Paul McDonagh-Smith is Digital Capability Leader at Massachusetts Institute of Technology. He has led teams to imagine, build, and bring to market innovative and groundbreaking Collaboration and Education Platforms. In his work with MIT Sloan’s Office of Executive Education, Paul partners with internal and external stakeholders to design, deliver and embed technology based education solutions to complex challenges, through a collaborative blend of technology, systems thinking, research, rapid prototyping and experimentation which strengthens creativity, productivity, and digital capabilities.
We sat down with him ahead of his presentation at the Data Visualisation Summit, taking place in London this November 16-17.
What role does data visualization play in your role at MIT?
In essence, Data Visualization supports two crucial aspects of our online learning experiences: sense-making and communication. Advances and evolutions in the diversity and depth of data sets that sit behind Visualization bring us nearer to an understanding of key dynamics of online teaching and learning. Clear, concise Data Visualization provides an evidence-based analysis of educational experiences that can be a powerful catalyst for change and improved outcomes. Interestingly, they also provide an opportunity to capture insights that have the potential to improve in-person learning experiences.
What are the biggest data viz challenges that you currently face in your role?
Data Visualization provides the opportunity to identify areas where we can improve teaching and learning experiences and outcomes. In order to secure this opportunity we need to be mindful of:
§ Context of the data
§ Visualizing what matters
§ Ensuring data quality
§ Relevance of outlier data
§ Building Visualization into Improvement process
What will you be discussing in your presentation at Data Visualization London?
The objective of the presentation will be to provide real world examples of how we are currently using Data Visualization to enhance online teaching and learning experiences. I will aim to show how Data Visualization enables the creation, capture and delivery of new educational value. An effort will be made to address key challenges/future ambitions.
Are there any approaches or technologies that you see impacting data visualization the most in the next 5 years?
In the near term (0-24 months) we might reasonably suspect that a range of approaches and technologies could significantly impact Data Visualization, including:
§ AI enhanced simulations | scenario planning
§ Mobile Data Visualization toolkits
§ Personal Data Visualization interfaces and management
§ Video Display of Data Visualization insights
You can hear more from Paul, along with other industry leaders, at the Data Visualisation Summit in November. You can view the full agenda here.