In the evolving landscape of language education, artificial intelligence and machine learning are often perceived as a threat, while they provide the potential of transforming the way how students engage with texts on a different level. None of them will be able to read or cross-read thousands of media texts, even less books. This is where TextMinR comes into play. Our web-based, AI-powered platform enables language teachers and learners to interactively explore and visualize connections among literary works, historical contexts and current news media topics. Through dynamic visualizations, such as co-occurrence graphs, timeline mappings and thematic heatmaps overlaying the world map our users, students and teachers alike, can rapidly sift through large corpora of news articles and classic literary texts, uncovering semantic relationships that would otherwise require extensive manual analysis. Developed collaboratively by technical vocational high school students as part of their diploma thesis projects, TextMinR uniquely combines educational design with hands-on implementations ranging from topic models and sentiment analysis to the design of a user-friendly user interface. The implementation was driven end-to-end by learners under the guidance of language teachers and the authors as the AI and UX specialists among the teachers. This approach unites the best of both worlds. Firstly, it provides the students who have worked on the project with excellent real-life experience in project work with dynamically shifting requirements and scarce resources. Secondly, it provides the teachers and project leads with the perspectives of their actual target group who know best how to grasp the interests of this age group and provide materials in an attractive manner. In classroom pilots, the TextMinR tool has successfully been implemented by three project groups of students who managed to incorporate direct feedback of language teachers, who applied their tool in class, and students, who worked with the tool for the first time. Not only was the tool met with a broad acceptance, but also the active participation in literature classes has been noticeably increased through applying this technology. The tool has initiated deeper discussions, enhanced critical reading skills and promoted reflective as well as responsible usage of AI technologies. By situating TextMinR at the intersection of vocational high school engineering pedagogy, AI innovation and collaborative and interactive learning, this paper demonstrates how student-led technical projects can yield useful resources for language and technical pedagogy, empowering both teachers and learners in the safe, interactive exploration of language and critical media usage, which is among the most relevant future skills.

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