3.2. Using AI as a lecturer

AI can help make learning more interactive, personalised, and learner-centred, shifting the focus toward independent and active learning.

Traditional lecture-based teaching methods often involve passive learning, where learners are expected to absorb the material presented by the lecturer through listening. However, this method may not always foster deep understanding or develop critical thinking and problem-solving skills, as learners are not actively engaged in learning. Active learning involves learners’ active participation and engagement in the learning process via discussions, group work, practical exercises, and problem-solving, all of which encourage more profound understanding and the application of skills. With AI applications, it is possible to create interactive learning materials and design and test various homework and group tasks that help achieve the learning outcomes of a course.

Using AI in different stages of teaching

AI applications can assist in course planning. For example, one can ask them for potential lecture outlines or test different ideas to combine lecture topics best. One can test and refine ideas by engaging in a dialogue with AI applications. AI also recommends what tasks should be included in the teaching process. Additionally, AI can check how well a text-based AI model can independently perform a task and how to make it more complex, requiring learners to contribute substantively and allowing them to learn.

Customised and personalised learning. With AI, a lecturer can offer learners the same learning content in various forms, such as video, text, or interactive tasks, tailored to the individual preferences of the learners, allowing them to learn in different contexts (e.g., listening to an audio lecture while walking or reading materials at a convenient time and place). AI can also be used to create task versions that consider previous mistakes made by students. However, it is crucial to note that students must consent to uploading their work to AI applications.

Various ways to use AI in teaching

• Creating simulations: AI enables the teaching of abstract topics through practical simulations, creating an interactive and engaging learning experience. AI helps to design and generate suitable materials or environments for this (e.g., Copilot, ChatGPT).

• Virtual Assistant: Lecturers can suggest using AI for independent study materials to help students better understand the material or to answer routine questions (e.g., Copilot Studio). AI also assists in creating texts and guide materials to support independent learning (e.g., Copilot, ChatGPT).

• Reducing language barriers: Language barriers have traditionally limited access to some data and resources, making teaching focused on a single linguistic area. AI translation applications help overcome this barrier, allowing access to data and examples that were previously unavailable. AI applications also enable better engagement with foreign-language guest lecturers, for instance, by adding subtitles to their lecture recordings in a language learners understand. Although translation applications are imperfect and may make errors, they facilitate understanding foreign-language texts (e.g., DeepL, ChatGPT). Furthermore, AI applications can be used in language learning, where learners can perform level-appropriate exercises in various language learning apps (e.g., combining regular Duolingo use in language learning).

• Developing discussion tasks: AI applications help quickly combine and synthesise different materials to create discussion tasks. For example, a lecturer can upload texts to ChatGPT for seminar preparation and ask for suggestions on designing a task suitable for the respective level. AI applications, such as NotebookLM, can be used to prepare synthesised text or create a synthesised podcast, from which a discussion task can be developed for students.

• Preparing lectures: A lecturer can input specific instructions into AI applications like ChatGPT or MS Copilot, providing details on the lecture topic, learner level, prior knowledge, time frame, and more. Based on this information, AI will suggest a lecture structure, which can then be adjusted or supplemented.

• Data analysis and prediction: AI can assist in analysing large amounts of data to identify patterns and trends, helping lecturers better understand the needs of learners and adjust their teaching strategies accordingly. AI can also guide students in using AI applications for data analysis and understanding how to reach conclusions.

• Faster and More Effective Feedback. The assessment process, which requires lecturers to review exams, essays, and other tasks, can take considerable time, meaning students often receive feedback late, which can hinder students from quickly adapting and improving their learning process. In addition, large learning groups may limit a lecturer’s ability to offer personalised feedback due to time constraints. AI-based applications can provide faster and more tailored feedback. Lecturers can also guide students on using AI as a mentor to receive constructive feedback before submitting work for final evaluation. Quick feedback and lecturer support are essential for students, allowing them to immediately improve their learning and move toward achieving the learning outcomes. On the other hand, AI-assisted evaluation can free the lecturer from routine tasks, allowing them to focus on more substantive and developmental activities, such as individual mentoring or explaining complex topics. This enhanced, time-saving approach contributes to the overall quality of the learning process.

