Research on methods for measuring examinee engagement with constructed-response items is limited. The present study used data from the PISA 2018 Reading domain to construct and compare indicators of test-taking effort on constructed-response items: response time, number of actions, the union (combining effortless responses detected by either…

Response time data from educational and psychological assessments have become more widely available in recent years. Although much research has been done on response time models, there is large variability between assessments and the factors that may affect response times. On the person's side, familiarity with online environments may largely…

Test-taking experience is a consequence of the interaction between students and assessment properties. We define a new notion, rapid-pacing behavior, to reflect two types of test-taking experience -- disengagement and speededness. To identify rapid-pacing behavior, we extend existing methods to develop response-time thresholds for individual items…

Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore,…

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 responses. In computer-based assessments, joint modeling of response times and action counts with item responses helps estimate the latent speed and action levels in addition to…

This study proposes explanatory cognitive diagnostic model (CDM) jointly incorporating responses and response times (RTs) with the inclusion of item covariates related to both item responses and RTs. The joint modeling of item responses and RTs intends to provide more information for cognitive diagnosis while item covariates can be used to predict…

The item responses of examinees who rapid-guess, who do not spend enough time reading and engaging with an item, will not reflect their true ability on that item. Rapid-disengagement refers to rapidly selecting a response to multiple-choice items (i.e., rapid-guess), omitting items, or providing short-unrelated answers to open-ended items in an…

One of the most common technology-enhanced items used in large-scale K-12 testing programs is the drag-and-drop response interaction. The main research questions in this study are: (a) Does adding a drag-and-drop interface to an online test affect the accuracy of student performance? (b) Does adding a drag-and-drop interface to an online test…

The present study used process data from a computer-based problem-solving task as indications of behavioural level of test-taking effort, and explored how behavioural item-level effort related to overall test performance and self-reported effort. Variables were extracted from raw process data and clustered. Four distinct clusters were obtained and…

The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…