IDENTIFYING THE SOCIOECONOMIC FACTORS ASSOCIATED WITH CHRONIC ABSENTEEISM IN RURAL INDIA USING EATTENDANCE
Emma Castro (School of Public Health), Youngwon Kim (College of Education), Yan Su (School of Nursing)
BACKGROUND
School dropout negatively impacts youth development as well as the social and economic vitality of the community. Targeting truancy among high-risk groups has been shown to reduce rates of drop out. In-depth study of absenteeism in India is particularly difficult due to poor data quality.
The Center for Sustainable Development at the Earth Institute sought to address this problem by implementing a biometric system of daily attendance tracking.
Random Intercept Effects & Coefficients of Random Slopes
EXPLORATORY DATA ANALYSIS
MODEL SELECTION
Linear Regression
Varying intercept
- M1 <- pct_absent ~ (1 | school)
- M2 <- pct_absent ~ sex + as.factor(grade) + caste + mandal + (1 | school)
- M3 <- pct_absent ~ sex + grade + caste + mandal
+ (1 | school)
- M4 <- pct_absent ~ sex + age + caste + mandal + (1 | school)
Varying intercept & Random slopes
- M5 <- pct_absent ~ sex + grade + caste + mandal + (1 + grade | school)
- M6 <- pct_absent ~ sex + age + caste + mandal + (1 + age | school)
RESULTS
- On average, female students missed fewer days of school during the 7-month study period than their male classmates. Being female was associated with a 6-point decrease in percentage of days missed.
- On average, students in older grades missed fewer days of school during the 7-month study period. A one-year increase in grade was associated with a 1.7 point decrease in percentage of days missed.
- Caste was not significantly associated with percentage of days missed for this particular model.
- Residence in the rural mandal of Narayankhed was associated with a 6-point increase in percentage of days missed as compared with semi-urban Gajwel.
DISCUSSION
- Policies/interventions aimed at improving attendance should target:
- Male students (and their parents)
- Younger students
- Rural districts
LIMITATIONS
- Sampling scheme hinders the generalizability of this study.
- Additional covariates, such as distance traveled and means of travel to school, would have added insight
- Qualitative data on reasons for absenteeism were collected but had too many problems to be used.
RESEARCH QUESTION
- Are certain socioeconomic factors associated with absenteeism among secondary school students monitored with eAttendance?
DESCRIPTION OF VARIABLES
Outcome
- Percentage of schools days missed during the 7-month study period
Dependent
- Mandal: Gajwel (5 schools), Narayankhed (5)
- Caste : scheduled tribe (ST), scheduled caste (SC), backwards caste (BC), open caste (OC)
- Grade : 6-10
- Sex : 343 males, 390 females
Grouping Variable
N=733 students within 10 schools; * p <.05, *** p < .001