Graph Out Loud: Pre-Service Teachers' Data Decisions and Interpretations of CBM Progress Graphs

Area of Science:

• Special Education
• Educational Psychology
• Learning Disabilities Research

Background:

• Data-based instruction (DBI) relies on teachers using student progress data for instructional decisions.
• Curriculum-based measurement (CBM) graphs are crucial tools for visualizing progress and guiding these decisions.
• Effective graph interpretation is vital for successful DBI implementation, yet this skill is under-researched in special education teachers.

Purpose of the Study:

• To investigate the graph interpretation and data decision-making skills of pre-service special education teachers.
• To identify factors influencing teachers' decisions to alter instruction based on CBM data.
• To understand potential misunderstandings in interpreting CBM progress graphs.

Main Methods:

• Examined data decisions of 32 U.S. pre-service special education teachers.
• Utilized think-aloud protocols while participants interpreted sequentially presented CBM graph data.
• Assessed decision-making in response to both dynamic (sequential) and static (10-week) CBM graphs.

Main Results:

• Pre-service teachers exhibited significant inconsistency in determining when and why to make instructional changes.
• Instructional decisions were frequently swayed by graph characteristics, such as data variability.
• Observed misunderstandings led to premature instructional adjustments and an over-reliance on isolated data points.

Conclusions:

• Pre-service special education teachers require targeted training in interpreting CBM graphs for effective data-based instruction.
• Inconsistent decision-making highlights a need to address potential misinterpretations of CBM data trends.
• Future research should focus on developing effective pedagogical strategies to enhance teachers' graph interpretation skills.