Artificial Intelligence (AI), Machine Learning (ML) , and Natural Language Processing (NLP) are rapidly evolving in mainstream society. Do a quick search on any social media platform and you will see hundreds of posts and videos either extolling these new tools or vilifying them. How can the field of institutional research look past the hyperbole and critically evaluate where and when it makes sense for us to adopt these tools? What are the best practices in utilizing them? How does prompt engineering represent a new critical skill for our field? What steps are needed to see a benefit from these approaches while protecting our institutions and our student’s data? How is Machine Learning similar but different to our normal statistical modeling? 

The webinar will provide an overview of how AI, ML, and NLP technologies, such as ChatGPT, Bard, Dall-E, Adobe Firefly, etc., can be leveraged in the field of institutional research and effectiveness. We will first provide a very high-level overview of what is AI, ML, and NLP and then quickly shift to discussing how these technologies can be used to streamline data collection, analysis, and reporting processes, and provide insights that can inform decision-making across various levels of an organization. The webinar will be interactive and provide practical examples of how AI and NLP technologies can be integrated into an institution's research and data analytics workflows. Given its popularity and broad adoption we will spend a greater portion of time on how NLP offers institutional researchers new ways to approach data challenges while placing a premium on the efficiencies delivered via this technology. In this two-part series, attendees will also be asked to experiment with NLP for a job-relevant task that you can apply to your day-to-day operations within the field.