Data Science in Education

Data Science in Education

Introduction

Data science and learning analytics in education are useful, but we have limited information about the effectiveness or recommendations to guide the design of learning opportunities for professionals working in education. At the same time, we know that, in general, well-designed learning opportunities, even those brief in duration, can improve computational skills. Our purpose is to explore the design and effects of data science workshops for educational researchers.


Publications

  • Rosenberg, J. M., & Staudt Willet, K. B. (in press). Balancing privacy and open science in the context of COVID-19: A response to Ifenthaler & Schumacher (2016). Educational Technology Research and Development.

Works-in-progress

  1. The design and effects of data science workshops for educational researchers
  2. Who is an educational data scientist?

Contributions

Conceptualization
Methodology
Software
Validation
Formal analysis
Investigation
Resources
Data curation
Writing - original draft
Writing - review & editing
Visualization
Supervision
Project administration
Funding acquisition

See the Contributor Roles Taxonomy (CRediT) from Elsevier for full definitions of these terms.


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K. Bret Staudt Willet
Ph.D. Candidate

I am a Ph.D. candidate in Educational Psychology & Educational Technology at Michigan State University. I research networked learning in online communities, exploring issues of agency in navigating the learning spaces afforded by social media.

Publications

Privacy and confidentiality are core considerations in education. At the same time, using and sharing data—and, more broadly, open …