Mapping Students’ Digital Eco-system Usage Patterns Using Kernel-Based Principal Component Analysis to Inform Course Design

In today’s technology-driven world, educators need to understand how students use Information and Communication Technologies (ICT) for educational purposes if they wish to effectively design curricula. Today, students seamlessly navigate various devices, creating complex, nontraditional learning environments from a young age. This means educators must recognize the positive affordances of technology while being cautious of negative aspects. Personalized learning opportunities can be developed by understanding students’ digital learning environments or digital eco-systems through learning analytics. This research aims to map students’ digital eco-system usage patterns to inform course design that aligns with student learning expectations as they relate to learning technology. To contextualize technologies and learning environments, a clear understanding of learners’ technological adoption and use in specific learning contexts is necessary. Artificial Intelligence techniques can be employed to better understand participants’ technological adoption and use in collaborative educational activities. In this study, participant activity was captured in log data, and Kernel-Based Principal Component Analysis (KPCA) was applied over one academic year. Key findings include a consistent decrease in online activity throughout the academic year and students favoring mobile and non-mobile devices at different times during activities, suggesting they selectively utilize different affordances based on context and purpose. If this is the case, it would be an insight into how they are shifting between device types depending on the context and purpose. These findings provide a clearer understanding of how the students behave within a digital eco-system of interconnected devices that function to support their learning. The results and implications for education were discussed, along with suggestions for future research.