20230329 AUW talk AI in education.pptx
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This 20 slide presentation, starts with an overview of AI, showing some AI tools, and sharing examples of AI for education options. The learning outcome of this presentation is to provide AUW students an insight into AI and how they can use it within their courses. By including short examples, it makes it easier to embed AI interactions into their courses.
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20230329 AUW talk AI in education.pptx
- 1. View of a wind farm on Panachaiko mountain in Greece. Photo: AI in ED? Use it & try & harness it! Slideshare.net/Ignatia/presentations Inge de Waard. AUW. 29/03/2023
- 2. Brief overview 2 AI in Education What is AI? What is Generative AI? AI in Education examples Discussion on risks and benefits AI tools brief selection
- 3. Who has tested or used AI tools? 3
- 4. History – What is AI? 4
- 5. Timeline from teaching machine to AI @Ignatia 5 Teaching Machine (Skinner) – Artificial Intelligence (1954) eLearning (1999) Big Data (2005) CCK08 MOOC (2008) Learning Analytics (LAK 2011) Deep Learning revolution (2012) Open AI founded (2015)
- 6. Learning and machine learning coming together 6 Coming together Merging into new field eLearning Artificial Intelligence Business indicators Big Data Machine learning Artificial Intelligence in Education Monolithic development
- 7. What is an algorithm? An algorithm is a set of rules to solve a problem. It is programmable It uses and can manipulate data. @Ignatia 7 Input (data) Algorithm Output (data)
- 8. 8 @Ignatia
- 10. 10 Innovations follow Gartner Hype Cycle
- 12. What is Generative AI? 12
- 13. 13 Generative Pre-trained Transformer (GPT), or generative artificial intelligence (AI) describes algorithms (such as ChatGPT using GPT) that can be used to create new content, including audio, code, images, text, simulations, and videos.
- 14. 14 Example video Using • Writing a script (storytelling) • Resemble AI creating a new AI voice based on your own (or a professor) • Midjourney: creating new images based on ‘prompts’ • D-ID to create avatars based on pictures or paintings • Edit the separate movies from D- ID into one single mp4 in Filmora
- 16. AI use in classrooms - examples Individual & group work: using Natural Language Programming (NLP) tools – e.g. ChatGPT 16 Choosing topic Define an essay topic Split classroom into groups Use AI tool X to find information Analyse in group Analyse what is useful Look for gaps / lacking details Check facts in output Add your knowledge and fill in the gaps Upload for peer review Discuss in groups Read other essays Discuss the process of using AI tool for essay writing What went well? What was difficult? How did you manage?
- 17. AI use in classrooms - examples Testing an AI as personal assistant – e.g. Bing (new version) or use KahnMigo 17
- 18. AI use in classrooms - examples Mash up tools for meaningful content creation or Educational processes – e.g. video 18 Learn a new language using Duolingo Max
- 19. But … what are the potential risks & benefits using AI in education? (add name or link in chat) 19
- 20. Benefits Basic work becomes easier Time saving Smart decision making / corrections Less repetitive tasks Increased decision making opportunities … Risks & Benefits of AI in education 20 Risks Increased digital divide Ethical issues (who benefits, remember Cambridge analytics scandal) Dominant societies feed information Getting lost in translation Extra server space needed = climate pollution …
- 21. Role models inspire our lives Mira Murati is Chief Technical Officer (CTO) of ChatGPT 21
- 22. AI tools in education, brief selection 22 •Originality.AI •Content At Scale •Writer •Crossplag •Copyleaks •D-ID avatar teachers •Synthesia: creating life like avatars •Creating an AI voice based on your own •Pictures and images: Dall-E, or Stable Diffusion •Open AI ChatGPT •Bing from Microsoft •Article on 10 GPT-3 AI writing tools •What is Generative AI •Academic article writing with AI •Alec Couros AI overview as introduction to teachers General information Authoring tools AI detection tools (remember room for improvement!) Content creation
- 23. www.innoenergy.com EIT InnoEnergy Kennispoort 6th floor John F. Kennedylaan 2 5612 AB Eindhoven The Netherlands Info@innoenergy.com Dr. Inge de Waard Inge.dewaard@innoenergy.com LinkedIn profile Slideshare.net/Ignatia
Editor's Notes
- Picture wind farm on Panachaiko mountain
- The first online learning teaching machine was invented by Skinner (Harvard university) in 1954. At the same time machine learning took off, mostly shaped by computer scientists. It took a couple of decades before the term eLearning emerged, embracing all types of online education. In 2005 Roger Mougalas from O’Reilly Media coined the term Big Data for the first time, only a year after they created the term Web 2.0. It refers to a large set of data that is almost impossible to manage and process using traditional business intelligence tools. CCK Connectivism and Connected Knowledge course was a course organised by Stephen Downes and George Siemens, both Canadians. Dave Cormier was one of the participants of the course, and he named it a Massive Open Online course or MOOC. The first Learning Analytics & Knowledge conference was organized in 2011 in Canada. This development was crucial for the next steps in big data combined with education. Some researchers assess that the October 2012 ImageNet victory anchored the start of a "deep learning revolution" that has transformed the AI industry. "Why Deep Learning Is Suddenly Changing Your Life". Fortune. 2016. Retrieved 13 April 2018.
- An algorithm is a set of rules to solve a problem. It can be any set of rules that is mathematically viable and programmable. It can also be used to manipulate data, so that a specific result is achieved.
- AI is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. Based on algorithms. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly. (e.g. Google draw) Deep learning: based on pattern recognition in big data