Left unread: how message orientation shapes engagement in adaptive nudging systems

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Authors: Maxim Boitcov, Капуза Анастасия Васильевна, Hussein Al-Safi, Nikita Vinogradov
Cited by: 0
References: 44

Abstract

Sustaining behavioural engagement remains a persistent challenge in online learning, where participation often declines over time despite widespread use of message-based nudges as a scalable form of support. Existing research has typically examined message content and learner interactivity in isolation, making it difficult to understand how these features jointly relate to behavioural engagement in adaptive systems that tailor messages to learners' prior behaviour. This study examines how reply behaviour is associated with subsequent behavioural engagement in a behaviour-triggered messaging system that differentiates between reinforcing and concern-oriented messages. During a four-week intervention in an online preparatory course, 144 students received supportive messages triggered by recent learning management system activity. All messages invited replies, enabling both one-way and two-way communication. Engagement was measured using the Coefficient of Retention (COR), a longitudinal composite indicator, capturing persistence across homework completion, webinar participation, and platform use. Multilevel regression analyses showed that replying to a message was not uniformly associated with higher engagement once prior engagement and homework performance were accounted for. However, this association differed by message type. Replies to reinforcing messages were marginally associated with higher subsequent engagement, whereas replies to concern-oriented messages were associated with lower engagement relative to non-replies. By contrast, non-response to concern-oriented messages was linked to modest increases in engagement. Overall, the findings suggest that the relationship between interactivity and engagement depends on message orientation within adaptive nudging systems.

Fields of Study & Subjects

Online Learning and Analytics Intelligent Tutoring Systems and Adaptive Learning Online and Blended Learning

Publication details

Journal / source
Interactive Learning Environments
Volume
34
Issue
8
Pages
5435–5448
Publication date
10 February 2026
Language
EN