Assessing Notification Timing Strategies for Improved Micro-Learning Engagement

Micro-learning has been widely adopted in recent years as an approach to improve online learning, particularly on mobile applications. Micro-learning is a method of dividing learning content into smaller lessons that can be completed within a short period (e.g., from ten to 15 minutes). While micro-...

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Published inIEEE access Vol. 13; pp. 64534 - 64545
Main Authors Nguyen Tran, H. T., Jou She, Wan, Kajimura, Shogo, Shibuya, Yu
Format Journal Article
LanguageEnglish
Published IEEE 2025
Subjects
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ISSN2169-3536
2169-3536
DOI10.1109/ACCESS.2025.3559521

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Abstract Micro-learning has been widely adopted in recent years as an approach to improve online learning, particularly on mobile applications. Micro-learning is a method of dividing learning content into smaller lessons that can be completed within a short period (e.g., from ten to 15 minutes). While micro-learning is often seen as a way to boost user engagement, strategies to optimize engagement within these applications remain underexplored. This study aims to examine the impact of notification delay times to enhance user engagement in language learning activities within micro-learning platforms. Specifically, we developed a notification system designed to encourage users to transition from social media usage to educational activities: in this case, the Duolingo application. Over a three-week period, we conducted a within-subject experiment with 10 different users, with each week dedicated to one of three notification delay times - the period of time our proposed system waits before sending a notification once a social media usage activity is recognized: immediate (0 minutes), 15 minutes, and 30 minutes. Our findings reveal that notifications sent after a delay of 15 and 30 minutes - significantly increase both the response rate and the duration of learning sessions compared to immediate notifications. This suggests that a strategic delay in sending study reminders can substantially enhance engagement and prolong the duration of learning, offering valuable insights into designing educational technologies that foster sustained learning habits.
AbstractList Micro-learning has been widely adopted in recent years as an approach to improve online learning, particularly on mobile applications. Micro-learning is a method of dividing learning content into smaller lessons that can be completed within a short period (e.g., from ten to 15 minutes). While micro-learning is often seen as a way to boost user engagement, strategies to optimize engagement within these applications remain underexplored. This study aims to examine the impact of notification delay times to enhance user engagement in language learning activities within micro-learning platforms. Specifically, we developed a notification system designed to encourage users to transition from social media usage to educational activities: in this case, the Duolingo application. Over a three-week period, we conducted a within-subject experiment with 10 different users, with each week dedicated to one of three notification delay times - the period of time our proposed system waits before sending a notification once a social media usage activity is recognized: immediate (0 minutes), 15 minutes, and 30 minutes. Our findings reveal that notifications sent after a delay of 15 and 30 minutes - significantly increase both the response rate and the duration of learning sessions compared to immediate notifications. This suggests that a strategic delay in sending study reminders can substantially enhance engagement and prolong the duration of learning, offering valuable insights into designing educational technologies that foster sustained learning habits.
Author Jou She, Wan
Shibuya, Yu
Kajimura, Shogo
Nguyen Tran, H. T.
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SubjectTerms Delays
Education
Employment
Fatigue
foreign language learning
micro-learning
Mobile applications
mobile notifications
Schedules
Social networking (online)
Surveys
Training
Usability
Videos
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Title Assessing Notification Timing Strategies for Improved Micro-Learning Engagement
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