AI is becoming increasingly integrated into every aspect of society, and there is an urgent need for early educational engagement to build foundational understanding. “Girls–the Future Calls” is a series of two-hour, hands-on Artificial Intelligence (AI) workshops designed to foster AI literacy and spark curiosity and narrow gender gaps in informatics among middle school students whose emerging abstract reasoning, identity exploration, and curiosity make them especially open to foundational AI concepts. This study addresses the urgent need to engage girls early in AI literacy to narrow the persistent gender gap in informatics, a field where women comprise only 22 percent of AI professionals globally and under 6 percent of AI–related software developers.

Grounded in constructivist learning theory, the 5E Instructional Model, each workshop began with an interactive introduction to spark students' interest and brainstorm about AI. Students received a paper with the tool names for notetaking during exploration. It comprises four thematic activity clusters: Programmable Robots, Hands-on AI Tools, Virtual Assistants, and Internet Safety, explicitly aligned to seventeen core AI competencies. These competencies are also mapped to established digital-literacy frameworks. The alignment ensures that each activity reinforces specific AI concepts and skills. Students rotated through all clusters, allowing each participant to engage with all activities. Following, students completed an age-adapted AI-literacy questionnaire, discussed each item in real-time, and indicated their preferred activity and interest in pursuing informatics. Each questionnaire item was tied to one or more of the core competencies and drew on formative-assessment principles, allowing immediate feedback and guided group discussion. Finally, participants were provided with a take-home list of AI resources and activities designed to reinforce workshop learning and encourage continued exploration of AI concepts.

This workshop demonstrated substantial positive outcomes. Analysis of responses from 164 participants (62 % girls) revealed an overall correct response rate of 46 %, with strengths in knowledge representation (74 %) and societal challenges (71 %), and identified conceptual gaps in distinguishing narrow versus general AI (10 %), understanding AI’s capabilities and limitations (14–16 %), and data-related concepts (12–19 %). Qualitative observations and facilitator feedback highlighted high engagement, especially with robot and creative AI stations, and an increased self-reported interest in informatics. Implications for enhancing middle school AI curricula include targeted activities to address identified conceptual gaps, extending workshop duration for deeper exploration, and developing teacher-training modules to sustain AI education beyond these sessions.

Keywords: Artificial Intelligence, Middle School, Gender Equality in Informatics, AI Education, AI activities.