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Peer reviewed
Direct linkÁlvarez-Bornstein, Belén; Montesi, Michela – Research Evaluation, 2020
The topic of acknowledgements has produced abundant research since the 1970s, though, as previous studies point out, the value of acknowledgements has not yet been demonstrated and further research is limited by lack of conceptualization. This study focuses on funding acknowledgements (FAs), considering that funding represents an important input…
Descriptors: Financial Support, Citations (References), Periodicals, Sciences
Reeves, Todd D.; Onder, Yasemin; Abdi, Beheshteh – Mid-Western Educational Researcher, 2020
Sound measurement of teacher self-efficacy and anxiety surrounding data-driven decision making is crucial in both theory-building and efficacy studies, as well as in practical contexts. The present study (N=457) thusly examined the validity of inferences drawn from the Data-Driven Decision-Making Efficacy and Anxiety Inventory (3D-MEA; Dunn et…
Descriptors: Test Validity, Data Use, Decision Making, Self Efficacy
Birzenieks, Linda; Hivers, Lisa; Cole, Naomi; Smyth, Eleisha; Raap, Lena Hoffman; Smith, Jane; Wood, Justin; Roche, Sue; Wrigley, Andrew; Arthur-Kelly, Michael – Australasian Journal of Special and Inclusive Education, 2020
This paper describes a collaborative approach to professional learning that has provided an opportunity for refreshed practices and growth in capacity in schools supporting students with various learning needs in several schools that are part of the Association of Independent Schools in the Australian Capital Territory. An action research approach…
Descriptors: Data Collection, Reliability, Professional Development, Action Research
Download full textFontichiaro, Kristin; Johnston, Melissa P. – Journal of Media Literacy Education, 2020
To meet the challenges of a data-driven society, high school students need new arrays of literacy skills. In the United States, school librarians, who work across disciplines, are well-positioned to help students improve their data practice, but they first need new domain knowledge. This article presents findings from an evaluating survey and…
Descriptors: High School Students, Information Literacy, Data, School Libraries
Harris, Frank – School Science Review, 2020
The year 2020 saw the outbreak of the COVID-19 pandemic that not only had wide-reaching social and economic consequences but also put healthcare systems under stress. Strategies for coping with the virus depended heavily on the interpretation of data. This article uses information from a UK upper tier local authority to examine how closely the…
Descriptors: Pandemics, COVID-19, Data Interpretation, Prediction
Zheng, Henry Y.; Mayberry, Eric; Stanley, Leanne – New Directions for Institutional Research, 2020
Data analytics is increasingly important to the operations and strategic growth of higher education institutions. In September 2019, three higher education professional associations issued a rare joint statement calling for the accelerated investment and intensified efforts to develop and deploy data analytics in support of campus decision making.…
Descriptors: Data Analysis, Decision Making, State Universities, Crisis Management
Bollig, Michael; Schnegg, Michael; Schwieger, Diego A. Menestrey – Field Methods, 2020
This article introduces ethnographic upscaling, an innovative procedure to explore and test hypotheses drawn from in-depth ethnographic findings in spatially continuous cases. The approach combines the strength of localized ethnographic descriptions with questionnaire-based regional surveys to study the distribution of ethnographic findings across…
Descriptors: Ethnography, Anthropology, Research Methodology, Hypothesis Testing
Durda, Tabea; Artelt, Cordula; Lechner, Clemens M.; Rammstedt, Beatrice; Wicht, Alexandra – International Review of Education, 2020
Low literacy among adolescents and adults worldwide remains a serious problem, even in economically developed countries. The consequences of low reading proficiency levels can be harmful in many ways for both the individuals concerned and their communities in terms of health, political, social and economic outcomes. While large-scale international…
Descriptors: Reading Achievement, Reading Skills, Low Achievement, Adolescents
Bonami, Beatrice; Piazentini, Luiz; Dala-Possa, André – Comunicar: Media Education Research Journal, 2020
Digital technology has provided users with new connections that have reset our understanding of social architectures. As a reaction to Artificial Intelligence (AI) and Big Data, the educational field has rearranged its structure to consider human and non-human stakeholders and their actions on digital platforms. In light of this increasingly…
Descriptors: Artificial Intelligence, Data, 21st Century Skills, Technology Uses in Education
Kaplan, Avi; Garner, Joanna K. – Journal of Experimental Education, 2020
In this commentary, we propose a framework for applying the Complex Dynamical Systems (CDS) approach in educational research. Drawing on the conceptual articles in the special issue for ontological, theoretical, and methodological principles, and on the empirical articles for examples of these principles' application, we suggest six interdependent…
Descriptors: Educational Research, Systems Approach, Theories, Goal Orientation
Winter, Sonja D.; Depaoli, Sarah – International Journal of Behavioral Development, 2020
This article illustrates the Bayesian approximate measurement invariance (MI) approach in Mplus with longitudinal data and small sample size. Approximate MI incorporates zero-mean small variance prior distributions on the differences between parameter estimates over time. Contrary to traditional invariance testing methods, where exact invariance…
Descriptors: Bayesian Statistics, Measurement, Data Analysis, Sample Size
Sun, Hanyu; Newsome, Jocelyn; McNulty, Jennifer; Levin, Kerry; Langetieg, Pat; Schafer, Brenda; Guyton, John – Field Methods, 2020
Over the past few decades, the survey industry has experienced a steady decline in response rates, which has posed numerous challenges for researchers, most notably concerns about nonresponse bias. We present results from three studies conducted in an attempt to increase response rates and reduce nonresponse bias for a U.S. national household…
Descriptors: National Surveys, Response Rates (Questionnaires), Statistical Bias, Mail Surveys
Detrich, Ronnie – School Psychology Review, 2020
Including cost-effectiveness data in the evaluation of programs is the next step in the evolution of evidence-based practice. Evidence-based practice is grounded in three complementary elements: best available evidence, professional judgment, and client values and context. To fully apply the cost-effectiveness data, school administrators will have…
Descriptors: Cost Effectiveness, Evidence Based Practice, Program Evaluation, Data Use
Mansolf, Maxwell; Vreeker, Annabel; Reise, Steven P.; Freimer, Nelson B.; Glahn, David C.; Gur, Raquel E.; Moore, Tyler M.; Pato, Carlos N.; Pato, Michele T.; Palotie, Aarno; Holm, Minna; Suvisaari, Jaana; Partonen, Timo; Kieseppä, Tuula; Paunio, Tiina; Boks, Marco; Kahn, René; Ophoff, Roel A.; Bearden, Carrie E.; Loohuis, Loes Olde; Teshiba, Terri; deGeorge, Daniella; Bilder, Robert M. – Educational and Psychological Measurement, 2020
Large-scale studies spanning diverse project sites, populations, languages, and measurements are increasingly important to relate psychological to biological variables. National and international consortia already are collecting and executing mega-analyses on aggregated data from individuals, with different measures on each person. In this…
Descriptors: Item Response Theory, Data Analysis, Measurement, Validity
Xiao, Jiaying; Bulut, Okan – Educational and Psychological Measurement, 2020
Large amounts of missing data could distort item parameter estimation and lead to biased ability estimates in educational assessments. Therefore, missing responses should be handled properly before estimating any parameters. In this study, two Monte Carlo simulation studies were conducted to compare the performance of four methods in handling…
Descriptors: Data, Computation, Ability, Maximum Likelihood Statistics
