معرفی
Leonora Kaldaras is an Assistant Professor in the Department of Curriculum & Instruction at Texas Tech University College of Education. Her research focuses on equitable personalized learning, AI-driven assessment systems, and cognitive development in STEM education. She holds a dual Ph.D. in Curriculum, Instruction and Teacher Education and Measurement and Quantitative Methods from Michigan State University (2020) and has worked with Nobel laureate Carl Wieman on AI-guided feedback tools.
- Education:
- Dual Ph.D. (2020), Michigan State University
- Science Education Certificate, BGSU
- B.S. in Chemistry (2009), BGSU
Research Interests: Personalizing learning through technology, equity in blended/personalized learning, and fostering knowledge transfer via self-guided strategies. She specializes in NGSS-aligned assessments and AI-enhanced feedback systems for STEM education.
Article Trends: Her recent work (2023-2025) emphasizes AI-driven assessment design, NGSS-aligned learning progressions, and cognitive frameworks for math-science integration. Earlier publications (2012-2016) focus on biophysics but transitioned to education post-2020.
Scientific Awards:
- New and Noteworthy Invited Symposium by American Chemical Society
- Top Downloaded Article (JRST, 2019)
- Top Cited Article (JRST, 2021-2022)
Grants: NSF DrK-12 Co-PI (2022-2026) for AI feedback systems in NGSS classrooms.
Labs & Collaborations: Formerly at Stanford University Graduate School of Education and University of Colorado Boulder PhET Interactive Simulations Project, working closely with Nobel laureate Dr. Carl Wieman.
