Behavioral Observation Accuracy Data for Paper vs. Computer Recording

60 five-minute videos of functional analysis sessions provide the basis for this dataset on observer accuracy. It includes recordings of four behavioral events by 11 observers, along with reference recordings for accuracy computation. The data was created by Javier Virúes‐Ortega of the University of Auckland and published in 2022.

Use Cases

• Compare accuracy rates between paper-and-pencil and computer-aided observation systems based on the described methodology.
• Analyze inter-observer agreement for behavioral events like problem behavior and compliance.
• Train or validate machine learning models for automated behavioral coding using the provided reference recordings.
• Study the reliability of systematic observation techniques over 10-second intervals.

Strengths

• Includes reference recordings for 60 sessions, enabling accuracy computation.
• Data from 11 observers allows for analysis of inter-rater reliability.
• Focuses on four clearly defined behavioral events: problem behavior, compliance, praise, and escape.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.
• Data may reflect temporal and methodological bias inherent to the specific study design.

Provenance

Source

University of Auckland, based on the publication by Virues-Ortega et al. in Behavior Research Methods.

Collection Method

Systematic observation recordings from video sessions of functional analyses.

Time Range

The underlying videos are of sessions based on protocols from 1982/1994; the dataset compilation was published in 2022.

Freshness

Last update date is unknown; freshness unverified.

Geography

Geography is not specified in the provided input.