Encouraging play experience expansion with machine-learning-based recommendation systems: user-experience design considerations in the use of recommendation system
Creators: name: Espinosa, Hernan
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 470102
subject: Communication technology and digital media studies

description: In this practice-led research project, I explore how user experience designers can incorporate components and features based on the resources that stem from the field of artificial intelligence (A.I.) into their designs. I focus my investigation on exploring how designers can build A.I. systems that communicate their outputs and functions meaningfully to their users. This issue is critical if designers are to build their users' trust, allow them to control these systems and build collaborations between the users and the machine learning system (Xu 2019; Wang et al. 2019; Lim et al. 2019; Abdul et al. 2018; Zhu et al. 2018; Holmquist 2017; Ehsan et al. 2021, pp. 3–4; Meron 2022; Llano et al. 2020).

Here, I explore two design frameworks designers may use to decide why and how they may use A.I.-based components as part of the products they build. Specifically, I explore how designers may use design principles extracted from the fields of explainable A.I. and personal informatics to design recommendation systems that, apart from offering recommendations based on their users' behaviours, can help those same users track their behaviours and performance in different contexts to assist them in setting learning and performance goals regarding different types of situations, like learning and training, and progress towards them. I examine these principles using them to design, through reflective practice, a companion recommendation system for StarCraft II. I review the theories and background that allow me to understand the design principles in detail. Hence, I explore various concepts and definitions from the fields of Artificial Intelligence, Human-Computer Interaction and Game Design to fully understand how to apply the principles to a design project.

I also use the ideas to build a design repertoire I can draw from as I build my project. For this reason, I analyse the case study of the course recommendation system of Super Mario Maker 2 using these principles as analytical benchmarks. This recommendation system helps players select what courses to play amidst the broad library of user-made Super-Mario-style courses that make up the game. Finally, I composed three design deliverables where I compiled the design of the user experience of StarCraft 2 Training Grounds. I analyse these deliverables and their development process to examine the use of the frameworks as design guides. User experience designers and scholars will find in this project multiple examples of implementations of the explainable A.I. and personal informatics frameworks to shape and test their ideas for integrating A.I. components, such as recommendation systems, as part of 2
their products and solutions. With these examples, user experience designers may understand how they can use these frameworks to reconcile the features and limitations of their products' technical components and the experiences they are trying to build.