Introduction to Data Wise: A Collaborative Process to Improve Learning & Teaching from edX

Educators have an ever-increasing stream of data at their fingertips, but knowing how to use this data to improve learning and teaching — how to make it less overwhelming, more useful, and part of an effective collaborative process — can be challenging.

Based on the book Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning, this course describes a clear, 8-step process for using a wide range of data sources to improve instruction. You will see what this disciplined way of working with colleagues can look and feel like in a school setting. You will also have the opportunity to share insights and experiences about school improvement with educators from around the world.

Introduction to Data Wise is open to all but is especially valuable for teachers and school and district leaders, as well as policymakers, and educational entrepreneurs who are dedicated to improving outcomes for students. There are several ways you could take this course:

Participate on your own.
Enroll with a few colleagues as part of a study group.
Formally integrate it into professional development in your workplace.

It is a self-paced course. You can go through the essential materials in a day or take several weeks to allow for reflection. There will be one month of active course facilitation, which will include discussion board moderation, office hours, and other live events.

This course provides an introduction to a rich portfolio of books, resources, training, and support developed by the Data Wise Project at the Harvard Graduate School of Education. The Data Wise Project works in partnership with teachers and school and system leaders to develop and field-test resources that support collaborative school improvement. We encourage you to explore these resources as you chart a course for using data to improve learning and teaching for all students.

What's inside

Learning objectives

Understand what the data wise improvement process is and how it can help you improve teaching and learning
Build skills in looking at a wide range of data sources, including test scores, student work, and teaching practice

Identify next steps in supporting a culture of collaborative data inquiry in your setting

Understand what the data wise improvement process is and how it can help you improve teaching and learning
Build skills in looking at a wide range of data sources, including test scores, student work, and teaching practice
Identify next steps in supporting a culture of collaborative data inquiry in your setting

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores how to use data to improve teaching and learning

Involves a hands-on approach to improving teaching and learning

Teaches skills in analyzing data from various sources

Designed for educators, including teachers and school leaders, who seek to improve student outcomes

Provides flexibility in course participation, allowing for self-paced or group-based learning

Offers opportunities for discussion and collaboration with educators worldwide

Reviews summary

Well received course

According to students, this course is well received. Learners are satisfied with the course, finding it interesting and useful. One student even expressed their interest in being accepted into the course. If you're interested in a course that is engaging, this may be the course for you.

The course was found to be interesting and useful.

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Data Wise: A Collaborative Process to Improve Learning & Teaching with these activities:

Review basic statistics concepts

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Review foundational statistics concepts to prepare for this course which extensively uses statistical data analysis.

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Revisit probability theory and distributions
Review hypothesis testing and confidence intervals
Practice interpreting statistical results

Seek Mentorship from Experienced Data Scientists

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Connect with experienced data scientists to gain insights, guidance, and support throughout the course.

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Identify potential mentors
Reach out and introduce yourself
Schedule regular meetings

Explore Data Analysis with Python

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Complete tutorials to familiarize yourself with Python programming and data analysis libraries used in this course.

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Set up your Python environment
Learn basic Python syntax and data structures
Explore data manipulation and visualization libraries

Six other activities

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Read 'Data Science for Business'

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Expand your understanding of data science concepts and their application in business.

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Read the book thoroughly
Take notes and summarize key concepts
Connect concepts to real-world business examples

Build a Data Analysis Portfolio

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Start a project where you collect, analyze, and visualize data to practice skills learned in the course.

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Identify a dataset of interest
Explore and clean the data
Perform statistical analysis
Create data visualizations
Write a project report

Join a Data Science Study Group

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Collaborate with peers to discuss course concepts, work on assignments, and prepare for assessments.

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Find or create a study group
Set regular meeting times
Prepare discussion topics

Solve Data Analysis Practice Problems

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Practice solving data analysis problems to reinforce concepts and improve problem-solving skills.

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Find practice problems online or in textbooks
Attempt to solve the problems independently
Review solutions and identify areas for improvement

Attend Machine Learning Workshops

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Enhance your skills by attending workshops focused on specific machine learning algorithms and techniques.

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Identify upcoming workshops
Register and attend the workshops
Actively participate and take notes

Create Infographics on Data Analysis Concepts

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Deepen your understanding by creating visual representations of complex data analysis concepts.

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Choose a data analysis concept
Gather and analyze data
Design and create an infographic

Career center

Learners who complete Introduction to Data Wise: A Collaborative Process to Improve Learning & Teaching will develop knowledge and skills that may be useful to these careers:

Teacher

Teachers facilitate learning and provide instruction to students in schools and other educational settings. This course can be extremely valuable for Teachers, as it focuses on using data to improve teaching and learning. Participants will gain skills in analyzing student data, identifying areas for improvement, and implementing data-driven strategies to enhance instruction. The emphasis on collaborative data inquiry can also be beneficial, as Teachers often work with colleagues to develop and implement effective teaching practices.

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Educational Researcher

Educational Researchers conduct research to improve teaching and learning methods and educational policies. The course's emphasis on using data to inform decision-making aligns well with the work of Educational Researchers. Participants will gain skills in analyzing and interpreting a wide range of data sources, which is essential for conducting educational research. The collaborative approach to data inquiry fostered in the course can also be valuable, as Educational Researchers often work with educators and policymakers to implement research findings.

