Exploring Student-, Teacher-, and Classroom-Level Factors That Influence Attendance and Performance Gains in Adult Education Programs

This study used archival data from 30,453 students enrolled in 289 adult education programs in the state of Georgia, United States during the 2018–2019 school year. We explored how student-, teacher-, and classroom-level factors predict student attendance and academic performance (reading, language, and math) over time. Results indicated several student-level factors predict attendance and educational performance, including age, gender, race/ethnicity, previous educational attainment, low-income status, special needs status, reported barriers to education, and dual enrollment. Depending on the academic subject, age, race, previous education, special needs, and dual enrollment predicted academic growth over time. Teacher-level factors such as teacher experience predicted educational performance; classroom factors such as whether the course was an Integrated Education and Training (IET) class predicted attendance, and distance classes predicted attendance and performance. Certification predicted growth over time for language, and employment status and designation as a distance class predicted growth over time for math. These findings will help state officials improve the delivery of services to further enhance and improve student outcomes.