Qiyun Wang
M.A. in Special and Inclusive Education (Specific Learning Difficulties), University College London, 2024
M.Ed. in Subject Teaching (Chinese Language and Literature), East China Normal University, 2021
B.A. in Special Education, East China Normal University, 2017
Email: qw3633@my.utexas.edu
Office: SZB
M.Ed. in Subject Teaching (Chinese Language and Literature), East China Normal University, 2021
B.A. in Special Education, East China Normal University, 2017
Email: qw3633@my.utexas.edu
Office: SZB
I am a PhD student in Special Education at The University of Texas at Austin, specializing in learning disabilities and behavioral disorders. My research focuses on a question that cuts across much of my work: how does the environment shape what we understand as learning difficulty?
I am interested in learning difficulty not simply as a stable characteristic of an individual learner, but as something that can emerge, intensify, or change through interactions among learners, instruction, technology, and broader educational structures. This leads me to ask a broader question: when we change the environment, can we also change the difficulty itself?
I approach this question across different levels of the educational system. My current work includes a systematic review and meta analysis of Lexia reading programs, research on school segregation and structural inequalities in early reading achievement, and experimental work examining how generative AI can provide adaptive reading support for students with learning disabilities.
Across these projects, I am especially interested in the connections among intervention, measurement, and context. I study how learning difficulties are identified, how instructional and institutional environments can amplify or reduce them, and how emerging technologies might reshape the conditions under which learners struggle or succeed.
Ultimately, my research aims to build a more contextual and dynamic understanding of learning disabilities, one that connects intervention science with measurement, technology, and educational inequality.
I am interested in learning difficulty not simply as a stable characteristic of an individual learner, but as something that can emerge, intensify, or change through interactions among learners, instruction, technology, and broader educational structures. This leads me to ask a broader question: when we change the environment, can we also change the difficulty itself?
I approach this question across different levels of the educational system. My current work includes a systematic review and meta analysis of Lexia reading programs, research on school segregation and structural inequalities in early reading achievement, and experimental work examining how generative AI can provide adaptive reading support for students with learning disabilities.
Across these projects, I am especially interested in the connections among intervention, measurement, and context. I study how learning difficulties are identified, how instructional and institutional environments can amplify or reduce them, and how emerging technologies might reshape the conditions under which learners struggle or succeed.
Ultimately, my research aims to build a more contextual and dynamic understanding of learning disabilities, one that connects intervention science with measurement, technology, and educational inequality.
