Foundational AI Literacy in Under-Resourced South African Schools: Baseline Orientations and Learner Reflections After a Low-Infrastructure Workshop

Background and objectives: Foundational artificial intelligence (AI) literacy is fast becoming essential to education and work, yet learners in under-resourced schools may have limited access. This feasibility study examined whether a low-infrastructure AI literacy workshop could be delivered to Grade 11 public school learners in Gauteng, South Africa, and described learners’ baseline AI-related orientations and their immediate responses and reflections after the workshop. Methods: The study adopted a pragmatic, convergent mixed-methods design. We recruited Grade 11 learners from under-resourced public schools in the Johannesburg South education district through purposive and convenience sampling. They attended a three-hour, facilitator-led workshop which did not require individuals to have digital devices. We administered anonymous paper questionnaires before the workshop (n = 237; three single-item self-report indicators) and after it (n = 220; structured evaluation items and open-ended questions). Baseline items were analysed using descriptive statistics, one-sample t-tests against the scale midpoint, and Pearson correlations; open-ended responses were analysed thematically. Results: Before the workshop, mean ratings for perceived AI clarity (M = 3.61, SD = 0.992), relevance to tertiary education (M = 3.80, SD = 0.796), and relevance to work (M = 4.17, SD = 0.795) all exceeded the neutral midpoint (p