Omiyakita_Elementary_School_Only Middle and Low Class students (N=42)
2023-11-05
#Import data #Only Midle and Low Class students (N=42)
read.csv("only_low_middle_level.csv") #only students who marked less than 12 in Pre_Test N=42## ID username feedback ITS pre_test_type post_test_type class
## 1 106 yessomen effort 12 A B 3
## 2 13 niceniku performance 12 A B 1
## 3 41 goramen effort 12 B A 2
## 4 52 nicetako performance 12 A B 2
## 5 83 niceimo performance 12 A B 3
## 6 7 gotamago effort 12 B A 1
## 7 35 yestofu effort 12 A B 1
## 8 37 gogyoza effort 12 B A 2
## 9 16 nicetamago performance 12 A B 1
## 10 25 oktamago performance 12 B A 1
## 11 54 niceyuba performance 12 A B 2
## 12 82 niceice performance 12 A B 3
## 13 5 gosoba effort 12 B A 1
## 14 34 yestamago effort 12 A B 1
## 15 44 gounagi effort 12 B A 2
## 16 79 gosomen effort 12 B A 3
## 17 23 oksoba performance 12 B A 1
## 18 46 nicegyoza performance 12 A B 2
## 19 93 oknabe performance 12 B A 3
## 20 102 yesnabe effort 12 A B 3
## 21 69 yessakana effort 12 A B 2
## 22 75 gonabe effort 12 B A 3
## 23 15 nicesushi performance 12 A B 1
## 24 49 niceonigiri performance 12 A B 2
## 25 91 okice performance 12 B A 3
## 26 29 yesfugu effort 12 A B 1
## 27 39 gokaki effort 12 B A 2
## 28 100 yesice effort 12 A B 3
## 29 10 nicecola performance 11 A B 1
## 30 12 nicemiso performance 12 A B 1
## 31 8 gotofu effort 10 B A 1
## 32 76 gonigiri effort 12 B A 3
## 33 27 okudon performance 12 B A 1
## 34 33 yessushi effort 12 A B 1
## 35 40 goonigiri effort 12 B A 2
## 36 74 goimo effort 12 B A 3
## 37 21 okmiso performance 12 B A 1
## 38 26 oktofu performance 12 B A 1
## 39 50 niceramen performance 12 A B 2
## 40 56 okika performance 12 B A 2
## 41 58 okonigiri performance 12 B A 2
## 42 96 oksake performance 12 B A 3
## PreTest_Total_Score PostTest_Total_Score Post_Pre Intrinsic_Value
## 1 1 0 -1 6
## 2 1 14 13 14
## 3 2 1 -1 11
## 4 2 3 1 8
## 5 2 13 11 3
## 6 3 9 6 10
## 7 3 10 7 9
## 8 3 3 0 6
## 9 3 3 0 9
## 10 3 4 1 7
## 11 3 12 9 7
## 12 3 1 -2 4
## 13 4 6 2 6
## 14 4 3 -1 6
## 15 5 8 3 8
## 16 5 10 5 8
## 17 5 9 4 14
## 18 5 2 -3 10
## 19 5 8 3 13
## 20 7 2 -5 12
## 21 8 11 3 5
## 22 8 6 -2 10
## 23 8 8 0 11
## 24 8 11 3 15
## 25 8 12 4 12
## 26 9 11 2 8
## 27 9 4 -5 15
## 28 9 6 -3 9
## 29 9 11 2 13
## 30 9 9 0 11
## 31 10 8 -2 13
## 32 10 12 2 13
## 33 10 12 2 12
## 34 11 11 0 15
## 35 11 12 1 13
## 36 11 3 -8 5
## 37 11 14 3 12
## 38 11 14 3 7
## 39 11 13 2 7
## 40 11 13 2 14
## 41 11 10 -1 9
## 42 11 13 2 11
## Self.regulation Self.efficacy Test_anxiety Survey_Total_Score
## 1 9 9 9 33
## 2 17 17 15 63
## 3 16 16 4 47
## 4 7 5 5 25
## 5 11 4 5 23
## 