The Lognormal Response Time (LNRT) model measures the speed of test-takers relative to the normative time demands of items on a test. The resulting speed parameters and model residuals are often analyzed for evidence of anomalous test-taking behavior associated with fast and poorly fitting response time patterns. Extending this model, we…

Preventing panel members from attriting is a fundamental challenge for panel surveys. Research has shown that response behavior in earlier waves (response or nonresponse) is a good predictor of panelists' response behavior in upcoming waves. However, response behavior can be described in greater detail by considering the time until the response is…

Preknowledge cheating jeopardizes the validity of inferences based on test results. Many methods have been developed to detect preknowledge cheating by jointly analyzing item responses and response times. Gaze fixations, an essential eye-tracker measure, can be utilized to help detect aberrant testing behavior with improved accuracy beyond using…

As the use of process data in large-scale educational assessments is becoming more common, it is clear that data on examinees' test-taking behaviors can illuminate their performance, and can have crucial ramifications concerning assessments' validity. A thorough review of the literature in the field may inform researchers and practitioners of…

Achievement tests are commonly used in education to evaluate students' academic performance and proficiency in specific subject areas. However, there is a major problem that threatens the validity of achievement test scores which is test-taking disengagement. Respondents provide answers that are inconsistent with their true ability level and can…

Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…

Many low-stakes assessments, such as international large-scale surveys, are administered during time-limited testing sessions and some test-takers are not able to endorse the last items of the test, resulting in not-reached (NR) items. However, because the test has no consequence for the respondents, these NR items can also stem from quitting the…

Process data are becoming more and more popular in education research. In the field of computer-based assessments of collaborative problem solving (ColPS), process data have been used to identify students' test-taking strategies while working on the assessment, and such data can be used to complement data collected on accuracy and overall…

Objective: To examine the manifestation of cognitive control deficit of children with different levels of hyperactivity, an "at risk" dimension for ADHD. Method: A group of children with high hyperactivity (N = 40) and another group of children with low levels of hyperactivity (N = 38) performed a modified stop-signal anticipation task,…

This study explored the use of stealth assessments within a digital game to assess second language (L2) Chinese learners' reading comprehension. Log data tracking learners' in-game behaviors from a game designed for Chinese dual language immersion classrooms (Poole et al., 2022) were used to construct Bayesian Belief Networks to model reading…

Background: Examinees may not make enough effort when responding to test items if the assessment has no consequence for them. These disengaged responses can be problematic in low-stakes, large-scale assessments because they can bias item parameter estimates. However, the amount of bias, and whether this bias is similar across administrations, is…

As researchers in the social sciences, we are often interested in studying not directly observable constructs through assessments and questionnaires. But even in a well-designed and well-implemented study, rapid-guessing behavior may occur. Under rapid-guessing behavior, a task is skimmed shortly but not read and engaged with in-depth. Hence, a…

This article presents a new approach to the analysis of how students answer tests and how they allocate resources in terms of time on task and revisiting previously answered questions. Previous research has shown that in high-stakes assessments, most test takers do not end the testing session early, but rather spend all of the time they were…

Object representations from convolutional neural network (CNN) models of computer vision (LeCun, Bengio, & Hinton, 2015) were used to drive a cognitive model of decision making, the linear ballistic accumulator (LBA) model (Brown & Heathcote, 2008), to predict errors and response times (RTs) in a novel object recognition task in humans.…

Despite being a popular topic in language testing, cognitive load has not received enough attention in vocabulary test items. The purpose of the current study was to scrutinize the cognitive load and vocabulary test items' differences, examinees' reaction times, and perceived difficulty. To this end, 150 students were selected using…