Educational Leadership
Educational Leadership (OAE 015) tests whether you can run a school's instructional, operational, and community systems at the same time, not merely describe them. The exam frames leadership around the Professional Standards for Educational Leaders (PSEL) and Ohio's improvement and evaluation systems, so answers must tie vision to measurable student learning and tie decisions to evidence.
Core rules and concepts
- Vision, mission, values: a vision states the future; a mission states the work. Both must be visible in the school improvement plan and in daily decisions.
- Instructional leadership: protect time for teaching; use walkthroughs and formative data to improve Tier 1 instruction; ensure Ohio's Learning Standards drive curriculum mapping and assessment.
- Data-driven improvement: the Ohio Improvement Process and OLAC tools require identifying a critical need from multiple data sources, focusing on a few goals, monitoring implementation, and then adjusting.
- Human capital: OTES 2.0 evaluation should feed coaching and professional learning; the Resident Educator program supports beginning teachers.
- Resource management: the schedule and budget are instructional decisions, so allocate them to close equity gaps rather than spread them evenly.
- Stakeholder engagement: families and community are partners in decisions, not audiences for announcements.
Worked example
You are a new principal; 8th-grade math proficiency trails the state by 18 points, and walkthrough data show little use of collaborative problem solving. Naming the gap as "low math scores" and buying a program would be a weak first move. Stronger reasoning: verify the need with multiple measures (state test, local benchmark, subgroup data), identify the instructional need, set a measurable goal, then support teachers through PLCs and coaching while monitoring implementation, and revisit the plan using interim data.
Traps
- Equity vs. equality: equal inputs do not close gaps.
- Confusing vision with mission.
- Treating evaluation as compliance rather than growth.
- Assuming correlation in data proves cause.