Making a computer game
SMLG’ (Self Managed League Gaming) is a game creation project that has been supported by learning advisor Louis since March. Its goal is to create a small 2d platform game, made entirely by students on the team. There is a real range of skills between them, and it’s been brilliant to see them working together and filling in one another’s weaknesses.
It has been a slow process, but we now have a variety of gameplay experiments and prototypes, as well as a mass of excellent pixel art, sound effects (two things that none of the children had previously done) storyboarding/writing and music. It has been amazing to witness their enthusiasm over the game, and to collaborate effectively both inside college without any supervision or prompting and through an online program called ‘Discord’. The students each have one or more roles within the team, and have settled into their specialisations but have not been shy to try new things and help one another out.
Recently we had a rare opportunity to visit a professional games studio (Studio Gobo), which everyone found inspiring and fun. The students had a chance to hear from representatives from seven different departments, who gave great explanations of what their jobs were, the ins and outs of their roles and how they got into the industry. The group was extremely well-behaved and mature, and Studio Gobo said they would be happy for us to return.
The game is far from finished, we hope by the end of next term to have a fully functioning demo. One of the older students who is leaving SML College to go to FE College has stated that she would like to continue working on it over the summer, via Discord, which we all found very impressive and encouraging.
“Machine learning and human intelligence. The future of education for the 21st-century.”
The title of this review is the title of Rose Luckin’s latest book and Rose delivered our Presidential Lecture on July 8 at SML College on this topic. Her chair at UCL Institute of Education is in Learner Centred Design. It’s in that capacity that we have worked together in the past and in her latest book she does make reference to research that she did with our students in SML College. So I can’t suggest that this review is a totally independent and unbiased piece.
We have both been totally committed to the notion of learner centred design in terms of the use of AI and computers. Too often shiny new technology has been introduced with little understanding of the context in which is being used and its value (or otherwise) to learners. Our approach in SML College is the same as Rose’s in that the first need is to find out what learners need to learn and then think about how to use the technology (if at all). We need to start with the problem and then go to the appropriate solution (which may be AI or may not), whereas, too often, the techie experts have started with the solution, namely a piece of hardware or software that they then want to attach to a problem or in some cases distort the problem to fit what they have available.
In her new book, she is especially careful to locate AI in its full educational and social context. For instance, she emphasises how as humans what we offer is an ability to work together and to bring a social intelligence to decisions about the application of AI (something AI alone cannot do). She shows how the limited view of learning that has dominated education is unhelpful. If education is just about drilling students in facts and data, then the role of the teacher can be replaced by AI . However for proper human learning the collaboration of learners is central and it’s where AI cannot contribute.
She takes a broader view of intelligence than the stance of IQ-driven educators. Social intelligence is central to human development and how we can best utilise AI in the future. The title of her book is apt, because a great deal of it is actually discussing the way we think about intelligence and the importance of, for instance, metacognition. It is like the process we use in SML College right at the start of the student’s life with us, namely having to think about the way that you think. If we are just thinking within boundaries that are imposed on us, as is the case typical schooling, then that’s an impoverished education. We have to be able to step back and understand, for instance, what we know and what we don’t know and how we can develop our knowledge and skills in a broader context. One of the many areas that she points out, is the notion of achieving mastery in a subject. It requires us to develop a way of thinking about what mastery means and to pursue that to the full, not through competing with others, but from having a real sense of what we mean by the learning we want to undertake. This includes the ability to self-assess – again a process mostly omitted in formal education but which is an important part of Self Managed Learning.
This capability is part of what is technically labelled as self-efficacy. To quote from Rose’s book. “An accurate perceived self-efficacy, based on accurate judgements about what we know, is a key ability for learning and will be so to an increased extent. It will be the most important ability for our future lifelong learning. It is also something that is unavailable to AI.” (Page 131). You can see from this view that she does not approach AI in a gung-ho mode as the answer to all our educational problems. Her balanced and sophisticated analysis is a breath of fresh air in the simplistic debates about AI. Paradoxically this is both a strength and a weakness of the book. Its strength is in the thoroughness of a world leader in her field. Its weakness is that it demands an open minded and in-depth take on a complex subject – and too many people are looking for the simple and easy answers they won’t get from the book.
Ian Cunningham July 2019
The book is “Machine Learning and Human Intelligence. The future of education for the 21st century’ published by UCL Institute of Education Press, 2018.