AI can also create automatic feedback tasks based on existing learning materials, such as self-assessment tests, which provide students with feedback on whether they have mastered the content. AI applications allow for adding clarifications or explanations for incorrect answers, enabling students to receive feedback on their mistakes.

When used skilfully, AI applications can help create more interactive learning materials and tasks. They can also adapt learning tasks and projects to different learners’ interests and prior knowledge, thus increasing student motivation. AI can also provide feedback to students during the learning process.

Practical recommendations for lecturers

• Stay updated on developments in the AI field.
• Look for ways to maximise the use of AI applications in teaching or research.
• Encourage students and colleagues to use AI applications.
• Think about integrating AI applications into teaching and combining them with other teaching methods.
• Offer students opportunities to develop their skills in using AI applications, as these will be increasingly important in their future careers.
• Recommend ways for students to reference the use of AI applications in their work correctly.
• Explain to students that the user is always responsible for the results obtained from an AI application.
• Define the conditions under which AI applications are appropriate for use in teaching and when they are not. Explain and justify your decision to students.
• If appropriate, consider replacing written assignments with other forms of work. When assessing written work, focus more on tracking the process of its creation and presentation.
• Do not input personal, confidential information or legally unpublished work into AI applications, as this violates personal and copyright rights.

Task: Planning a Lecture or Seminar Using AI

Objective: Understand how AI applications can assist in planning a lecture or seminar.

Instructions: Before starting, read the Google article “Prompt Engineering for Generative AI” to understand how to write effective prompts, which will help you create precise instructions for AI to achieve the best possible outcome.

Write a detailed prompt: When writing a prompt to create lecture or seminar content for AI, be as specific and thorough as possible so that AI understands what content it needs to generate.

Include the following information in your prompt:

• Lecture/seminar title: a clear and explicit title
• Role: specify your position in this teaching process (e.g., history professor, political science lecturer)
• Overview of the lecture/seminar: provide a summary of what the lecture/seminar should cover
• Detailed breakdown: divide the lecture/seminar into parts and specify the points that need to be addressed in each section
• Interactive elements: consider which interactive elements (e.g., discussion questions, multimedia resources, or activities) should be included
• Learning objectives: clearly state what learners should have learned or be able to do by the end of the lecture/seminar
• Required materials: list any materials or resources you will need

Task: Adapting an assignment using AI

Objective: Try visualising a text-based task.

First step: Choose a core concept or fundamental term from the content of one of your current courses. It could be a theory, process, or definition (e.g., the idea of the security dilemma in international relations). Create a visual (e.g., infographic, flowchart, mind map) using Microsoft Copilot or ChatGPT to convey the key points of the selected concept.

Second step: Reflect on the process of creating the visual.

Evaluate how AI helped in creating the visual.

How do you assess the usefulness of AI compared to creating the visual by hand?

Sample output:

Security dilemma. Image: Napkin AI (2024).

Task: Using AI in learning

This task aims to demonstrate how to develop students’ ability to conceptualise the use of AI in their learning process and encourage them to assess AI output critically.

Task: Reflective questions about using AI

Objective: Encourage learners to use AI in their learning process and develop their ability to evaluate AI outputs critically.

Instructions: Develop a worksheet with three reflective questions (you can ask AI to help you with this). Ask learners to complete this worksheet after using an AI application for course tasks or in the broader learning process.

Sample questions:

• Describe: In which stages of the task did you use AI and why?
• Evaluate: What was the most helpful thing you gained from using AI to solve this task?
• Analyse your learning experience: Did AI function effectively as a learning assistant? Justify your opinion.