Associative Recognition Data with Response Signal Procedure and ACT-R Model Fits

An ACT-R model provided an excellent quantitative account of data from response signal experiments on associative recognition. The data, from Carnegie Mellon University, examines how associative fan affects the speed-accuracy tradeoff in memory retrieval. It includes results from experiments with both briefly studied and well-learned materials.

Use Cases

• Modeling speed-accuracy tradeoff functions based on response signal procedure data.
• Investigating the effect of associative fan on memory retrieval accuracy and latency.
• Validating ACT-R model predictions against empirical data on associative recognition.
• Analyzing the time course of memory retrieval for briefly studied versus well-learned materials.

Strengths

• Data is supported by a detailed ACT-R model that provided an excellent quantitative account of the results.
• Experiments investigate a specific cognitive phenomenon (associative fan) using a controlled response signal procedure.
• Includes data from both new experiments and a replication of a previous study, allowing for comparison.

Limitations

• Description metadata is limited; actual data quality, format, and structure require manual inspection after download.
• Row count, column definitions, and sample data are unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Carnegie Mellon University, author Darryl W. Schneider.

Collection Method

Data gathered from response signal procedure experiments on associative recognition.