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David Rutkowski; Leslie Rutkowski; Greg Thompson; Yusuf Canbolat – Large-scale Assessments in Education, 2024
This paper scrutinizes the increasing trend of using international large-scale assessment (ILSA) data for causal inferences in educational research, arguing that such inferences are often tenuous. We explore the complexities of causality within ILSAs, highlighting the methodological constraints that challenge the validity of causal claims derived…
Descriptors: International Assessment, Data Use, Causal Models, Educational Research
Mirazchiyski, Plamen V. – Large-scale Assessments in Education, 2021
This paper presents the R Analyzer for Large-Scale Assessments (RALSA), a newly developed R package for analyzing data from studies using complex sampling and assessment designs. Such studies are, for example, the IEA's Trends in International Mathematics and Science Study and the OECD's Programme for International Student Assessment. The package…
Descriptors: Measurement, Data Analysis, Open Source Technology, Computer Software
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
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

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