Microeconometric Approaches in Exploring the Relationships Between Early Alert Systems and Student Retention: A Case Study of a Regionally Based University in Australia

Early alert systems (EAS) are an important technological tool to help manage and improve student retention. Data spanning 16,091 students over 156 weeks was collected from a regionally based university in Australia to explore various microeconometric approaches that establish links between EAS and student retention outcomes. Controlling for numerous confounding variables, significant relationships between the EAS and student retention were identified. Capturing dynamic relationships between the explanatory variables and the hazard of discontinuing provides new insight into understanding student retention factors. We concluded that survival models are the best methods of understanding student retention when temporal data is available.

Toward a typology of weak-signal early alert systems: functional early warning systems in the post-COVID age

PurposeThe study aims to expand on the concept of an early warning system (EWS) by introducing weak-signal detection, human-in-the-loop (HIL) verification and response tuning as integral parts of an EWS's design.Design/methodology/approachThe authors bibliographically highlight the evolution of EWS over the last 30+ years, discuss instances of EWSs in various types of organizations and industries and highlight limitations of current systems.FindingsProposed system to be used in the transforming of weak signals to early warnings and associated weak/strong responses.Originality/valueThe authors contribute to existing literature by presenting (1) novel approaches to dealing with some of the well-known issues associated with contemporary EWS and (2) an event-agnostic heuristic for dealing with weak signals.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2020-0513.

Making good suggestions in analytics-based early alert systems

Purpose The purpose of this paper is to answer the following questions: On which early alert system suggestions are students more likely to act? What factors drive students’ decisions to act on early alert system recommendations? Design/methodology/approach This study examined whether students’ behaviour changed after receiving the results of an early alert system (CDR). In the middle of a semester, 423 students with varying levels of English proficiency were invited to try the CDR and complete a questionnaire that asked about their perception of the tool and whether they planned to act on the recommendations they received. Findings Results suggested that students mainly planned to take the assessment-related recommendations provided through the CDR to improve their assessment performance. Results also suggested that student anxiety and student ability affected the likelihood that students would act on the recommendations. Practical implications These findings provide useful insights for early alert system designers to establish a system that generates useful recommendations for students. Originality/value The findings of this study contribute to the development of early alert systems. Designers can now realise what suggestions can be effectively offered to students.