The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…

This paper describes a partnership-based approach for analyzing data from a learning management system (LMS) used by students in grades 6-12. The goal of the partnership was to create indicators for the ways in which students navigated digital learning activities, referred to as playlists, that were comprised of resources, pre-assessments, and…

The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new…

Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

Recognizing that children's learning outcomes generally remain low, in its recent 2017--2021 Education and Skills Sector Plan (ESSP) the Government of Zambia prioritized improving learning outcomes through strategies that addressed gaps in education system quality, access, equity and efficiency. What resources and contextual factors are associated…