Associate Professor in Educational Leadership (Research Methodology)

About the role

Texas A&M University – San Antonio seeks a dynamic leader for a full‑time tenure‑track Associate Professor position in Educational Leadership with a focus on research methodology. The role involves teaching graduate and post‑graduate courses, guiding doctoral students, and contributing to the department’s scholarly activities.

Key responsibilities

• Teach graduate and post‑graduate courses in educational leadership and research methods each semester.
• Assist doctoral students in designing and refining statistical analyses and research methodologies for their dissertations.
• Serve on dissertation committees and mentor doctoral candidates.
• Develop, manage, and update course syllabi to meet departmental and college standards.
• Plan and deliver lectures, facilitate class discussions, and create assignments.
• Assess student performance through participation, assignments, examinations, and provide grades.
• Provide additional mentorship and support to students as needed.
• Perform other duties assigned by the department chair.

Required profile

• Earned doctoral degree from an accredited institution in Measurement/Evaluation, Research Methods, Educational Psychology, School Psychology, Organizational Behavior, or a closely related field.
• Demonstrated record of teaching measurement/evaluation courses at the doctoral level with an emphasis on statistical analysis.
• Strong publication record utilizing quantitative methodologies.
• Experience serving on dissertation committees for doctoral candidates employing quantitative methods.
• Preferred: Proven success mentoring doctoral candidates to degree completion.
• Preferred: Publications using Structural Equation Modeling, Hierarchical Linear Modeling, and/or Linear Regression Modeling.
• Preferred: Administrative experience in K‑12 education, including superintendent certification.

Required skills

• Statistical analysis
• Quantitative research methodologies
• Structural Equation Modeling
• Hierarchical Linear Modeling
• Linear Regression Modeling