Data Analysis Plan
I designed the full data analysis plan which could be used as a template for any district that adopts the course, allowing for modifications to align with their specific needs and initiatives. Key elements of the plan include:
Key metrics to track
Data collection methods
Data preparation and integration
Data analysis framework and methods
Challenges in data interpretation
Actionable insights and continuous improvement strategies
End-to-end data workflow
Reporting and review timeline
Appendix with templates and examples to ensure reliability and validity in data collection (e.g., teacher evaluation rubric, data dictionary)
You can interact with the plan on the embedded content below.
As this instructional design project reaches the evaluation phase, it underscores the strategic blueprint laid out for continuous improvement and learner success. While this plan has not yet been carried out, the proposed evaluation outlines a comprehensive approach that emphasizes user feedback, UX assessments, and quality assurance practices. The aim is to ensure that the course, once implemented, meets the instructional objectives and supports user engagement and learning effectiveness.
The entire ADDIE process—from analysis to this proposed evaluation—illustrates a thorough, user-centered approach designed to anticipate challenges and integrate responsive solutions. The detailed plan for the evaluation stage reflects a commitment to gathering meaningful insights, analyzing outcomes, and applying findings to inform future iterations and enhancements.
Looking ahead, this structured evaluation proposal positions the project for ongoing adaptation and refinement. By fostering a cycle of continuous learning and improvement, the groundwork laid through this ADDIE framework sets the stage for future projects that prioritize innovative, impactful, and learner-focused design. This process reaffirms that effective instructional design is not just about the initial launch but about long-term growth, responsiveness, and a dedication to quality.
In this section, I present a proposed plan for the evaluation stage of the course. This plan outlines how I will assess the effectiveness of the course through data collection and analysis, ensuring that the course meets its intended goals. The evaluation will leverage both qualitative and quantitative feedback to identify areas of success and opportunities for improvement. By incorporating these insights, I can make data-driven adjustments to enhance the course’s impact and ensure it remains relevant and effective over time.
Kirkpatrick’s Four-Level Evaluation Model
Kirkpatrick’s Four-Level Evaluation Model is a widely recognized framework used to assess training effectiveness, broken down into Reaction, Learning, Behavior, and Results. Each level offers valuable insights into how well the training meets its objectives and impacts both educators and their students. Below, I have provided an interactive visualization explaining how this model applies to the course evaluation, with detailed examples of its implementation.
To further demonstrate my evaluation methodology recommendations, I have included a data visualization that outlines how qualitative data will be collected and analyzed. Click on each of the interactive buttons below to learn about data sources for each stage, the reasoning for the data collection, and how the data will be analyzed.