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Data Analyst

Data Analysts collect, clean, and analyze data to help businesses and organizations make informed decisions. The skills developed in this course, such as examining various data sources, identifying trends, and drawing insights, can provide a solid foundation for a career as a Data Analyst. The course's focus on collaborative data inquiry can also be valuable in this role, as Data Analysts often work with teams to interpret and communicate data.

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Research Analyst

Research Analysts collect, analyze, and interpret data to help businesses and organizations make informed decisions. The skills developed in this course, such as data analysis, interpretation, and communication, are highly relevant to Research Analysts. The collaborative approach to data inquiry fostered in the course can also be valuable, as Research Analysts often work with teams to gather and interpret data.

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Principal

Principals lead and manage schools, overseeing educational programs and administrative operations. This course can be beneficial for aspiring and current Principals, as it provides a framework for using data to improve school performance. Participants will gain skills in analyzing school data, identifying areas for improvement, and developing data-driven strategies to enhance teaching and learning. The emphasis on collaborative data inquiry can also be valuable, as Principals often work with teachers and other stakeholders to develop and implement school improvement plans.

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Superintendent

Superintendents lead and manage school districts, overseeing educational programs and administrative operations across multiple schools. This course may be useful for those interested in becoming Superintendents, as it provides a framework for using data to improve district-wide performance. Participants will gain skills in analyzing district data, identifying areas for improvement, and developing data-driven strategies to enhance teaching and learning across the district. The emphasis on collaborative data inquiry can also be valuable, as Superintendents often work with principals, teachers, and other stakeholders to develop and implement district improvement plans.

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Learning and Development Manager

Learning and Development Managers plan, implement, and evaluate employee training and development programs within organizations. This course aligns with the responsibilities of Learning and Development Managers, providing knowledge about data-informed decision-making and collaborative approaches to improving teaching and learning. By understanding how to use data to identify learning needs and evaluate program effectiveness, participants can contribute to the design and delivery of impactful learning and development initiatives.

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Instructional Coach

Instructional Coaches support and mentor teachers to improve their teaching practices. This course aligns well with the work of Instructional Coaches, as it emphasizes the use of data to inform instructional decision-making. Participants will gain skills in analyzing student data, identifying areas for improvement, and providing data-driven feedback to teachers. The collaborative approach to data inquiry can also be valuable, as Instructional Coaches often work with teachers to develop and implement effective teaching strategies.

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Quantitative Researcher

Quantitative Researchers use statistical methods to analyze data and draw conclusions. This course aligns well with the work of Quantitative Researchers, as it emphasizes the use of data to inform decision-making. Participants will gain skills in collecting, analyzing, and interpreting data, which are essential for conducting quantitative research. By understanding how to use data to identify patterns and trends, participants can contribute to a deeper understanding of complex issues.

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Instructional Designer

Instructional Designers develop and deliver instructional materials and programs to meet specific learning needs. This course can provide a solid foundation for Instructional Designers, as it emphasizes data-driven decision-making and the collaborative development of instructional materials. Gaining skills in analyzing data and identifying trends can help Instructional Designers create effective and engaging learning experiences.

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Policy Analyst

Policy Analysts research, analyze, and make recommendations on public policies. This course can be beneficial for Policy Analysts as it provides a structured approach to using data to inform policy decisions. Participants will gain skills in identifying relevant data sources, analyzing trends, and drawing conclusions, which are essential for effective policy analysis. The collaborative approach to data inquiry emphasized in the course can also be valuable, as Policy Analysts often work with stakeholders to develop and implement policies.

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Program Evaluator

Program Evaluators assess the effectiveness of social programs and interventions. This course provides valuable knowledge and skills for Program Evaluators, as it focuses on using data to measure and analyze the impact of programs. Participants will learn how to collect, analyze, and interpret data to make evidence-based recommendations for program improvement.

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Curriculum Developer

Curriculum Developers design, develop, and evaluate educational curriculum for schools, businesses, and other organizations. This course may be useful, providing foundational knowledge about how to use data to improve teaching and learning, which is crucial in curriculum development. The emphasis on collaborative data inquiry can be particularly valuable as curriculum developers often work with teachers and other educators to develop and implement curriculum.

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Higher Education Administrator

Higher Education Administrators manage the operations of colleges and universities. This course may be useful for those interested in Higher Education Administration, as it provides a framework for using data to improve decision-making in educational settings. Participants will gain skills in identifying and analyzing data, developing data-driven strategies, and evaluating the impact of decisions. These skills can be valuable for Higher Education Administrators who seek to improve student outcomes, enhance operational efficiency, and make informed decisions.

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Data Science Manager

Data Science Managers lead teams of data scientists and oversee data science projects. While this course may not be directly related to the technical aspects of data science, it can provide a foundation in data-driven decision-making, which is essential for Data Science Managers. By understanding how to use data to identify problems, develop solutions, and measure outcomes, participants can effectively manage data science teams and contribute to the success of data science projects.

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