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Aarnes Gudmestad; Thomas A. Metzger – Language Learning, 2025
In this Methods Showcase Article, we illustrate mixed-effects modeling with a multinomial dependent variable as a means of explaining complexities in language. We model data on future-time reference in second language Spanish, which consists of a nominal dependent variable that has three levels, measured over 73 participants. We offer step-by-step…
Descriptors: Second Language Learning, Spanish, Applied Linguistics, Predictor Variables
Jacquelynne S. Eccles; Allan Wigfield – Educational Psychology Review, 2024
To address the seven guiding questions posed for authors of articles in this special issue, we begin by discussing the development (in the late 1970s-early 1980s) of Eccles' expectancy-value theory of achievement choice (EEVT), a theory developed to explain the cultural phenomenon of why girls were less likely to participate in STEM courses and…
Descriptors: Educational Theories, Academic Achievement, Females, Student Participation
Chi Kit Jacky Ng; Lok Yin Joyce Kwan; Wai Chan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In the past decade, moderated mediation analysis has been extensively and increasingly employed in social and behavioral sciences. With its widespread use, it is particularly important to ensure the moderated mediation analysis will not bring spurious results. Spurious effects have been studied in both mediation and moderation analysis, but this…
Descriptors: Mediation Theory, Social Sciences, Behavioral Sciences, Predictor Variables
Gabriele Morganti; Alexandra Lascu; Gennaro Apollaro; Laura Pantanella; Mario Esposito; Alberto Grossi; Bruno Ruscello – Sport, Education and Society, 2024
Talent identification and development systems (TIDS) adopt a deterministic perspective (i.e. athletes' future state/performances can be predicted by observations of their initial state/performance), which encourages early identification and specialisation in sport. In this framework, the main aim of sport systems is to enhance predictability and…
Descriptors: Talent Identification, Talent Development, Athletics, Athletes
Teacher Shortages: A Framework for Understanding and Predicting Vacancies. EdWorkingPaper No. 22-684
Danielle Sanderson Edwards; Matthew A. Kraft; Alvin Christian; Christopher A. Candelaria – Annenberg Institute for School Reform at Brown University, 2023
We develop a unifying conceptual framework for understanding and predicting teacher shortages at the state, region, district, and school levels. We then generate and test hypotheses about geographic and subject variation in teacher shortages using data on unfilled teaching positions in Tennessee during the fall of 2019. We find that teacher…
Descriptors: Teacher Shortage, Faculty Mobility, Predictor Variables, Public School Teachers
Nancy Montes; Fernanda Luna – UNESCO International Institute for Educational Planning, 2024
This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…
Descriptors: Data Collection, Data Use, At Risk Students, Foreign Countries
Yeh, Stuart S. – Education and Urban Society, 2020
Empirical results are consistent with the hypothesis that socioeconomic factors contribute to initial disparities in performance that are perpetuated by demoralizing grading, testing, and grouping practices throughout the K-12 years. The hypothesis may explain why the achievement gap increases after children enter the school system, why Black…
Descriptors: Accountability, Value Added Models, Achievement Gap, Racial Differences
Howell, Roy D.; Breivik, Einar – Measurement: Interdisciplinary Research and Perspectives, 2016
In this article, Roy Howell, and Einar Breivik, congratulate Aguirre-Urreta, M. I., Rönkkö, M., & Marakas, G. M., for their work (2016) "Omission of Causal Indicators: Consequences and Implications for Measurement," Measurement: Interdisciplinary Research and Perspectives, 14(3), 75-97. doi:10.1080/15366367.2016.1205935. They call it…
Descriptors: Causal Models, Measurement, Predictor Variables
Quille, Keith; Bergin, Susan – Computer Science Education, 2019
Background and Context: Computer Science attrition rates (in the western world) are very concerning, with a large number of students failing to progress each year. It is well acknowledged that a significant factor of this attrition, is the students' difficulty to master the introductory programming module, often referred to as CS1. Objective: The…
Descriptors: Computer Science Education, Introductory Courses, Programming, Student Attrition
New York State Education Department, 2020
This document describes the model used to measure student growth for institutional accountability in New York State for the 2018/19 school year and how three years of student growth results were combined to generate a three-year growth measure called the Growth Index. The Growth Index was first used in 2017/18 to make accountability…
Descriptors: Growth Models, Accountability, Scores, Predictor Variables
Rubin, Marc – New England Journal of Higher Education, 2017
The "2018 Guide to New England Colleges & Universities" data published by "Boston" magazine in association with the New England Board of Higher Education provided the author the opportunity to examine the schools' "prices," defined as "tuition plus fees," as a function of several independent factors. By…
Descriptors: Fees, Institutional Characteristics, Paying for College, Student Costs
New York State Education Department, 2019
This document describes the model used to measure student growth for institutional accountability in New York State for the 2017/18 school year and how three years of student growth results were combined to generate a three-year growth measure called the Growth Index. The Growth Index is new in 2017/18 and is used to make accountability…
Descriptors: Growth Models, Accountability, State Departments of Education, Scores
Swinson, Ronnie; Clark, Aaron C.; Ernst, Jeremy V.; Sutton, Kevin – Technology and Engineering Teacher, 2016
Today's engineers, designers, and technologists are often thrust into the role of problem solver, from the initial design phase of a product or process all the way to final development. Many engineers in manufacturing environments are tasked with solving problems and continuously improving processes to enhance company profitability, efficiency,…
Descriptors: Technology Education, Engineering Education, Simulation, Problem Solving
Jackson, C. Kirabo – Education Next, 2019
When students look back on their most important teachers, the social aspects of their education are often what they recall. Learning to set goals, take risks and responsibility, or simply believe in oneself are often fodder for fond thanks--alongside mastering precalculus, becoming a critical reader, or remembering the capital of Turkmenistan. The…
Descriptors: Teacher Effectiveness, Teacher Influence, Teacher Student Relationship, Secondary School Teachers
Balch, Ryan; Koedel, Cory – Education Policy Analysis Archives, 2014
State and local education agencies across the United States are increasingly adopting rigorous teacher evaluation systems. Most systems formally incorporate teacher performance as measured by student test-score growth, sometimes by state mandate. An important consideration that will influence the long-term persistence and efficacy of these systems…
Descriptors: Teacher Evaluation, Stakeholders, Teacher Attitudes, Observation