(1386) LA: Visual Analysis

Introduction

  • Overview of visual analysis activity for upcoming assignment.

  • Acknowledgment of repeated attempts to create the video.

  • Encouragement to reach out via email for clarification.

Addressing Student Anxiety

  • Recognition of students' worries about the assignment due to its novelty.

  • Previous experience involved surface-level data analysis (e.g., simple graphing).

  • Importance of engaging in a critical visual analysis.

Systematic Visual Analysis Process

  • Guide based on Ledford and Gast's Chapter Eight and Barton et al.

  • Steps to follow during the visual analysis:

Step 1: Review Graphs

  • Check equal and appropriate scaling of axes:

    • Ensure y-axis scaling matches the unit of analysis (e.g., percentage of intervals should max at 100).

    • Comparability of scaling across participants' graphs is essential.

  • Examine data series conditions:

    • Understand participant, behavior, or context represented.

    • Provide a summary statement of findings on axis scaling and condition labeling.

  • Adequate replicates and time representation identification is critical.

Step 2: Examine Research Questions

  • Utilize previously graph dataset related to referral concern evaluation.

  • Form a clear research question using independent and dependent variables and participant details.

  • Based on the research question:

    • Predict pattern changes during baseline and post-intervention implementation.

  • Formulating a hypothesis will clarify expected outcomes.

Step 3: Review Data Points

  • Assess number of data points per condition for stability:

    • Minimum of five data points suggested for establishing a functional relationship.

    • Acknowledge circumstances where fewer points may exist due to applied settings.

  • Options when faced with inadequate data:

    • Proceed with visual analysis explaining the rationale or correct data scaling issues.

Step 4: Level, Trend, and Variability Analysis

  • Analyze each condition:

    • Level: Mean data heights for each condition.

    • Trend: Identify increasing, decreasing, or stable patterns.

    • Variability: How data fluctuates within each condition.

  • Aim for stability in behavior post-intervention to confirm effectiveness.

Step 5: Analyze Adjacent Conditions

  • Assess changes between adjacent conditions (A to B, B to A, etc.).

  • Focus on:

    • Magnitude of changes and any immediate impacts post-intervention.

    • Trends in behavior patterns and identify consistency with therapeutic goals.

Step 6: Consistency of Behavior Change

  • Determine consistency across conditions:

    • Evaluate if changes replicate expected patterns during interventions and across baselines.

  • Discuss findings regarding magnitude of change if consistent.

  • If no change, explain why experimental control cannot be established.

Summative Conclusion

  • Conclude with analysis of functional relationships and experimental control quality.

  • Sum up findings for each participant regarding behavior changes linked to interventions.

Data Summation

  • Calculate mean, median, and range for conditions of each participant:

    • Create a table to summarize these data effectively.

    • Each phase to have its distinct mean, median, and range summaries.

Final Thoughts

  • Acknowledge the complexity of the assignment and the importance of practice.

  • Emphasize that experts still practice and debate visual analysis.

  • Offer support and encouragement for questions and concerns, reminding students of available help.