What are missing in the U.S. education policy of “college for all” are supporting data and indicators on K-16 education pathways, i.e, how well all students get ready and stay on track from kindergarten through college. This study creates synthetic national longitudinal education database that helps track and support students’ educational pathways by combining two nationally-representative U.S. sample datasets: Early Childhood Longitudinal Study- Kindergarten (ECLS-K; Kindergarten through 8th grade) and National Education Longitudinal Study (NELS; 8th grade through age 25). The merge of these national datasets, linked together via statistical matching and imputation techniques, can help bridge the gap between elementary and secondary/postsecondary education data/research silos. Using this synthetic K-16 education longitudinal database, this study applies machine learning data analytics in search of college readiness early indicators among kindergarten students. It shows the utilities and limitations of linking preexisting national datasets to impute education pathways and assess college readiness. It discusses implications for developing more holistic and equitable educational assessment system in support of K-16 education longitudinal database.

Family routines and practices are recognized as critical determinants of child development. Despite extensive research on the socio-emotional benefits of family routines for school readiness in various contexts, there remains limited empirical evidence directly linking these routines to academic performance. This is because a lot of existing literature has focused on younger children below 8 years. This study sought to address this gap by examining the role of family routines on academic performance among middle school students in informal settlements. The study involved 351 middle school students and their parents from informal settlements in Nairobi, Kenya. Family routines were assessed using a structured questionnaire adapted from the Family Routine Inventory (FRI) scale. Academic performance data were obtained from the most recent school examinations of each participating student across five subjects (English, Kiswahili, Mathematics, Science, and Social Studies) as percentage scores. Results show that routines related to basic needs provision were the strongest predictors of academic performance, followed by academic monitoring routines. Emotional support routines moderately contributed to academic outcomes, while routines related to family outings and bonding had a limited impact. The study recommends further exploration of context-specific family routines using longitudinal designs to identify long-term impacts.