Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which…

With the wide expansion of distributed learning environments the way we learn became more diverse than ever. This poses an opportunity to incorporate different data sources of learning traces that can offer broader insights into learner behavior and the intricacies of the learning process. We argue that combining analytics across different…

This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…

Machine learning has achieved state-of-the-art performance in many areas, including image recognition and natural language processing. However, there are still many challenges and mysteries attracting numerous researchers. This dissertation comprises a series of works concerning problems at the intersection of computer science theory, adversarial…

As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI…

eLearning is fast progressing scientific field proposing novel and specific approaches in a range of domains. It is well established practice in universities, schools and organizations for delivering interactive, adaptive and flexible training, taking advantage of contemporary and emerging technologies. Informatics is a continuously evolving…

One of the main generic competencies in Higher Education is "Learning to Learn". The key component of this competence is the capacity for self-regulated learning (SRL). For this competence to be developed, peer feedback seems useful because it fosters evaluative judgement. Following the principles of peer feedback processes, an online…

Our aim in this paper is to improve the efficiency of a learning process by using learners' traces to detect particular needs. The analysis of the semantic path of a learner or group of learners during the learning process can allow detecting those students who are in needs of help as well as identify the insufficiently mastered concepts. We…

Using data to understand learning and improve education has great promise. However, the promise will not be achieved simply by AI and Machine Learning researchers developing innovative models that more accurately predict labeled data. As AI advances, modeling techniques and the models they produce are getting increasingly complex, often involving…

The goal of learning analytics is to optimize learning and the environments in which it occurs. Since 2011, when learning analytics was defined as a separate and distinct area of academic inquiry, the literature has identified a need for research that presents evidence of effective learning analytics, as well as, learning analytics research that…

This paper reports the findings of a research using marks of students in learning activities of an online module to build a predictive model of performance for the final assessment of the module. The objectives were (1) to compare the performances of students of two cohorts in terms of continuous learning assessment marks and final learning…

This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…

The field of learning analytics (LA) has seen a gradual shift from purely data-driven approaches to more holistic views of improving student learning outcomes through data-informed learning design (LD). Despite the growing potential of LA in higher education (HE), the benefits are not yet convincing to the practitioner, in particular aspects of…

This paper presents the findings of a mixed-methods research that explored the potentials emerging from aligning learning design (LD) and learning analytics (LA) during the design of a predictive analytics solution and from involving the instructors in the design process. The context was a past massive open online course, where the learner data…

For the forty-fourth time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented online and onsite during the annual AECT Convention. Volume 1 contains papers dealing primarily with research and development topics. Papers dealing with…