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How can academic writing in higher education remain meaningful for both learning and assessment in a world where generative AI tools like ChatGPT are always available to students? And how should educators respond? This self-study course offers a research-informed and practice-oriented exploration of these questions. It is designed for university instructors and supervisors who support students in writing term papers, essays and theses and who recognize that a “business as usual” approach is no longer sufficient in the age of AI. You will begin by examining why many existing approaches to supporting and assessing academic writing were already problematic even before the widespread use of AI. Building on this, you will explore how AI is transforming academic work and what this means for teaching practice. The course shows how to design and supervise term papers and theses in ways that both support student learning and allow for meaningful assessment of students’ competencies. The focus is on both conceptual foundations and practical strategies, including feedback processes, structured reflection, and alternative approaches to grading. You will learn how to reduce incentives for academic dishonesty through transparent guidelines, process-oriented supervision, and clearly defined roles – without relying on control or mistrust. The course is modular, academically grounded, and closely aligned with real challenges in higher education. It offers practical examples, reflection prompts, and concrete tools to support the development of your own teaching practice. This way, you can increase your confidence in the quality of your supervision – even in the age of AI.
By the end of this course, you will be able to:
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