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A multi-strategy cognitive diagnosis model based on response times and fixation counts
Junhuan Wei1, Chun Wang2, Yan Cai3,4
1School of Psychology, Jiangxi Normal University, Nanchang, China.
Behavior Research Methods
|February 27, 2026
Summary
This study introduces a new cognitive diagnosis model that combines response times (RTs) and eye movement fixation counts (FCs) to better understand problem-solving strategies. The model enhances diagnostic accuracy and strategy classification compared to traditional methods.
Area of Science:
- Cognitive Psychology
- Educational Measurement
- Psychometrics
Background:
- Individuals use multiple cognitive strategies for problem-solving, not just one.
- Response times (RTs) and eye movement fixation counts (FCs) are key process data for understanding cognitive effort.
- Analyzing RTs and FCs can reveal hidden problem-solving strategies.
Purpose of the Study:
- To develop a unified cognitive diagnosis model integrating RTs and FCs for strategy selection (MS-CDM-RTFC).
- To improve diagnostic accuracy and gain deeper insights into cognitive processes during strategy selection.
- To evaluate the practical applicability of the MS-CDM-RTFC model.
Main Methods:
- Developed the multi-strategy cognitive diagnosis modeling framework (MS-CDM-RTFC).
- Integrated individual response times (RTs) and eye movement fixation counts (FCs) into the model.
- Evaluated the model using data from Raven's Advanced Progressive Matrices (APM).
Main Results:
- The MS-CDM-RTFC model demonstrated higher parameter recovery.
- Attribute classification accuracy was significantly improved with the new model.
- The MS-CDM-RTFC model outperformed traditional multi-strategy models in simulations.
Conclusions:
- The MS-CDM-RTFC framework offers a more accurate method for diagnosing cognitive strategies.
- Integrating process data like RTs and FCs enhances understanding of cognitive processes.
- This approach provides superior performance over existing multi-strategy cognitive diagnosis models.
