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Roy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
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Mahmoud Abdasalam; Ahmad Alzubi; Kolawole Iyiola – Education and Information Technologies, 2025
This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…
Descriptors: Grades (Scholastic), Prediction, Accuracy, Artificial Intelligence
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Megan Senseney; Jeffrey C. Oliver – College & Research Libraries, 2025
The University of Arizona Libraries has conducted a pilot implementation of a year-long Digital Scholarship and Data Science Fellowship (DS[superscript 2]F) to address increasing interest in digital and data-intensive scholarship among graduate students. This article provides details regarding the model for the fellowship program; a description of…
Descriptors: Academic Libraries, Fellowships, Graduate Students, Data Science
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María Cioè-Peña – Journal of Language, Identity, and Education, 2025
Within educational research, qualitative data offers unique opportunities to contextualize findings that arise from large-scale quantitative data collection processes. Still, to date, most educational research is based on researchers' determination of what is important, not the participants'. Participatory Rank Methodology (PRM) is a…
Descriptors: Public Health, Educational Research, Data Collection, Research Methodology
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Jarred Pernier; Freddy Juarez; Brittany Devies – New Directions for Student Leadership, 2025
Metrics, outcomes, and assessment are important, yet often forgotten, elements of effective leadership programs. This article will provide an overview of metrics, outcomes, and assessment in regard to leadership programs. The article will then provide example programs and practical guidance on using metrics, outcomes, and assessment in leadership…
Descriptors: Leadership Training, Educational Assessment, Evaluation Methods, Outcome Measures
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Brandi Nicole Hinnant-Crawford; Stacey Caillier – Learning Professional, 2025
History shows that learning and collaborative inquiry are the path forward. Continuous improvement can produce great thinking and learning that enables the continuation to support the most vulnerable children. Civil rights organizers, such as Septima Clark, are viewed as model improvers. Regarded by many as the queen of the Civil Rights Movement,…
Descriptors: Educational Improvement, Educational Cooperation, Inquiry, Data Use
Kankana Mukhopadhyay; Siok Kuan Tambyah; Fong Kai Jun – Sage Research Methods Cases, 2025
In this case study, we discuss the affordances of using vignettes in a survey to capture the perceptions of the actual experiences from diverse participants in short-term overseas experiential learning trips, even after a significant time lag. The evidence is drawn from an ongoing research study examining the impact of these trips on various…
Descriptors: Experiential Learning, Field Trips, Data Collection, College Students
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Sultan A. Almelhes – SAGE Open, 2025
Many people around the globe are aiming to learn the Arabic language, even though it is difficult to learn. Therefore, many online institutions are offering the service of teaching Arabic as a second language to non-native speakers, but these institutions always encounter different issues in enhancing their performance. Thus, this study aimed to…
Descriptors: Arabic, Second Language Instruction, Electronic Learning, Data Analysis
Susan Athey; Raj Chetty; Guido Imbens – National Bureau of Economic Research, 2025
Researchers increasingly have access to two types of data: (i) large observational datasets where treatment (e.g., class size) is not randomized but several primary outcomes (e.g., graduation rates) and secondary outcomes (e.g., test scores) are observed and (ii) experimental data in which treatment is randomized but only secondary outcomes are…
Descriptors: Observation, Research Problems, Bias, Data Science
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Odden, Tor Ole B.; Silvia, Devin W.; Malthe-Sørenssen, Anders – Journal of Research in Science Teaching, 2023
This article reports on a study investigating how computational essays can be used to help students in higher education STEM take up disciplinary epistemic agency--cognitive control and responsibility over one's own learning within the scientific disciplines. Computational essays are a genre of scientific writing that combine live, executable…
Descriptors: Computation, Essays, Undergraduate Students, STEM Education
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Arantes, Janine Aldous; Vicars, Mark – Learning, Media and Technology, 2023
In the recent Australian 2021 census, the socio-technical construct of algorithmically driven decision-making processes made LGBTQI+ data as a category of diversity, inclusion and belonging an absent presence. In this paper, we position the notion of 'data justice' in relation to the entrenchment of inequalities and exclusion of LGBTQI+ lives and…
Descriptors: Foreign Countries, Homosexuality, LGBTQ People, Data
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Kuntz, Emily M.; Massey, Cynthia C.; Peltier, Corey; Barczak, Mary; Crowson, H. Michael – Teacher Education and Special Education, 2023
Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…
Descriptors: Graphs, Preservice Teachers, Accuracy, Decision Making
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Reyna, Mercedes; Peppino Margutti, Micaela; Vilchez, Ana Carolina; Villasuso, Ana Laura – Biochemistry and Molecular Biology Education, 2023
Lipidomics is a discipline that focuses on the identification and quantification of lipids. Although a part of the larger omics field, lipidomics requires specific approaches for the analysis and biological interpretation of datasets. This article presents a series of activities for introducing undergraduate microbiology students to lipidomic…
Descriptors: Biology, Microbiology, Science Instruction, College Science
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Boels, Lonneke – Teaching Statistics: An International Journal for Teachers, 2023
Gaze data are still uncommon in statistics education despite their promise. Gaze data provide teachers and researchers with a new window into complex cognitive processes. This article discusses how gaze data can inform and be used by teachers both for their own teaching practice and with students. With our own eye-tracking research as an example,…
Descriptors: Statistics Education, Eye Movements, Data, Cognitive Processes
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Jen Munson; Erin E. Baldinger – Journal of the Learning Sciences, 2023
Background: Emotions are inherently intertwined with learning and disciplinary identity, and this relationship demands that teachers attend and respond to students' emotions. In this study, we forward a theory that the development of "pedagogical empathy," or the capacity to understand the implications of student emotions and use…
Descriptors: Educational Practices, Psychological Patterns, Empathy, Decision Making
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