Predicting restriction of life-space mobility: a machine learning analysis of the IMIAS study.

Background: Some studies have employed machine learning (ML) methods for mobility prediction modeling in older adults. ML methods could be a helpful tool for life-space mobility (LSM) data analysis.

Aim: This study aimed to evaluate the predictive value of ML algorithms for the restriction of life-space mobility (LSM) among elderly people and to identify the most important risk factors for that prediction model.

Unveiling educational patterns at a regional level in Colombia: data from elementary and public high school institutions.

Even though the field of Learning Analytics (LA) has experienced an expressive growth in the last few years. The vast majority of the works found in literature are usually focusing on experimentation of techniques and methods over datasets restricted to a given discipline, course, or institution and are still few works manipulating region and countrywide datasets. This may be since the implementation of LA in national or regional scope and using data from governments and institutions poses many challenges that may threaten the success of such initiatives, including the same availability of data.