6 15 12 9 46
## 7 13 14 14 50
## 8 15 6 4 31
## 9 13 10 8 40
## 10 14 13 9 43
## 11 13 12 13 45
## 12 17 11 4 36
## 13 11 12 7 36
## 14 12 11 7 36
## 15 11 12 8 39
## 16 14 7 7 36
## 17 13 11 5 43
## 18 16 11 4 41
## 19 17 15 16 61
## 20 18 17 15 62
## 21 15 11 7 38
## 22 11 9 14 44
## 23 15 15 4 45
## 24 17 16 17 65
## 25 14 17 14 57
## 26 11 9 15 43
## 27 18 14 12 59
## 28 8 7 12 36
## 29 18 16 15 62
## 30 15 15 16 57
## 31 16 17 15 61
## 32 16 15 12 56
## 33 14 11 12 49
## 34 16 17 13 61
## 35 19 17 5 54
## 36 10 6 6 27
## 37 15 12 12 51
## 38 14 11 13 45
## 39 14 8 7 36
## 40 18 20 14 66
## 41 14 12 9 44
## 42 11 13 11 46read.csv("only_low_middle_level_effort.csv") #only students who marked less than 12 in Pre_Test and effort feedback group N=20## ID username feedback ITS pre_test_type post_test_type class
## 1 106 yessomen effort 12 A B 3
## 2 41 goramen effort 12 B A 2
## 3 7 gotamago effort 12 B A 1
## 4 35 yestofu effort 12 A B 1
## 5 37 gogyoza effort 12 B A 2
## 6 5 gosoba effort 12 B A 1
## 7 34 yestamago effort 12 A B 1
## 8 44 gounagi effort 12 B A 2
## 9 79 gosomen effort 12 B A 3
## 10 102 yesnabe effort 12 A B 3
## 11 69 yessakana effort 12 A B 2
## 12 75 gonabe effort 12 B A 3
## 13 29 yesfugu effort 12 A B 1
## 14 39 gokaki effort 12 B A 2
## 15 100 yesice effort 12 A B 3
## 16 8 gotofu effort 10 B A 1
## 17 76 gonigiri effort 12 B A 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
## PreTest_Total_Score PostTest_Total_Score Post_Pre Intrinsic_Value
## 1 1 0 -1 6
## 2 2 1 -1 11
## 3 3 9 6 10
## 4 3 10 7 9
## 5 3 3 0 6
## 6 4 6 2 6
## 7 4 3 -1 6
## 8 5 8 3 8
## 9 5 10 5 8
## 10 7 2 -5 12
## 11 8 11 3 5
## 12 8 6 -2 10
## 13 9 11 2 8
## 14 9 4 -5 15
## 15 9 6 -3 9
## 16 10 8 -2 13
## 17 10 12 2 13
## 18 11 11 0 15
## 19 11 12 1 13
## 20 11 3 -8 5
## Self.regulation Self.efficacy Test_anxiety Survey_Total_Score
## 1 9 9 9 33
## 2 16 16 4 47
## 3 15 12 9 46
## 4 13 14 14 50
## 5 15 6 4 31
## 6 11 12 7 36
## 7 12 11 7 36
## 8 11 12 8 39
## 9 14 7 7 36
## 10 18 17 15 62
## 11 15 11 7 38
## 12 11 9 14 44
## 13 11 9 15 43
## 14 18 14 12 59
## 15 8 7 12 36
## 16 16 17 15 61
## 17 16 15 12 56
## 18 16 17 13 61
## 19 19 17 5 54
## 20 10 6 6 27read.csv("only_low_middle_level_performance.csv") #only students who marked less than 12 in Pre_Test and performance feedback group N=22## ID username feedback ITS pre_test_type post_test_type class
## 1 13 niceniku performance 12 A B 1
## 2 52 nicetako performance 12 A B 2
## 3 83 niceimo performance 12 A B 3
## 4 16 nicetamago performance 12 A B 1
## 5 25 oktamago performance 12 B A 1
## 6 54 niceyuba performance 12 A B 2
## 7 82 niceice performance 12 