Handbook of Data Mining and Learning Analytics

Data mining is an increasingly valuable tool within the institution of higher education.  Educational Data Mining (EDM) has emerged as a field in its own right, focusing on data mining techniques to advance teaching, learning, and research in higher education. The Handbook of Data Mining in Educational Research addresses the impacts of data mining on education for the mutual benefit of computer science and educational practitioners and researchers.
The book is divided into three parts. Part I defines and discusses the four guiding principles of data mining, and the type and organization of data needed to carry a successful EDM study at both the macro and micro levels. Part II showcases the pedagogical applications of EDM and contains case studies from Business education, Health Sciences education, and Physical Sciences education to highlight the successful and not-so-successful application of data mining research in an educational setting.
Part III focuses exclusively on EDM as a part of advancing educational research. Applications of EDM include the identification of at-risk students, the potential to close socioeconomic gaps in achievement, teacher evaluation, and peer conferencing.