- Who is a good candidate for the program?
DS4EDU is designed for educational practitioners – individuals who are well positioned to make an impact on science-informed ed-tech. Potential participants could include instructional designers, educational technologists, administrators, policymakers, teaching consultants and assessment specialists, product owners and educational researchers. Candidates should have prior foundational knowledge in statistics and/or learning design and should have proposals for projects that are appropriate for a year-long program and would support educational data science methods for analysis. Participants should hold at least a bachelor’s degree, and currently serve in roles in which the year-long project integrates with and contributes to day-to-day responsibilities
- Must I attend Summer School to participate?
Yes – the in-person Summer School program is a key part of DS4EDU for fellows.
- Is this a funded fellowship?
The program provides support for fellows’ costs related to attending Summer School (food, lodging, some travel). Similarly, it will provide support for participants who return to serve as mentors. However, stipends or other funding are not provided, in accordance with the Methods Training for Education Research program requirements.
- Is statistics expertise required?
Applicants should have prior foundational knowledge in statistics and/or learning design. However, the program is designed to help fill gaps and refresh knowledge in these foundationals.
- Should candidates already be involved in ed-tech?
The program is designed assuming some prior knowledge in learning design or statistics, and will be of most benefit to candidates who are positioned to contribute to edtech policy or products. However, the program is designed to help fill gaps and refresh knowledge in statistics and learning design foundations.
- What are ideal projects?
Projects should be of sufficient complexity to support a 1-year effort and should involve some aspects of educational technology and advanced data analysis (as appropriate for the application of data science methods for education research). We anticipate that projects will be directly relevant to participants’ current professional goals and responsibilities, such that they can emerge from the program with useful artifacts that can make a difference in their field and career. Ideal projects will be positioned to engage in the full design-deploy-data cycle (potentially over multiple iterations); projects that have the potential to “close the loop” are likely to have the greatest impact and see the most benefit from the learning engineering approach.
- What is the time commitment for the program?
Weekly time commitments over the one-year program will vary based on individual’s prior knowledge and on the complexity of the individual project. Fellows are likely to spend 4-6 hours a week during the initial remote learning period. During the 1-week summer school, Fellows should expect to put in full-time effort (the formal program normally runs from 8:00 AM to 5:00 PM, but participants normally spend some evenings working on their projects). During the remaining 9 months, we estimate that fellows will average a few hours per week.
- Do fellows receive a credential?
Fellows will receive a certificate for participating in and completing the DS4EDU program.