T3 March 4 2024

Hello AI Enthusiasts 👋

It’s been another exciting week at the intersection of AI and Higher Education!

In my corner of the world, this week I had the honor of contributing insights into the future of research within Business Schools to members of the Australian Business Deans Council (ABDC).

Additionally, I refined my AI for Research Workbook, gearing up to deliver AI literacy seminars at two universities in New Zealand. The 45-page booklet is full of lesson plans to help bring AI digital literacy training into university research training classrooms.

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Weekly AI News Updates

Catch up on the latest AI news in higher education with this selection of curated articles from around the globe.

Is your university leveraging AI tools to enhance operational efficiencies?

If not, GPTs are something you should put on the top of your #MustLearnThisAboutAI list. Learn about GPTs, discover productivity enhancements, and get started building your own GPTs in this blog post.

A series of short conversations on AI, from Monash University in Australia. I enjoyed this latest chat with the legendary George Siemens.

Three key takeaways:

  • AI is not being taken seriously enough by Higher Education, unless you consider setting up generative AI committees as actual work.

  • AI will help return us to core human values.

  • The critical challenge for Higher Education is understanding the intersection of humans and AI.

The University of Michigan is developing an AI coaching bot that aims to strengthen students' critical thinking and self-regulated learning skills. The bot will guide students to understand the conceptual framework of a problem, allowing them to self-solve similar problems in the future.

The goal is to develop a platform for the next generation of engineers and scientists to transform raw data into actionable knowledge. The bot will use a coaching method that emphasizes asking students to evaluate their problem-solving process and identify incorrect methods or answers.

Universities need to place a stronger emphasis on teaching writing skills to undergraduate students in the age of artificial intelligence (AI), according to Joel Heng Hartse, a senior lecturer at Simon Fraser University, and Taylor Morphett, an instructor at Kwantlen Polytechnic University. They argue that writing is a technology that restructures thought and is a crucial tool for thinking that students need to master.

They disagree with the idea that AI tools can replace the need for humans to learn how to write, as the output produced by AI does not reflect intellectual engagement. The authors suggest that universities should expand and improve their writing programs, particularly in Canada where writing education has been historically underemphasized.

They propose that academic writing courses should be required for all undergraduates, teaching them to think, synthesize information, judge the credibility of sources, and interact with an audience.

Ohio University professor Basil Masri Zada has incorporated artificial intelligence (AI) into digital arts and technology courses using the Ohio Supercomputer Center's (OSC) resources. Masri Zada collaborated with OSC to host the Stable Diffusion AI software on their machines, allowing students to access it remotely through OSC's OnDemand platform.

The Stable Diffusion software, an open-source generative AI tool, was used in two main courses within the curriculum to produce diverse forms of artistic expression. Masri Zada and his students were able to explore the impact of training materials on AI behavior and understand biases present in existing training data.

The implementation of AI in the courses expanded students' creative processes and allowed them to create work that would not have been possible without the technology. Masri Zada plans to continue using OSC resources to enhance the software and incorporate more training data sets in future projects.

Mississippi State University's Department of Computer Science and Engineering has launched a new open-access academic journal called AI Letters. The journal aims to rapidly disseminate breakthroughs in AI research, covering topics such as machine learning, robotics, natural language processing, and computer vision. It features a rapid double-blind peer review process, with submissions evaluated and published within two to three weeks.

That’s a Wrap!

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Take care and chat soon,

Bron