A new era in Education: Equipping first-year students with AI-driven study skills
DOI:
https://doi.org/10.56433/mae00e73Keywords:
AI Literacy, Learning with AI, New Learning Techniques;, Learning Analytics, AI TutorAbstract
The rise of Artificial Intelligence (AI) has ushered in new modes of learning, with students of all ages sharing a common desire for greater efficiency. Tasks that traditionally consumed significant time—such as researching and summarising academic literature, visualising data or querying AI for exam-relevant topics—are among the many areas where learners are turning to AI for support.
Yet, the abundance and diversity of AI tools can be overwhelming. Students require clear guidance to identify which tools serve which purposes; without it, frustration mounts and procrastination may follow—undermining academic success. AI reaches its full potential only when paired with established learning strategies like self-organisation and critical thinking.
This was the impetus for FernUniversität to introduce a new extracurricular course, Learning with AI, into its studyFIT programme. Aimed at first-year students from all faculties, the course offers a practical introduction focused on developing the study skills outlined above. It was developed by an interdisciplinary team of experts in AI and data literacy, media didactics and academic writing, along with student assistants from various disciplines. Lasting 25 to 30 hours, the course is grounded in the AI Course Design Planning Framework (Schleiss et al., 2023) and aligns with the university’s AI guidelines (Biederbeck et al., 2024).
In our case study, we present the course design and highlight student feedback and data gathered through a mandatory initial and follow-up survey, as well as through learning analytics. We also reflect on key lessons learned and detail how the evaluation process has informed adjustments to both course design and content. In doing so, we address how support services can foster AI literacy among first-year students of all ages, considering their varied backgrounds in knowledge and technical competence.
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Copyright (c) 2026 Dr Andre Biederbeck, Dr Moritz Kohls
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