3 Steps to Embed AI into Higher Ed Courses

I recently attended a Governors’ and Trustees’ Conference in London, United Kingdom. The target audiences were mainly local primary and secondary school governing board members. Unsurprisingly, the conference’s purpose was to inform the governing board about ed-tech opportunities and risks. 

Through various workshops, the conference sought to enable governors to re-imagine use cases of ed-tech. Focus primarily involved using AI tools, such as ChatGPT, from educators’ perspectives, embracing ed-tech to drive efficiencies in administrative-related tasks, curriculum implementation, assessment designs and marking mock papers. Most importantly, the focus was enhancing students’ experiences and unique learning journeys. 

Despite resource constraints and challenging pay and working conditions in higher education, here are three steps educators, including myself, may take to embed AI in their courses.

Step 1. Assess Curriculum, Learning Outcomes, Assessment Strategies and Pedagogical Approaches 

Although AI is increasingly used from students’ perspectives, only 9% of students surveyed through the Higher Education Policy Institute claimed that their institutions have completely changed assessment strategies and approaches. This phenomenon shows an excellent opportunity for HE educators, particularly course directors and module leaders in collaboration with education technologists, to accelerate the embedding of AI in their courses. This may also change how we assess students because AI is reshaping our expectations of global workforces, particularly skills, capabilities and capacities. 

Educators should be encouraged to think systematically before embedding AI tools in their courses and attempting to redesign each course/module component. Each institution would have different missions, visions, and strategies for teaching, learning, research, innovation, and student experience. 

Educators, therefore, must revisit their affiliated institutions’ strategies, policies and performance indicators. For example, institutions would need to consider student satisfaction through the National Student Survey (NSS), the QAA subject benchmark statements of their subject areas, and industry expectations of the future global workforce to ensure all these factors are aligned to meet the needs and standards from different stakeholders’ perspectives.

Step 2. Personalize Students’ Learning Journeys

Perhaps the UK higher ed sector recognizes that university students’ usage of AI tools in their learning journeys could be considered a norm. Based on the Higher Education Policy Institution poll results, 53% of 1,250 UK undergraduate students surveyed used generative AI tools to complete their assignments, mainly to unfold ‘concepts’ in their subject areas, summarize journals, edit their work and generate text. 

Educators may need more support and resources from the ed-tech technicians and senior leadership teams to achieve step two. Educators may learn from software-as-a-service (SaaS) companies, such as Miro, to embed a product adoption platform or even AI-powered chatbots in their software portal to enhance the user onboarding experience, monitor each user’s usage and interaction and collect timely feedback from each user. 

This approach may be applied to virtual learning environments, including Moodle and Canvas, to help educators manage extensive student portfolios, monitor learners’ progress and provide timely and personalized feedback on their learning journeys.

Step 3. Teach Students How to Use AI Tools Ethically and Responsibly 

Each institution would have slightly different policies on how academics, professional staff and students may use AI in their work. 

Suppose AI tools are permitted in teaching and learning. In that case, the first step for educators is to understand the AI governance landscape and relevant policies at their affiliated institutions before they design and deliver training for their students to understand AI, AI ethics, and AI governance and become AI-literate. Educators may design and deliver AI literacy based on the AI-literacy Mapped Bloom’s taxonomy.

As an educator, I noticed that the UK higher ed sector has focused on exploring the use of AI tools in teaching, learning, researching and increasing efficiencies since ChatGPT became one of the most popular AI tools in 2023. The higher education sector was mainly concerned with whether AI tools could be used ethically and responsibly in teaching and learning and may decide to discourage using AI tools in assessment due to potential risks of plagiarism. 

For example, at Oxford and Cambridge Universities, the “unauthorised [sic] use of AI tools in examinations and other assessed work” is considered academic misconduct. Researchers, including Warschauer, also suggest AI tools may discourage students from writing confidently and critically. 

Despite these concerns, the UK higher ed sector has recently focused more on AI ethics and governance. For example, the Russell Group published its five principles in July 2023 for empowering educators and students to ethically and responsibly use AI tools and the Quality Assurance Agency for Higher Education published the “Generative Artificial Intelligence in Education in response to the Department of Education call for evidence” in September 2023.

What’s Next?

There is no doubt that the speed of the technologies transforming our behaviors is dramatic, sometimes positive and sometimes disruptive. Proactively examining new technologies and teaching practices to engage with our students becomes vital. As an educator, I constantly learn with my students as I see myself proactively acting as their bridge to becoming career-ready and the future workforce to build a better world.