A B 3
## 8 23 oksoba performance 12 B A 1
## 9 46 nicegyoza performance 12 A B 2
## 10 93 oknabe performance 12 B A 3
## 11 15 nicesushi performance 12 A B 1
## 12 49 niceonigiri performance 12 A B 2
## 13 91 okice performance 12 B A 3
## 14 10 nicecola performance 11 A B 1
## 15 12 nicemiso performance 12 A B 1
## 16 27 okudon performance 12 B A 1
## 17 21 okmiso performance 12 B A 1
## 18 26 oktofu performance 12 B A 1
## 19 50 niceramen performance 12 A B 2
## 20 56 okika performance 12 B A 2
## 21 58 okonigiri performance 12 B A 2
## 22 96 oksake performance 12 B A 3
## PreTest_Total_Score PostTest_Total_Score Post_Pre Intrinsic_Value
## 1 1 14 13 14
## 2 2 3 1 8
## 3 2 13 11 3
## 4 3 3 0 9
## 5 3 4 1 7
## 6 3 12 9 7
## 7 3 1 -2 4
## 8 5 9 4 14
## 9 5 2 -3 10
## 10 5 8 3 13
## 11 8 8 0 11
## 12 8 11 3 15
## 13 8 12 4 12
## 14 9 11 2 13
## 15 9 9 0 11
## 16 10 12 2 12
## 17 11 14 3 12
## 18 11 14 3 7
## 19 11 13 2 7
## 20 11 13 2 14
## 21 11 10 -1 9
## 22 11 13 2 11
## Self.regulation Self.efficacy Test_anxiety Survey_Total_Score
## 1 17 17 15 63
## 2 7 5 5 25
## 3 11 4 5 23
## 4 13 10 8 40
## 5 14 13 9 43
## 6 13 12 13 45
## 7 17 11 4 36
## 8 13 11 5 43
## 9 16 11 4 41
## 10 17 15 16 61
## 11 15 15 4 45
## 12 17 16 17 65
## 13 14 17 14 57
## 14 18 16 15 62
## 15 15 15 16 57
## 16 14 11 12 49
## 17 15 12 12 51
## 18 14 11 13 45
## 19 14 8 7 36
## 20 18 20 14 66
## 21 14 12 9 44
## 22 11 13 11 46read.csv("only_low_middle_level_only_value.csv") #Feedback(effort=1,performance=2)## ID feedback ITS class PreTest_Total_Score PostTest_Total_Score Post_Pre
## 1 33 1 12 1 11 11 0
## 2 40 1 12 2 11 12 1
## 3 74 1 12 3 11 3 -8
## 4 21 2 12 1 11 14 3
## 5 26 2 12 1 11 14 3
## 6 50 2 12 2 11 13 2
## 7 56 2 12 2 11 13 2
## 8 58 2 12 2 11 10 -1
## 9 96 2 12 3 11 13 2
## 10 8 1 10 1 10 8 -2
## 11 76 1 12 3 10 12 2
## 12 27 2 12 1 10 12 2
## 13 29 1 12 1 9 11 2
## 14 39 1 12 2 9 4 -5
## 15 100 1 12 3 9 6 -3
## 16 10 2 11 1 9 11 2
## 17 12 2 12 1 9 9 0
## 18 69 1 12 2 8 11 3
## 19 75 1 12 3 8 6 -2
## 20 15 2 12 1 8 8 0
## 21 49 2 12 2 8 11 3
## 22 91 2 12 3 8 12 4
## 23 102 1 12 3 7 2 -5
## 24 44 1 12 2 5 8 3
## 25 79 1 12 3 5 10 5
## 26 23 2 12 1 5 9 4
## 27 46 2 12 2 5 2 -3
## 28 93 2 12 3 5 8 3
## 29 5 1 12 1 4 6 2
## 30 34 1 12 1 4 3 -1
## 31 7 1 12 1 3 9 6
## 32 35 1 12 1 3 10 7
## 33 37 1 12 2 3 3 0
## 34 16 2 12 1 3 3 0
## 35 25 2 12 1 3 4 1
## 36 54 2 12 2 3 12 9
## 37 82 2 12 3 3 1 -2
## 38 41 1 12 2 2 1 -1
## 39 52 2 12 2 2 3 1
## 40 83 2 12 3 2 13 11
## 41 106 1 12 3 1 0 -1
## 42 13 2 12 1 1 14 13
## Intrinsic_Value Self.regulation Self.efficacy Test_anxiety
## 1 15 16 17 13
## 2 13 19 17 5
## 3 5 10 6 6
## 