Greetings we are Laura Pryor and Nichole Stewart, graduate students and recent alumnae of AEA’s Graduate Education Diversity Initiative (GEDI) program (2011-2012 cohort). Laura is an incoming doctoral student at UC Berkeley’s Graduate School of Education and Nichole is a fifth year doctoral student in University of Maryland Baltimore County’s Public Policy department with a specialization in evaluation and analytical methods.
Over the course of our respective internships we discovered that 1) we both love data(!!) and 2) new evaluators are increasingly expected to understand data and take on the role of data scientists.
Data science encompasses both quantitative and qualitative competencies and is applicable to any evaluation project. Like data scientists, evaluators are often active in the design and implementation of four related areas: data collection, management, analysis, and visualization. But how do new evaluators build their “toolbox” of skills and improve their practice while still in school and early in their careers?
- EXPLORE – New evaluators, regardless of methodological emphasis, should invest time in learning ‘about data.’ Acquiring this knowledge and becoming proficient with statistics, research design, and other data tools often take many years of experience. We’ve found that taking the time to learn about ‘what data is,’ the many contexts in which it is used, and the data skills involved with evaluation all helps improve the initial learning curve towards data proficiency.
- PRACTICE – Graduate students and new evaluators should also be active in local or online groups and communities. Volunteer to take on a small data project for a professor or find a public data source and conduct your own analysis.
- Check out Jeffery Stanton’s introduction to data science and learning the basics of the open source R in a free e-book: http://jsresearch.net/wiki/projects/teachdatascience
- Purchase ArcGIS for Home Use for $100 and/or sign up for a free ArcGIS Online account to begin making maps
- Select elective graduate courses introducing data science that expands your knowledge base beyond what your curriculum requires.
- Visit Coursera and find free classes on Data Science, Data Analysis or Statistics
- Search YouTube for free software training videos or subscribe to Lynda.com for a $25/month fee
- Download free, trial or student versions of Tableau or Adobe Creative Cloud
- Find a hackathon in your area like Hack for Change Baltimore and attend as a content/subject matter expert to help build an application
- Check out Data Kind and get involved with this community of data scientists working with social organizations
- Go to Meetup and join a group like Data Science MD to attend events with other data scientists
- Pick up programming languages at Code Academy
- Find professionals with similar interests in a LinkedIn group
AEA is celebrating GSNE Week with our colleagues in the Graduate Student and New Evaluators AEA Topical Interest Group. The contributions all this week to aea365 come from our GSNE TIG members. Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to email@example.com. aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.