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Lavigne, Cheryl S.; Tremblay, Kathryn A.; Binder, Katherine S. – Journal of Psycholinguistic Research, 2022
The goal of this study was to describe how underlying vocabulary knowledge manifests into vocabulary usage, and in turn, how usage predicts writing quality among adult basic education (ABE) learners. ABE learners were administered tasks that measured vocabulary knowledge, in the forms of both vocabulary breadth and depth. Participants were also…
Descriptors: Vocabulary Development, Adult Basic Education, Correlation, Language Usage
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Deepa, V.; Sujatha, R.; Baber, Hasnan – Higher Learning Research Communications, 2022
Objectives: The purpose of this study is to examine the influence of social media engagement, which includes frequency of using social media platforms (FSMP) and social media involvement, on the academic distraction and academic performance of the student. The study further tests the moderating role of attention control on the relationship between…
Descriptors: Social Media, Attention, Attention Control, Academic Achievement
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Bulathwela, Sahan; Verma, Meghana; Pérez-Ortiz, María; Yilmaz, Emine; Shawe-Taylor, John – International Educational Data Mining Society, 2022
This work explores how population-based engagement prediction can address cold-start at scale in large learning resource collections. The paper introduces: (1) VLE, a novel dataset that consists of content and video based features extracted from publicly available scientific video lectures coupled with implicit and explicit signals related to…
Descriptors: Video Technology, Lecture Method, Data Analysis, Prediction
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Hur, Paul; Lee, HaeJin; Bhat, Suma; Bosch, Nigel – International Educational Data Mining Society, 2022
Machine learning is a powerful method for predicting the outcomes of interactions with educational software, such as the grade a student is likely to receive. However, a predicted outcome alone provides little insight regarding how a student's experience should be personalized based on that outcome. In this paper, we explore a generalizable…
Descriptors: Artificial Intelligence, Individualized Instruction, College Mathematics, Statistics
Austin Slaughter – MDRC, 2022
New student success interventions generate costs for colleges (for example, staff time and supplies). However, if they lead more students to remain enrolled, cause students to attempt more credits, and improve longer-term student outcomes, they can also generate tuition revenue and state funding (for public institutions in states that allocate…
Descriptors: College Students, State Aid, Educational Equity (Finance), Academic Achievement
Andrea M. Connolly – ProQuest LLC, 2022
Given the rapid growth of K-12 online learning, research is needed in the effective identification of at-risk students so that administrators and teachers can develop appropriate supports and interventions. The purpose of this research was to determine if student success in an online course could be predicted for English Learners (EL) using…
Descriptors: Prediction, Academic Achievement, Virtual Schools, Elementary Secondary Education
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Joseph H. Paris; Rachel Heiser – Journal of Postsecondary Student Success, 2022
Upon the advent of the COVID-19 pandemic, hundreds of higher education institutions in the United States temporarily or permanently adopted test- optional admissions policies. Growth in the number of test- optional institutions and the longstanding criticism of standardized admissions tests as limited and unreliable predictors of college success…
Descriptors: Prediction, Test Validity, College Admission, Admission Criteria
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Serra, Michael J.; England, Benjamin D. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
Soliciting predictions about hypothetical memory performance (without having participants engage in a related memory task) is a simple way for researchers to examine people's metacognitive beliefs about how memory functions. Using this methodology, researchers can vary what information is provided as part of the scenario or how the memory…
Descriptors: Metacognition, Memory, Retention (Psychology), Prediction
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Rutchick, Abraham M.; Ross, Bryan J.; Calvillo, Dustin P.; Mesick, Catherine C. – Cognitive Research: Principles and Implications, 2020
The "surprisingly popular" method (SP) of aggregating individual judgments has shown promise in overcoming a weakness of other crowdsourcing methods--situations in which the majority is incorrect. This method relies on participants' estimates of other participants' judgments; when an option is chosen more often than the average…
Descriptors: Prediction, Predictive Measurement, Evaluative Thinking, Metacognition
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Powell, Cynthia B.; Simpson, Joseph; Williamson, Vickie M.; Dubrovskiy, Anton; Walker, Deborah Rush; Jang, Ben; Shelton, G. Robert; Mason, Diana – Chemistry Education Research and Practice, 2020
Completion of a first-semester chemistry (Chem I) course lays the foundation for understanding second-semester chemistry (Chem II) topics. The purpose of this study is to evaluate the influence of basic arithmetic skills on students' Chem II success in understanding mathematics-grounded concepts (e.g., solutions and aqueous reactions, kinetics,…
Descriptors: Arithmetic, Mathematics Skills, Science Achievement, Chemistry
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Korchi, Adil; Dardor, Mohamed; Mabrouk, El Houssine – Education and Information Technologies, 2020
Learning techniques have proven their capacity to treat large amount of data. Most statistical learning approaches use specific size learning sets and create static models. Withal, in certain some situations such as incremental or active learning the learning process can work with only a smal amount of data. In this case, the search for algorithms…
Descriptors: Learning Analytics, Data, Computation, Mathematics
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Walmsley, Stephen; Gilbey, Andrew – Applied Cognitive Psychology, 2020
One of the key findings of prospect theory is that people tend to treat potential gains differently to potential losses. Consistent with earlier findings across a range of areas, pilots were risk averse when faced with an uncertain situation involving monetary gains and risk seeking when faced with a monetary loss. Prospect theory has largely been…
Descriptors: Decision Making, Risk, Weather, Air Transportation
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Silverstein, Todd P. – Biochemistry and Molecular Biology Education, 2020
The Hill equation, which models the cooperative ligand-receptor binding equilibrium, turns out to be useful in modeling the progression of infectious disease outbreaks such as CoViD-19. The equation fits well the data for total and daily case numbers, allows tentative predictions for the half-point and end point of the epidemic, and presents a…
Descriptors: COVID-19, Kinetics, Biochemistry, Molecular Structure
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Richard, Céline; Neel, Mary Lauren; Jeanvoine, Arnaud; Mc Connell, Sharon; Gehred, Alison; Maitre, Nathalie L. – Journal of Speech, Language, and Hearing Research, 2020
Purpose: We sought to critically analyze and evaluate published evidence regarding feasibility and clinical potential for predicting neurodevelopmental outcomes of the frequency-following responses (FFRs) to speech recordings in neonates (birth to 28 days). Method: A systematic search of MeSH terms in the Cumulative Index to Nursing and Allied…
Descriptors: Neonates, Prediction, Responses, Child Development
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Johnson, Tamar; Siegelman, Noam; Arnon, Inbal – Cognitive Science, 2020
Over the last decade, iterated learning studies have provided compelling evidence for the claim that linguistic structure can emerge from non-structured input, through the process of transmission. However, it is unclear whether individuals differ in their tendency to add structure, an issue with implications for understanding who are the agents of…
Descriptors: Individual Differences, Cognitive Ability, Learning Processes, Language Acquisition
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