The Legacy Project Plan I developed for the Axtell Agriculture Education Program exemplifies my commitment to using data to inform and improve CTE programs. This artifact demonstrates both data-driven decision making and equity analysis. First, my Legacy Project Plan demonstrates data-driven decision making through structured conversations, observations, and informal needs assessments with my cooperating teacher. We identified a need for civic engagement opportunities within the program and recognized that there was no formal structure for service-learning. I used this data to guide the project plan of a monthly community service newsletter, a volunteer handbook, and school-wide civic engagement events. These initiatives provide equitable access for all students to participate in meaningful service projects, leadership roles, and real-world learning experiences. The Legacy Project Plan also involved equity analysis by ensuring that service-learning activities were designed to be inclusive, accessible, and meaningful for students of all backgrounds. I plan to prioritize student feedback and community input to structure events and resources that cater to diverse interests and needs. By gathering feedback from my cooperating teacher, I can use this data to make ongoing adjustments to maintain relevance and inclusivity. I will incorporate this Legacy Project Plan into my agriculture education program by creating real-world engagement opportunities for all students in a CTE program.

The Evaluation of Instruction (SOAP) for Husker High School Day demonstrates my commitment to using data to inform and improve CTE instruction and programming. This artifact shows my understanding of both data collection & analysis and data-driven decision making. At the end of Husker High School Day, I collected reflective data about student engagement, participation, and learning outcomes across several lessons, including Plant Science, Animal Science, Agribusiness, and PST (Power, Structure, and Technical Systems). First, my SOAP Evaluation demonstrated data collection and analysis through structured observations, formative assessments, and anecdotal notes. I gathered data on instructional effectiveness and student understanding. I noted varying levels of engagement, prior knowledge, and learning challenges among students, which allowed me to make informed judgments about the success of each lesson and identify areas for improvement. In addition, my SOAP Evaluation demonstrates strong Data-Driven decision-making. I used the data to identify specific strategies for improving future instruction, such as the need for better questioning techniques, stronger transitions between activities, and methods to re-engage students when attention falters. By closely analyzing student responses and behaviors, I identified strategies to adjust my instructional practices to better support all learners in future lessons. I plan to incorporate this SOAP Evaluation into my agriculture education program through data-driven approaches to enhance both individual lesson quality and overall program effectiveness.