Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…

Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…

Incorporating non-verbal data streams is essential to understanding the dynamics of interaction within collaborative learning environments in which a variety of verbal and non-verbal modes of communication intersect. However, the complexity of non-verbal data -- especially gathered in the wild from collaborative learning contexts -- demands…

Learning analytics (LA) involves the measurement, collection, analysis, and reporting of data about learners and their contexts, aiming to understand and optimize both the learning process and the environments in which it occurs. Among many themes that the LA community considers, natural language processing (NLP) algorithms have been widely…

Generative AI (GenAI) has the potential to revolutionize the analysis of educational data, significantly impacting learning analytics (LA). This study explores the capability of non-experts, including administrators, instructors, and students, to effectively use GenAI for descriptive LA tasks without requiring specialized knowledge in data…

This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…

Protection of student privacy is critical for scaling up the use of learning analytics (LA) in education. Poorly implemented frameworks for privacy protection may negatively impact LA outcomes and undermine trust in the discipline. To design and implement models and tools for privacy protection, we need to understand privacy itself. To develop…

Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…

The generation, use, and analysis of educational data comes with many promises and opportunities, especially where digital materials allow usage of learning analytics (LA) as a tool in data-based decision-making (DBDM). However, there are questions about the interplay between teachers, students, context, and technology. Therefore, this paper…

This paper describes a partnership-based approach for analyzing data from a learning management system (LMS) used by students in grades 6-12. The goal of the partnership was to create indicators for the ways in which students navigated digital learning activities, referred to as playlists, that were comprised of resources, pre-assessments, and…

Collaboration is a complex, multidimensional process; however, details of how multimodal features intersect and mediate group interactions have not been fully unpacked. Characterizing and analyzing the temporal patterns based on multimodal features is a challenging yet important work to advance our understanding of computer-supported collaborative…

Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…

There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by…

Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…