Related papers: MakOne: Behavioural Data of University Students' S…
Adaptive intelligent educational systems are gaining popularity, offering personalized learning experiences to students based on their individual needs and styles. One crucial feature of such systems is real-time personalized feedback.…
In a mobile learning environment, students can learn via mobile devices without being limited by time and space. Therefore, it is vital to develop tools to assist students to learn and assess their knowledge in such environments. This paper…
In this paper, automated user verification techniques for smartphones are investigated. A unique non-commercial dataset, the University of Maryland Active Authentication Dataset 02 (UMDAA-02) for multi-modal user authentication research is…
Engagement is an essential indicator of the Quality-of-Learning Experience (QoLE) and plays a major role in developing intelligent educational interfaces. The number of people learning through Massively Open Online Courses (MOOCs) and other…
Mobile learning through wireless enabled laptops (say, within a university campus) can make use of the learning management system that is already available through internet or intranet. Without restrictions within the four walls of computer…
With the rapid emergence of K-12 online learning platforms, a new era of education has been opened up. It is crucial to have a dropout warning framework to preemptively identify K-12 students who are at risk of dropping out of the online…
Among the seventeen Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the Fifth SDG is a call for action to turn Gender Equality into a fundamental human right and an…
Mobile health (mHealth) systems help researchers monitor and care for patients in real-world settings. Studies utilizing mHealth applications use Ecological Momentary Assessment (EMAs), passive sensing, and contextual features to develop…
Understanding food consumption patterns and contexts using mobile sensing is fundamental to build mobile health applications that require minimal user interaction to generate mobile food diaries. Many available mobile food diaries, both…
As higher education increasingly adopts blended learning, understanding students preferences for online interaction platforms becomes critical for effective course delivery and engagement. This study investigates the platforms undergraduate…
Objective: This study aims to identify the social determinants of mental health among undergraduate students in Bangladesh, a developing nation in South Asia. Our goal is to identify the broader social determinants of mental health among…
This paper presents a unique driving dataset collected in Nigeria via mobile phone sensors to support a machine learning model for detecting alcohol-influenced driving behaviours, with the long-term aim of integrating this model into a…
We conduct the most comprehensive study of WLAN traces to date. Measurements collected from four major university campuses are analyzed with the aim of developing fundamental understanding of realistic user behavior in wireless networks.…
We present a novel longitudinal multimodal corpus of physiological and behavioral data collected from direct clinical providers in a hospital workplace. We designed the study to investigate the use of off-the-shelf wearable and…
We introduce Sense{\mu} (pronounced "sense me"), a mobile application that aims at supporting awareness in parent- child relationships through the sensing capabilities of mobile devices. We discuss the relevance of three types of awareness…
Sub-Saharan Africa faces persistently high student-teacher ratios and shortages of qualified teachers, limiting students' access to personalized learning support and formative assessment. To address this challenge, we present Adesua, a…
Emotional and mental well-being are vital components of quality of life, and with the rise of smart devices like smartphones, wearables, and artificial intelligence (AI), new opportunities for monitoring emotions in everyday settings have…
Technologies related to the Internet of Things (IoT) have seen remarkable growth in recent years. This has facilitated, among many other reasons, that monitoring systems have spread in many everyday areas, including both industry and the…
Recent research has demonstrated the capability of behavior signals captured by smartphones and wearables for longitudinal behavior modeling. However, there is a lack of a comprehensive public dataset that serves as an open testbed for fair…
Recent research has demonstrated the capability of physiological signals to infer both user emotional and attention responses. This presents an opportunity for leveraging widely available physiological sensors in smartwatches, to detect…