Preventing Student and Faculty Attrition in Times of Change

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)

Abstract

A good university experience can help motivate and retain students and faculty. Universities place a strong focus on the student population to reduce attrition levels. Models of attrition and their applications are becoming important and useful given the greater amounts of data available to institutions. Yet, these data focus on transactional events rather than the learning journey. In contrast, there seems to be less emphasis on faculty attrition, and data surrounding this phenomenon is lacking. Here, I argue that teaching and data associated with teaching can help promote retention of both students and academics. To capture the effects of teaching (positive or negative) on faculty, we need better data to understand the dynamics behind teaching load and delivery. I provide a model that can help initiate hypothesis testing and data gathering. This model focuses on minimal amounts of data to understand cohorts (student and academic) at different stages of their journey. I provide a framework to produce positive feedback loops that would benefit learners and scholars alike.

Original languageEnglish
Title of host publicationRadical Solutions and Learning Analytics
Subtitle of host publicationPersonalised Learning and Teaching Through Big Data
EditorsDaniel Burgos
Place of PublicationSingapore
PublisherSpringer
Chapter8
Pages115-129
Number of pages15
ISBN (Electronic)9789811545269
ISBN (Print)9789811545252
DOIs
Publication statusPublished - 2020
Externally publishedYes

Publication series

NameLecture Notes in Educational Technology
ISSN (Print)2196-4963
ISSN (Electronic)2196-4971

Keywords

  • Attrition
  • Learning analytics
  • Student data
  • Teacher data
  • University experience

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