Learning analytics (LA) adoption is a challenging task for higher education institutions (HEIs) since it involves different aspects of the academic environment, such as information technology infrastructure, human resource management, ethics, and pedagogical issues. Therefore, it is necessary to provide institutions with supporting instruments to…

This single-site case study will seek to answer the following question: how is the concept of privacy addressed in relation to a student success information system within a small, public institution of higher education? Three themes were found within the inductive coding process, which used interviews, documentation, and videos as data resources.…

This paper explores the integration of generative AI (GenAI) in the feedback process in higher education through a learning analytics (LA) tool, examined from a feedback literacy perspective. Feedback literacy refers to students' ability to understand, evaluate, and apply feedback effectively to improve their learning, which is crucial for…

Inadequate consideration of course workload in undergraduate students' course selections has contributed to adverse academic outcomes. At the same time, credit hours, the default institutional metric to convey time-based course workload to students, has been shown to capture students' experienced workload insufficiently. Recent research documents…

In this paper, we explore the design of a student-facing dashboard for online and distance learning with a focus on capturing and addressing specific learning needs. A participatory process involving 20 students was employed, which included a screening questionnaire and focus group discussions. The selection of data points to be displayed on the…

Complex thinking competency enhances the high cognitive capacities necessary for the future of education. This study aimed to analyze these capacities through its sub-competencies (critical, systemic, and scientific thinking). We worked with the Cross Industry Standard Process for Data Mining methodology, with an original database of class data of…

While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…

Researchers in learning analytics have created indicators with learners' trace data as a proxy for studying learner behaviour in a college course. Student Approaches to Learning (SAL) is one of the theories used to explain these behaviours, distinguishing between deep, surface, and organized study. In Latin America, researchers have demonstrated…

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…

Behavioural engagement as a predictor of academic success hinges on the interplay between effort and time. Exploring the longitudinal development of engagement is vital for understanding adaptations in learning behaviour and informing educational interventions. However, person-oriented longitudinal studies on student engagement are scarce.…

Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major selection using a large language model (LLM), GPT-4. Through a three-phase survey, we compare GPT suggestions and responses for undeclared first- and second-year students…

Learning analytics dashboard (LAD) development has been criticized for being too data-driven and for developers lacking an understanding of the nontechnical aspects of learning analytics (LA). The ability of developers to address their understanding of learners as well as systematic efforts to involve students in the development process are…

There is a growing interest in the research and use of automated feedback dashboards that display classroom analytics; yet little is known about the detailed processes instructors use to make sense of these tools, and to determine the impact on their teaching practices. This research was conducted at a public Midwestern university within the…

Computational thinking (CT) is a critical 21st-century skill that equips undergraduate students to solve problems systematically and think algorithmically. A key component of CT is computational creativity, which enables students to generate novel solutions within programming constraints. Humanoid robots are increasingly explored as promising…

This study investigates the integration of artificial intelligence into the Think-Pair-Share (TPS) methodology through a learning analytics lens. Using a mixed-methods quasi-experimental design (N=140), we examined how an AI-enhanced collaborative platform influences creative thinking among computer science undergraduates. The experimental group…