Cheating detection in large-scale assessment received considerable attention in the extant
literature. However, none of the previous studies in this line of research investigated the …

Preknowledge cheating jeopardizes the validity of inferences based on test results. Many
methods have been developed to detect preknowledge cheating by jointly analyzing item …

Generative artificial intelligence (AI) technology is expected to have a profound impact on
chemical education. While there are certainly positive uses, some of which are being …

Computer-based learning environments can easily collect student response times. These
can be used for multiple purposes, such as modeling student knowledge and affect, domain …

With the advance of computer-based assessments, many process data, such as response
times (RTs), action sequences, Eye-tracking data, the log data for collaborative problem …

Using eye-tracking, this study examined the role of semantic transparency in L2 learners'
incidental learning of compounds from reading and how real-time processing of novel …

Recent approaches to the detection of cheaters in tests employ detectors from the field of
machine learning. Detectors based on supervised learning algorithms achieve high …

Respondents' problem-solving behaviors comprise behaviors that represent complicated
cognitive processes that are frequently systematically tied to one another. Biometric data …

Multiple group modeling is one of the methods to address the measurement noninvariance
issue. Traditional studies on multiple group modeling have mainly focused on item …

The pervasive issue of cheating in educational tests has emerged as a paramount concern
within the realm of education, prompting scholars to explore diverse methodologies for …