Course:
"Defining the Best Education: Metrics, Comparative Analysis and Insights"
Language:
EN
Form:
on-line
Duration:
5 hours (on-line)
+30 min. break
+30 min. break
Aligned with SDG:
Place:
Dates:
Lang.:
ON-LINE
5 Oct. 2025
ON-LINE
22 Nov. 2025
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COURSE OBJECTIVE:
The objective of this course, "Defining the Best Education: Metrics, Comparative Analysis, and Insights", is to provide participants with a clear understanding of how to assess and define the best educational systems using data-driven metrics and comparative analysis. By the end of this course, participants will gain the tools and knowledge necessary to critically evaluate educational frameworks and identify key indicators that contribute to their success.
This course will cover various metrics, including academic performance, access to resources, teacher quality, and student outcomes. Participants will learn how to compare these metrics across different educational systems, with a focus on international case studies and the Happy City Index project, which uses data to shape urban policies and enhance quality of life.
Leveraging my experience in data analysis, I will guide participants in understanding data integrity, sourcing, and how to interpret complex educational data for actionable insights. Participants will learn how to use these insights to propose data-backed strategies aimed at improving educational policies and practices in their cities or countries.
This course is designed for policymakers, educators, and data analysts who are interested in using data to improve educational systems. Whether participants aim to enhance the educational offerings in their own cities or contribute to global educational research, this course will provide them with the analytical tools and insights needed to achieve their goals.
The objective of this course, "Defining the Best Education: Metrics, Comparative Analysis, and Insights", is to provide participants with a clear understanding of how to assess and define the best educational systems using data-driven metrics and comparative analysis. By the end of this course, participants will gain the tools and knowledge necessary to critically evaluate educational frameworks and identify key indicators that contribute to their success.
This course will cover various metrics, including academic performance, access to resources, teacher quality, and student outcomes. Participants will learn how to compare these metrics across different educational systems, with a focus on international case studies and the Happy City Index project, which uses data to shape urban policies and enhance quality of life.
Leveraging my experience in data analysis, I will guide participants in understanding data integrity, sourcing, and how to interpret complex educational data for actionable insights. Participants will learn how to use these insights to propose data-backed strategies aimed at improving educational policies and practices in their cities or countries.
This course is designed for policymakers, educators, and data analysts who are interested in using data to improve educational systems. Whether participants aim to enhance the educational offerings in their own cities or contribute to global educational research, this course will provide them with the analytical tools and insights needed to achieve their goals.
COURSE LEADERS:
I am a data analyst with over five years of experience in data processing and analysis across various industries, including technology, education, immigration, and petrochemicals. My expertise includes utilizing Power BI, SQL, and Python, as well as applying machine learning techniques to extract meaningful insights from complex datasets.
I hold a Master’s degree in Computer Science from Kharazmi University, and throughout my professional journey, I have participated in various international projects and research initiatives. Additionally, I have completed multiple international training courses in machine learning, further strengthening my knowledge and skills in this field.
With a strong passion for data analysis and knowledge sharing, I am eager to contribute to this training program by sharing my experiences and helping participants develop and apply data-driven skills effectively.
The course will be led by Bartosz Bartoszewicz, a highly accomplished former Deputy Mayor with nearly two decades of experience in local government. Throughout his distinguished career, he has been at the forefront of urban transformation and digital innovation, winning the prestigious Innovation in Politics Award, organised by the Austrian Innovation in Politics Institute. This recognition highlights his outstanding contribution to advancing smart city initiatives and improving quality of life through innovative policies.
Bartosz holds a Doctorate, with his doctoral thesis focusing on the quality of life in urban areas—an area that remains central to his work in public administration and city management. As an academic lecturer, he has taught sharing his knowledge and expertise with the next generation of leaders and urban policymakers. His extensive experience in both theory and practice has enabled him to bridge the gap between academic research and real-world application, enriching his teaching and professional approach.
