinsic value between the effort and performance group
#p-value = 0.7638
var.test(datapt13e$Intrinsic_Value,datapt13p$Intrinsic_Value)#等分散##
## F test to compare two variances
##
## data: datapt13e$Intrinsic_Value and datapt13p$Intrinsic_Value
## F = 1.0044, num df = 29, denom df = 28, p-value = 0.9925
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.4735988 2.1194632
## sample estimates:
## ratio of variances
## 1.004374t.test(Intrinsic_Value ~ feedback,var.equal=T,data = datapt13)##
## Two Sample t-test
##
## data: Intrinsic_Value by feedback
## t = -0.3019, df = 57, p-value = 0.7638
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -1.930171 1.424423
## sample estimates:
## mean in group effort mean in group performance
## 10.33333 10.58621#T-test
#Self efficacy between the effort and performance group
#p-value = 0.7863
var.test(datapt13e$Self.efficacy,datapt13p$Self.efficacy)#等分散##
## F test to compare two variances
##
## data: datapt13e$Self.efficacy and datapt13p$Self.efficacy
## F = 1.0183, num df = 29, denom df = 28, p-value = 0.9635
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.4801612 2.1488315
## sample estimates:
## ratio of variances
## 1.018292t.test(Self.efficacy ~ feedback,var.equal=T,data = datapt13)##
## Two Sample t-test
##
## data: Self.efficacy by feedback
## t = -0.2724, df = 57, p-value = 0.7863
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -2.322956 1.766634
## sample estimates:
## mean in group effort mean in group performance
## 13.06667 13.34483#T-test
#Self regulation between the effort and performance group
#p-value = 0.2489
var.test(datapt13e$Self.regulation,datapt13p$Self.regulation)#等分散##
## F test to compare two variances
##
## data: datapt13e$Self.regulation and datapt13p$Self.regulation
## F = 1.2945, num df = 29, denom df = 28, p-value = 0.497
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.6103994 2.7316771
## sample estimates:
## ratio of variances
## 1.294491t.test(Self.regulation ~ feedback,var.equal=T,data = datapt13)##
## Two Sample t-test
##
## data: Self.regulation by feedback
## t = -1.1649, df = 57, p-value = 0.2489
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -2.3408790 0.6190399
## sample estimates:
## mean in group effort mean in group performance
## 13.96667 14.82759#Test
#Anxiety between the effort and performance group
#p-value = 0.6912
var.test(datapt13e$Test_anxiety,datapt13p$Test_anxiety)#等分散##
## F test to compare two variances
##
## data: datapt13e$Test_anxiety and datapt13p$Test_anxiety
## F = 0.95968, num df = 29, denom df = 28, p-value = 0.9115
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.4525225 2.0251421
## sample estimates:
## ratio of variances
## 0.9596774t.test(Test_anxiety ~ feedback,var.equal=T,data = datapt13)##
## Two Sample t-test
##
## data: Test_anxiety by feedback
## t = -0.39929, df = 57, p-value = 0.6912
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -2.800134 1.869099
## sample estimates:
## mean in group effort mean in group performance
## 10.50000 10.96552#Analysis 18 #Correlation #Students who Marked less than 13 in the Pre-test（N=59）
library(corrplot)## corrplot 0.92 loadedround(cor(datapt13v),2)## ID feedback ITS class PreTest_Total_Score
## ID 1.00 -0.09 0.25 0.94 0.08
## feedback -0.09 1.00 0.06 -0.11 -0.05
## ITS 0.25 0.06 1.00 0.20 -0.06
## class 0.94 -0.11 0.20 1.00 0.04
## PreTest_Total_Score 0.08 -0.05 -0.06 0.04 1.00
## PostTest_Total_Score -0.06 0.16 0.02 -0.13 0.61
## Post_Pre -0.17 0.24 0.08 -0.19 -0.39
## Intrinsic_Value -0.06 0.04 -0.14 -0.06 0.47
## Self.regulation -0.20 0.15 -0.14 -0.16 0.26
## Self.efficacy -0.09 0.04 -0.16 -0.12 0.43
## Test_anxiety 0.08 0.05 -0.17 -0.01 0.35
## Survey_Total_Score -0.06 0.08 -0.19 -0.10 0.47
## PostTest_Total_Score Post_Pre Intrinsic_Value
## ID -0.06 -0.17 -0.06
## feedback 0.16 0.24 0.04
## ITS 0.02 0.08 -0.14
## class -0.13 -0.19 -0.06
## PreTest_Total_Score 0.61 -0.39 0.47
## PostTest_Total_Score 1.00 0.50 0.40
## Post_Pre 0.50 1.00 -0.05
## Intrinsic_Value 0.40 -0.05 1.00
## Self.regulation 0.26 0.02 0.53
## Self.efficacy 0.41 0.00 0.76
## Test_anxiety 0.38 0.06 0.54
## Survey_Total_Score 0.46 0.01 0.87
## Self.regulation Self.efficacy Test_anxiety
## ID -0.20 -0.09 0.08
## feedback 0.15 0.04 0.05
## ITS -0.14 -0.16 -0.17
## class -0.16 -0.12 -0.01
## PreTest_Total_Score 0.26 0.43 0.35
## PostTest_Total_Score 0.26 0.41 0.38
## Post_Pre 0.02 0.00 0.06
## Intrinsic_Value 0.53 0.76 0.54
## Self.regulation 1.00 0.62 0.17
## Self.efficacy 0.62 1.00 0.59
## Test_anxiety 0.17 0.59 1.00
## Survey_Total_Score 0.66 0.92 0.77
## Survey_Total_Score
## ID -0.06
## feedback 0.08
## ITS -0.19
## class -0.10
## PreTest_Total_Score 0.47
## PostTest_Total_Score 0.46
## Post_Pre 0.01
## Intrinsic_Value 0.87
## Self.regulation 0.66
## Self.efficacy 0.92
## Test_anxiety 0.77
## Survey_Total_Score 1.00cor_matrix<-round(cor(datapt13v),2)
corrplot(corr=cor_matrix)
