AI literacy capabilities for educators
AI and other emerging technologies are reshaping how we live, work, and study. In response, educators must evolve their pedagogical practices, and develop digital capabilities and basic AI literacies to safely and effectively integrate AI into higher education (including taking an informed position on where its use should be limited) and to equip students for their evolving disciplines and professions.
This resource identifies key themes and capabilities necessary for effective educational practice and supports staff to consider and position the potentials and pitfalls of AI in education. The content is curated from a range of sources, offering a foundation in key areas to help educators develop their thinking. The resources do not focus on specific AI tools (current or emerging) but focus on principles that can be applied more widely. These pages offer a structured, sequential approach to capacity-building, connecting educators with an evolving ecosystem of support resources. The aim is to play a role in fostering and expanding a range of AI-related capabilities to help educators actively shape the future of higher education.
Navigate the tabs to explore the four themes.
1. Understand the dimensions of human agency when using and evaluating AI toolsHuman agency in the context of AI refers to the capacity of individuals to make their own choices and to act thoughtfully and knowledgeably when interacting with AI systems. This involves understanding how AI tools can influence decision-making processes and the extent to which users can shape the outputs of these tools. Working to ensure that AI systems enhance rather than diminish human agency is crucial for fostering trust in AI and human decision-making, which will lead to more effective human-AI collaboration. |
2. Teach students the importance of human agency when using AI toolsEducating students about human agency in AI will highlight the importance of maintaining involvement in the process and making informed decisions when using AI tools. This includes recognising the potential for AI to both empower and constrain human actions. By fostering a critical understanding of AI, students can learn to leverage these tools responsibly and effectively. An understanding of human agency and its relationship with different technologies will allow educators to communicate what kind of agency is important, when and why, in their specific field. |
1. Develop a basic understanding of ethicsBefore using AI, it is necessary to understand ethical issues that broadly affect AI use, including negotiating bias, equity and access issues, the need for demonstrating accountability, environmental impact, and maintaining privacy and respecting ownership rights. |
2. Understand the principles for ethical AI use and human and non-human collaborationIn addition to understanding foundational ethical AI issues, you will need to understand discipline-specific ethical principles that relate to your aligned industries. For example, industry practices may have specific requirements for accuracy, transparency, and accountability. Responsibility for ethical breaches often remains with humans, and understanding of the intersection between agency and ethical use is essential for fostering trust and ensuring that AI systems are used responsibly in collaboration. |
3. Teach students about ethics of AI in general/disciplinary/related professional contextsTeaching and assessing students about AI ethics involves integrating ethical considerations into your curriculum. This includes discussing the ethical implications of AI in specific professional contexts and evaluating students' understanding of these issues. By incorporating ethical discussions into their education, your students can develop an industry-oriented understanding of the changing responsibilities associated with evolving AI capacities. In general, documenting AI use, reflecting on AI use and clearly explaining AI use are key aspects of operating ethically with academic and professional integrity. However, each discipline and profession may be developing specific guidelines and protocols. |
1. Define AI and understand AI modelsUnderstanding the basic elements of generative AI large-language-models, and the differences between different types of AI systems, will support a greater understanding of how they work and how trustworthy they are for different applications. This will inform your ability to both identify and discuss discipline-specific issues and consider the implications of AI for your evolving field(s). |
2. Identify categories of AIAI training influences both the ability of AI to interpret input, and the type and complexity of output the AI can produce. Understanding the types of AI will help you recognise and understand the scope and potential of different AI systems. All of these different types of tools have different issues and affordances to consider. |
3. Evaluate AI tools for educationEvaluating AI tools for education requires being clear about the particular use case, the role of tools in supporting learning outcomes, as well as the potential risks. Like apps and software, there are a wide range of AI tools that have a range of functions. Educators need to explore and critically evaluate tools to make informed decisions about how to structure activities to learn with AI. Trying things with both colleagues and students can help us discover the potentials and pitfalls of tools together. |
4. Operate responsibily with enterprise-validated AI toolsThere are an increasing range of AI tools available and AI is increasingly being integrated into commonly used tools such as Gemini in the Google suite and Copilot in Microsoft 365. Enterprise tools have been reviewed for reliability, security, and compliance with Monash standards. Enterprise tools also include increased levels of data protection. Only approved enterprise AI tools should be used for Monash private, sensitive, and very sensitive data to ensure proper data and privacy protection. Start with Monash provided access to AI. |
1. Consider the possibilities and actualities opened up by the availability of AIFrom the printing press to computers, from the Internet to video conferencing and up to contemporary AI, technologies continue to be entangled in pedagogical practices. As the TPACK model suggests, educators need to coordinate combinations of technological, pedagogical and content knowledge. Building contemporary knowledge of the possibilities and challenges of emerging AI technologies should inform thoughtful, purposeful, ethical and inventive integration of AI into teaching and learning activities. This includes navigating and balancing both potential benefits and risks. |
