Generative AI tools (GenAI) are increasingly used for academic tasks, including qualitative data analysis for the Scholarship of Teaching and Learning (SoTL). In our practice as academic developers, we are frequently asked for advice on whether this use for GenAI is reliable, valid, and ethical. Since this is a new field, we have not been able to…

The possibilities of Learning Analytics as a tool for empowering teachers and educators have created a steep interest in how to provide so-called actionable insights. However, the literature offers little in the way of defining or discussing what the term "actionable insight" means. This selective literature review provides a look into…

This paper introduces a learning analytics policy and strategy framework developed by a cross-European research project team -- SHEILA (Supporting Higher Education to Integrate Learning Analytics), based on interviews with 78 senior managers from 51 European higher education institutions across 16 countries. The framework was developed adapting…

Higher education institutions and involved stakeholders can derive multiple benefits from learning analytics by using different data analytics strategies to produce summative, real-time, and predictive insights and recommendations. However, are institutions and academic as well as administrative staff prepared for learning analytics? A learning…

In this article we report on the findings of a project funded by the Australian Office for Learning and Teaching and entitled "Learning Analytics: Assisting Universities with Student Retention." While this project was primarily focused on retention as a potential outcome of learning analytics, its application could be related to the…

Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a model based on temporal relationships of heterogeneous data as the basis for building predictive models. We show how within- and between-semester temporal patterns can provide insight into the…

There is little debate regarding the importance of student feedback for improving the learning process. However, there remain significant workload barriers for instructors that impede their capacity to provide timely and meaningful feedback. The increasing role technology is playing in the education space may provide novel solutions to this…

In this paper, we describe the analysis of multimodal data collected on small collaborative learning groups. In a previous study, we asked pairs (N=84) with no programming experience to program a robot to solve a series of mazes. The quality of the dyad's collaboration was evaluated, and two interventions were implemented to support collaborative…

Knowledge tracing is a fundamental area of educational data modeling that aims at gaining a better understanding of the learning occurring in tutoring systems. Knowledge tracing models fit various parameters on observed student performance and are evaluated through several goodness of fit metrics. Fitted parameter values are of crucial interest in…

Recently, the possibilities for leveraging "big data" in research and pedagogy have given rise to the growing field of "learning analytics" in online education. While much of this work has focused on quantitative metrics, some have called for critical perspectives that interrogate such data as an interplay between technical…

Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…

Research in computer-based learning environments has long recognized the vital role of adaptivity in promoting effective, individualized learning among students. Adaptive scaffolding capabilities are particularly important in open-ended learning environments, which provide students with opportunities for solving authentic and complex problems, and…

This study aims to apply a sequential analysis to explore the effect of learning motivation on online reading behavioral patterns. The study's participants consisted of 160 graduate students who were classified into three group types: low reading duration with low motivation, low reading duration with high motivation, and high reading duration…

In higher education settings more and more learning is facilitated through online learning environments. To support and understand students' learning processes better, learning analytics offers a promising approach. The purpose of this study was to investigate students' expectations toward features of learning analytics systems. In a first…

This study investigates how multimodal user-generated data can be used to reinforce learner reflection, improve teaching practices, and close the learning analytics loop. In particular, the aim of the study is to utilize user gaze and action-based data to examine the role of a mirroring tool (i.e., Exercise View in Eclipse) in orchestrating basic…