AI-based Assessment: Promises, Progress, and Pitfalls
Artificial Intelligence (AI) assessment applications are becoming ubiquitous in testing and assessment in healthcare, education, and business, but there is still much to learn about how AI can enhance or hamper the assessment process in these contexts. The goal of this intermediate-level program is to provide researchers and practitioners an opportunity to learn more about the advantages and disadvantages of using AI-based assessment from five psychologists representing different fields of psychology. This workshop is co-hosted by Buros Center for Testing and UNL MAP Academy. Continuing education credits are available (2.5 credit hours). See CE Sponsor approvals.
Learning Objectives
At the end of this presentation, participants will be able to:
- Describe at least three advantages and disadvantages of AI-based assessments.
- Apply recommendations and cautions for utilizing AI-based assessment in research or professional practice.
- Identify research that is still needed to support the use of AI-based assessment as an evidence-based practice.
Audience
Professional educators, clinicians/counselors, industrial/organizational psychologists, measurement professionals, researchers, and graduate students
Program Recording
CLICK HERE to access the recording of the webinar.
Questions: Dr. Jessica Jonson
Presenter Panel
Qiwei (Britt) He, PhD
Associate Professor, Interdisciplinary Program of Data Science and Analytics
Georgetown University
Ivan Hernandez, PhD
Assistant Professor, Industrial-Organizational Psychology
Virginia Tech
Matteo Malgaroli, PhD
Assistant Professor, Psychiatry
NYU Grossman School of Medicine