To explore their role in enhancing graduate employability, the study investigated the effectiveness of student internships as pedagogical practices in promoting employability skills amongst graduating students in four Social Science Degree programmes of selected universities in Zambia. Qualitative and quantitative data were collected from 162 participants through the questionnaires and interview guides using a mixed-methods approach. The participants included different actors in the labour industry as critical informants; graduating students taking Social Science Degree Programmes; Lecturers, and Employers. The quantitative and qualitative data were analysed using the SPSS version 24 and Atlas. Ti. Version 8, respectively. This study employed the Human Capability Approach and Human Capital theories. Findings indicated that although internship practices were considered an essential component in the social science degree programmes for skills development, their effectiveness in promoting employability skills amongst graduating students varied from one programme to the other. The findings have implications on how universities and the labour industry could work together to design and implement internship experiences for students in social science degree programmes that are more effective in promoting the acquisition of employability skills in Zambia.

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.