ISEA: A Data Science Training Program to Advance Educational Research and Practice
With the rise of artificial intelligence (AI) in all aspects of society, there has been an increasing talent gap in AI and machine learning, especially in applying these tools in education. Through a collaboration between the UW College of Education, the UW eScience Institute, and faculty from other higher education institutions including the University of Oregon and the University of Maryland, a training program called Innovation Science for Education Analytics (ISEA) will launch in January 2024 thanks to a 3-year grant from the Institute of Education Sciences (IES).
ISEA seeks to advance computational and analytic capacity in K-12 education. The program will recruit a cohort of 15-20 fellows each year with the goal of developing a new pool of talented individuals who have integrated expertise across engineering, statistics, and K-12 education. ISEA is designed as a targeted training program that emphasizes state-of-the-art data analytics informed by education domain knowledge, computational workflows, immediate applications, and career advising.
The program is recruiting education researchers, school district data analysts, and technology industry employees who have some background in statistics. Graduate students, post-doctoral students, early career researchers and assistant professors who are interested in deepening their knowledge of engineering and machine learning, specifically for education data science, are encouraged to apply. District and state data scientists as well as industry professionals who would like to shapen their skills or integrate educational domain knowledge in their work are also encouraged to apply.
To be eligible for the training program, fellows must:
- Be a US citizen or permanent resident
- Have obtained a bachelor’s degree by September 2023
- Have at least some familiarity with statistics and computational software
- Have a strong interest in educational data science
- Maintain a commitment to collaboration and educational equity
We are currently recruiting our first cohort of fellows for the 2023-24 academic year. The first year of the program will run from January 2024 through July 2024 and will require a part-time commitment from fellows (approx. 3-5 hrs/wk remotely between January and May 2024 in addition to required full-time participation in an in-person one-week Hackweek in late June/early July 2024 in Seattle, WA). We will offer limited travel support for fellows who need financial support to attend in-person Hackweek.
The application timeline is as follows:
- August 15, 2023: Application opens
- October 21, 2023: Application closes
- November 6, 2023: Interview notifications
- November 27, 2023: Final application decision notifications
For additional questions, please contact Lovenoor Aulck (laulck@uw.edu) and Min Sun (misun@uw.edu).
People
Core Faculty
Professor in Education, Founder and Co-Director of EPAL
Director of Education and Research at eScience Institute, Research Associate Professor in Engineering
Associate Vice Provost for Academic Data Analytics and Research Associate Professor at the University of Oregon
Data Scientist at the University of Washington Provost’s Office and Affiliate Faculty at the University of Washington Information School
Executive Director of the University of Washington eScience Institute
Instructors
Expert faculty will instruct individual webinar sessions pertaining to their interests and expertise, mentor fellows on their projects, and engage in generative discussions. We identified five leading scholars with deep education data science expertise across a broad range of content domains who have agreed to serve as our instructors.
University of Maryland
University of Washington College of Education
University of Maryland
University of Oregon
Vanderbilt University
Advisory Board
We have recruited renowned scholars in education data analytics and industry leaders in K-12 and EdTech to guide the ISEA training.
Annenberg Institute at Brown University
University of California, Berkeley
Edthena
Google Education
Seattle Public Schools
Data Science Initiative in Microsoft Research