Conversational AI as a catalyst for informal learning: An empirical large-scale study on LLM use in everyday learning

Large language models have not only captivated the public imagination but have also sparked a profound rethinking of how we learn. In the third year following the breakthrough launch of ChatGPT, everyday informal learning has been transformed as these novel tools become easily and widely available. Who is embracing LLMs for self-directed learning, and who remains hesitant? What are their reasons for adoption or avoidance? What learning patterns emerge with this novel technological landscape? We present an in-depth analysis from a large-scale survey of 776 German participants, showcasing that 87% of our respondents already incorporate LLMs into their everyday learning routines for a wide variety of (learning) tasks. Young adults among German-based, digitally engaged users are at the forefront of adopting LLMs, primarily to enhance their learning experiences independently of time and space. Four types of learners emerge across learning contexts, depending on the tasks they perform with LLMs and the devices they use to access them. Interestingly, our respondents exhibit paradoxical behaviors regarding their trust in LLMs’ accuracy and privacy protection measures. Our implications emphasize the importance of including different media types for learning, enabling collaborative learning, providing sources, and meeting the needs of different types of learners and learning by design.