Joanna Zweig and César Idrovo discuss Discovery Curves - a model to chart a team’s ability to learn-, and a group improvement process using past experiences and identifying common characteristics.
Ruth Lennon discusses the challenges, the benefits and the lessons learned transitioning from a traditional education form to a BYOD in the cloud-based one.
Alex Adamopoulos emphasizes the need for hands-on learning, a method that is faster, cheaper and produces better results than taking some training or certification courses.
Chris Granger discusses the need for enhancing the learning tools starting from his own experience watching through a mirror people trying to solve problems at Microsoft.
Chris Matts discusses ways of learning - Kolb’s Circle of Learning, Meme Wombling, Hangover – with a focus on the cycle starting from Unconscious Incompetence to Conscious Competence.
Benjamin Mitchell believes that Kanban risks to become a fad if it does not cover gaps related to experiencing embarrassment and threat, proposing a solution based on the double-loop learning model.
Patrick Kua talks on the need to preserve an open mind and learning attitude while being on the craftsmanship journey from beginner to expert.
Jon Jagger on achieving expertise through deliberate practice, a process of doing new things or old ones but with a new approach, leading to improved technical agility through increased self awareness
Karl Scotland on Kanban as a way of creating a model improving a business’ capability to meet its purpose based on systems thinking, workflow, visualization, work in process, cadence, and learning.
Liz Keogh talks about perverse incentives that hinder the ability to reach the purpose for which they were created for, outlining the need to focus on the system built not its solutions.
Fraser Speirs presents how computers are used at Cedars School, makes some suggestions on what educational software needs in order to be efficient, and how he sees the future of ICT in education.
Mike Lee considers that a software engineer makes great applications not because he follows good rules but because he has a better way of looking at the world and he learns from experience.