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Martin, Andrew J.; Collie, Rebecca J.; Durksen, Tracy L.; Burns, Emma C.; Bostwick, Keiko C. P.; Tarbetsky, Ana L. – International Journal of Research & Method in Education, 2019
This review explores predictors and consequences of students' growth goals and growth mindset in school with particular emphasis on how correlational statistical methods can be applied to illuminate key issues and implications. Study 1 used cross-sectional data and employed structural equation modelling (SEM) to investigate the role of growth…
Descriptors: Goal Orientation, Student Educational Objectives, Predictor Variables, Statistical Analysis
Gabriel, Florence; Signolet, Jason; Westwell, Martin – International Journal of Research & Method in Education, 2018
Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…
Descriptors: Artificial Intelligence, Mathematics Instruction, Numeracy, Models
Golino, Hudson F.; Gomes, Cristiano M. A. – International Journal of Research & Method in Education, 2016
This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…
Descriptors: Item Response Theory, Regression (Statistics), Difficulty Level, Goodness of Fit