Engagement variables

Competence Variable

scimo_student_survey$competence <- composite_mean_maker(scimo_student_survey, confident1, capable1)

Reliabilities for competence (.86)

# competence_reliability <- select(scimo_student_survey, confident1, capable1)
# cronbach(competence_reliability)

Reliabilities for behavioral engagement (.80)

# behavioral_reliability <- select(scimo_esm, conc, hardwk)
# cronbach(behavioral_reliability)

Reliabilities for cognitive engagement (.80)

# cognitive_reliability <- select(scimo_esm, imp_y, imp_fut)
# cronbach(cognitive_reliability)

Reliabilities for affective engagement (.75)

# affective_reliability <- select(scimo_esm, enjoy, interest)
# cronbach(affective_reliability)

Descriptives of engagement and competence, and utility value variables

library(psych)
## 
## Attaching package: 'psych'
## The following objects are masked from 'package:ggplot2':
## 
##     %+%, alpha
describe(scimo_esm$cognitive_engagement)
##    vars    n mean   sd median trimmed  mad min max range skew kurtosis
## X1    1 3997 1.15 0.92      1    1.08 1.48   0   3     3 0.36    -0.91
##      se
## X1 0.01
describe(scimo_esm$behavioral_engagement)
##    vars    n mean   sd median trimmed  mad min max range  skew kurtosis
## X1    1 4103 1.82 0.88      2    1.88 0.74   0   3     3 -0.38    -0.69
##      se
## X1 0.01
describe(scimo_esm$affective_engagement)
##    vars    n mean   sd median trimmed  mad min max range skew kurtosis
## X1    1 4107 1.26 0.88      1    1.22 0.74   0   3     3 0.25    -0.81
##      se
## X1 0.01
describe(scimo_student_survey$competence)
##    vars   n mean   sd median trimmed  mad min max range  skew kurtosis
## X1    1 232 5.01 1.42      5    5.11 1.48   1   7     6 -0.57    -0.05
##      se
## X1 0.09
describe(scimo_value$high_utility_sum)
##    vars   n mean   sd median trimmed mad min max range skew kurtosis   se
## X1    1 480  0.6 1.25      0    0.31   0   0  10    10  3.5    16.42 0.06

Frequencies for demographics and utility value

table(scimo_value$high_utility_sum)
## 
##   0   1   2   3   4   5   6   7   8   9  10 
## 327  92  27  19   6   3   1   2   1   1   1

Demographics

Gender(1=male, 2=female)

table(scimo_student_survey$gender)
## 
##   1   2 
## 129 115

Race

table(scimo_student_survey$race)
## 
##   1   2   3   4   5   6 
##   5 101  28  90   2  15

Age

describe(scimo_student_survey$age)
##    vars   n  mean   sd median trimmed  mad min max range skew kurtosis
## X1    1 244 15.31 1.11     15   15.23 1.48  14  18     4 0.35    -0.84
##      se
## X1 0.07

Grade

table(scimo_student_survey$grade)
## 
##   1   2   3   4 
## 104  52  82   6

Subject

table(scimo_student_survey$subject)
## 
##  1  2  3  4 
## 49 75 60 60

Free Lunch

table(scimo_student_survey$Lunch)
## 
##   0   1 
## 137 103

Parent Education

table(scimo_student_survey$pared)
## 
##  0  1  2  3  4  5  6  7  8  9 
## 20 26 50  5 18 13 45 26  7 34