Practical Answers from ATI Psychometricians: An Outcomes Update

Practical Answers from ATI Psychometricians: An Outcomes Update

ATI’s researchers have been using data from our national database to investigate practical questions with answers that will be helpful to programs implementing ATI’s suite of solutions. We’ll be talking about:

  • The impact of SmartPrep use on TEAS scores
  • How educators can incorporate scores from multiple TEAS attempts into the decision-making process
  • How scores from Content Mastery Series assessments can provide early information about students’ progress toward NCLEX readiness
  • The impact of a consistent policy for ATI product implementation.
    Plus, we’ll share many other recent research findings!

Michelle Dunham

Michelle Dunham, PhD, is the Senior Research Scientist at Assessment Technologies Institute. As a specialist in educational research and measurement, Dr. Dunham has more than 12 years’ experience publishing and presenting in the fields of nursing education and K-12 education. Dr. Dunham has played a key role in the development of assessments, tutorials, and predictive models that have improved hundreds of thousands of nursing students’ academic and professional careers. Dr. Dunham has written and presented multiple nursing student education research studies and has directly consulted on research design, data analysis, and interpretation of findings for more than 150 faculty or graduate nursing students using ATI data in their research.

Xin Lucy Liu

Xin Lucy Liu, PhD, is a seasoned psychometrician, statistician, and researcher in nursing education assessment. She is the author of numerous peer-reviewed publications and presentations on issues related to nursing assessment. During her decade-long career in an operational and research position, Dr. Liu has provided psychometric and statistical consultation on research design and analysis scope to internal and external clients, many of whom are university and college professors. Her amiable teamwork approach and insightful statistical skills have made her a highly sought partner on research studies and publications, some of which have been submitted to and published in leading journals such as “Journal of Nursing Education” and “Nurse Educator.” She has more than 10 years of hands-on experiences in cutting-edge statistical analysis, modeling, and data manipulation.

Tony Juve

Tony Juve, PhD, earned his doctorate in educational psychology with an emphasis on measurement, assessment, and statistics from the University of Missouri-Columbia. He joined the ATI Psychometrics team in 2008 and currently conducts research to support the technical integrity of Ascend Learning assessment products. Dr. Juve also teaches statistics in the graduate program at Mid-America Nazarene University. In his free time, he enjoys painting and fly fishing. His published work includes: “Use of the ATI Testing Policy and Its Impact on Nursing Program Outcomes,” “ATI’s Product Use Case Study: Using Educational Nursing Products to Achieve Strong Outcomes,” “Learning Strategies: Your Guide to Classroom and Test-Taking Success,” “Testing and Assessment.” He also has contributed to “21st Century Psychology: A Reference Handbook” “Test Construction,” Handbook of the Teaching of Psychology,” and “An Introduction to Statistics and Research Methods: Becoming a Psychological Detective.

Jennifer Brussow

Jennifer Brussow, PhD, received her doctorate in Research, Evaluation, Measurement, and Statistics from the University of Kansas in 2018. In her current position as a Psychometrician at Ascend Learning, she uses a variety of statistical procedures to conduct research to assemble construct and criterion validity evidence for certification and licensure assessments. She also develops predictive models around student success, leads psychometric discussions during product development, and develops score reports and reporting guidelines. In her years of experience in the field of assessment, she has also worked as a psychometrician for examinations for students with significant disabilities and led evaluations of educational interventions. Her research projects include investigating factor structure, differential item functioning, and scores’ relationship to external variables, and she has published peer-reviewed articles, research briefs, and whitepapers.