A persistent challenge for the learning analytics community is how to achieve a meaningful impact on educational practice. This paper proposes that Porter’s Value Chain framework provides a useful lens for addressing this challenge. This study developed operational definitions of a Learning Analytics Value Chain and mapped learning analytics research output (3,720 publications) over the last 16 years to its five stages: 1. Concept Development, 2. Prototyping & Efficacy, 3. Evaluation, 4. Dissemination, and 5. Impact & Iteration.

This study aims to evaluate how immersive content can enhance student engagement, learning outcomes, and satisfaction in an open and distance learning context. The paper gives an overview of the background research and study design that investigates the impact of immersive virtual learning environments on distance education by integrating WebXR with GenAI into Moodle, a widely used virtual learning environment (VLE). The design considers two groups of learners, an experimental group and a control group. The experimental group will engage with WebXR having GenAI agents and the control group will experience the same course content delivered through conventional online teaching methods. Using Learning Analytics (LA) and the DeLone and McLean Information Systems Success Model as an evaluation framework, the research will assess a number of dimensions, including system quality, information quality, service quality, user satisfaction, intention to use, net benefit, engagement, and learning gain. A mixed methods approach will be employed to collect feedback from distance learners through an online survey. This data will be combined with log data from the VLE and WebXR after anonymization. The findings are expected to provide information on the effectiveness of WebXR in enhancing the online learning experience and will offer practical recommendations for integrating Extended Reality (XR) tools into existing LMS platforms to support innovative and engaging education in distance learning contexts.

This paper reports on a study aimed at identifying training requirements for both staff and students in higher education to enable more widespread use of learning analytics. Opinions of staff and students were captured through ten focus groups (37 students; 40 staff) and two surveys (1,390 students; 160 staff). Participants were predominantly from two higher education institutions in Ireland. Analysis of the results informed a framework for continuous professional development in learning analytics focusing on aspects of using data, legal and ethical considerations, policy, and workload. The framework presented here differentiates between the training needs of students, academic staff and professional services staff.

Learning analytics is an interdisciplinary and inclusive field, a fact which makes the establishment of methodological norms both challenging and important. This community-building workshop intends to convene methodology-focused researchers to discuss new and established approaches, comment on the state of current practice, author pedagogical manuscripts, and co-develop guidelines to help move the field forward with quality and rigor.