2. Use AI in designing learning, in teaching and assessmentThere are a number of different ways to integrate AI in teaching, learning and assessment. This might include activities to “learn about AI” or activities to “use and work with AI” in ways that are relevant to the unit. You can engage in conversations about AI and its implications and/or engage with AI tools, carefully using and critically evaluating them. You can use AI to support your teaching and assessment, or design AI discussions and AI tools into the curriculum to support your teaching, how the students learn, and how their understanding and skills are assessed. For example, AI can be used to incite thinking, build feedback literacy or provide additional opportunities for practice and support. |
3. Communicate your educational rationale for your use of AI tools in teaching and assessmentCommunicating the educational rationale for using AI tools involves explaining the benefits and purposes of your suggested uses of these tools. This might usefully include consideration of the industries that your students are orienting towards. Clearly explain “why” and “how,” connecting explicitly to learning outcomes and preparation for future endeavours. Engage students in dialogue about what they are learning and the ways you have designed their learning journeys with combinations of both individual and collaborative (including with AI) demonstrations of knowledge and skills. Make sure you have designed activities to make visible the kinds of learning that are valued in your unit and set up enforceable conditions that support this (e.g. direct observation of the learning process). |
4. Recognise and mitigate risks in using AI for teaching and assessmentRecognising and mitigating risks in using AI for teaching and assessment involves identifying potential issues such as accuracy, reliability, bias, data ownership and privacy, over-reliance on technology, facilitating equivalencies and capacities for students to opt out of using AI and avoiding trivial uses of AI (where use of AI does not add anything meaningful to the activity). This includes implementing safeguards and practices to make it more likely that AI tools are used ethically and responsibly, and that AI supports rather than undermines the educational process. Your understanding of AI issues from earlier themes is critical here. |
5. Use AI to support personalised and differentiated learningAI can support more personalised and differentiated learning by calibrating educational content to individual student needs and contexts. This includes using AI to generate multiple variations to better address diverse needs. It also includes showing students how to use AI to engage with information in different ways (e.g. translating between media, languages, tones, styles, etc.) |
6. Assess in ways that enable cultivation of human agencyCultivate human agency by designing assessments that empower students to actively engage in their learning and demonstrate their understanding in meaningful ways. This includes designing tasks and environments that require students to: demonstrate critical thinking and interrogation of information and its sources, evaluate and incorporate actionable feedback from multiple sources (including AI), demonstrate self-direction and autonomy, and constructively collaborate with multiple intelligences. It may include involving students in the co-design of some aspects of the assessment. It is also important to reinforce with your students that humans have responsibility and accountability for the outcomes produced with AI collaborators. |
7. Assess in ways that enable cultivation of collaboration (human and non-human)Assessing in ways that enable collaboration involves designing assessments that encourage teamwork. This can include the effective use of AI tools, such as creating tasks that require students to work together with AI systems to solve problems, analyse data, or create content. By fostering an environment where students can collaborate with AI, you can help to prepare students for future work scenarios that involve human-AI partnerships in your field. Similarly, you can collaborate with students to learn together about the potentials and implications of AI. In doing so, you do not have to be an expert - you can be a collaborator or another collaborator. |
8. Use AI to support student feedback and markingIf used carefully, AI can support your assessment work to improve the clarity of student guidance and the quality of your feedback. For example, AI can be used to help educators calibrate and clarify their rubrics and align them to the specified learning outcomes. AI can help you convert your own notes on students’ work into carefully crafted feedback comments (do not upload student work into an AI application unless you have every student’s explicit consent and are using Monash enterprise systems with appropriate data and privacy protection). You can also guide students on how they can use AI, if they choose, to help them engage with your feedback comments, e.g. by supporting them to understand their strengths and areas for improvement, and develop strategies to address these. Help your students understand that if they use AI tools to generate feedback on their work, they should do so critically and in ways that complement rather than replace teacher feedback (Read this paper published from our AI in HE students and AI research project). |
9. Evaluate use of AI in teaching and learningDevelop feedback cycles to evaluate and reflect on your teaching and learning with diverse AI systems. This should be integrated into your normal processes of collecting feedback from students during the teaching period about the effectiveness of teaching design, materials and delivery. |
10. Use AI to expand professional developmentTechnologies, disciplines and practices are continually evolving and add to the needs for life-long learning to inform our teaching practices. As we navigate the transformation of higher education with emerging technologies, you are encouraged to experiment and innovate, reflect on your efforts and share them with colleagues. Continue to learn about AI while recognising that AI can also support your own professional development by providing personalised content, training, suggestions, and coaching related to teaching in your field. AI can also support ongoing professional development in your students, providing them with tools for lifelong learning. |