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Reimagining higher education teaching in the age of AI

Hanelie Adendorff, Magriet de Villiers, Dalene Joubert, Melissa van der Vyver, Jan Petrus Bosman, and Sonja Strydom

The course is structured around three themes:

AI and HE: What is the hype about?

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The course is structured around three themes:

AI and HE: What is the hype about?

Here we look at the question: Could AI be the much-needed opportunity for higher education to reimagine teaching, learning, and assessment practices? To begin answering this, we will first explore where we are and how we got here and then investigate the intersection and interplay of AI and HE.

Re-imagining the HE-landscape in the age of AI

The logical follow-up question is: What do our graduates need from us and what will the world need from them? We don't know what the future holds, but we do know that it will be AI-infused. Assuming that human-machine relationships will be key to the successful navigation of this uncharted territory, we will look at AI literacies as a means of cultivating futures-readiness. To this end, we will delve deeper into key topics, such as understanding the possibilities, risks, and limitations of AI. We will also explore practical applications of AI tools, fostering critical thinking skills, and adopting a values-based approach to responsible AI use.

Responding to the invitation to change

The final question to consider, is: How can we prepare our graduates for the future? Reframing of the AI disruption as an invitation to change, we will look at possible responses to achieving the requisite literacies. To better understand how these skills can be applied in practice, we will analyse examples and case studies from various sources. You will also be afforded an opportunity to apply some of the thinking to your own context.

What you'll learn

This course is designed for any professional, involved with teaching in the higher education context, who is interested in the interaction between user-facing AI tools and education.

At the end of this course, participants will be able to:

  • Explain the impact of AI on teaching in HE.
  • Describe key AI terms and concepts, such as LLM, generative AI, and other types of AI relevant to HE.
  • Discuss ways of thinking about human relationships with machines with a view on to uncertain futures.
  • Discuss the components of AI literacies as well as their importance and value.
  • Highlight the criticality of a values-based approach to the responsible use of AI.
  • Considerations of user-facing AI tools in HE.

What's inside

Learning objectives

  • ways of thinking about human relationships with machines with a view on to uncertain futures.
  • the components of ai literacies as well as their importance and value.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
This course is designed for higher educators who teach in the context of the interaction between AI and education
Taught by professors recognized for their work in higher education, this course covers the hype, reimagined landscape, and invitations to change related to the use of AI in higher education
Examines user-facing AI tools, which explores how they can be used and implemented in the learning environment
Requires learners to have a basic understanding of AI and higher education

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Activities

Coming soon We're preparing activities for Reimagining higher education teaching in the age of AI. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Reimagining higher education teaching in the age of AI will develop knowledge and skills that may be useful to these careers:
AI Ethicist
AI Ethicists advise organizations on the ethical implications of artificial intelligence. This course may be useful as it delves into the values-based approach to the responsible use of AI.
Higher Education Faculty
Higher Education Faculty teach and conduct research at higher education institutions. As AI becomes more prevalent in higher education, understanding its impact and potential uses will be important for Higher Education Faculty. This course could help Higher Education Faculty stay abreast of these changes.
AI Teacher
As technology advances, AI is being used to teach students in new and engaging ways. This course may help an AI Teacher, as it explores the possibilities, risks, and limitations of AI as it relates to higher education.
Instructional Technology Specialist
Instructional Technology Specialists partner with educators to ensure that technology is used effectively to support learning. This course may be helpful for the role as it delves into the risks, possibilities, and limitations of AI as it relates to higher education, as well as how to use it responsibly.
Higher Education Administrator
Higher Education Administrators are responsible for the overall operation and management of an academic institution. This course may be useful for this role as it covers the impact of AI on teaching and learning in higher education, and how to use it responsibly.
Educational Researcher
Educational Researchers conduct research on education and learning. This course would provide Educational Researchers with an in-depth look at the ways AI may be used in higher education.
Data Scientist
Data Scientists use their knowledge and training to extract meaningful insights and knowledge from data. This course might be useful as it explores user-facing AI, which may be useful to a Data Scientist.
Instructional Coach
Instructional Coaches work with teachers to improve their teaching practice. This course could help an Instructional Coach, as it explores generative AI, which could be a valuable tool in higher education.
Education Consultant
Education Consultants advise and assist educational institutions, organizations, and individuals. This course could be helpful as it provides ways of thinking about human relationships with machines on the uncertain futures of education.
Instructional Designer
Instructional Designers create and develop educational programs and materials. This course may be useful as it provides future-readiness as well as explores AI literacies, which may be valuable to an Instructional Designer.
Quantitative Researcher
Quantitative Researchers gather and analyze numerical data. This course could be useful as it introduces key AI concepts that relate to higher education and future readiness.
Curriculum Developer
Curriculum Developers design and implement educational programs and experiences. This course may be useful as it explores user-facing AI tools in higher education, which could be incorporated into a curriculum.
Artificial Intelligence Researcher
An Artificial Intelligence Researcher designs and builds new artificial intelligence software. This course may be useful as it introduces you to the relationship between humans and technology, as well as ethics, which are important in developing responsible AI.
Learning Scientist
Learning Scientists investigate how people learn. This course could be useful as it provides context for future-readiness and the impact of AI on learning.
Postdoctoral Research Fellow
Postdoctoral Research Fellows work on research projects for a defined period of time after earning a doctorate. This course could be helpful as it will guide your thinking on the future and its uncertainties as well as provide value through an exploration of AI literacies.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Reimagining higher education teaching in the age of AI.
Provides a comprehensive overview of the Fourth Industrial Revolution, covering its impact on society, economy, and the future of work. It valuable resource for those who want to understand the challenges and opportunities of the AI age.
Explores the future of humanity in the age of AI, covering its potential impact on our lives, society, and the economy. It valuable resource for those who want to think about the long-term implications of AI.
Comprehensive textbook on deep learning, covering its mathematical foundations, algorithms, and applications. It valuable resource for those who want to learn the technical details of deep learning.
Comprehensive textbook on reinforcement learning, covering its mathematical foundations, algorithms, and applications. It valuable resource for those who want to learn the technical details of reinforcement learning.
Provides a comprehensive overview of machine learning from a probabilistic perspective, covering its mathematical foundations, algorithms, and applications. It valuable resource for those who want to learn the theoretical foundations of machine learning.
Comprehensive textbook on statistical learning, covering its mathematical foundations, algorithms, and applications. It valuable resource for those who want to learn the technical details of statistical learning.

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