4 12 15 12 12
## 5 7 14 11 13
## 6 7 14 8 7
## 7 14 18 20 14
## 8 9 14 12 9
## 9 11 11 13 11
## 10 13 16 17 15
## 11 13 16 15 12
## 12 12 14 11 12
## 13 8 11 9 15
## 14 15 18 14 12
## 15 9 8 7 12
## 16 13 18 16 15
## 17 11 15 15 16
## 18 5 15 11 7
## 19 10 11 9 14
## 20 11 15 15 4
## 21 15 17 16 17
## 22 12 14 17 14
## 23 12 18 17 15
## 24 8 11 12 8
## 25 8 14 7 7
## 26 14 13 11 5
## 27 10 16 11 4
## 28 13 17 15 16
## 29 6 11 12 7
## 30 6 12 11 7
## 31 10 15 12 9
## 32 9 13 14 14
## 33 6 15 6 4
## 34 9 13 10 8
## 35 7 14 13 9
## 36 7 13 12 13
## 37 4 17 11 4
## 38 11 16 16 4
## 39 8 7 5 5
## 40 3 11 4 5
## 41 6 9 9 9
## 42 14 17 17 15
## Survey_Total_Score
## 1 61
## 2 54
## 3 27
## 4 51
## 5 45
## 6 36
## 7 66
## 8 44
## 9 46
## 10 61
## 11 56
## 12 49
## 13 43
## 14 59
## 15 36
## 16 62
## 17 57
## 18 38
## 19 44
## 20 45
## 21 65
## 22 57
## 23 62
## 24 39
## 25 36
## 26 43
## 27 41
## 28 61
## 29 36
## 30 36
## 31 46
## 32 50
## 33 31
## 34 40
## 35 43
## 36 45
## 37 36
## 38 47
## 39 25
## 40 23
## 41 33
## 42 63setwd("/Users/satoushintarou/Desktop/Master thesis/大宮北小/Data") #Directory
datal<-read.csv("only_low_middle_level.csv")
datale<-read.csv("only_low_middle_level_effort.csv")
datalp<-read.csv("only_low_middle_level_performance.csv")
datalv<-read.csv("only_low_middle_level_only_value.csv")#Students who Marked 0〜75 Percentile in the Pre-test
#Pre-Test 75 percentile = score "12"
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")
quantile(data$PreTest_Total_Score)## 0% 25% 50% 75% 100%
## 1 5 10 12 14summary(data$PreTest_Total_Score)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.000 5.000 10.000 8.908 12.000 14.000#Demographic
#Students who Marked 0〜75 Percentile in the Pre-test (N=42)
table(datal$feedback)##
## effort performance
## 20 22#Analysis 7 #Compare Pre- vs. Post-Test #Only Middle and Low Level Students (N=42)
#Comment:This result is the same as all students (N=65), Analysis 1.
#T-test
#Pre-test and Post-test
#p-value = 0.02167
t.test(datal$PreTest_Total_Score, datal$PostTest_Total_Score, paired=TRUE)##
## Paired t-test
##
## data: datal$PreTest_Total_Score and datal$PostTest_Total_Score
## t = -2.3872, df = 41, p-value = 0.02167
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## -2.7250286 -0.2273524
## sample estimates:
## mean difference
## -1.47619#Analysis 8 #Compare Pre-Test / Effort vs. Performance Group #Compare Post-Test / Effort vs. Performance Group #Only Middle and Low Level Students (N=42)
#Comment:There is a significant difference, "Post-test between the effort and performance group"（p-value = 0.03929）. This is not the case for all students (N=65), Analysis2.
