The Effect of Item Preknowledge on Response Time: Analysis of Two Datasets Using the Multiple‐Group Lognormal Response Time Model with a Gating Mechanism

2021 ◽  
Author(s):  
Cengiz Zopluoglu ◽  
Murat Kasli ◽  
Sarah L. Toton
Keyword(s):  
Response Time ◽  
Response Time Analysis ◽  
Time Analysis ◽  
Time Model ◽  
Multiple Group ◽  
Response Time Model ◽  
Gating Mechanism ◽  
Item Preknowledge

scholarly journals The Effect of Item Preknowledge on Response Time: Analysis of an Experimental Dataset Using the Multiple-Group Lognormal Response Time Model with a Gating Mechanism

2020 ◽  
Author(s):  
Cengiz Zopluoglu ◽  
Murat Kasli ◽  
Sarah Linnea Toton
Keyword(s):  
Response Time ◽  
Group Extension ◽  
Implicit Assumption ◽  
Time Model ◽  
Experimental Dataset ◽  
Multiple Group ◽  
Gating Mechanism ◽  
Time Patterns ◽  
Time Information ◽  
Item Preknowledge

Response time information has recently attracted a significant amount of attention in the literature as it may provide meaningful information about item preknowledge. The methods that propose the use of response time information in identifying examinees with potential item preknowledge make an implicit assumption that the examinees with item preknowledge differ in their response time patterns compared to other examinees without item preknowledge. In this study, we analyzed the differences in response time of examinees with potential item preknowledge and examinees without item preknowledge based on a real experimental dataset provided by Toton and Maynes (2019). A multiple-group extension of van der Linden’s Lognormal Response Model with a gating mechanism was used to capture the differences in latent speed for control and experimental groups on disclosed and undisclosed items. The model used in the study and estimated parameters from this experimental dataset may inform future simulation studies in this area of research to simulate realistic datasets with item preknowledge behavior.

scholarly journals A Deterministic Gated Lognormal Response Time Model to Identify Examinees with Item Preknowledge

2020 ◽  
Author(s):  
Murat Kasli ◽  
Cengiz Zopluoglu ◽  
Sarah Linnea Toton
Keyword(s):  
Response Time ◽  
Simulation Study ◽  
Bayesian Framework ◽  
Time Model ◽  
Experimental Dataset ◽  
Meaningful Information ◽  
Response Time Model ◽  
Proposed Model ◽  
Item Preknowledge

Response time (RT) information has recently attracted a significant amount of attention in the literature as it may provide meaningful information about item preknowledge. In this study, a Deterministic Gated Lognormal Response Time (DG-LNRT) model is proposed to identify examinees with potential item preknowledge using RT information. The proposed model is applied to a real experimental dataset provided by Toton and Maynes (2019) in which item preknowledge was manipulated, and its performance is demonstrated. Then, the performance of the DG-LNRT model is investigated through a simulation study. The model is estimated using the Bayesian framework via Stan. The results indicate that the proposed model is viable and has the potential to be useful in detecting cheating by using response time differences between compromised and uncompromised items.

A Response Time Model on the Role of Spectral and Duration Cues in Vowel Perception

2014 ◽  
Author(s):  
Gabriel Tillman ◽  
Don van Ravenzwaaij ◽  
Scott Brown ◽  
Titia Benders
Keyword(s):  
Response Time ◽  
Time Model ◽  
Vowel Perception ◽  
Response Time Model
Sign in / Sign up

Export Citation Format

Share Document