Nisreen Daoud

Dr. Nisreen Daoud serves as Associate Professor in the Department of Education at Capital University, where she teaches curriculum, instruction, and literacy courses while directing the Capital City Teacher Residency (CCTR) program. Her background includes five years of elementary teaching in socioeconomically diverse Northern Virginia classrooms, working with special education students and English language learners.

Her educational qualifications feature:

• Ph.D. in Education and Human Development (Literacy and Reading/Teaching and Teacher Education) from George Mason University
• M.Ed. in Curriculum and Instruction with Elementary Education concentration from George Mason University
• B.S. in Psychology

Dr. Daoud's research investigates teacher education through school-university partnerships, with emphasis on culturally responsive adolescent literacy instruction and clinical experience design. She examines how mentorship structures impact early-career teacher development and explores project-based approaches to integrating citizenship education within literacy frameworks.

Her 2015-2020 publications reveal consistent focus on adapting teacher preparation to contemporary challenges, including pandemic-era instructional design and power dynamics in clinical settings. Key thematic threads include validating reading motivation instruments, extending doctoral training through Professional Development Schools, and implementing youth-centered project-based learning.

As CCTR director, she oversees clinical supervision protocols and develops career advancement resources for novice educators. Her mentorship framework incorporates structured classroom observations and tailored professional development pathways for teachers navigating their initial years in diverse educational environments.

She leads the Capital City Teacher Residency program—a strategic partnership between Capital University and local schools—focusing on intensive clinical preparation and retention strategies for new teachers through embedded residency models.