#T-test
#Pre-test between the effort and performance group
#p-value = 0.8772
var.test(datale$PreTest_Total_Score,datalp$PreTest_Total_Score)##
## F test to compare two variances
##
## data: datale$PreTest_Total_Score and datalp$PreTest_Total_Score
## F = 0.84727, num df = 19, denom df = 21, p-value = 0.7209
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.3468983 2.1121928
## sample estimates:
## ratio of variances
## 0.8472657t.test(PreTest_Total_Score ~ feedback, var.equal=T,data = datal)##
## Two Sample t-test
##
## data: PreTest_Total_Score by feedback
## t = -0.15556, df = 40, p-value = 0.8772
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -2.353277 2.016913
## sample estimates:
## mean in group effort mean in group performance
## 6.650000 6.818182#T-test
#Post-test between the effort and performance group
#p-value = 0.03929
var.test(datale$PostTest_Total_Score,datalp$PostTest_Total_Score)##
## F test to compare two variances
##
## data: datale$PostTest_Total_Score and datalp$PostTest_Total_Score
## F = 0.84365, num df = 19, denom df = 21, p-value = 0.7138
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.345418 2.103180
## sample estimates:
## ratio of variances
## 0.8436504t.test(PostTest_Total_Score ~ feedback, var.equal=T,data = datal)##
## Two Sample t-test
##
## data: PostTest_Total_Score by feedback
## t = -2.131, df = 40, p-value = 0.03929
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -5.2607167 -0.1392833
## sample estimates:
## mean in group effort mean in group performance
## 6.8 9.5#Analysis 9 #Compare Test Score Increase (増加量) / Effort vs. Performance Group #Only Middle and Low Level Students (N=42)
#Comment:This result is the same as all students (N=65), Analysis 3.
#T-test
#Post_Pre[(Post_Test_Total_Score)ー(Pre_Test_Total_Score)] between the effort and performance group
#p-value = 0.03926
var.test(datal$Post_Pre,datal$Post_Pre)##
## F test to compare two variances
##
## data: datal$Post_Pre and datal$Post_Pre
## F = 1, num df = 41, denom df = 41, p-value = 1
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.5375237 1.8603832
## sample estimates:
## ratio of variances
## 1t.test(Post_Pre ~ feedback,var.equal=T,data = datal)##
## Two Sample t-test
##
## data: Post_Pre by feedback
## t = -2.1313, df = 40, p-value = 0.03926
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -4.9326576 -0.1309788
## sample estimates:
## mean in group effort mean in group performance
## 0.150000 2.681818#Analysis 10 #Regression Model #Only Middle and Low Level Students (N=42)
#Comment:???
#y="Post-test", x="Feedback type" and "Pre-test"
model5 <- lm(PostTest_Total_Score ~ feedback*PreTest_Total_Score, data = datal)
summary(model5)##
## Call:
## lm(formula = PostTest_Total_Score ~ feedback * PreTest_Total_Score,
## data = datal)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.3787 -2.3356 0.5795 2.0475 8.0882
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.21454 1.85270 1.735 0.0908 .
## feedbackperformance 2.08054 2.50344 0.831 0.4111
## PreTest_Total_Score 0.53917 0.25016 2.155 0.0375 *
## feedbackperformance:PreTest_Total_Score 0.07755 0.33249 0.233 0.8168
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.647 on 38 degrees of freedom
## Multiple R-squared: 0.3252, Adjusted R-squared: 0.272
## F-statistic: 6.105 on 3 and 38 DF, p-value: 0.001704model6 <- lm(PostTest_Total_Score ~ feedback+PreTest_Total_Score, data = datal)
summary(model6)##
## Call:
## lm(formula = PostTest_Total_Score ~ feedback + PreTest_Total_Score,
## data = datal)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.4399 -2.2384 0.6025 2.1370 7.8924
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9226 1.3493 2.166 0.036490 *
## feedbackperformance 2.6019 1.1134 2.337 0.024670 *
## PreTest_Total_Score 0.5831 0.1628 3.582 0.000934 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.603 on 39 degrees of freedom
## Multiple R-squared: 0.3243, Adjusted R-squared: 0.2896
## F-statistic: 9.357 on 2 and 39 DF, p-value: 0.0004794library(ggplot2)
ggplot(datal, 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 = datal)
summary(model7)##
## Call:
## lm(formula = Post_Pre ~ feedback * PreTest_Total_Score, data = datal)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.3787 -2.3356 0.5795 2.0475 8.0882
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.21454 1.85270 1.735 0.0908 .
