Automated Educative Nudges to Reduce Missed Assignments in College

Abstract

As institutions of higher education increasingly utilize online learning management systems, college students are asked to submit more assignments online. Under this regime, when most assignments are posted and submitted online, it is possible to know if a student is missing a submission for an imminent deadline, and to intervene proactively to reduce missed assignments and improve student outcomes. Toward this goal, we designed and evaluated a scalable targeted intervention: a mobile app that would deploy push notifications when students were missing submissions for assignments with imminent deadlines. Results from two experimental pilots demonstrate that this intervention system significantly decreased missed assignments compared with control notifications about instructor announcements to the class (in Experiment 1), and improved assignment adherence and course grades compared with courses that were not using the app (in Experiment 2). We discuss the benefits and theoretical implications of this behavioral guide rail, a purely informative proactive intervention to mitigate risk in advance of a negative outcome.

Nudging Learning Behaviour: A Systematic Review

“…Of which, ten studies were selected in this review after the screening. The ten studies covered diverse areas ( setting and problem ) that included evaluating the effects of self‐directed scheduling (Baker et al, 2016), improving cooperative learning (Buchs et al, 2016), enhancing learning experiences and outcomes (Dart & Spratt, 2020), reducing procrastination in a competitive learning environment (Li et al, 2021), informing on imminent submission deadlines (Motz et al, 2021), persuading students to improve their study consistency (O'Connell & Lang, 2018), evaluating the impact on procrastination (Onji & Kikuchi, 2011), improving the enrolment rate of tutoring services (Pugatch & Wilson, 2018), evaluating the impact of learning outcome (Sinha et al, 2021), and improving task performance (Smith et al, 2018). These ten included studies were published between 2011 to 2021 across six different countries.…”

“…Five studies fulfilled all the MMAT criteria (Dart & Spratt, 2020; Li et al, 2021; O'Connell & Lang, 2018; Pugatch & Wilson, 2018; Smith et al, 2018). Another four were unable to fulfil the randomisation criteria (MMAT 2.1) in the quantitative RCT category as the studies did not specify how the randomisation schedule were generated (Baker et al, 2016; Buchs et al, 2016; Motz et al, 2021; Sinha et al, 2021), and one did not account for the confounders (MMAT 3.4) in the quantitative non‐randomised category (Onji & Kikuchi, 2011).…”

The Influence of Automated Praise on Behavior and Performance

“…Throughout the Spring 2019 semester, regardless of condition assignment for the current study, all app users received notifications about imminent deadlines, recent instructor announcements, and upcoming calendar events according to their preferences within the app (for additional details, see Motz, Mallon, and Quick, 2020).…”

Wearable technology for automatizing science-based study strategies: Reinforcing learning through intermittent smartwatch prompting.

“…Still, it is likely advantageous to learning to have the wearer attempt to self-generate an answer rather than to recognize it from among a set of options (Rowland, 2014), and nothing precludes mentally generating longer answers on the part of the wearer. Moreover, Heitmayer and Lahlou (2021) recently showed that only 11% of smartphone interactions are notification-initiated, pointing toward another potential advantage of smartwatches over smartphones for uses requiring frequent notifications, including other forms of education-related nudges (e.g., Motz, Canning, Green, Quick, & Mallon, 2020a; Motz, Mallon, & Quick, 2020b). Therefore, future research should compare smartwatch to smartphone delivery formats.…”