Year TWO

This is a doctoral-level seminar that will focus on the use of artificial intelligence (Al) technologies, including generative Al (GenAl), in education. The objective of this course is for students to learn about the domain of education as well as how to conduct research.​

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Examines development of self-regulatory and motivational processes as they relate to educational practice. Emphasizes how processes influence students' self-motivation and achievement in various domains.

Emphasizes advanced methods of conducting research using quantitative methods of data collection, and analysis appropriate for research in education. Includes design of experimental and quasiexperimental research studies, and methods of analysis appropriate to these studies, including analyzing variance and multiple linear regression.

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Provides an introduction to systematic cycles of design-based research in education. Explores cycles of research within design, development and implementation of educational and training interventions applicable to all content domains.

This independent study will examine how instructional designers at George Mason University meet the needs of neurodivergent students, including those with ADHD and autism, in their instructional designs. This stems from an urgent need for more evidence-based and inclusive instructional practices that support cognitive diversity, alongside the emerging opportunities and challenges presented by artificial intelligence (Al) in this field.

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This independent study will focus on neurodivergence-centered planning supports in graduate learning contexts. Provides an introduction to systematic cycles of design-based research in education. Explores cycles of research within design, development and implementation of educational and training interventions applicable to all content domains.