1. Data Preparation

• Cleaned and standardized dataset entries (e.g., gender labels, duplicate removal, missing values filled using consistency-based methods).

• Grouped and merged categorical variables (e.g., age ranges, education levels) to improve clarity and reduce redundancy.

• Loaded the processed dataset into Tableau for dashboard development.

2. Dashboard Design & Visualization
Designed four interactive Tableau dashboards, each tied to a guiding research question:

• Key Factors Influencing Student Performance – Bar Graphs comparing average exam scores against hours studied, sleep hours, and physical activity.

• Socioeconomic Factors vs. Academic Success – Box & Whisker Plots highlighting performance disparities by family income and parental education.

• Attendance Frequency vs. Performance – Scatter Plots revealing correlations between attendance and exam scores.

• Gender-Based Differences in Performance – Tree Maps visualizing proportional contributions of male vs. female students to performance outcomes.

3. Usability Testing & Feedback

• Conducted think-aloud protocol sessions, pre-post evaluations, and semi-structured interviews with two participants (a student and a data analyst).

• Insights gained:

  • Bar graphs and scatter plots were highly effective for trend interpretation.

  • Tree maps were less intuitive for precise comparisons, and box plots posed challenges for non-technical users.

  • Suggested improvements included clearer axis labels, refined color coding, and increased interactivity with tooltips and filters.

• Iterated the dashboards accordingly, simplifying complex visuals and enhancing chart clarity.