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Gomes, Cristiano Mauro Assis; Jelihovschi, Enio – International Journal of Research & Method in Education, 2020
Regression Tree Method is not yet a mainstream method in Education, despite of being a traditional approach in Machine Learning. We advocate that this method should become mainstream in Education, since, in our point of view, it is the most suitable method to analyse complex datasets, very common in Education. This is, for example, the case of…
Descriptors: Regression (Statistics), Statistical Analysis, Educational Research, Classification
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
Glackin, Melissa; Hohenstein, Jill – International Journal of Research & Method in Education, 2018
Teacher self-efficacy has predominantly been explored using quantitative instruments such as Likert scales-based questionnaires. Several researchers have questioned these methods, suggesting they offer only a limited view of the concept. This paper considers their claim by exploring the self-efficacy of UK secondary science teachers participating…
Descriptors: Foreign Countries, Self Efficacy, Teacher Characteristics, Faculty Development
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
Hampden-Thompson, Gillian; Lubben, Fred; Bennett, Judith – International Journal of Research & Method in Education, 2011
Quantitative secondary analysis of large-scale data can be combined with in-depth qualitative methods. In this paper, we discuss the role of this combined methods approach in examining the uptake of physics and chemistry in post compulsory schooling for students in England. The secondary data analysis of the National Pupil Database (NPD) served…
Descriptors: Research Methodology, Physics, Chemistry, Measures (Individuals)
The Use of National Data Sets to Baseline Science Education Reform: Exploring Value-Added Approaches
Homer, Matt; Ryder, Jim; Donnelly, Jim – International Journal of Research & Method in Education, 2011
This paper uses data from the National Pupil Database to investigate the differences in "performance" across the range of science courses available following the 2006 Key Stage 4 (KS4) science reforms in England. This is a value-added exploration (from Key Stage 3 [KS3] to KS4) aimed not at the student or the school level, but rather at…
Descriptors: Secondary School Science, Courses, Educational Change, Foreign Countries