What does this research mean for the field?

A joint item response theory (IRT) model that integrates bounded continuous responses with response times improves the reliability of ability measurement compared to models that discretize responses or ignore time. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To develop a joint item response theory model that leverages bounded continuous scores and response times simultaneously to improve ability estimation reliability.

September 3, 2026Transactions of the Japanese Society for Artificial IntelligenceOpen Access

Joint Model of a Zero-One Inflated Continuous Item Response Theory Model and a Lognormal Response Time Model for Ability Measurement Using Bounded Continuous Responses and Response Times

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Authors

MUMasaki Uto TGTeruyoshi Goto

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Overview

Statistical modeling reveals improved ability measurement reliability in computer-based testing, indicating that auxiliary response times enhance short tests.

Key Points

To develop a joint item response theory model that leverages bounded continuous scores and response times simultaneously to improve ability estimation reliability.
Integrated a zero-one-inflated beta continuous-response model with a lognormal response-time model through correlated latent traits for ability and speed.
Evaluated model estimation precision and reliability using both simulation experiments and an empirical real-data application.
Demonstrated consistent reliability gains over continuous item response models without timing data and joint response-time models relying on discretized responses.
Yielded the largest reliability improvements when latent traits for ability and response speed were highly correlated.

Cite This Study

Uto et al. (2026) studied this question.

synapsesocial.com/papers/6a9934ea636c6408cfa7c9fd https://doi.org/10.1527/tjsai.41-5_lf26-n

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September 3, 2026Transactions of the Japanese Society for Artificial IntelligenceOpen Access

Joint Model of a Zero-One Inflated Continuous Item Response Theory Model and a Lognormal Response Time Model for Ability Measurement Using Bounded Continuous Responses and Response Times

View Full Paper

Ask AI

Bookmark

Authors

MUMasaki Uto TGTeruyoshi Goto

Discussion

Member takes

Overview

Statistical modeling reveals improved ability measurement reliability in computer-based testing, indicating that auxiliary response times enhance short tests.

Key Points

To develop a joint item response theory model that leverages bounded continuous scores and response times simultaneously to improve ability estimation reliability.
Integrated a zero-one-inflated beta continuous-response model with a lognormal response-time model through correlated latent traits for ability and speed.
Evaluated model estimation precision and reliability using both simulation experiments and an empirical real-data application.
Demonstrated consistent reliability gains over continuous item response models without timing data and joint response-time models relying on discretized responses.
Yielded the largest reliability improvements when latent traits for ability and response speed were highly correlated.

Cite This Study

Uto et al. (2026) studied this question.

synapsesocial.com/papers/6a9934ea636c6408cfa7c9fd https://doi.org/10.1527/tjsai.41-5_lf26-n

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