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Velayutham, Sunitadevi; Aldridge, Jill M. – Research in Science Education, 2013
The primary aim of this study was two-fold: 1) to identify salient psychosocial features of the classroom environment that influence students' motivation and self-regulation in science learning; and 2) to examine the effect of the motivational constructs of learning goal orientation, science task value and self-efficacy in science learning on…
Descriptors: Foreign Countries, Grade 8, Structural Equation Models, Student Motivation
Lawanto, Oenardi; Santoso, Harry B.; Liu, Yang – Educational Technology & Society, 2012
In this study, the relationship between students' interest in engineering design activities and their expectancy for success in grades 9-12 was evaluated. The theoretical frameworks developed by Eccles and colleagues (i.e., expectancy value) and Butler and Cartier (i.e., what the students bring to contexts under a self-regulated learning…
Descriptors: Design, Engineering Education, Expectation, Student Interests
Townsend, Cathy J. – ProQuest LLC, 2010
This quantitative, causal-comparative study utilized ex post facto data to examine the impact of education support advisors (ESAs) on the discipline, attendance, and achievement of at-risk students in Grades 3-12. Fourteen education support advisors working in 16 elementary and 8 secondary schools of this mid-Atlantic school district consistently…
Descriptors: Caring, African American Students, Discipline, Recognition (Achievement)
Hess, Robert T.; Robbins, Pam – Corwin, 2012
Using data for school improvement is a key goal of Race to the Top, and now is the time to make data-driven school improvement a priority. However, many educators are drowning in data. Boost your professional learning community's ability to translate data into action with this new book from Pam Robbins and Robert T. Hess. "The Data Toolkit"…
Descriptors: Data, Educational Improvement, Educational Change, Teamwork