This website uses cookies, including third party ones, to allow for analysis of how people use our website in order to improve your experience and our services. By continuing to use our website, you agree to the use of such cookies. Click here for more information on our
and .overview
Key Learning Objectives
- Develop a basic working knowledge of data science and analytics applied to learning
- Master key concepts and techniques to build a successful learning analytics capability
- Explore the latest use cases and applications of analytics in education and learning
- Discover how privacy and ethics can play a pivotal role in education & learning analytics
- Develop an understanding of tools and technologies available for analytics
- Develop a learning analytics action plan for your school or educational institution
Delegates are requested to bring their laptops on day 2 of the course.
About the Course
Data and analytics have been a catalyst for transformation in many industries. In education, data science and analytics has the potential to vastly transform how learning happens. This course provides the latest concepts, tools and techniques to build, influence the development and manage the delivery of a successful learning analytics capability in schools and education institutions. Delivered through an interactive approach utilising the latest theories and tools, participants of this course are exposed to the latest developments in learning analytics, basic techniques of data science and various use cases and examples of how schools, universities and other education institutions have applied analytics in educational and learning contexts.
Participants are also exposed to the latest thinking in data strategy and managing data science and analytics teams and projects in educational settings.
Who Will Benefit
Anyone who wants to understand the role analytics plays in driving competitive advantage in educational institutions or schools and in student’s individual learning but have not had any (or major) exposure to the field. It can also be beneficial to those in education who want to pursue a change in career and work more closely with analytics, data science and machine learning capacity but have not had a chance to figure out how to go about it. Lastly, it can benefit anyone who works (or manages a team) in a business or technical role in education and uses data to answer questions, solve problems or build data-driven solutions but want to have a different, fresh perspective in the field.
Testimonials
“Really enjoyable course in an exciting and growing subject. Felipe was an enthusiastic, encouraging and engaging presenter!”
Business Intelligence Lead, Forensicare
“Felipe was very knowledgeable in skills, theory, best practices and current information on data visualisation. Very engaged and supportive in listening to our ideas and input with great discussions and teaching.”
Creative Designer, UNSW Sydney
Course Outline
DAY ONE
Understand the power and purpose of learning analytics
- History of learning analytics and adjacent topics, recent developments and future outlook
- Learning analytics as decision-making engine for educators and institutions
- Knowing your why, and what your learning analytics capability needs to achieve
Implementing a learning analytics capability
- Making sense of your educational institution’s capacity to build learning analytics
- Plotting a roadmap from conception to execution of learning analytics experiences
- In-depth understanding on what makes successful organisations do learning analytics right
Applications and case studies of learning analytics
- Discuss and illustrate main applications of analytics to improve learning
- How predictive analytics, adaptive learning and feedback are applied in learning analytics
- Practical interactive activities exploring use cases of learning analytics
Data, technology and privacy for successful learning analytics
- Overview of data, technology, privacy and ethics issues in a learning analytics environment
- Managing data and technology effectively and the importance of tool selection and usage
- Fundamentals for data manipulation in the context of learning analytics
DAY TWO
Data science fundamentals in the context of learning analytics
- Explore fundamental concepts of data science behind learning analytics
- Understand latest concepts in data science powering learning analytics solutions
- Working with predictive analytics models and basic algorithms in learning analytics
An exercise of predictive analytics in a fictitious learning environment
- Introduce and work through elements of a data science project with a fictitious example
- Explore and apply statistical learning models and methods for learning analytics
- Building analytics for student profiling, experience and retention strategies
Learning analytics feedback through data visualisation dashboards
- Selecting the right visualisation for feedback through dashboards
- Working with complex charts and data visualisations
- Creating a clear and accessible data visualisation model
Learning analytics in action
- Revisit main themes, tools, techniques and strategies
- Build a practical action plan to apply learning analytics to your institution or classroom
- Group discussion, final reflections and insights
On-site & in-house training
Deliver this course how you want, where you want, when you want – and save up to 40%! 8+ employees seeking training on the same topic?
Talk to us about an on-site/in-house & customised solution.
contact
Still have a question?
Sushil Kunwar
Training Consultant
+61 (0)2 9080 4395
training@informa.com.au