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Building Data Science Capabilities into University Data Warehouse to Predict Graduation

EasyChair Preprint 200

11 pagesDate: May 31, 2018

Abstract

The discipline of data science emerged to combine statistical methods with computing. At Aalto University, Finland, we have taken first steps to bring educational data science as a part of daily operations of Management Information Services. This required changes in IT environment: we enhanced data warehouse infrastructure with a data science lab, where we can read predictive model training data from data warehouse database and use the created predictive models in database queries. We then conducted a data science pilot with an objective to predict students’ graduation probability and time-to-degree with student registry data. Further ethical and legal considerations are needed before using predictions in daily operations of the university.

Keyphrases: Business Intelligence, Data Warehouse, GDPR, Graduation, Predictive Analytics, educational data science, institutional analytics, time-to-degree

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:200,
  author    = {Joonas Pesonen and Anna Fomkin and Lauri Jokipii},
  title     = {Building Data Science Capabilities into University Data Warehouse to Predict Graduation},
  doi       = {10.29007/57bl},
  howpublished = {EasyChair Preprint 200},
  year      = {EasyChair, 2018}}
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