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Item Response Time Analysis Using Ex-Gaussian Distribution for Disengagement Detection in Online Low-Stakes Tests
(2026-01-01)
Chotikakamthorn, N.
This study addresses the problem of detecting disengagement in online low-stakes tests used in blended learning within higher education. The detection method was developed based on an analysis of item responses and associated response times. The method applied the ex-Gaussian mixture model to response times, rather than the conventional lognormal model. The mixture component with the smallest Gaussian mean was chosen to represent the response times distribution of early correct responses. The selected mixture component was used to obtain the model’s mode, which then served as the threshold for classifying item responses into early and subsequent response groups. Based on the two classified groups, descriptive statistics and graphical visualizations were introduced to support manual inspection and provide insight into item- and person-level characteristics. A test statistic for disengagement detection was formulated based on the distribution of the number of early responses. Drawing on prior knowledge of the success probabilities associated with disengaged responses, two detection boundaries were defined to classify item-preknowledge and rapid-guessing behaviors. Unlike existing model-based methods for rapid guessing and item preknowledge behavior detections, the proposed non-parametric method does not require prior knowledge of item or person parameters, nor does it involve modeling or estimating such characteristics. The method’s performance was assessed using both real and simulated data, and results for true positive rates and false positive rates were reported under various test conditions. The findings indicate that the method’s performance improves with an increasing number of test items and a higher proportion of disengaged responses. Simulation results further demonstrated the method’s robustness to measurement error and small variations in response times, in contrast to the person-level adaptation of the NT10 and CUMP methods, whose performance varied significantly under the same conditions.
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Query decomposition method for multi-keyword search in P2P systems
(2015-01-01)
Chotikakamthorn, N.
;
Jitnupong, T.
A problem of multi-keyword search in a structured peer-to-peer (P2P) distributed computing system is considered. Methods have been developed to employ term-set indexing in a P2P system. Such an approach is an attempt to avoid excessive communication cost incurred by intersection operations in a single-term indexing method. In addition to limiting the maximum term-set size, index pruning was proposed to avoid exponential growth of the term-set index size. However, to obtain a global search result, query decomposition and query result intersection operations are still needed when the number of query terms exceeds the maximum term-set size. With index pruning employed, how a multiterm query is decomposed and affects the quality of retrieval results in terms of recall and precision is shown. A near-optimal query decomposition method is proposed to alleviate such a problem. Results from the simulation demonstrate the improvement gained by the proposed method.
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Alternative formulation of Bayesian-based digital matting technique
(2006-10-09)
Chotikakamthorn, N.
An alternative formulation to the original Bayesian-based digital matting technique is described. With the new formulation, a user does not need to choose an image-dependent noise variance parameter, as in the original method. An iterative algorithm that avoids exhaustive search is provided. Performance comparison with the original method is given. © The Institution of Engineering and Technology 2006.
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Multimodal Synchronization for Human-Machine Interaction in Virtual Environment
(2002-12-01)
Wongwirat, O.
;
Chotikakamthorn, N.
;
Ohara, S.
Human-machine interfacing technologies lead the human to communicate with virtual environment in various effective format and more interactive manner. With the combination of keyboard, mouse, haptic, gesture, speech, and vision modes, the interfaces allow human to be involved with the virtual environment in multimodal form, as if they are embedded as a part of simulation. However, with different mechanism and computing method in multimode interface, they lack of synchronization to support human interaction in the virtual environment. This paper explained human-machine interfacing techniques and proposed multimodal synchronization mechanism to control the tempo and to solve the problems of multimodal interaction. The experimental set to verify human perception with multimode human-machine interface in distributed virtual environment was described at the end. The result gave some figure of how human could adjust their perception to be synchronized with the interactive event in the virtual environment through multimode interface.

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