## feedbackperformance 2.08054 2.50344 0.831 0.4111
## PreTest_Total_Score -0.46083 0.25016 -1.842 0.0733 .
## feedbackperformance:PreTest_Total_Score 0.07755 0.33249 0.233 0.8168
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.647 on 38 degrees of freedom
## Multiple R-squared: 0.2324, Adjusted R-squared: 0.1718
## F-statistic: 3.835 on 3 and 38 DF, p-value: 0.01711model8 <- lm(Post_Pre ~ feedback+PreTest_Total_Score, data = datal)
summary(model8)##
## Call:
## lm(formula = Post_Pre ~ feedback + PreTest_Total_Score, data = datal)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.4399 -2.2384 0.6025 2.1370 7.8924
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9226 1.3493 2.166 0.0365 *
## feedbackperformance 2.6019 1.1134 2.337 0.0247 *
## PreTest_Total_Score -0.4169 0.1628 -2.561 0.0144 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.603 on 39 degrees of freedom
## Multiple R-squared: 0.2313, Adjusted R-squared: 0.1919
## F-statistic: 5.867 on 2 and 39 DF, p-value: 0.00592library(ggplot2)
ggplot(datal, 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 11 #Compare Math Motivation Score (算数学習への意欲) / Effort vs. Performance Group #Only Middle and Low Level Students (N=42)
#Comment:This result is the same as all students (N=65), Analysis 5.
#T-test
#Math motivation score between the effort and performance group
#p-value = 0.4601
var.test(datale$Survey_Total_Score,datalp$Survey_Total_Score)#等分散##
## F test to compare two variances
##
## data: datale$Survey_Total_Score and datalp$Survey_Total_Score
## F = 0.84405, num df = 19, denom df = 21, p-value = 0.7146
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.3455823 2.1041802
## sample estimates:
## ratio of variances
## 0.8440517t.test(Survey_Total_Score ~ feedback,var.equal=T,data = datal)##
## Two Sample t-test
##
## data: Survey_Total_Score by feedback
## t = -0.74594, df = 40, p-value = 0.4601
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -9.863750 4.545568
## sample estimates:
## mean in group effort mean in group performance
## 44.75000 47.40909#T-test
#Intrinsic value between the effort and performance group
#p-value = 0.4742
var.test(datale$Intrinsic_Value,datalp$Intrinsic_Value)#等分散##
## F test to compare two variances
##
## data: datale$Intrinsic_Value and datalp$Intrinsic_Value
## F = 0.9637, num df = 19, denom df = 21, p-value = 0.941
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.3945694 2.4024525
## sample estimates:
## ratio of variances
## 0.9636979t.test(Intrinsic_Value ~ feedback,var.equal=T,data = datal)##
## Two Sample t-test
##
## data: Intrinsic_Value by feedback
## t = -0.72241, df = 40, p-value = 0.4742
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -2.796474 1.323747
## sample estimates:
## mean in group effort mean in group performance
## 9.40000 10.13636#T-test
#Self efficacy between the effort and performance group
#p-value = 0.6163
var.test(datale$Self.efficacy,datalp$Self.efficacy)#等分散##
## F test to compare two variances
##
## data: datale$Self.efficacy and datalp$Self.efficacy
## F = 1.0201, num df = 19, denom df = 21, p-value = 0.959
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.4176529 2.5430030
## sample estimates:
## ratio of variances
## 1.020077t.test(Self.efficacy ~ feedback,var.equal=T,data = datal)##
## Two Sample t-test
##
## data: Self.efficacy by feedback
## t = -0.5051, df = 40, p-value = 0.6163
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -3.000793 1.800793
## sample estimates:
## mean in group effort mean in group performance
## 11.9 12.5#T-test
#Self regulation between the effort and performance group
