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Download full textHaara, Frode Olav – European Journal of Science and Mathematics Education, 2022
This article reports on how a pedagogical entrepreneurship approach combined with fundamental elements of mathematical modelling may be used to strengthen students' development of mathematical literacy in upper primary school. This is done first through a review of the relationship between pedagogical entrepreneurship in mathematics, mathematical…
Descriptors: Mathematical Models, Entrepreneurship, Mathematics Instruction, Knowledge Level
Direct linkMerino, Barbara J.; Holmes, Pauline – Teacher Education Quarterly, 2006
Much has been written about the value of teacher research for inservice teachers. Despite the existence of several studies affirming these words, studies that richly describe how student teachers learn to do teacher research and then investigate the impact of inquiry on student teachers and teacher educators, particularly in culturally and…
Descriptors: Student Teachers, Student Teacher Attitudes, Teacher Educators, English Instruction
Carmo, Mafalda, Ed. – Online Submission, 2017
This book contains a compilation of papers presented at the International Conference on Education and New Developments (END 2017), organized by the World Institute for Advanced Research and Science (W.I.A.R.S.). Education, in our contemporary world, is a right since we are born. Every experience has a formative effect on the constitution of the…
Descriptors: Educational Quality, Models, Vocational Education, Outcomes of Education
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
