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Tamir, Emanuel; Grabarski, Mirit K. – Journal of Educational Administration, 2020
Purpose: This paper aims to apply the garbage can model to identify factors that affect managerial decision-making processes in educational systems undergoing reforms. Design/methodology/approach: This paper used a qualitative approach using semi-structured interviews with 39 teachers and managers in schools undergoing a system-wide reform.…
Descriptors: Educational Change, Educational Administration, Decision Making, Risk
Ezquerra, Angel; Fernandez-Sanchez, Belen; Magana, Marina; Mingo, Beatriz – Journal of Turkish Science Education, 2017
The necessity of an adequate scientific literacy among the population in general and students in particular is a fact. Two of the main obstacles in science education that hinder it are the lack of connection between the contents worked in class and the students' day-to-day, and the misunderstanding of scientific language. In the present study, a…
Descriptors: Scientific Literacy, Science Education, Scientific Concepts, Language Usage
Washington-Ottombre, Camille; Bigalke, Siiri – International Journal of Sustainability in Higher Education, 2018
Purpose: This paper aims to compose a systematic understanding of campus sustainability innovations and unpack the complex drivers behind the elaboration of specific innovations. More precisely, the authors ask two fundamental questions: What are the topics and modes of implementation of campus sustainability innovations? What are the external and…
Descriptors: Higher Education, Educational Innovation, Sustainability, Program Implementation
Willhide, Robert Jesse – US Census Bureau, 2014
This report is part of a series of reports that provides information on the structure, function, finances, taxation, employment, and pension systems of the United States' approximately 90,000 state and local governments. This report presents data on state and local government employment and payroll based on information collected by the 2013 Annual…
Descriptors: Surveys, Government Employees, Statistical Analysis, Income