#p-value = 0.4314
var.test(datale$Self.regulation,datalp$Self.regulation)#等分散##
## F test to compare two variances
##
## data: datale$Self.regulation and datalp$Self.regulation
## F = 1.5032, num df = 19, denom df = 21, p-value = 0.3647
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.6154652 3.7474422
## sample estimates:
## ratio of variances
## 1.503215t.test(Self.regulation ~ feedback,var.equal=T,data = datal)##
## Two Sample t-test
##
## data: Self.regulation by feedback
## t = -0.79483, df = 40, p-value = 0.4314
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -2.512153 1.093971
## sample estimates:
## mean in group effort mean in group performance
## 13.70000 14.40909#T-test
#Anxiety between the effort and performance group
#p-value = 0.6392
var.test(datale$Test_anxiety,datalp$Test_anxiety)#等分散##
## F test to compare two variances
##
## data: datale$Test_anxiety and datalp$Test_anxiety
## F = 0.73257, num df = 19, denom df = 21, p-value = 0.4992
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.2999372 1.8262562
## sample estimates:
## ratio of variances
## 0.7325678t.test(Test_anxiety ~ feedback,var.equal=T,data = datal)##
## Two Sample t-test
##
## data: Test_anxiety by feedback
## t = -0.47248, df = 40, p-value = 0.6392
## alternative hypothesis: true difference in means between group effort and group performance is not equal to 0
## 95 percent confidence interval:
## -3.238530 2.011257
## sample estimates:
## mean in group effort mean in group performance
## 9.75000 10.36364#Analysis 12 #Correlation #Only Middle and Low Level Students (N=42)
library(corrplot)## corrplot 0.92 loadedround(cor(datalv),2)## ID feedback ITS class PreTest_Total_Score
## ID 1.00 -0.11 0.28 0.94 0.01
## feedback -0.11 1.00 0.08 -0.14 0.02
## ITS 0.28 0.08 1.00 0.23 -0.18
## class 0.94 -0.14 0.23 1.00 0.00
## PreTest_Total_Score 0.01 0.02 -0.18 0.00 1.00
## PostTest_Total_Score -0.16 0.32 -0.04 -0.20 0.48
## Post_Pre -0.18 0.32 0.11 -0.21 -0.35
## Intrinsic_Value -0.21 0.11 -0.21 -0.20 0.38
## Self.regulation -0.23 0.12 -0.19 -0.16 0.23
## Self.efficacy -0.23 0.08 -0.25 -0.25 0.27
## Test_anxiety 0.00 0.07 -0.25 -0.10 0.35
## Survey_Total_Score -0.20 0.12 -0.28 -0.21 0.38
## PostTest_Total_Score Post_Pre Intrinsic_Value
## ID -0.16 -0.18 -0.21
## feedback 0.32 0.32 0.11
## ITS -0.04 0.11 -0.21
## class -0.20 -0.21 -0.20
## PreTest_Total_Score 0.48 -0.35 0.38
## PostTest_Total_Score 1.00 0.65 0.30
## Post_Pre 0.65 1.00 -0.01
## Intrinsic_Value 0.30 -0.01 1.00
## Self.regulation 0.20 0.02 0.57
## Self.efficacy 0.26 0.04 0.74
## Test_anxiety 0.42 0.15 0.53
## Survey_Total_Score 0.37 0.07 0.86
## Self.regulation Self.efficacy Test_anxiety
## ID -0.23 -0.23 0.00
## feedback 0.12 0.08 0.07
## ITS -0.19 -0.25 -0.25
## class -0.16 -0.25 -0.10
## PreTest_Total_Score 0.23 0.27 0.35
## PostTest_Total_Score 0.20 0.26 0.42
## Post_Pre 0.02 0.04 0.15
## Intrinsic_Value 0.57 0.74 0.53
## Self.regulation 1.00 0.72 0.23
## Self.efficacy 0.72 1.00 0.50
## Test_anxiety 0.23 0.50 1.00
## Survey_Total_Score 0.74 0.91 0.74
## Survey_Total_Score
## ID -0.20
## feedback 0.12
## ITS -0.28
## class -0.21
## PreTest_Total_Score 0.38
## PostTest_Total_Score 0.37
## Post_Pre 0.07
## Intrinsic_Value 0.86
## Self.regulation 0.74
## Self.efficacy 0.91
## Test_anxiety 0.74
## Survey_Total_Score 1.00cor_matrix<-round(cor(datalv),2)
corrplot(corr=cor_matrix)
#Comment: "Self efficacy × Post-test" and "Self regulation × Post-test" is a significant correlation in the case of all students (N=65), but it is not here.