In addition to his academic work, Bartosz delivered presentations at international conferences on urbanisation, sustainable city management, and digital transformation. His insights have shaped discussions on the future of cities, particularly regarding the integration of smart technologies and sustainable urban planning. His work provides a deep dive into how cities can harness technology to improve residents' lives while promoting sustainability and resilience.
With a career spanning leadership, academia, and international speaking engagements, Bartosz Bartoszewicz offers a wealth of knowledge and practical insights. He combines the experience of a long-serving mayor with a solid academic foundation, providing a unique perspective on the challenges and opportunities of urban transformation. Participants in the course will gain invaluable knowledge from his diverse background, exploring both the practical and theoretical aspects of innovation, urban management, and smart city development.
PROGRAM
Module 1. Introduction to Education Metrics and Data Analysis
- Overview of educational systems and their key components
- Introduction to educational metrics: academic performance, teacher quality, student outcomes
- The role of data analysis in evaluating education
- Overview of educational systems and their key components
- Introduction to educational metrics: academic performance, teacher quality, student outcomes
- The role of data analysis in evaluating education
Module 2: Key Metrics for Defining Quality Education
- In-depth analysis of key educational indicators
- How to measure and compare different educational systems
- Understanding global educational frameworks
- In-depth analysis of key educational indicators
- How to measure and compare different educational systems
- Understanding global educational frameworks
Module 3: Comparative Analysis of Educational Systems
- Techniques for comparative analysis
- Case studies from various countries (including data from the Happy City Index project)
- Identifying strengths and weaknesses in different educational systems
- Techniques for comparative analysis
- Case studies from various countries (including data from the Happy City Index project)
- Identifying strengths and weaknesses in different educational systems
Module 4: Practical Tools for Analyzing Educational Data
- Introduction to data visualization tools and techniques
- How to interpret and present data effectively
- Hands-on exercises using educational datasets (online tools provided)
- Introduction to data visualization tools and techniques
- How to interpret and present data effectively
- Hands-on exercises using educational datasets (online tools provided)
Module 5: Using Data for Policy Recommendations
- How to transform data insights into actionable policy suggestions
- Best practices for presenting data-driven recommendations
- Real-world examples from global educational research
- How to transform data insights into actionable policy suggestions
- Best practices for presenting data-driven recommendations
- Real-world examples from global educational research
Module 6: Wrap-Up and Q&A
- Recap of key learnings from the day.
- Open floor for questions and discussion.
- Next steps and further resources for continued learning.
Module: Workshops in groups
An online course is an excellent opportunity to broaden your knowledge. However, we recognise that a significant value of courses lies in the exchange of experiences among participants. This requires a certain level of openness and willingness to collaborate, which can sometimes only be fully unlocked through face-to-face interaction and the use of appropriate workshop solutions. That is why the programme for in-person courses includes 'Workshops in groups using real documents and a selected workshop format,' lasting approximately 90 minutes. These workshops are conducted during the second part of the course.
COURSE METHOLODOGY:
The course will be delivered entirely online, using a combination of theoretical content and practical exercises to engage participants and ensure effective learning. The methodology will focus on a blended learning approach, integrating lectures, case studies, and interactive activities.
Theoretical Content: Each session will begin with a structured lecture to introduce key concepts, frameworks, and metrics related to education. This will provide participants with a solid foundation in the subject matter.
Interactive Discussions: Following the lectures, participants will engage in discussions to explore real-world applications of the topics covered. These discussions will be moderated in real-time, allowing for dynamic interaction between participants.
Practical Exercises: A key feature of the course will be the hands-on exercises, where participants will analyze educational data using online tools. This will enable them to apply the theoretical concepts learned in a practical context.
Case Studies: Throughout the course, case studies from various countries and educational systems will be presented. Participants will analyze these case studies, comparing data and identifying trends, strengths, and weaknesses.
Feedback and Reflection: At the end of each session, participants will be given the opportunity to ask questions, reflect on the content, and receive feedback. This ensures that the learning process is continuous and that participants have the opportunity to clarify any doubts.
The course will be designed to encourage active participation, critical thinking, and the development of practical skills necessary for analyzing educational data.
