DIGITAL LIBRARY
ANALYTIC FRAMEWORKS FOR UNDERSTANDING THE STUDENT EXPERIENCE IN FLEXIBLE ONLINE UNDERGRADUATE PROGRAMS
Athabasca University (CANADA)
About this paper:
Appears in: INTED2015 Proceedings
Publication year: 2015
Pages: 1848-1858
ISBN: 978-84-606-5763-7
ISSN: 2340-1079
Conference name: 9th International Technology, Education and Development Conference
Dates: 2-4 March, 2015
Location: Madrid, Spain
Abstract:
Flexible online learning provides educational opportunities for adults who otherwise might not be able to complete an undergraduate degree on a campus-based environment but most public accountability and comparative institutional ranking schemes do not accommodate non-traditional delivery models. In North America the drive for public accountability coupled with demands for readily available consumer information have increased required reporting from public, private, and for-profit institutions. Unfortunately, comparative data sets tend to focus on first-time, full-time, students and thereby exclude a significant number of undergraduate students. Other popular measurement tools focus on campus-based interactions and services and generally disregard the growing number of online students. Initial models for predictive analytics incorporating data from learning management systems also appear to have imbedded assumptions from more traditional delivery models and cohorts.

This study compares the common benchmarks for student engagement, satisfaction, and degree attainment from publicly available data for adult focused higher education institutions. It highlights how approaches to reporting retention and graduation rates vary between and among adult focused institutions. Then a test application of the data definitions from Predictive Analytics Reporting (PAR) Framework (http://www.parframework.org/) will be applied to records from flexible online undergraduate programs. The strengths and limitations of the PAR Framework will be further illustrated by applying its measures to assess the impact of initiatives to improve the clarity of learner pathways and the options for competency based evaluations (including learning portfolio assessments) at an open university. The case study will underscore some of the limitations common data definitions and the subsequent assumptions in the data models applied to non-traditional students. It stresses the need to use both a quantitative and qualitative lens to better understand their experiences.
Keywords:
Flexible learning, benchmarks, adult learners, engagement, analytics.