Disrupted Focus: Observing Multi-Device Interference in a University Library Setting

In-Person

Abstract

As digital platforms, open educational resources, and AI-supported tools increasingly shape higher education, students are learning in environments characterised by constant access to multiple devices. While these technologies expand flexibility and access, they may also contribute to fragmented attention and interruptions during independent learning activities. This presentation examines how students navigate multi-device learning environments within a university library. Using non-intrusive naturalistic observation over a four-hour period, 27 students engaged in independent academic work were observed in a university library. All participants used library desktop computers while simultaneously interacting with personal devices. Of the observed students, 17 used a phone alongside the desktop computer, 2 used both a laptop and phone, 1 used two phones and a tablet, and several students frequently alternated between devices throughout their learning activities. Observations revealed repeated device-switching behaviors, dual-screen engagement, prolonged pauses between academic actions, and interruptions in task continuity. Rather than viewing digital devices solely as learning supports, this study highlights the complex tensions between accessibility, openness, and attentional fragmentation in contemporary learning spaces. The findings raise important questions about how educators, instructional designers, and institutions can create distraction-aware learning environments that support sustained engagement without limiting access to digital resources.

The presentation concludes by discussing practical implications for the design of open and technology-rich learning environments, including adaptive interfaces, micro-modular learning structures, and embedded attention-support strategies that may help reduce cognitive overload during independent learning

Presenters

Stephen Ameko

Graduate Student

Stephen Kwame Ameko is a PhD student in the Department of Instructional Technology and Learning Sciences at Utah State University. His research explores the intersection of educational technology, digital learning environments, and student engagement, with a particular focus on digital distraction, multi-device learning behaviours, and technology-mediated learning experiences in higher education. His work examines how instructional design and emerging technologies, including artificial intelligence, influence attention, independent learning, and classroom engagement. Stephen’s broader academic interests include educational policies, instructional design, learning sciences, educational technology, and the development of distraction-aware learning environments that support meaningful and sustained student learning.