Announcing the winners of the 2025 Tools Competition!
Focus Area:
Prize Level:
CHECKPOINT is a tool to generate assessment items that target specific misunderstandings and common errors exhibited by students. For teachers, CHECKPOINT can help identify and select content that is best suited to gauge student learning. For researchers, the tool supports the creation of psychometrically stable pretests and post-tests to evaluate learning interventions.
Anthony Botelho
Assistant Professor
Anthony Botelho
Assistant Professor
Anthony Botelho, Ph.D. is an assistant professor of Educational Technology in the School of Teaching and Learning at the University of Florida. Dr. Botelho is an expert in developing and deploying technology to study student learning across educational contexts. His research combines theory, methodologies, and application across fields including education, cognitive psychology, artificial intelligence, and computer science. Toward this, Dr. Botelho has leveraged quantitative methodologies including learning analytics, machine learning, and natural language processing to study cognitive, behavioral, and affective constructs of learning in online and classroom settings. Dr. Botelho also engages in interdisciplinary collaboration with educators and researchers across disciplines to design, develop, and refine human-in-the-loop systems and methodologies to advance instructional practices and our understanding of how students learn.
Jinnie Shin
Assistant Professor
Jinnie Shin
Assistant Professor
Jinnie Shin, Ph.D., is an Assistant Professor of Research and Evaluation Methodology in the School of Human Development and Organizational Studies in Education within the College of Education at the University of Florida. She has expertise in application of theory-based natural language processing and learning analytics in education research. In her work, she has focused on investigating how to bridge the gap between psychometric analysis and artificial intelligence in education research. Dr. Shin has experience with various international industry projects with the Medical Council of Canada, American College Testing, and the New Zealand Qualifications Authority, which focus on providing effective solutions to complex education problems using deep learning and natural language processing research.
Avery Closser
Assistant Professor
Avery Closser
Assistant Professor
Avery Harrison Closser, Ph.D., is an Assistant Professor in Emerging Technologies and Learning in the School of Teaching and Learning. Her research intersects educational technology, learning sciences, and cognitive psychology in pursuit of leveraging the inherently embodied nature of learning to improve instructional content in educational technologies. She specializes in experimental testing and investigates how details in students’ learning environments shape performance and understanding in mathematics, aiming to improve open-access digital materials and educational tools.
