This paper introduces CoCo, a system designed to support and encourage collaborative learning among colocated students sharing a single mobile device. It provides teachers with the possibility to create digital lessons, configure parameters for collaborative activities such as the number of students and tablets, and monitor students' progress. On…

Emotions are vital to learning success, especially in online learning environments. They make the difference between learning success and failure. Unfortunately, learners' emotional state is still rarely considered in online learning and teaching, although it is an important driver of learning success. This paper reports a work-in-progress…

This work proposes Dynamic Linear Epsilon-Greedy, a novel contextual multi-armed bandit algorithm that can adaptively assign personalized content to users while enabling unbiased statistical analysis. Traditional A/B testing and reinforcement learning approaches have trade-offs between empirical investigation and maximal impact on users. Our…

Learning Analytics (LA) captures the digital footprint of students' online learning activity. This study describes students' navigational behavior in an e-learning setting by processing the LA data obtained from Blackboard LMS. This is an attempt to understand the navigational behavior of students and the relationship with learning performance.…

Randomized A/B tests within online learning platforms enable us to draw unbiased causal estimators. However, precise estimates of treatment effects can be challenging due to minimal participation, resulting in underpowered A/B tests. Recent advancements indicate that leveraging auxiliary information from detailed logs and employing design-based…

Learning analytics includes interventions that will support learning and improve learning environments. Despite the fact that learning analytics is a promising field of study, the lack of empirical evidence on the effects of learning analytics-based interventions has been widely addressed in recent years. In this context, insights validated by…

Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…

A learner model reflects learning patterns and characteristics of a learner. A learner model with learning history and its effectiveness plays a significant role in supporting a learner's understanding of their strengths and weaknesses of their way of learning in order to make proper adjustments for improvement. Nowadays, learners have been…

The purpose of this paper is to present an empirical investigation of the critical determinants for the adoption of learning analytics in higher education. A conceptual model was proposed to understand better the adoption of learning analytics in higher education by teaching staff. Structural equation modelling is used for testing and validating…

Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…

This study explores the potential of using screen time data in learning management systems (LMS) to estimate student learning time (SLT) and validate the credit value of courses. Gathering comprehensive data on actual student learning time is difficult, so this study uses LMS Moodle logs from a computer programming course with 490 students over 16…

Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

Recommender systems in educational contexts have proven effective to identify learning resources that fit the interests and needs of learners. Their usage has been of special interest in online self-learning scenarios to increase student retention and improve the learning experience. In current recommendation techniques, and in particular, in…

Universities increasingly implement online delivery to strengthen students' access and flexibility. However, they often do so with limited understanding of the impact of online pedagogy on student engagement. To explore these issues, a research project was conducted investigating the use of course-specific learning analytics to 'nudge' students…

Open Online Courses can serve different purposes: in the case of Orient@mente at the University of Torino, they aim at facilitating the transition from secondary to tertiary education with automatic evaluation tests that students can try in order to understand their capabilities in - and their attitude towards - certain disciplines, and with…