Working with academic texts involves more than simply understanding the subject matter. When preparing for a seminar, for example, students must be able to contextualize texts within the course’s subject area, as well as identify and appropriately address any difficulties in comprehension. When analyzing literature for term papers, numerous other skills become important, including the ability to critically engage with self-selected research texts.

AI tools now promise to make it easier to tackle these challenges by suggesting and answering questions about the text, explaining sections of the text, or even summarizing entire texts. As a result, reading proficiency may be increasingly eroded or may not be developed at all. At the same time, difficulties with reading and comprehension are potentially masked, making them harder to address in courses.

This creates a new need to discuss the importance of reading in higher education and the design of reading processes. In this workshop, we will therefore explore ways to motivate and guide reading in the age of AI—with and without the use of AI tools.

Objectives:

Participants will

• reflect on their expectations regarding students’ reading proficiency and identify the challenges students face when working with academic literature
• reflect on changes in students’ reading practices brought about by AI
• share experiences regarding text analysis in teaching
• test various reading strategies with and without AI tools
• develop concepts for their own teaching

Content:

• Models and measures for promoting students’ reading proficiency
• The impact of AI on students’ reading habits
• Selected reading strategies—with and without AI—for use in teaching
• Development of individualized teaching concepts with feedback

Lecturer: Dr. Nora Hoffmann