Experience and expertise from across the institution to explore the potential of AI in education. We’ve developed resources, guidance and examples to support each other in navigating emerging technologies and their implications for teaching learning and assessment.

AI has many possibilities and is opening new frontiers while challenging us to rethink and expand our practices. AI is already part of our lives in many ways, how might it be part of our educational experiences and deliveries?

From creating presentations of content like this video, or generating transcripts from the video for ease of interaction or creating quizzes to interact further with the content…

…To a diverse range of ways educators and students can experiment with using AI for teaching, learning and assessment, including the summary below which is based on the seven approaches proposed by Ethan Mollick and Lilach Mollick in June 2023, and examples provided by Stanford University…

  • Role: Providing feedback

    Example: Students using chatbots (e.g. ChatGPT, CoPilot) to get feedback on the structure of an essay or to find errors in a piece of programming code & critically examining feedback generated by chatbots.

    Pedagogical Benefit: Frequent feedback improves learning outcomes, even if all advice is not taken.

    Pedagogical Risk: Not critically examining feedback, which may contain errors.

  • Role: Direct instruction

    Example: Users can prompt chatbots to generate explanations and analogies for concepts based on your or your students' interests or to ask open-ended questions that encourage further thinking

    Pedagogical Benefit: Personalised direct instruction is very effective.

    Pedagogical Risk: Uneven knowledge base of AI. Serious confabulation risks.

  • Role: Prompt metacognition

    Example: Educators and students could use a chatbot to reflect on their experience working on a group project or to reflect on how to improve study habits, using a predefined structure

    Pedagogical Benefit: Opportunities for reflection and regulation, which improve learning outcomes.

    Pedagogical Risk: Tone or style of coaching may not match students. Risks of incorrect advice.

  • Role: Increase team performance

    Example: AI chatbots can play a number of roles within a team. For example, teams can use a chatbot to synthesise ideas, develop a timeline of action items, or provide differing perspectives or critiques of the team's ideas.

    Pedagogical Benefit: Provide alternate viewpoints, help learning teams function better.

    Pedagogical Risk: Confabulation and errors. “Personality” conflicts with other team members.

  • Role: Receive explanations

    Example: Educators might prompt a chatbot to act as a novice learner and ask you questions about a topic

    Pedagogical Benefit: Teaching others is a powerful learning technique.

    Pedagogical Risk: Confabulation and argumentation may derail the benefits of teaching.

  • Role: Deliberate practice

    Example: Users can prompt the chatbot to create a realistic ethical dilemma that applies to the discipline or to role-play as a patient or client in a relevant scenario. At Monash users can work with the project ATLAS team to develop a custom application for their students. So far we have EDU, ARTS, SCI, and MNHS applications underway -happy for more.

    Pedagogical Benefit: Practising and applying knowledge aids transfer.

    Pedagogical Risk: Inappropriate fidelity.

  • Role: Accomplish tasks

    Dreaming—Helping you think
    Brainstorming, Concept Expansion, Concept Mapping, Collaborative Writing, Scenario Building, Simulating Discussions

    Drudgery—Lightening your load
    Summarization, Data Cleansing, Progress Tracking, Content Moderation, Synthetic Data, Review and Feedback

    Designing—Designing content
    Lesson Plan Generation, Project Planning, Content Personalization, Accessibility Design, Interactive Experiences, Curriculum Mapping

    Pedagogical Benefit: Helps educators & students accomplish more within the same time frame.

    Pedagogical Risk: Outsourcing thinking, rather than work.

…and beyond as new technologies and practices emerge.

Video creation: Hour One AI / Video Transcript: Stanford Teaching Commons

Transcript: AI tools are already a part of our daily lives. Any technology that predicts an outcome based on large sets of data can be considered as artificial intelligence. For example, a streaming service platform recommending a new movie to you makes a prediction based on your past viewing history, while a map tool gives you navigational directions based on data from other drivers.

The resources section provides a range of materials to help colleagues think through and prepare for evolving education in the age of AI. The contributors section identifies the diverse participants in our learning circle to whom we owe tremendous thanks for their heroic efforts.