Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- Creators: Computer Science and Engineering Program
Social injustice issues are a familiar, yet very arduous topic to define. This is because they are difficult to predict and tough to understand. Injustice issues negatively affect communities because they directly violate human rights and they span a wide range of areas. For instance, injustice issues can relate to unfair labor practices, racism, gender bias, politics etc. This leaves numerous individuals wondering how they can make sense of social injustice issues and perhaps take efforts to stop them from occurring in the future. In an attempt to understand the rather complicated nature of social injustice, this thesis takes a data driven approach to define a social injustice index for a specific country, India. The thesis is an attempt to quantify and track social injustice through social media to see the current social climate. This was accomplished by developing a web scraper to collect hate speech data from Twitter. The tweets collected were then classified by their level of hate and presented on a choropleth map of India. Ultimately, a user viewing the ‘India Social Injustice Index’ map should be able to simply view an index score for a desired state in India through a single click. This thesis hopes to make it simple for any user viewing the social injustice map to make better sense of injustice issues.
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.
Th NTRU cryptosystem is a lattice-based encryption scheme. Several parameters determine the speed, size, correctness rate and security of the algorithm. These parameters need to be carefully selected for the algorithm to function correctly. This thesis includes a short overview of the NTRU algorithm and its mathematical background before discussing the results of experimentally testing various different parameter sets for NTRU and determining the effect that different relationships between these parameters have on the overall effectiveness of NTRU.
This paper addresses echo chambers, an online phenomena wherein social media users can "only hear their own voice". In this paper I will examine the history and recent proliferation of online echo chambers. I will outline a comprehensive theory of echo chamber generation and maintenance, intended for educational value. I then conduct my own experiment based on previous echo chamber detection work.