Barrett, The Honors College Thesis/Creative Project Collection

The pandemic that hit in 2020 has boosted the growth of online learning that involves the booming of Massive Open Online Course (MOOC). To support this situation, it will be helpful to have tools that can help students in choosing between the different courses and can help instructors to understand what the students need. One of those tools is an online course ratings predictor. Using the predictor, online course instructors can learn the qualities that majority course takers deem as important, and thus they can adjust their lesson plans to fit those qualities. Meanwhile, students will be able to use it to help them in choosing the course to take by comparing the ratings. This research aims to find the best way to predict the rating of online courses using machine learning (ML). To create the ML model, different combinations of the length of the course, the number of materials it contains, the price of the course, the number of students taking the course, the course’s difficulty level, the usage of jargons or technical terms in the course description, the course’s instructors’ rating, the number of reviews the instructors got, and the number of classes the instructors have created on the same platform are used as the inputs. Meanwhile, the output of the model would be the average rating of a course. Data from 350 courses are used for this model, where 280 of them are used for training, 35 for testing, and the last 35 for validation. After trying out different machine learning models, wide neural networks model constantly gives the best training results while the medium tree model gives the best testing results. However, further research needs to be conducted as none of the results are not accurate, with 0.51 R-squared test result for the tree model.

This creative project is a short story in the Gothic genre followed by an explanation of certain literary elements and decisions. The Gothic genre often explores supernatural and uncomfortable topics that can challenge the reader’s perception and understanding of the world. Through this means of storytelling, authors are given the opportunity to connect the supernatural with complex and sensitive topics that may be difficult or even taboo to speak about in certain locations and time periods. In this thesis, I embrace the traditions of the Gothic-genre with a story that focuses on the issues prevalent today. The years 2020 and 2021 have been unprecedented times for humanity. Technology continues to grow at an alarming rate, suicide rates of young people have been on the rise for years, and a global pandemic has people adapting to all new ways of living. During these ever changing times, it is the Gothic that may provide guidance through these uncertainties by shedding light on the problems that will plague humanity both today and tomorrow. The story follows an outcast from society who aids in the creation of a divine monster, and the consequences that follow.

Engaging users is essential for designers of any exhibit, such as the human-computer interface, the visual effects, or the informational content. The need to understand users’ experiences and learning gains has motivated a focus on user engagement across computer science. However, there has been limited review of how human-computer interaction research interprets and employs the concepts in museum and exhibit settings, specifically their joint effects. The purpose of this study is to assess users’ experience and learning outcome, while interacting with a web application part of an exhibit that showcases the NASA Psyche spacecraft model. This web application provides an interactive menu that allows the user to navigate on the touch panel installed within the Psyche Spacecraft Exhibit. The user can press the button on the menu which will light up the corresponding parts of the model with a detailed description displayed on the panel. For this study, participants were required to take a questionnaire, a pretest, and a posttest. They were also required to interact with the web application while wearing an Emotiv EPOC+ EEG headset that measures their emotions while they were visiting the exhibit. During the study, data such as questionnaire results, sensed emotions from the EEG headset, and pretest and posttest scores were collected. Using the information gathered, the study explores user experience and learning gains through both biometrics and traditional tools. The findings show that users felt engaged and frustrated the most and that users gained more knowledge but at varying degrees from the interaction. Future work can be done to lower the levels of frustration and keep learning gains at a more consistent rate by improving the exhibit design to better meet various learning needs and visitor profiles.

The study of macaque monkeys harbors advancements in the field of biomedical research. It is imperative to understand the genetic composition of different species of macaques to assess their accuracy as non-human primate (NHP) models for disease detection and treatment assessments. We sought to characterize the hybridization and admixture of the Southeast Asian macaques using single nucleotide polymorphism markers and analyzing the populations on the mainland and the island. Using AMOVA tests and STRUCTURE analysis, we determined that there are three distinct populations: Macaca mulatta, M. fascicularis fascicularis, and M. f. aurea. Furthermore, the island species holds an isolated population of M. f. aurea that demonstrate high inbreeding and genetic uniqueness compared to the mainland species. Findings from this study confirm that NHP models may need to be modified or updated according to changing allelic frequencies and genetic drift.

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.