#Comment: This result is the same as all students (N=65) , Analysis6
##Significant Correlation##
#Pre-Test × Post-Test
#p-value = 3.362e-07, cor 0.607494
cor.test(datapt13$PreTest_Total_Score,datapt13$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datapt13$PreTest_Total_Score and datapt13$PostTest_Total_Score
## t = 5.7741, df = 57, p-value = 3.362e-07
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.4161518 0.7473173
## sample estimates:
## cor
## 0.607494#Math Motivation Score × Pre-test
#p-value = 0.000166, cor 0.4710983
cor.test(datapt13$Survey_Total_Score,datapt13$PreTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datapt13$Survey_Total_Score and datapt13$PreTest_Total_Score
## t = 4.0322, df = 57, p-value = 0.000166
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.2445143 0.6488977
## sample estimates:
## cor
## 0.4710983#Math Motivation Score × Post-test
#p-value = 0.0002872, cor 0.4556647
cor.test(datapt13$Survey_Total_Score,datapt13$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datapt13$Survey_Total_Score and datapt13$PostTest_Total_Score
## t = 3.8647, df = 57, p-value = 0.0002872
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.2259477 0.6373733
## sample estimates:
## cor
## 0.4556647#Intrinsic value × Post-test
#p-value = 0.001855, cor 0.3969238
cor.test(datapt13$Intrinsic_Value,datapt13$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datapt13$Intrinsic_Value and datapt13$PostTest_Total_Score
## t = 3.2649, df = 57, p-value = 0.001855
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.1567772 0.5927554
## sample estimates:
## cor
## 0.3969238#Test anxiety × Post-test
#p-value = 0.002695, cor 0.3837765
cor.test(datapt13$Test_anxiety,datapt13$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datapt13$Test_anxiety and datapt13$PostTest_Total_Score
## t = 3.1377, df = 57, p-value = 0.002695
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.1416115 0.5826016
## sample estimates:
## cor
## 0.3837765#Self efficacy × Post-test
#p-value = 0.001372, cor 0.4071618
cor.test(datapt13$Self.efficacy,datapt13$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datapt13$Self.efficacy and datapt13$PostTest_Total_Score
## t = 3.3656, df = 57, p-value = 0.001372
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.1686657 0.6006193
## sample estimates:
## cor
## 0.4071618#Self regulation × Post-test
#p-value = 0.04345, cor 0.2638605
cor.test(datapt13$Self.regulation,datapt13$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datapt13$Self.regulation and datapt13$PostTest_Total_Score
## t = 2.0653, df = 57, p-value = 0.04345
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.008341907 0.487033914
## sample estimates:
## cor
## 0.2638605##No significant##
#Math motivation score × Score increase（増加量）
cor.test(datapt13$Survey_Total_Score,datapt13$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datapt13$Survey_Total_Score and datapt13$Post_Pre
## t = 0.10521, df = 57, p-value = 0.9166
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2430158 0.2690559
## sample estimates:
## cor
## 0.01393362#Intrinsic value × Score increase
cor.test(datapt13$Intrinsic_Value,datapt13$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datapt13$Intrinsic_Value and datapt13$Post_Pre
## t = -0.38174, df = 57, p-value = 0.7041
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.3026664 0.2082775
## sample estimates:
## cor
## -0.05049815#Self efficacy × Score increase
cor.test(datapt13$Self.efficacy,datapt13$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datapt13$Self.efficacy and datapt13$Post_Pre
## t = -0.0074283, df = 57, p-value = 0.9941
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2570014 0.2551627
## sample estimates:
## cor
## -0.0009839029#Self regulation × Score increase
cor.test(datapt13$Self.regulation,datapt13$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datapt13$Self.regulation and datapt13$Post_Pre
## t = 0.17065, df = 57, p-value = 0.8651
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2348440 0.2770761
## sample estimates:
## cor
## 0.02259723#Test anxiety × Score increase
cor.test(datapt13$Test_anxiety,datapt13$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datapt13$Test_anxiety and datapt13$Post_Pre
## t = 0.44744, df = 57, p-value = 0.6563
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1999509 0.3105382
## sample estimates:
## cor
## 0.0591606