Motivational Profiles in Timss Mathematics: Exploring Student Clusters Across Countries and Time, Michaelides Michalis P., Brown Gavin T. L., Eklцf Hanna
This open access report explores the nature and extent of students' misconceptions and misunderstandings related to core concepts in physics and mathematics and physics across grades four, eight and 12. Twenty years of data from the IEA's Trends in International Mathematics and Science Study (TIMSS) and TIMSS Advanced assessments are analyzed, specifically for five countries (Italy, Norway, Russian Federation, Slovenia, and the United States) who participated in all or almost all TIMSS and TIMSS Advanced assessments between 1995 and 2015.
The report focuses on students' understandings related to gravitational force in physics and linear equations in mathematics. It identifies some specific misconceptions, errors, and misunderstandings demonstrated by the TIMSS Advanced grade 12 students for these core concepts, and shows how these can be traced back to poor foundational development of these concepts in earlier grades. Patterns in misconceptions and misunderstandings are reported by grade, country, and gender. In addition, specific misconceptions and misunderstandings are tracked over time, using trend items administered in multiple assessment cycles.
The study and associated methodology may enable education systems to help identify specific needs in the curriculum, improve inform instruction across grades and also raise possibilities for future TIMSS assessment design and reporting that may provide more diagnostic outcomes.
Автор: Michalis P. Michaelides; Gavin T. L. Brown; Hanna Название: Motivational Profiles in TIMSS Mathematics ISBN: 3030261824 ISBN-13(EAN): 9783030261825 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Поставка под заказ.
Описание: This open access book presents a person-centered exploration of student profiles, using variables related to motivation to do school mathematics derived from the IEA’s Trends in International Mathematics and Science Study (TIMSS) data. Statistical cluster analysis is used to identify groups of students with similar motivational profiles, across grades and over time, for multiple participating countries.While motivational variables systematically relate to school outcomes, linear relationships can obscure the diverse makeup of student subgroups, each with varying combinations of motivation, emotions, and attitudes. In this book, a person-centered analysis of distinct and meaningful motivational profiles and their differences on sociodemographic variables and mathematics performance broadens understanding about the role that motivation characteristics play in learning and achievement in mathematics. Exploiting the richness of IEA’s TIMSS data from many countries, extracted clusters reveal consistent, as well as certain nuanced patterns that are systematically linked to sociodemographic and achievement measures. Student clusters with inconsistent motivational profiles were found in all countries; mathematics self-confidence then emerged as the variable more closely associated with average achievement. The findings demonstrate that teachers, researchers, and policymakers need to take into account differential student profiles, prioritizing techniques that target skill and competence in mathematics, in educational efforts to develop student motivation.
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