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Bashir, Rabia; Dunn, Adam G.; Surian, Didi – Research Synthesis Methods, 2021
Few data-driven approaches are available to estimate the risk of conclusion change in systematic review updates. We developed a rule-based approach to automatically extract information from reviews and updates to be used as features for modelling conclusion change risk. Rules were developed to extract relevant information from published Cochrane…
Descriptors: Literature Reviews, Data, Automation, Statistical Analysis
Lewis, Norman P. – Journalism and Mass Communication Educator, 2021
A thematic evaluation of data journalism courses resulted in a typology that parses the field and offers guidance to educators. At the center is pattern detection, preceded by data acquisition and cleaning, and followed by data representation. The typology advances academic understanding by offering a precise conceptualization that distinguishes…
Descriptors: Data Analysis, Journalism Education, Classification, Audiences
Watson, Gregory S.; Green, David W.; Watson, Jolanta A. – Journal of Chemical Education, 2021
In some universities, there is a significant population of first year chemistry students who enter the system with very little prior knowledge of the subject. This, coupled with preconceived ideas of subject difficulty, necessitates that the introduction of key concepts is carried out in a nonthreatening, engaging, simplistic, and efficacious…
Descriptors: Chemistry, Scientific Concepts, College Freshmen, Instructional Innovation
Condor, Aubrey; Litster, Max; Pardos, Zachary – International Educational Data Mining Society, 2021
We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…
Descriptors: Automation, Grading, Test Items, Generalization
McNeish, Daniel; Harring, Jeffrey R. – Grantee Submission, 2021
Growth mixture models (GMMs) are a popular method to uncover heterogeneity in growth trajectories. Harnessing the power of GMMs in applications is difficult given the prevalence of nonconvergence when fitting GMMs to empirical data. GMMs are rooted in the random effect tradition and nonconvergence often leads researchers to modify their intended…
Descriptors: Growth Models, Classification, Posttraumatic Stress Disorder, Sample Size
Das, Arijit – Online Submission, 2021
In this approach, formulae-based mnemonics by using the classification of negative charge (localized or delocalized) have been highlighted by innovative and time economic way to enhance interest of students' who belong to paranoia zone of chemistry for the prediction of hybridization state of carbon atom containing negative charge (one or more)…
Descriptors: Organic Chemistry, Mnemonics, Classification, Mathematical Formulas
Magooda, Ahmed; Elaraby, Mohamed; Litman, Diane – Grantee Submission, 2021
This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different tasks (extractive summarization, language modeling, concept detection, and paraphrase detection) both individually and in combination, with the goal of enhancing the target…
Descriptors: Data Analysis, Synthesis, Documentation, Training
Sebastian Moncaleano – ProQuest LLC, 2021
The growth of computer-based testing over the last two decades has motivated the creation of innovative item formats. It is often argued that technology-enhanced items (TEIs) provide better measurement of test-takers' knowledge, skills, and abilities by increasing the authenticity of tasks presented to test-takers (Sireci & Zenisky, 2006).…
Descriptors: Computer Assisted Testing, Test Format, Test Items, Classification
Rogers, Angela – Mathematics Education Research Group of Australasia, 2023
Place value is one of the 'big ideas' in number and plays a critical role in helping students develop their number sense, problem solving and computation skills. Yet, the elegant simplicity of our place value system belies the abstract nature of the construct. This paper presents data from 606 Year 3-6 students (ages 8-12) from two metropolitan…
Descriptors: Number Concepts, Teaching Methods, Problem Solving, Computation
Bonifay, Wes; Depaoli, Sarah – Prevention Science, 2023
Statistical analysis of categorical data often relies on multiway contingency tables; yet, as the number of categories and/or variables increases, the number of table cells with few (or zero) observations also increases. Unfortunately, sparse contingency tables invalidate the use of standard goodness-of-fit statistics. Limited-information fit…
Descriptors: Bayesian Statistics, Programming Languages, Psychopathology, Classification
Smithson, Conor J. R.; Eichbaum, Quentin G.; Gauthier, Isabel – Cognitive Research: Principles and Implications, 2023
We investigated the relationship between category learning and domain-general object recognition ability (o). We assessed this relationship in a radiological context, using a category learning test in which participants judged whether white blood cells were cancerous. In study 1, Bayesian evidence negated a relationship between o and category…
Descriptors: Recognition (Psychology), Classification, Learning Processes, Medicine
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation
Lomer, Sylvie; Mittelmeier, Jenna; Courtney, Steve – Higher Education Research and Development, 2023
Although internationalisation underpins many practices in higher education, its adopted approaches can be uneven between institutions and create ambiguous conceptualisations of how it is enacted in practice. Therefore, a whole-sector analysis can provide insight into whether spaces exist for new and innovative approaches to internationalisation,…
Descriptors: Classification, Higher Education, Institutional Characteristics, Institutional Mission
Ben-Yaacov, Anat; Hershkovitz, Arnon – Journal of Educational Computing Research, 2023
Block programming has been suggested as a way of engaging young learners with the foundations of programming and computational thinking in a syntax-free manner. Indeed, syntax errors--which form one of two broad categories of errors in programming, the other one being logic errors--are omitted while block programming. However, this does not mean…
Descriptors: Programming, Computation, Thinking Skills, Error Patterns
Cox, Deniese; Prestridge, Sarah; Hodge, Steven – International Journal of Research & Method in Education, 2023
Researchers who investigate value-laden professional practices face the challenge of creating a space in which to explore workplace priorities. Education professionals, for example, are keyed to the development and wellbeing of their students, yet frequently work in environments in which there are constraints on their practice. These professionals…
Descriptors: Reflection, Protocol Analysis, Classification, Online Courses