I AM A.I. Gradient Descent - an Open-Source Digital Game for Inquiry-Based CLIL Learning

Carina Geldhauser, Andreas Daniel Matt, Christian Stussak

Abstract: We present an interactive online workshop for K-12 students, which aims in familiarizing students with core concepts of AI. The workshop consists of a variety of resources, inspired by inquiry-based learning techniques, of which we present in detail one module, centered around a browser-based game called Gradient Descent. This module introduces the mathematical concepts behind a gradient descent-based optimization algorithm through the computer game of a treasure hunt at an unknown sea surface landscape. Finally, we report on student feedback for the module in a series of content and language integrated learning in German (CLiLiG) workshops for students aged 14-17 in 30 countries.