This creative project develops an environment in which three species inhabit a shared land and models the movement of the creatures to determine the survival rates over time in specific conditions. The three species modelled include a predator and a prey species with movement capabilities as well as a stagnant fruit species. There are a variety of configurable variables that can be used to modify and control the simulation to observe how the resulting population charts change. The big difference between this project and a normal approach to simulating a predation relationship is that actual creatures themselves are being created and their movement is simulated in this virtual environment which then leads to population counts, rather than integrating differential equations relating the population sizes of both species and purely tracking the populations but not the creatures themselves. Because of this difference, my simulation is not meant to handle all the complexities of life that come in the real-world but instead is intended as a simplified approach to simulating creatures' lives with the purpose of conveying the idea of a real predation relationship. Thus, the main objective of my simulation is to produce data representative of real-world predator-prey relationships, with the overall cyclical pattern that is observed in natural achieved through simulating creature movement and life itself rather than estimating population size change.

This research study investigates the design principles and best practices for incorporating gamification in EduMobile apps for teaching about mosquito breeding grounds. With limited research investigating the effectiveness of EduMobile apps in engaging and educating students on complex topics, this study aims to uncover best practices for designing EduMobile apps for early learners (elementary and middle schoolers). A convenience sample of adults who were not part of the target demographic were recruited to test the app. The System Usability Scale was used to measure user satisfaction, and question-wise t-tests were conducted to analyze the effectiveness of specific design changes. Results show a significant difference in user satisfaction between the original and revised designs, with question 5 of the System Usability Scale driving the overall difference in score. Inconsistent design was found to increase extraneous cognitive load and split attention, while consistency within different views was shown to increase user perception of system integration. These findings suggest that incorporating gamification and following best practices in designing EduMobile apps can increase student engagement and motivation in learning about mosquito breeding grounds.

The purpose of this research thesis paper is to provide further insight into the development of extended reality (XR), augmented reality (AR), and virtual reality (VR) technologies within the educational space and survey how well they are received as well as whether or not they can provide additional learning benefit in regards to other learning mediums such as reading textbooks, watching videos on the subject matter, and other such more traditional mediums. The research conducted consisted of a collaborative effort alongside the School of Biological and Health Systems Engineering (SBHSE) personnel and using their provided resources in order to generate a framework with the aforementioned technology, to aid in the development of a web-based XR system which will serve primarily as a means for SBHSE students at Arizona State University (ASU) to enhance their learning experience when it comes to topics such as anatomy and physiology of the human body, with the potential of extending this technology towards other subject matters as well, such as other STEM-related fields. Information about the initial research which included an analysis of the pertinent readings that support a benefit to using XR technology as a means to deliver course content is what is first focused on throughout this document. Then, the process that went into the design and development of the base framework that was in joint collaboration with the SBHSE will be covered. And, to conclude, a case study to generate applicable data to support the argument is covered as well as the results from it, which presented a potential for a future development plan and next steps plan once the developed materials and research are handed off.

NASA has partnered with multiple colleges, including ASU, on a mission to study an asteroid called Psyche. Psyche is the first asteroid discovered made of metal, mostly iron, that is close enough for us to study and could give insight into what Earth’s core is like. The mission plans and research documents on how the various measurement tools work are not engaging to those without a background in STEM. This serves as inspiration to make a web-based game in order to make the information more engaging to the player. This web-based game will take the user through the Psyche mission going from the assembly of the measurement tools all the way to when the satellite is orbiting the asteroid. The creative project consisted of creating a simulation for a young audience, between ages 10 and 18, to experience what the mission could look like once the satellite is at the Psyche asteroid and what the data collected could mean. The asteroid could have been formed through a process called the dynamo process or it could be a piece of a larger parent body. It could be made mostly of metal or silicates, which will be determined during the mission. These are some of the results that will be generalized and relayed to the player. This creative project includes the four main sections of the orbit phase of the mission in which the users will perform tasks to collect some data in order to see some of the generalized possible results of the study of Psyche. Some of the data collected would be the amount of metal making up the asteroid and figuring out what the gravitational pull is. The first main section will use the magnetometer, the second section will use the multispectral imager, the third section will use X-Band Radio Waves, and the fourth section will use the gamma ray and neutron spectrometer.

A Skunkworks project is the name given to a small team of individuals leading an innovative undertaking, and conducting research and development outside of the normal scope of an organization. With this concept in mind, our team of six individuals was tasked with finding and conceptualizing innovative solutions within varying business markets of interest. Our team started off with five markets that we identified issues in and were passionate about solving. These included Sports Engagement, Education, Student Debt, Digital Literacy, and Viral Health. From extensive research, trial and error, and endless conversations we settled on creating business models in two final areas: Student Debt and Viral Health. Our research in Student Debt led us to the discovery that the average Arizona State student, takes out $21,237 in loans for their four year degree and in the whole state of Arizona, a student takes on an average of $22,253. Our solution to this problem was to create a student financial app that served as an efficient debt tracker that provided important information about finances, investing, and student loan information. Additionally, our team also wanted the address the issue of sexually transmitted diseases, just a small scope of Viral Health, within Arizona State University. Our research led us to discover that 50% of people report not getting tested, and from this population most reported it was due to anxiety and financial issues. From our research the StayInformed app was created to provide students with better accessibility to both at-home and clinic testing services, and updated education on sexual health. With this project model we hope to increase the rate of students testing and allow students more agency over their sexual health. Although these two services are addressing very different markets, they both utilize forward thinking technology to create much needed solutions and better the lives of students.

Machine learning is a rapidly growing field, with no doubt in part due to its countless applications to other fields, including pedagogy and the creation of computer-aided tutoring systems. To extend the functionality of FACT, an automated teaching assistant, we want to predict, using metadata produced by student activity, whether a student is capable of fixing their own mistakes. Logs were collected from previous FACT trials with middle school math teachers and students. The data was converted to time series sequences for deep learning, and ordinary features were extracted for statistical machine learning. Ultimately, deep learning models attained an accuracy of 60%, while tree-based methods attained an accuracy of 65%, showing that some correlation, although small, exists between how a student fixes their mistakes and whether their correction is correct.