Jul 2026· Compass: Journal of Learning and Teaching in Higher Education· Vol 18· 0 citations
TL;DR
This case study examines how students were positioned as experts in shaping artificial intelligence (AI) literacy curricula at a United Kingdom university, and contributes to the current discourse on fostering critical, responsible AI literacies in HE through the lens of students as partners.
Abstract
This case study examines how students were positioned as experts in shaping artificial intelligence (AI) literacy curricula at a United Kingdom university. Academic staff, students and professional services collaborated to co-create an AI literacy framework with a focus on generative AI, addressing institutional and learner needs. Guided by partnership principles of reciprocity, respect and shared responsibility, the project responded to the opportunities and challenges of AI in higher education (HE).
Following a cross-disciplinary survey which captured student perceptions of generative AI use, two student partners were appointed; their roles evolved from research interns to co-designers and co-evaluators during this funded project. They have co-led focus groups with students, conducted data analysis and synthesis and undertaken peer consultation and evaluation to co-develop guidance resources on ethics, integrity, bias and responsible AI use.
Two key outputs resulted from this collaboration: a four-step AI literacy framework and an online tutorial which are now embedded in central pre-enrolment and academic skills programmes. Framing students as co-designers helped both 1) to enrich staff understanding of student perceptions of generative AI use for learning and 2) to enable the students to enhance their research, collaboration, communication and leadership skills. The study contributes to the current discourse on fostering critical, responsible AI literacies in HE through the lens of students as partners.
Despite growing emphasis on AI literacy education, empirical research examining how secondary students engage with and apply AI concepts in authentic project-based learning environments remains limited, particularly among students from historically underserved communities. This mixed-methods study examined African American high school students’ experiences in an AI-enhanced mobile app design project in which generative AI served as a collaborative design partner. Grounded in AI literacy frameworks, the program combined foundational AI instruction with a four-month project-based experience focused on designing AI-enhanced mobile applications. Qualitative data included focus group interviews, student design artifacts, presentations, and researcher field notes, while quantitative data included pre- and post-AI literacy assessments and surveys. Analysis of student design artifacts and presentations revealed that participants demonstrated emerging understanding of AI concepts by proposing AI-enabled features such as recommendation systems, chatbots, and information verification tools within their mobile app designs. Survey results indicated improvements in professional skills, particularly in collaboration, communication, and problem-solving. Knowledge assessment results showed modest but non-significant changes in students’ conceptual AI knowledge, with variation in individual learning trajectories. The study also identified several instructional challenges, including differences in students’ technological readiness and tensions surrounding AI use, ranging from overreliance to avoidance of AI use due to concerns about academic penalties. These findings highlight the potential of AI-enhanced project-based learning to support students’ development and application of AI literacy while underscoring the need for instructional scaffolding to guide students’ effective and ethical use of AI as a collaborative partner in K-12 learning environments.
Jung Won Hur, Jay Bhuyan, Fan Wu et al.· Discover Education· 0 citations
Examination of a classroom practice using Personary, a digital mind-mapping platform with an optional AI-assisted mode, to explore how university students conceptualize competencies needed in the AI era shows that students understood AI-era competencies as multidimensional capacities rather than as technical skills alone.
A seven-component Student-AI-Centered conceptual framework that integrates AI into curricula while emphasising ethical awareness, diverse assessment modalities and ongoing educator support is proposed, which bridges the gap between teacher-centered, student and AI-centered paradigms.
Annisa Fitri, Hamza Yusuf, Abdur Razzaq et al.· Education Innovations: Syste...· 0 citations
This article argues for a reframing of AI literacy in MA TESOL education from a compliance-driven competency to a co-constructed process of inquiry, reflection, and critical engagement. The discussion is prompted by a classroom activity in which an AI-generated annotated bibliography, which contained entirely fabricated references, was initially judged by postgraduate students to be credible and academically appropriate. Whilst the exercise exposed challenges associated with verifying AI-generated academic content, it also highlighted broader questions about how AI literacy is conceptualised and developed within TESOL. Drawing on thematic analysis of interviews with two international MA TESOL students, the study explores how students understand, use, and evaluate AI following institutional guidance and targeted classroom input. Findings reveal emerging but cautious forms of AI literacy characterised by scepticism, risk awareness, verification practices, and anxiety regarding plagiarism and academic integrity. Despite explicit instruction, participants positioned AI primarily as a source of potential error rather than as a pedagogical resource. This article therefore proposes a co-constructed model of AI literacy that values dialogue, shared inquiry, scaffolded experimentation, and process-oriented assessment that enables students to develop reflective, context-sensitive, and professionally relevant AI practices.
Rhian Webb· Language Teacher Education R...· 0 citations
Artificial Intelligence (AI) is transforming higher education and reshaping the capabilities graduates require for professional practice. As AI becomes increasingly embedded in workplaces, universities must move beyond teaching AI tools and instead develop curricula that foster AI literacy, critical thinking, ethical reasoning and effective human–AI collaboration. However, there is limited guidance on how these capabilities can be systematically embedded across higher education programs.
This paper proposes the Human-Centred AI Education Framework, comprising five developmental stages: AI Awareness, AI-Assisted Learning, Critical Evaluation, Human–AI Collaboration, and Professional Practice. The framework provides a structured approach for integrating AI into teaching, learning and assessment while maintaining the central role of human judgement, accountability and responsible AI use.
The framework is demonstrated through a postgraduate project management subject in which students used Generative AI to support authentic learning activities. Classroom observations indicate that structured AI integration promotes critical evaluation, reflective practice and professional judgement by encouraging students to evaluate rather than simply accept AI-generated outputs.
The paper contributes a practical curriculum framework that can be adapted across disciplines to prepare graduates for responsible participation in AI-enabled professional environments while preserving the human-centred capabilities essential for lifelong learning and professional practice.
P. Wong· International journal of res...· 0 citations
The findings indicate that primary school teachers’ AI literacy is not limited to technical proficiency but constitutes an integrated professional competence characterised by an “awareness-driven, knowledge-supported, competence-oriented, and ethics-guided” mechanism.
Yang-Hua Qiu· International Educational Re...· 0 citations
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