A DATASET OF HANOI METROPOLITAN UNIVERSITY STUDENTS INCLUDES FACTORS AFFECTING ACADEMIC PERFORMANCE AND LEARNING PROCESS

Abstract

    This article presents the results of a study on the construction of a data base in the field of education sciences concerning the learning activities of natural sciences students at the Faculty of Pedagogy at Hanoi Metropolitan University. The data set not only focuses on information collection, but also high lights factors that affect students' learning processes to guide educational activities, analyze support for decision-making and improve learning effectiveness. Data collection uses two main methods: direct collect of persons through questionnaires and indirect collect through educational management units. After data cleaning and preprocessing, the dataset contains 992 samples and 89 data fields from 10 cohorts (K14 to K23). These data are divided into three main groups: demographic information, factors affecting learning results, and learning results (including general education performance and university module results). This data set, in particular, was processed and cleaned with preliminary statistical analysis tools. We then make some recommendations for universities, faculty and students to improve the quality of education. This is a solid foundation for the study of educational sciences, applying machine learning and deep learning methods to predict learners' academic outcomes.