有想做一个关于教师使用AI技术的培训

European country.Our world-leading status is down to our thriving research base and the pipeline ofA pro-innovation approach to AI regulationexpertise graduating through our universities,the ingenuity of our innovators and the government’slong-term commitment to invest in AI.To ensure we become an AI superpower,though,it is crucial that we do all we can to create the rightenvironment to harness the benefits of AI and remain at the forefront of technological developments.That includes getting regulation right so that innovators can thrive and the risks posed by AI can beaddressed.These risks could include anything from physical harm,an undermining of national security,as well asrisks to mental health.The development and deployment of AI can also present ethical challengeswhich do not always have clear answers.Unless we act,household consumers,public services andbusinesses will not trust the technology and will be nervous about adopting it.Unless we build publictrust,we will miss out on many of the benefits on offer.Indeed,the pace of change itself can be unsettling.Some fear a future in which AI replaces ordisplaces jobs,for example.Our white paper and our vision for a future AI-enabled country is one inwhich our ways of working are complemented by AI rather than disrupted by it.In the modern world,toomuch of our professional lives are taken up by monotonous tasks – inputting data,filling out paperwork,scanning through documents for one piece of information and so on.AI in the workplace has thepotential to free us up from these tasks,allowing us to spend more time doing the things we trained for– teachers with more time to teach,clinicians with more time to spend with patients,police officers withmore time on the beat rather than behind a desk – the list goes on.Indeed,since AI is already in our day-to-day lives,there are numerous examples that can help toillustrate the real,tangible benefits that AI can bring once any risks are mitigated.Streaming services

The scariest thing about cognitive atrophy is that it’s hard to notice in the moment.With physical muscles,I can feel a difference.A year ago,I got busy and stopped lifting weights for two months.I felt a difference when I lifted a couch or when I was carrying a lot of groceries.I knew,in my daily life,that I needed to get back to the gym.But in the case of Google Maps,it happened without me realizing it at all.I thought I had retained my spatial reasoning skills because I had used them for two decades.But then,they evaporated and I didn’t noticed it until it was too late.As educators,we want to take a vintage innovation approach that embraces the overlap of old school tools and new technology.We want to embrace the overlap of best practices and next practices:But this requires an intentionality that can be a challenge in a tech-infused world.We start using auto-fill in Google and don’t realize we’re using it.We go to ChatGPT to design some scaffolds and supports and we don’t realize that we have stopped thinking intentionally about it.One potential solution is to track how often we use AI.As educators,we can do a time audit where we track how often we use AI versus engaging in a fully human-centered approach.We can step away from the tech and ask if we are growing too dependent on machine learning.We might even choose deliberate times to be fully tech-free.In the end,cognitive atrophy will be one of the most significant challenges of AI.As educators,we need to be intentional about how we use it professionally and with our students so that we don’t off-load the thinking to a machine.We need to draw students into these conversations as well so that they can learn to use AI wisely as they navigate an uncertain future.

In terms of learning,we also need to engage in hands-on,minds-on,technically minimal learning in order to master a skill.In other words,we shouldn’t use AI when we are first learning a new skill.When Learning a Skill,Start with the Human Element FirstI reached out to my friend Trevor Muir and asked him,“What would you recommend to tackle the problem of cognitive atrophy?” His response was,“I love this topic.I’ve been thinking about it in writing.I don’t think teachers should use AI with students in writing until students have mastered it first.”If we ask students to use AI for writing,they need to know what good writing looks like.That takes time.And effort.And a whole bunch of mistakes.If we want students to edit an AI generated text with their own voice,we need them to find their creative voice first.This is true of AI in writing but also AI in math.We don’t want students using AI to check their processes if they haven’t first learned the mathematical process.It’s true of computer coding,where we might start with a Scratch project,then hand-written code,then an AI and coding hybrid.Be Deliberate About What You Off-Load to AIA couple of months ago,I wrote about seven things we should consider when deciding to use AI.People often ask,“When is it okay to use AI?” The short answer is,“It depends on the learning task.” In using AI,we don’t want the machine to do the learning for us.This is why we should start with the learning tasks and then ask,“Does the AI help or hinder the learning in this situation?” The core idea here is that we need to use the learning targets to drive the AI and not the other way around.If you’re teaching a coding class,you might want to be tight with students on using generative AI to create any kind of code.You might want students to learn how to code by hand first and then,after mastering the language,use AI-generated code as a time-saving device.