Advanced Certificate in Educational Evaluation: Data Mastery

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The Advanced Certificate in Educational Evaluation: Data Mastery is a comprehensive course designed to empower educators and evaluation professionals with the skills to leverage data for improved educational outcomes. In an era of evidence-based decision making, this course is increasingly important, providing learners with the ability to collect, analyze, and interpret data to inform policy and practice.

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With a focus on industry-relevant skills, this certificate course equips learners with the tools to design and implement evaluation plans, understand statistical methods, and communicate findings effectively. This course not only enhances technical skills but also develops critical thinking and problem-solving abilities. In a competitive job market, the Advanced Certificate in Educational Evaluation: Data Mastery offers a distinct advantage, opening doors to various career advancement opportunities. Whether you're an educator, researcher, or evaluation specialist, this course provides the essential skills to excel in your field and make meaningful contributions to educational evaluation.

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Detalles del Curso

โ€ข Advanced Statistical Analysis: This unit covers various advanced statistical methods and techniques used in educational evaluation, such as regression analysis, factor analysis, and structural equation modeling.
โ€ข Data Visualization and Reporting: In this unit, students learn how to effectively present quantitative data and evaluation findings using data visualization tools and techniques, as well as how to write clear and concise evaluation reports.
โ€ข Survey Design and Implementation: This unit focuses on the principles and best practices of survey design and implementation, including question development, sampling, and data collection methods.
โ€ข Experimental Design and Quasi-Experimental Design: Students learn about the different types of experimental and quasi-experimental designs used in educational research and evaluation, including randomized controlled trials, regression discontinuity designs, and interrupted time series designs.
โ€ข Longitudinal Data Analysis: This unit covers the methods and techniques used to analyze longitudinal data, including multilevel modeling, growth curve modeling, and survival analysis.
โ€ข Multivariate Analysis: This unit covers the principles and techniques of multivariate analysis, including multiple regression, discriminant analysis, and factor analysis.
โ€ข Measurement and Evaluation: This unit focuses on the principles and best practices of measurement and evaluation in education, including the development and validation of assessment instruments and the use of data to inform decision making.
โ€ข Program Evaluation: This unit covers the principles and best practices of program evaluation, including the design and implementation of evaluations of educational programs and interventions.
โ€ข Data Ethics and Confidentiality: Students learn about the ethical and legal considerations surrounding the collection, storage, and use of educational data, including issues related to confidentiality, privacy, and informed consent.

Trayectoria Profesional

Requisitos de Entrada

  • Comprensiรณn bรกsica de la materia
  • Competencia en idioma inglรฉs
  • Acceso a computadora e internet
  • Habilidades bรกsicas de computadora
  • Dedicaciรณn para completar el curso

No se requieren calificaciones formales previas. El curso estรก diseรฑado para la accesibilidad.

Estado del Curso

Este curso proporciona conocimientos y habilidades prรกcticas para el desarrollo profesional. Es:

  • No acreditado por un organismo reconocido
  • No regulado por una instituciรณn autorizada
  • Complementario a las calificaciones formales

Recibirรกs un certificado de finalizaciรณn al completar exitosamente el curso.

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Tarifa del curso

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