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Jyun-Hong Chen; Hsiu-Yi Chao – Journal of Educational and Behavioral Statistics, 2024
To solve the attenuation paradox in computerized adaptive testing (CAT), this study proposes an item selection method, the integer programming approach based on real-time test data (IPRD), to improve test efficiency. The IPRD method turns information regarding the ability distribution of the population from real-time test data into feasible test…
Descriptors: Data Use, Computer Assisted Testing, Adaptive Testing, Design
Emily C. Hanno; Ximena A. Portilla; JoAnn Hsueh – Child Development Perspectives, 2025
In this article, we adopt culturally relevant perspectives on developmental science that acknowledge and value the diversity of backgrounds and experiences of young children and their families to identify opportunities to advance the measurement of early childhood development. We focus on direct child assessments that can drive more equitable…
Descriptors: Young Children, Child Development, Equal Education, Evaluation Methods
Jeremiah T. Stark – ProQuest LLC, 2024
This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…
Descriptors: High School Students, Graduation Rate, Predictor Variables, Predictive Validity
Kaiwen Man – Educational and Psychological Measurement, 2024
In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…
Descriptors: Prior Learning, Testing, Behavior, Artificial Intelligence
Duncan Culbreth; Rebekah Davis; Cigdem Meral; Florence Martin; Weichao Wang; Sejal Foxx – TechTrends: Linking Research and Practice to Improve Learning, 2025
Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…
Descriptors: High School Students, COVID-19, Pandemics, Progress Monitoring
Irene-Angelica Chounta; Alejandro Ortega-Arranz; Sophia Daskalaki; Yannis Dimitriadis; Nikolaos Avouris – International Journal of Educational Technology in Higher Education, 2024
This paper aims to address Digital Readiness in Higher Education Institutions from the perspective of data-informed and evidence-based assessment of Digital Readiness. Related research suggests that existing instruments for assessing digitalization aspects are limited to self-assessment, and there is a need for data-informed frameworks that will…
Descriptors: Colleges, Technological Literacy, Stakeholders, Foreign Countries
Salles, Franck; Dos Santos, Reinaldo; Keskpaik, Saskia – Large-scale Assessments in Education, 2020
During this digital era, France, like many other countries, is undergoing a transition from paper-based assessments to digital assessments in education. There is a rising interest in technology-enhanced items which offer innovative ways to assess traditional competencies, as well as addressing problem solving skills, specifically in mathematics.…
Descriptors: Foreign Countries, Didacticism, Mathematics Tests, Learning Analytics
Mohan, Kaushik; Bergner, Yoav; Halpin, Peter – Technology, Knowledge and Learning, 2020
Technology-based assessments that involve collaboration among students offer many sources of process data, although it remains unclear which aspects of these data are most meaningful for making inferences about students' collaborative skills. Recent research has focused mainly on theory-based rubrics for qualitative coding of process data (e.g.,…
Descriptors: Computer Assisted Testing, Student Evaluation, Cooperation, Grade 12
Hebbecker, Karin; Förster, Natalie; Forthmann, Boris; Souvignier, Elmar – Journal of Educational Psychology, 2022
The idea of data-based decision-making (DBDM) at the classroom level is that teachers use assessment data to adapt their instruction to students' individual needs and thus improve students' learning progress. In this study, we first investigate this theoretically assumed DBDM process, and second, we evaluate the effectiveness of teacher support on…
Descriptors: Data Use, Evidence Based Practice, Decision Making, Formative Evaluation
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
Bergner, Yoav; von Davier, Alina A. – Journal of Educational and Behavioral Statistics, 2019
This article reviews how National Assessment of Educational Progress (NAEP) has come to collect and analyze data about cognitive and behavioral processes (process data) in the transition to digital assessment technologies over the past two decades. An ordered five-level structure is proposed for describing the uses of process data. The levels in…
Descriptors: National Competency Tests, Data Collection, Data Analysis, Cognitive Processes
Hahnel, Carolin; Kroehne, Ulf; Goldhammer, Frank; Schoor, Cornelia; Mahlow, Nina; Artelt, Cordula – British Journal of Educational Psychology, 2019
Background: With digital technologies, competence assessments can provide process data, such as mouse clicks with corresponding timestamps, as additional information about the skills and strategies of test takers. However, in order to use variables generated from process data sensibly for educational purposes, their interpretation needs to be…
Descriptors: Computer Assisted Testing, Test Interpretation, Foreign Countries, College Students
Masango, Mxolisi; Muloiwa, Takalani; Wagner, Fezile; Pinheiro, Gabriela – Journal of Student Affairs in Africa, 2020
Knowing relevant information about students entering the higher education (HE) system is becoming increasingly important, thus enabling higher education institutions (HEIs) to design effective studentcentred support programmes. Therefore, HEIs should ascertain all relevant information about their students before the commencement of the academic…
Descriptors: Test Construction, Test Use, Biographical Inventories, Questionnaires
von Davier, Matthias; Khorramdel, Lale; He, Qiwei; Shin, Hyo Jeong; Chen, Haiwen – Journal of Educational and Behavioral Statistics, 2019
International large-scale assessments (ILSAs) transitioned from paper-based assessments to computer-based assessments (CBAs) facilitating the use of new item types and more effective data collection tools. This allows implementation of more complex test designs and to collect process and response time (RT) data. These new data types can be used to…
Descriptors: International Assessment, Computer Assisted Testing, Psychometrics, Item Response Theory
Juškaite, Loreta – International Baltic Symposium on Science and Technology Education, 2019
The new research results on the online- testing method in the Latvian education system for a learning process assessment are presented. Data mining is a very important field in education because it helps to analyse the data gathered in various researches and to implement the changes in the education system according to the learning methods of…
Descriptors: Foreign Countries, Information Retrieval, Data Analysis, Data Use
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