##Significant Correlation##
#Pre-Test × Post-Test
#pp-value = 0.001324, cor 0.4792036
cor.test(datal$PreTest_Total_Score,datal$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datal$PreTest_Total_Score and datal$PostTest_Total_Score
## t = 3.453, df = 40, p-value = 0.001324
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.2051516 0.6835756
## sample estimates:
## cor
## 0.4792036#Math Motivation Score × Pre-test
#p-value = 0.01315, cor 0.3796418
cor.test(datal$Survey_Total_Score,datal$PreTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datal$Survey_Total_Score and datal$PreTest_Total_Score
## t = 2.5954, df = 40, p-value = 0.01315
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.08558573 0.61285844
## sample estimates:
## cor
## 0.3796418#Math Motivation Score × Post-test
#p-value = 0.01461, cor 0.3742882
cor.test(datal$Survey_Total_Score,datal$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datal$Survey_Total_Score and datal$PostTest_Total_Score
## t = 2.5528, df = 40, p-value = 0.01461
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.07938783 0.60894701
## sample estimates:
## cor
## 0.3742882#Intrinsic value × Post-test
#p-value = 0.05005, cor 0.3043299
cor.test(datal$Intrinsic_Value,datal$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datal$Intrinsic_Value and datal$PostTest_Total_Score
## t = 2.0206, df = 40, p-value = 0.05005
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.0004391956 0.5567632484
## sample estimates:
## cor
## 0.3043299#Test anxiety × Post-test
#p-value = 0.005469, cor 0.4212233
cor.test(datal$Test_anxiety,datal$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datal$Test_anxiety and datal$PostTest_Total_Score
## t = 2.9373, df = 40, p-value = 0.005469
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.1345126 0.6428545
## sample estimates:
## cor
## 0.4212233##No significant##
#Self efficacy × Post-test
#p-value = p-value = 0.1014, cor 0.2562308/a significant correlation in the case of all students (N=65).
cor.test(datal$Self.efficacy,datal$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datal$Self.efficacy and datal$PostTest_Total_Score
## t = 1.6765, df = 40, p-value = 0.1014
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.05172905 0.51969044
## sample estimates:
## cor
## 0.2562308#Self regulation × Post-test
#p-value = 0.2106, cor 0.1972309/a significant correlation in the case of all students (N=65).
cor.test(datal$Self.regulation,datal$PostTest_Total_Score)##
## Pearson's product-moment correlation
##
## data: datal$Self.regulation and datal$PostTest_Total_Score
## t = 1.2724, df = 40, p-value = 0.2106
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1135045 0.4728193
## sample estimates:
## cor
## 0.1972309#Math motivation score × Score increase（増加量）
cor.test(datal$Survey_Total_Score,datal$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datal$Survey_Total_Score and datal$Post_Pre
## t = 0.45447, df = 40, p-value = 0.6519
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2374297 0.3675975
## sample estimates:
## cor
## 0.07167384#Intrinsic value × Score increase
cor.test(datal$Intrinsic_Value,datal$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datal$Intrinsic_Value and datal$Post_Pre
## t = -0.04359, df = 40, p-value = 0.9654
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.3101737 0.2976628
## sample estimates:
## cor
## -0.006892088#Self efficacy × Score increase
cor.test(datal$Self.efficacy,datal$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datal$Self.efficacy and datal$Post_Pre
## t = 0.28029, df = 40, p-value = 0.7807
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2631990 0.3435821
## sample estimates:
## cor
## 0.04427403#Self regulation × Score increase
cor.test(datal$Self.regulation,datal$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datal$Self.regulation and datal$Post_Pre
## t = 0.1014, df = 40, p-value = 0.9197
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2893105 0.3184104
## sample estimates:
## cor
## 0.01603043#Test anxiety × Score increase
cor.test(datal$Test_anxiety,datal$Post_Pre)##
## Pearson's product-moment correlation
##
## data: datal$Test_anxiety and datal$Post_Pre
## t = 0.96865, df = 40, p-value = 0.3385
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1598975 0.4352936
## sample estimates:
## cor
## 0.1513912