Consumer automotive vehicles have been an essential part of daily life for many over several decades. Many people also find that the multimedia screens found in the center consoles of many modern vehicles are robust enough to complete a certain number of tasks, such as navigating to a destination, playing music, or taking a phone call. As a result, it is important for designers to look into their decisions and how they might affect the overall experience a person has while interacting with multimedia screen as they are driving a vehicle. This study aims to look into how existing design decisions present themselves in the multimedia screens of modern vehicles and which principles of design users favor when interacting with the systems. With 188 participants and three vehicles tested, including the 2019 Toyota Highlander equipped with native software, the 2019 Hyundai Sonata equipped with Android Auto, and the 2020 Hyundai Elantra equipped with Apple CarPlay, it was found that design principles found in Human Computer Interaction, such as Gestalt principles, are relevant in allowing for a more positive, enjoyable experience in completing tasks such as navigation, playing music, and taking a phone call.

Augmented reality offers a unique and innovative way to interact and connect with the natural world through the digital world. In an effort to better facilitate learning, this project makes use of web-based augmented reality. This project employs JavaScript libraries, AR.js and Three.js, to provide an augmented reality experience that better links real-world objects to information in a more digestible format. As well as discusses the many issues with technology and how to work around them and ultimately solve them.

Bad actor reporting has recently grown in popularity as an effective method for social media attacks and harassment, but many mitigation strategies have yet to be investigated. In this study, we created a simulated social media environment of 500,000 users, and let those users create and review a number of posts. We then created four different post-removal algorithms to analyze the simulation, each algorithm building on previous ones, and evaluated them based on their accuracy and effectiveness at removing malicious posts. This thesis work concludes that a trust-reward structure within user report systems is the most effective strategy for removing malicious content while minimizing the removal of genuine content. This thesis also discusses how the structure can be further enhanced to accommodate real-world data and provide a viable solution for reducing bad actor online activity as a whole.