partnership of AI-mediated learning while instilling the values of quality standards . 9 If engaging AI-mediated learning , students need to be trained to understand how to have meaningful interactions with the technology to elucidate its full potential as a learning partner .
Challenges and Ethical Considerations
Realising the benefits of generative AI in educational settings necessitates overcoming challenges , including various ethical considerations , the digital divide , and the potential for AI to perpetuate biases . The potential of AI to inadvertently exacerbate educational inequalities or to undermine academic integrity presents significant hurdles to its effective and ethical application in higher education . 10 Moreover , the rapid pace of AI development often outstrips the formulation of comprehensive governance frameworks and ethical guidelines , leading to a fragmented and inconsistent approach to AI integration across institutions . While educators are reporting the effectiveness of AI tools in streamlining administrative tasks , a barrier to its adoption is the lack of clear strategies to upskill staff in supporting students in its ethical use .
User engagement with ChatGPT declined overall by around 10 % mid-last year , but an informal Australian survey found that there is steady growth in the number of students using AI for selfdirected learning and assessments . The survey results aligned with sentiments shared by the student panel from the Educators Forum . Generative AI can support the exploration of topics and brainstorm ideas , but inaccuracies , also known as hallucinations , and biases are recognised as limitations . The survey also highlighted that students are more confident in understanding these imitations than educators , demonstrating inconsistencies between the expectations of learning institutions of their teachers and the actual AI knowledge and confidence amongst staff . 11
Maintaining academic integrity has always been an important focus in education . With the accessibility of generative AI tools , it is understandable that educators have increasing concerns given that the detectability rates of AI in assessments are inaccurate or very low . Assessment policies must be updated to ensure students have clear guidelines on the practical use of AI . In response to the rapidly changing landscape of AI and its ethical use in education , the Tertiary Education Quality and Standards Agency ( TEQSA ) provides advice for students navigating how AI may be an effective study collaborator . 12 The era of ChatGPT reinforces the need to cultivate open , respectful conversations of its use and limitations , AI professional development opportunities , and to revisit effective assessment design .
Conclusion
Looking ahead , the future of AI in education hinges on the balance between leveraging its potential to transform teaching and learning practices and addressing the ethical , technical , and pedagogical challenges it presents . This entails fostering a collaborative ecosystem wherein educators , technologists , policymakers , and students collectively explore the possibilities and limitations of AI . Engaging in this ‘ dance ’ with AI requires a commitment to ongoing dialogue , critical examination , and adaptive innovation to ensure that AI serves as a catalyst for enhancing , rather than detracting from , the educational experience .
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