Rearchitecting Data for Researchers: A Collaborative Model for Enabling Institutional Learning Analytics in Higher Education

Main Article Content

Steven Lonn
Benjamin Koester

Abstract

This article presents the case of the Learning Analytics Architecture (LARC) dataset, a collaborative effort at the University of Michigan to develop a common and extensible tool using administrative data and designed primarily for learning analytics researchers to investigate enrolled students’ academic careers, demographics, and related teaching and learning outcomes. The institutional context prior to the creation of the dataset and the rationale, design, development, and maintenance involved in creating LARC are all detailed. Also discussed are the procedures for access, documentation, and ensuring the continued usability and relevance of the dataset for a growing learning analytics and data science research community. The authors conclude the case description with recommendations for institutions seeking to replicate this effort.

Article Details

How to Cite
Lonn, S., & Koester, B. (2019). Rearchitecting Data for Researchers: A Collaborative Model for Enabling Institutional Learning Analytics in Higher Education. Journal of Learning Analytics, 6(2), 107–119. https://doi.org/10.18608/jla.2019.62.8
Section
Data and Tool Reports

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