Human-Computer Interaction

Serious Games & Pedagogical Agents for Teaching Machine Learning

This call for a thesis or project is open for the following modules:
If you are interested, please get in touch with the primary contact person listed below.


Machine learning is becoming increasingly prevalent in our daily lives and has grown to be one of the most important topics in science. Many schools and universities already teach it as part of their curricula. Unfortunately, students perceive machine learning and their inner workings as hard to learn and understand. Teaching these concepts could be assisted with Serious Games, which are games used for purposes other than mere entertainment, e.g., learning (1). These games envelop the concepts they want to teach in-game mechanics and require the players to repeatedly apply them, supporting learning by repetition and generating flow (2). They have been shown to improve the high-level understanding of the enveloped concepts (3). Pedagogical Agents have also been shown to be beneficial in learning applications. They support learning by offering explanations and guidance, giving feedback, and motivating students. They positively affect learning performance and have been shown to increase student motivation (4). They are beneficial in more complex topics (5) and are thus also suitable for helping students learn machine learning.

This project or thesis is concerned with further developing Traversing the Pass, a serious game about the basics of machine learning enhanced with pedagogical agents (6). Possible further developments are restructuring the gameplay to resemble a factory builder or evaluating the effect of different pedagogical agents on learning outcomes.


This project will focus on the following tasks:



Contact Persons at the University Würzburg

Philipp Krop (Primary Contact Person)
Human-Computer Interaction Group, University of Würzburg

Dr. Sebastian Oberdörfer
Human-Computer Interaction Group, University of Würzburg

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