Perspectives on civics and citizenship education in Australia: Findings from the recent inquiry through AI-augmented analysis

This article explores how generative artificial intelligence (AI) can assist in analysing public submissions to government inquiries, using the 2024 Australian Joint Standing Committee on Electoral Matters (JSCEM) inquiry into civics education and engagement as a case study. Using a large language model (LLM)-supported approach, we processed the full corpus of submissions to extract claims, classify themes and map the dominant challenges and recommendations. With more than 100 diverse submissions from individuals and organizations, the inquiry highlighted widespread concern over civic literacy, misinformation, youth disengagement and the quality of civics and citizenship education (CCE) in Australia. Five systemic themes emerged from the data: ‘Curriculum Challenges’, ‘Media and Trust’, ‘Equity and Access’, ‘Youth Engagement’ and ‘Teacher Capacity’. We present these findings with examples from the data and compare these themes with the final recommendations from the JSCEM’s From Classroom to the Community report, identifying points of alignment and divergence. While the Committee’s recommendations strongly align with calls for curriculum reform and media literacy, there is weaker alignment with stakeholder concerns around teacher capacity and youth engagement. This article contributes to both civic education research and emerging methods of using AI to support democratic processes by offering a transparent model for analysing large volumes of qualitative policy submissions.