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Parian Haghighat; Denisa Gandara; Lulu Kang; Hadis Anahideh – Grantee Submission, 2024
Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and inaccessible for evaluation or modification by researchers and practitioners, limiting their accountability and ethical design. Moreover, predictive models are often opaque…
Descriptors: Prediction, Learning Analytics, Multivariate Analysis, Regression (Statistics)
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Cheng, Xue Jun; McCarthy, Callum J.; Wang, Tony S. L.; Palmeri, Thomas J.; Little, Daniel R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Upright faces are thought to be processed more holistically than inverted faces. In the widely used composite face paradigm, holistic processing is inferred from interference in recognition performance from a to-be-ignored face half for upright and aligned faces compared with inverted or misaligned faces. We sought to characterize the nature of…
Descriptors: Holistic Approach, Models, Comparative Analysis, Correlation
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Akhmetzyanova, Anna I. – International Journal of Environmental and Science Education, 2016
The relevance of this problem is related to the urgent need to explain peculiarities of anticipation and probabilistic forecasting in adolescence. It has revealed a contradiction: on the one hand, the problem of anticipation in ontogenesis is well developed, and, on the other hand, there remain understudied mechanisms of anticipation in…
Descriptors: Probability, Prediction, Adolescents, Foreign Countries
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Mao, Ye; Lin, Chen; Chi, Min – Journal of Educational Data Mining, 2018
Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…
Descriptors: Prediction, Pretests Posttests, Bayesian Statistics, Short Term Memory
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Dossanova, ?ssem; Lozovoy, Vasiliy; Wood, Dan; ??nekenova, ?enzhekyz; Botabayeva, ?igul; Dossanov, Bolatbek; Lozovaya, Yelena; ?marov, ?algat – International Journal of Environmental and Science Education, 2016
The reproductive system of adolescents is exposed to a high risk of anomalies. In spite of the successes of surgical correction, the percentage of postoperative complications remains high. Special attention should be paid to circumcision, which is regarded as a religious tradition in many countries and carried out with sanitary violations. This…
Descriptors: Adolescents, Males, Surgery, Human Body
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Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G. – Research Synthesis Methods, 2015
In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall…
Descriptors: Bayesian Statistics, Meta Analysis, Prediction, Nonparametric Statistics
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Hooper, Jay; Cowell, Ryan – Educational Assessment, 2014
There has been much research and discussion on the principles of standards-based grading, and there is a growing consensus of best practice. Even so, the actual process of implementing standards-based grading at a school or district level can be a significant challenge. There are very practical questions that remain unclear, such as how the grades…
Descriptors: True Scores, Grading, Academic Standards, Computation
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Akar, Sacide Guzin Mazman; Altun, Arif – Contemporary Educational Technology, 2017
The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been…
Descriptors: Individual Differences, Learning Processes, Programming, Self Efficacy
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Koon, Sharon; Petscher, Yaacov; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
This study examines whether the classification and regression tree (CART) model improves the early identification of students at risk for reading comprehension difficulties compared with the more difficult to interpret logistic regression model. CART is a type of predictive modeling that relies on nonparametric techniques. It presents results in…
Descriptors: At Risk Students, Reading Difficulties, Identification, Reading Comprehension