Global Certificate in Education Analytics: Student Success Strategies

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The Global Certificate in Education Analytics: Student Success Strategies is a comprehensive course designed to meet the growing industry demand for data-driven decision-making in education. This certificate equips learners with essential skills to analyze student performance data, identify success strategies, and develop data-informed solutions to improve student outcomes.

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ใ“ใฎใ‚ณใƒผใ‚นใซใคใ„ใฆ

With a strong focus on practical applications, this course teaches learners to use cutting-edge tools and techniques to collect, analyze, and interpret data. Learners will also gain skills in communicating data insights effectively to various stakeholders, making data-informed decisions, and designing evidence-based policies and interventions. As data becomes increasingly critical in education, this course offers a unique opportunity for educators, administrators, policymakers, and researchers to advance their careers by gaining essential skills in education analytics. By completing this course, learners will be able to drive student success, improve educational outcomes, and contribute to a data-driven education system.

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ใฉใ“ใ‹ใ‚‰ใงใ‚‚ๅญฆ็ฟ’

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ๅพ…ๆฉŸๆœŸ้–“ใชใ—

ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข Unit 1: Introduction to Education Analytics: Understanding the role of data-driven decision making in student success.
โ€ข Unit 2: Data Collection Methods: Exploring quantitative and qualitative data sources for student success analysis.
โ€ข Unit 3: Data Analysis Techniques: Applying statistical methods and data visualization tools for interpreting student success data.
โ€ข Unit 4: Predictive Analytics in Education: Leveraging predictive models to identify at-risk students and inform intervention strategies.
โ€ข Unit 5: Implementing Early Warning Systems: Designing and deploying systems that monitor student progress and alert stakeholders to potential issues.
โ€ข Unit 6: Evidence-Based Interventions: Evaluating the effectiveness of intervention strategies and adjusting them based on data.
โ€ข Unit 7: Data-Informed Instructional Design: Using analytics to inform course design, delivery, and assessment.
โ€ข Unit 8: Ethical Considerations in Education Analytics: Ensuring privacy, security, and fairness in the use of student data.
โ€ข Unit 9: Collaboration and Communication: Building partnerships between educators, administrators, and data analysts to support student success.
โ€ข Unit 10: Continuous Improvement: Establishing a culture of data-driven decision making and ongoing evaluation in educational institutions.

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ใ‚ณใƒผใ‚นใ‚’ๅฎŒไบ†ใ™ใ‚‹ใฎใซใฉใ‚Œใใ‚‰ใ„ๆ™‚้–“ใŒใ‹ใ‹ใ‚Šใพใ™ใ‹๏ผŸ

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ใ“ใฎใ‚ณใƒผใ‚นใฎๆ”ฏๆ‰•ใ„ใฎใŸใ‚ใซไผš็คพ็”จใฎ่ซ‹ๆฑ‚ๆ›ธใ‚’ใƒชใ‚ฏใ‚จใ‚นใƒˆใ—ใฆใใ ใ•ใ„ใ€‚

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ใ‚ญใƒฃใƒชใ‚ข่จผๆ˜Žๆ›ธใ‚’ๅ–ๅพ—

ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
GLOBAL CERTIFICATE IN EDUCATION ANALYTICS: STUDENT SUCCESS STRATEGIES
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
London College of Foreign Trade (LCFT)
ๆŽˆไธŽๆ—ฅ
05 May 2025
ใƒ–ใƒญใƒƒใ‚ฏใƒใ‚งใƒผใƒณID๏ผš s-1-a-2-m-3-p-4-l-5-e
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