Designing early warning systems through machine learning (ML) models to identify students
at risk of dropout can improve targeting mechanisms and lead to efficient social policy …

The integration of Multimodal Data (MMD) and embodied learning systems (such as Motion
Based Educational Games, MBEG), can help learning researchers to better understand the …

Dropout rates for students in high education are remarkably high, and the phenomenon has
been investigated in several studies. Student dropout represents a loss of human capital …

В статье представлен научно обоснованный подход к анализу больших объёмов
данных цифровых следов студентов в социальных сетях, который позволяет …

Student dropout is a worldwide problem that affects an entire society; thus, being of great
concern for academic institutions that seek to retain their students through different …

The present work is performed to propose an innovative model called Semi-Parametric
Generalized Linear Mixed effect Model (SPGLMM), able to uncover subpopulations induced …

In this thesis, student data from Aalto University's Computer Science program was used to
generate multiple binary classification machine learning models to predict whether students …

1. Introduction. Many studies deal with hierarchical data, ie data containing observations
naturally nested within groups. Examples of such data are longitudinal data, repeated …

The goal of this dissertation is to study and develop approaches to automating detection of
social signals from speech using extemporaneous talk gathered in naturalistic settings. All …

The goal of this dissertation is to study and develop approaches to automating detection of
social signals from speech using extemporaneous talk gathered in naturalistic settings. All …