Generative Artificial Intelligence in Teaching, Learning and Assessment Centre for Innovation in Education
Generative artificial intelligence in education: call for evidence Department for Education Citizen Space
This course is suitable for those with no previous experience in Generative AI, coding, or machine learning. Generative AI has not only captured the attention of tech enthusiasts and researchers but has also started to permeate the education sector, significantly impacting students and the future of employment. The rise of this transformative technology raises intriguing questions about the role it plays in shaping educational experiences and the implications it has on the evolving job market. Join us for a free 2.5-hour training session that provides an introduction to the basics of Generative AI and its use cases, with a focus on Google Cloud tools and technologies. This session is designed for individuals who are interested in learning about Generative AI but have little to no experience in the field.
Transparency and accountability are essential when incorporating generative AI in eLearning. Learners should be aware that they are interacting with AI-based systems and understand the limitations and capabilities of the technology. Additionally, AI can help ensure that the course content is specific and relevant, reflecting genrative ai industry dynamics and incorporating popular best practices. Effective prompts should be specific and concise, clearly articulating the learning objective and guiding the AI in the direction of the desired response. Long, convoluted prompts can be confusing for the AI and make it difficult to achieve the desired outcome.
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This list is not exhaustive and there are probably many more teaching artefacts that generative AI can help with the creation of, that can only be thought of by the subject expert, deeply immersed in ensuring the success of their students. Similarly, early drafts of learning outcomes can be put to generative AI to seek clearer or more student-focused ways to pitch the learning outcomes for a course or a module. The tool in effect becomes more than a proof-reader, enabling us to engage in critical conversation with ourselves by challenging the meaning of our own words. Whether planning a new course or reviewing an old one, the planning process takes considerable effort. Systems like ChatGPT and Bing Chat, if prompted carefully and thoughtfully, can be invaluable in supporting this work. The first step is to define the learning objectives and outcomes that need to be achieved through the training program.
Generative AI has the potential to transform instructional design by assisting in the creation of course outlines, lesson plans, and training materials. We are currently working on detailed guidance for students and staff, but in the meantime, here is some interim guidance on how to use Generative AI appropriately. This guidance takes cognisance of the UK Higher Education Quality Assurance Agency’s Generative AI guidance and was drafted with input from OU academics, professional services colleagues, and students. You will gain practical experience using widely recognised Generative AI tools, including ChatGPT, MidJourney, Stable Diffusion, Deforum, ModelScope, AutoGPT and more to produce text, images, animations, and videos. We will dive deep into the technical underpinnings of Generative AI, investigating how AI models can be trained and refined. This new depth of online engagement has profound implications for the future of work, education, entertainment, and social interaction.
Generative AI in learning, teaching and assessment at the OU
I believe it is much needed in contemporary society to have effective communication between these camps, and people should know the underlying logic and assumptions of these two camps before they develop beliefs and actions about AI. It should be so, especially for current and future leaders in the private and public sectors. They really need to gain a deep understanding of the potential, promise and perils of AI. It can be for students who wish to work in any sector that is now embracing this technology. It’s important to note that although we need IT developers and data scientists to create AI and data-driven solutions, we need more skilled professionals who know both technology and management to diffuse such innovations. By actively addressing biases in generative AI and ensuring transparency and accountability, instructional designers can maintain ethical practices in eLearning.
Founder of the DevEducation project
Considering these perspectives is crucial for a balanced and inclusive approach to AI integration in education. Responsible regulation, transparency, and addressing student concerns are essential as we shape the future of AI in education. While exploring concepts and receiving feedback is generally acceptable, using AI to generate work submitted as one’s own is not. Apprehensions included potential job losses from automation and the need to develop AI skills for future employment opportunities.
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As an institution, we acknowledge the threat to assessment, such as academic misconduct, and the challenges such as inbuilt bias and fictitious answers. Equally, we acknowledge the opportunity for staff development that can help staff to make the best use of Generative AI tools to continue innovating and delivering high quality LTA. To get on board, Google is offering 11 free courses covering AI concepts, tools, and architectures that can enhance your skills at work and elsewhere. These courses explore generative AI, language models, responsible AI, image generation, and more. This piece delves into the contemporary cybersecurity landscape, identifying and analyzing the top five threats in today’s digital realm.
The Department will use the responses from this call for evidence as well as continued engagement with the education and EdTech sectors to inform future policy work. The Department does not intend to follow this engagement with a formal consultation at this time. Some may doubt that generative AI tools like ChatGPT can save time, especially given the need to carefully check the outputs from such systems. There are many reasons for this, including digital capability, capital investment, critical perspectives towards technology, and a reliance on a handful of tech enthusiasts to lead the way. Discover the Transformer architecture and the BERT model, along with the self-attention mechanism.
Centre for Innovation in Education
Thus, the polyglot notebook brings together a variety of LLM components including prompt templates, chains, and semantic memory access, without first familiarising themselves with specific frameworks such as Semantic Kernel or LangChain. The polyglot nature of the architecture, coupled with the sharing of values across disparate languages, empowers developers to embark on developing traditional code artefacts, intertwining them with the LLM components. In the ever-evolving landscape of technology, artificial intelligence (AI) continues to make remarkable strides, reshaping the way we learn and work and challenging traditional paradigms. Among the various branches of AI, generative AI has emerged as a groundbreaking field that holds immense potential to transform the way we create, innovate, and learn. Together, they are designed to teach individuals and business owners about the inner workings of AI and how it can save you time in the office. News of the training courses comes after a pair of troubling reports claimed that millions of Brits lack vital digital skills, which in turn is costing their employers over £5 billion in earnings.