Design, Sites, and Data Sources
The OTTERS project is focused on learning about the OtterBot interactive chatbot, a tool that aims to serve all students from families with low incomes in Washington state.
Phase 1 of the project will focus primarily on student characteristics, OtterBot engagement data, and College Bound Scholarship data. The team will also use scholarship data (containing information from both FAFSA and Washington Application for State Financial Aid), National Student Clearinghouse Data, and/or data from the Washington State Education Research and Data Center to better understand the outcome levels in this population and to gain initial insights into the extent to which OtterBot engagement may be associated with outcomes, such as financial aid application completion and postsecondary matriculation. The team will make use of a variety of analytic methods, including funnel analysis, sentiment analysis and natural language processing, clustering, sequence analysis, and variable importance analysis. The exact methods used will be adjusted based on data quality and exploratory analyses.
Qualitative data collection will explore insights from the quantitative data. For example, focus groups and surveys aim to understand why people engage or do not engage with OtterBot. Are messages culturally competent? What environmental and behavioral conditions might explain rates of completion at key steps between different groups? What additional supports might be required to equitably serve Washington college-bound students?
