Motivational Profiles in TIMSS Mathematics :Exploring Student Clusters Across Countries and Time
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.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.
تنسيق الكتاب
مجاني
تعليقات
لقطة التصنيف
اختر صف بالأسفل لتصفية التعليقات.
0
0
0
0
0
0
بصورة إجمالية
متوسط تقييم المستخدمين
مراجعة هذا الكتاب
شارك أفكارك مع القراء
مزيد من المعلومات
description_of_book
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 Mathemat
معلومات إضافية:
البائع
الناشر
تاريخ الإصدار
01 يناير 2019
ردمك -الرقم الدولي المعياري للكتب-
978-3-030-26183-2
عن المؤلفين:
Michalis P. Michaelides is an Assistant Professor in the Department of Electrical Engineering, Computer Engineering and Informatics. He received a BSEE (1997) and a MSEE (1998), both with honors, from the School of Electrical and Computer Engineering at Purdue University, West Lafayette, IN, USA. During 1999-2007 he has worked in the Cyprus industry as a Medical Service Engineer and as an Information Technology Officer. In 2009, he received his PhD from the Department of Electrical and Computer Engineering at the University of Cyprus and during the next two years he was employed as a research fellow at the KIOS Research Center for Intelligent Systems and Networks at the University of Cyprus. Michalis research interests include communication systems, wireless sensor networks, event detection and localization, fault detection and diagnosis, fault tolerance, collaborative signal and information processing, computational intelligence with applications to environmental monitoring, intelligent irrigation systems, intelligent buildings, intelligent ports and sea traffic management. In 2014, he received the Elsevier Building and Environment Journal Best Paper Award. Michalis P. Michaelides is an Assistant Professor in the Department of Electrical Engineering, Computer Engineering and Informatics. He received a BSEE (1997) and a MSEE (1998), both with honors, from the School of Electrical and Computer Engineering at Purdue University, West Lafayette, IN, USA. During 1999-2007 he has worked in the Cyprus industry as a Medical Service Engineer and as an Information Technology Officer. In 2009, he received his PhD from the Department of Electrical and Computer Engineering at the University of Cyprus and during the next two years he was employed as a research fellow at the KIOS Research Center for Intelligent Systems and Networks at the University of Cyprus. Michalis research interests include communication systems, wireless sensor networks, event detection and localization, fault detection and diagnosis, fault tolerance, collaborative signal and information processing, computational intelligence with applications to environmental monitoring, intelligent irrigation systems, intelligent buildings, intelligent ports and sea traffic management. In 2014, he received the Elsevier Building and Environment Journal Best Paper Award.
Michalis P. Michaelide
Professor Gavin Brown is the Director of the Quantitative Data Analysis and Research Unit and the Associate Dean Postgraduate (Research) within the Faculty of Education & Social Work, at The University of Auckland. He is the Chief Section Editor for Frontiers in Education: Assessment, Testing, and Applied Measurement.
Gavin T. L. Brown
Elena C. Papanastasiou, is a Dean at the University of Nicosia, Cyprus, where she teaches courses in Educational Research, Quantitative Methods, and Assessment. She has received her PhD in Measurement and Quantitative Methods from Michigan State University, and her Honors B.Sc. in Elementary Education from The Pennsylvania State University. Since 2001, Dr Papanastasiou has held academic positions at the University of Kansas and the University of Cyprus. So far she has published a two-volume co-edited book on the history of the International Association for the Evaluation of Educational Achievement (IEA), more than 60 peer reviewed journal publications, book chapters and peer reviewed conference proceedings, and three editions of a co-authored book on research methodology. Her co-authored book on research methodology is one of the main textbooks used in Cyprus and Greece in many educational research courses. In addition to her publications, her methodological and statistical consulting services are being extensively used to lead the methodological work of research teams in Cyprus, Europe and the USA. This methodological work includes applications of structural equation modeling, multilevel modeling, other advanced multivariate statistical analyses, as well as mixed methods for responding to research problems. Dr Papanastasiou also serves as the General Assembly representative of Cyprus in the International Association for the Evaluation of Educational Achievement (IEA), while in 2014 she had been elected in the Standing Committee of the IEA. She also serves in the Publications Committee of the IEA, as well as in the Professional Development Committee of the Association for Educational Assessment.
Elena C. Papanastasiou
جدول المحتوى
