Alina Von Davier
Alina von Davier
Chief of Assessment at Duolingo
Alina A. von Davier is a researcher, innovator, and an executive leader with over 20 years of experience in EdTech and in the assessment industry. She is currently the Chief of Assessment at Duolingo, where she leads the Duolingo English Test research and development area. She is also the Founder and CEO of EdAstra Tech, a service-oriented EdTech company. In 2022, she joined the University of Oxford as an Honorary Research Fellow, and Carnegie Mellon University as a Senior Research Fellow. She currently serves as a Non-executive Director on the Board for MACAT, an EdTech company focused on critical and creative thinking, learning and assessment and she is a Venture Partner for LearnLaunch Fund and Accelerator. Her research is in the field of computational psychometrics, machine learning, and education.
Von Davier was a Chief Officer at ACT, where she led ACTNext, an innovation unit. Previously she was a Senior Research Center Director at Educational Testing Service. Von Davier earned an M.S. in Mathematics from the University of Bucharest in 1990, and a Doctorate in Mathematics from Otto von Guericke University Magdeburg in 2000. She also completed classes in an Executive MBA program from Harvard Business School in 2019.
Von Davier’s work has been widely recognized in the academic community. In 2019, she was a finalist for the Innovator award from the EdTech Digest. In 2020, she received ATP’s Career Award for her contributions to assessment. The American Educational Research Association awarded her the Division D Signification Contribution Educational Measurement and Research Methodology Award for her publications “Computerized Multistage Testing: Theory and Applications” (2014) and an edited volume on test equating, “Statistical Models for Test Equating, Scaling, and Linking” (2011). In 2022 she also received the Brad Hanson award from National Council in Education (NCME) for her work on adaptive testing and for the co-authored book on computer adaptive testing with R.
See von Davier’s GoogleScholar page:
https://scholar.google.com.br/citations?user=Eu9DtEsAAAAJ&hl=en
Plenary Speaker Friday 10:30 AM
Human-Centered AI and Trust Building in Language Learning and Testing Systems
Artificial intelligence (AI) has revolutionized the landscape of language learning and testing in recent years. The rapid development of AI technologies has led to the creation of advanced language learning platforms and assessment tools that can adapt to individual learners' needs, providing personalized tests and feedback. As AI systems become increasingly integrated into educational contexts, it is essential to explore the concept of human-centered AI and the role of trust in these systems. Human-centered AI refers to the design and implementation of AI technologies that prioritize human values, needs, and goals. In the context of language learning and testing, this means creating AI systems that align with pedagogical principles, ethical considerations of educators and learners, and test takers' experience and access. Trust in AI systems is crucial for the widespread adoption of these technologies, as users must feel confident in the reliability, fairness, and accuracy of the AI-driven recommendations and assessments. In this presentation, I will discuss the current state of human-centered AI in language learning and testing, addressing the design principles and ethical considerations that must be taken into account when developing AI-driven tools. I will also discuss the features of human-in-the-loop AI as one approach to support human-centered AI processes and decisions in learning and assessment systems. Furthermore, I will explore the notion of trust in AI systems, examining factors that influence user trust, such as transparency, explainability, and accountability. By emphasizing the importance of human-centered AI and trust in AI systems, we aim to encourage the future development of more effective, inclusive, and ethically sound language learning and testing technologies. I will illustrate these principles with the Duolingo English Test Responsible AI Standards (Burstein, 2023) and their role in supporting both the test development process and its audit.