The course will be delivered entirely online, using a combination of theoretical content and practical exercises to engage participants and ensure effective learning. The methodology will focus on a blended learning approach, integrating lectures, case studies, and interactive activities.
Theoretical Content: Each session will begin with a structured lecture to introduce key concepts, frameworks, and metrics related to education. This will provide participants with a solid foundation in the subject matter.
Interactive Discussions: Following the lectures, participants will engage in discussions to explore real-world applications of the topics covered. These discussions will be moderated in real-time, allowing for dynamic interaction between participants.
Practical Exercises: A key feature of the course will be the hands-on exercises, where participants will analyze educational data using online tools. This will enable them to apply the theoretical concepts learned in a practical context.
Case Studies: Throughout the course, case studies from various countries and educational systems will be presented. Participants will analyze these case studies, comparing data and identifying trends, strengths, and weaknesses.
Feedback and Reflection: At the end of each session, participants will be given the opportunity to ask questions, reflect on the content, and receive feedback. This ensures that the learning process is continuous and that participants have the opportunity to clarify any doubts.
The course will be designed to encourage active participation, critical thinking, and the development of practical skills necessary for analyzing educational data.
COURSE SUMMARY:
This course will be delivered entirely online, focusing on educational data analysis, various educational metrics, and how to use these data to improve the quality of education. Participants will become familiar with key concepts such as evaluating academic performance, teacher quality, and student outcomes. The course will also delve into comparative analysis of different educational systems, using global data to gain a better understanding of these systems.
Each session will begin with an introduction to theoretical content and key concepts, and participants will analyze and evaluate educational systems using data. Case studies from various countries will be presented to compare and identify the strengths and weaknesses of different educational systems.
The objective of this course is to enhance participants' skills in analyzing educational data, foster critical thinking, and develop a deeper understanding of how to measure and assess educational quality. Upon completing the course, participants will be able to conduct more accurate educational analyses and use data to provide policy recommendations and improve educational systems.
This course will be delivered entirely online, focusing on educational data analysis, various educational metrics, and how to use these data to improve the quality of education. Participants will become familiar with key concepts such as evaluating academic performance, teacher quality, and student outcomes. The course will also delve into comparative analysis of different educational systems, using global data to gain a better understanding of these systems.
Each session will begin with an introduction to theoretical content and key concepts, and participants will analyze and evaluate educational systems using data. Case studies from various countries will be presented to compare and identify the strengths and weaknesses of different educational systems.
The objective of this course is to enhance participants' skills in analyzing educational data, foster critical thinking, and develop a deeper understanding of how to measure and assess educational quality. Upon completing the course, participants will be able to conduct more accurate educational analyses and use data to provide policy recommendations and improve educational systems.
TERMS AND CONDITIONS FOR COURSES AND TRAININGS SESSIONS OF HAPPY CITY ACADEMY - SELECTED KEY RULES:
Enrollment
Enrollment is confirmed upon submitting a completed enrollment form and paying the Initial Payment of £30. The remaining balance must be paid at least 30 days before the course starts. For enrollments made less than 30 days before the start date, payment of the full course fee is required at the time of enrollment.
Confirmation
Participants will receive a confirmation email, including the course schedule, venue or platform details, and contact information.
Withdrawal Rights
Participants may withdraw within 14 days of enrollment for a full refund, including the Initial Payment.
Terms and Conditions for Courses and Training Sessions of Happy City Academy
Enrollment is confirmed upon submitting a completed enrollment form and paying the Initial Payment of £30. The remaining balance must be paid at least 30 days before the course starts. For enrollments made less than 30 days before the start date, payment of the full course fee is required at the time of enrollment.
Confirmation
Participants will receive a confirmation email, including the course schedule, venue or platform details, and contact information.
Withdrawal Rights
Participants may withdraw within 14 days of enrollment for a full refund, including the Initial Payment.
Terms and Conditions for Courses and Training Sessions of Happy City Academy
COSTS OF PARTICIPATING IN THE COURSE:
