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Esther Ulitzsch; Janine Buchholz; Hyo Jeong Shin; Jonas Bertling; Oliver Lüdtke – Large-scale Assessments in Education, 2024
Common indicator-based approaches to identifying careless and insufficient effort responding (C/IER) in survey data scan response vectors or timing data for aberrances, such as patterns signaling straight lining, multivariate outliers, or signals that respondents rushed through the administered items. Each of these approaches is susceptible to…
Descriptors: Response Style (Tests), Attention, Achievement Tests, Foreign Countries
Gorgun, Guher; Bulut, Okan – Large-scale Assessments in Education, 2023
In low-stakes assessment settings, students' performance is not only influenced by students' ability level but also their test-taking engagement. In computerized adaptive tests (CATs), disengaged responses (e.g., rapid guesses) that fail to reflect students' true ability levels may lead to the selection of less informative items and thereby…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
Goldhammer, Frank; Hahnel, Carolin; Kroehne, Ulf; Zehner, Fabian – Large-scale Assessments in Education, 2021
International large-scale assessments such as PISA or PIAAC have started to provide public or scientific use files for log data; that is, events, event-related attributes and timestamps of test-takers' interactions with the assessment system. Log data and the process indicators derived from it can be used for many purposes. However, the intended…
Descriptors: International Assessment, Data, Computer Assisted Testing, Validity
Rios, Joseph A.; Deng, Jiayi – Large-scale Assessments in Education, 2021
Background: In testing contexts that are predominately concerned with power, rapid guessing (RG) has the potential to undermine the validity of inferences made from educational assessments, as such responses are unreflective of the knowledge, skills, and abilities assessed. Given this concern, practitioners/researchers have utilized a multitude of…
Descriptors: Test Wiseness, Guessing (Tests), Reaction Time, Computer Assisted Testing
Provasnik, Stephen – Large-scale Assessments in Education, 2021
This paper presents the concepts and observations in the author's keynote address at the May 2019 "Opportunity versus Challenge: Exploring Usage of Log-File and Process Data in International Large-Scale Assessments" conference in Dublin, Ireland. This paper recaps briefly some key points that emerged at the December 2018 ETS symposium on…
Descriptors: Data Collection, Cognitive Processes, Ethics, Student Evaluation
Han, Areum; Krieger, Florian; Borgonovi, Francesca; Greiff, Samuel – Large-scale Assessments in Education, 2023
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…
Descriptors: Behavior Patterns, Cooperative Learning, Problem Solving, Reaction Time
Avvisati, Francesco; Borgonovi, Francesca – Large-scale Assessments in Education, 2023
Written instructions seldom need to be read when playing videogames. Instead, gaming often involves early information foraging and expansive exploration behaviors. We use data from the Programme for International Student Assessment (PISA) to explore whether students who regularly play videogames (daily gamers) adopt behaviors that are typical of…
Descriptors: Video Games, Science Process Skills, Problem Solving, Discovery Learning
Soland, James; Kuhfeld, Megan; Rios, Joseph – Large-scale Assessments in Education, 2021
Low examinee effort is a major threat to valid uses of many test scores. Fortunately, several methods have been developed to detect noneffortful item responses, most of which use response times. To accurately identify noneffortful responses, one must set response time thresholds separating those responses from effortful ones. While other studies…
Descriptors: Reaction Time, Measurement, Response Style (Tests), Reading Tests
Jiang, Yang; Gong, Tao; Saldivia, Luis E.; Cayton-Hodges, Gabrielle; Agard, Christopher – Large-scale Assessments in Education, 2021
In 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to…
Descriptors: Data Use, Learning Analytics, Test Items, Measurement
Kuang, Huan; Sahin, Fusun – Large-scale Assessments in Education, 2023
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…
Descriptors: Test Items, Comparative Analysis, Mathematics Tests, Reaction Time
Costa, Denise Reis; Chen, Chia-Wen – Large-scale Assessments in Education, 2023
Given the ongoing development of computer-based tasks, there has been increasing interest in modelling students' behaviour indicators from log file data with contextual variables collected via questionnaires. In this work, we apply a latent regression model to analyse the relationship between latent constructs (i.e., performance, speed, and…
Descriptors: Achievement Tests, Secondary School Students, International Assessment, Foreign Countries