In educational assessments and achievement tests, test developers and administrators commonly assume that test-takers attempt all test items with full effort and leave no blank responses with unplanned missing values. However, aberrant response behavior--such as performance decline, dropping out beyond a certain point, and skipping certain items…

Common response-time-based approaches for non-effortful response behavior (NRB) in educational achievement tests filter responses that are associated with response times below some threshold. These approaches are, however, limited in that they require a binary decision on whether a response is classified as stemming from NRB; thus ignoring…

The use of multistage adaptive testing (MST) has gradually increased in large-scale testing programs as MST achieves a balanced compromise between linear test design and item-level adaptive testing. MST works on the premise that each examinee gives their best effort when attempting the items, and their responses truly reflect what they know or can…

The Programme for International Student Assessment (PISA) student questionnaire, despite being designed for low cognitive demand, may induce test burden due to its 306-item length, resulting in increased item nonresponse toward the questionnaire's end. Using the PISA 2018 response data from 80 countries and a cross-classified mixed effects model,…

Mathematical achievement and the factors that influence students' skills to apply their knowledge and reasoning to solving real-world problems are considered a critical area of study within the PISA framework. This study presents a systematic review of the impact of teaching strategies and practices on students' mathematical achievements in PISA.…

The highly adaptive testing (HAT) design is introduced as an alternative test design for the Programme for International Student Assessment (PISA). The principle of HAT is to be as adaptive as possible when selecting items while accounting for PISA's nonstatistical constraints and addressing issues concerning PISA such as item position effects.…

Many international large-scale assessments (ILSAs) have switched to multistage adaptive testing (MST) designs to improve measurement efficiency in measuring the skills of the heterogeneous populations around the world. In this context, previous literature has reported the acceptable level of model parameter recovery under the MST designs when the…

Science, Technology, Engineering, and Math (STEM) skills are increasingly required of students to be successful in higher education and the workforce. Therefore, modeling assessment outcomes accurately, often using more types of student data to get a complete picture of student learning, is increasingly relevant. The Program for International…

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…

Item nonresponses are prevalent in standardized testing. They happen either when students fail to reach the end of a test due to a time limit or quitting, or when students choose to omit some items strategically. Oftentimes, item nonresponses are nonrandom, and hence, the missing data mechanism needs to be properly modeled. In this paper, we…

Despite the general consensus on the positive impact of formative assessment on student learning, researchers have not shown the underlying mechanisms between specific formative assessment strategies and academic performance on an international sample. This study examines the link between student and teacher reports of teachers' formative…

Country differences in response styles (RS) may jeopardize cross-country comparability of Likert-type scales. When adjusting for rather than investigating RS is the primary goal, it seems advantageous to impose minimal assumptions on RS structures and leverage information from multiple scales for RS measurement. Using PISA 2015 background…

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…

Gender differences in item nonresponse are well-documented in high-stakes achievement tests, where female students are shown to omit more items than male students. These gender differences in item nonresponse are often linked to differential risk-taking strategies, with females being risk-averse and unwilling to guess on an item, even if it could…

For assessment scales applied to different groups (e.g., students from different states; patients in different countries), multigroup differential item functioning (MG-DIF) needs to be evaluated in order to ensure that respondents with the same trait level but from different groups have equal response probabilities on a particular item. The…