Computer Sciences Commons^™

8. Ai And Writing Classrooms: A Study Of Purposeful Use And Student Responses To The Technology, Laura Dumin

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

Given that Al is here for the foreseeable future, I revamped my spring 2023 English courses to include using Al in purposeful ways. I submitted an IRB to test different approaches to integrating Al into my classrooms. The study asked students in three different English courses to complete pre- and post-reflections about their understanding of Al and its uses.

This chapter will discuss how my students responded to the use of Al in the writing classroom, how student attitudes toward Al shifted over the course of the semester, ideas for how to use Al in writing classrooms, and the main …

Part Ii: Section 2: Research Studies, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

5. Navigating Benefits And Concerns When Discussing Genai Tools With Faculty And Staff, Reed Hepler

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

The author works as a Digital Initiatives Librarian and is earning a second Master's Degree in Instructional Design and Technology. He viewed ChatGPT immediately as yet another potentially useful technology. When educators at his institution promoted differing viewpoints regarding ChatGPT and other Al tools, he set out to demonstrate a method of Al integration similar to that of other technological tools. Using the Technology Consumer or Producer model and his own experience, he presented, discussed, and wrote about ChatGPT, its ethical issues, and its uses and impact on education. Reed shares his insights regarding creating instruction and training for educators. …

3. Empowering Educators In The Age Of Generative Ai: A Critical Media Literacy Approach, Ali Söken, Kysa Nygreen

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This chapter draws from the authors' experience teaching an undergraduate course in the context of Generative Al (GenAl), and shares three instructional innovations we are implementing in response: 1) establishing an appropriate tone; 2) designing in-class activities to engage critically with GenAl; and 3) revising assessment and grading policies. These adaptations are informed by the framework of Critical Media Literacy (CML), which grounds the course. They aim to strike a balanced view that acknowledges both challenges and potentials of GenAl. This chapter aims to furnish a contextual framework for fellow educators to critically engage with the realm of GenAl. Core …

2. Some Ethical Considerations For Teaching And Generative Ai In Higher Education, Lydia Wilkes

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

The chapter discusses some ethical considerations for teaching and generative Al in higher education with a focus on large language models like ChatGPT. These considerations include generative Al's effects on the environment and labor, its reliance on data and tendency to violate privacy, the biases encoded in it, and the digital divide. As more sophisticated generative Al is integrated into word processors, these ethical concerns will become more difficult to perceive and the ethics of using Al more difficult to parse. This chapter concludes with a note on power and justice.

Part I: Section 1: Framing Concepts, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

Introduction, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

With the rapid development of generative Al, teachers are experiencing a new pedagogical challenge, one that promises to forever change the way we approach teaching and learning. As a response to this unprecedented teaching context, this collection-Teaching and Generative Al: Pedagogical Possibilities and Productive Tensions-provides interdisciplinary teachers, librarians, and instructional designers with practical and thoughtful pedagogical resources for navigating the possibilities and challenges of teaching in an Al era. Because our goal with this edited collection is to present nuanced discussions of Al technologies across disciplines, the chapters collectively acknowledge or explore both possibilities and tensions-including the strengths, …

Land Acknowledgement/Foreword, Tazin Daniels

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

In the rapidly evolving landscape of higher education, the emergence of Generative Artificial Intelligence (Al) stands as a beacon of both innovation and introspection, heralding a new era in teaching and learning. This book serves as a guide for college instructors who find themselves at the cusp of this technological revolution-those who are intrigued yet perhaps apprehensive, eager to explore yet unsure where to begin. As we begin this journey, it is vital to acknowledge the spectrum of emotions that accompany its integration into academia: from excitement and curiosity to caution and concern. Recognizing and normalizing these feelings is the …

13. Rude Reflections: Current Ai Acts As A Mirror Of Our Flawed Society, Belinda 'Ofakihevahanoa Fotu

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

In face-to-face classrooms, culturally and critically conscious teachers fight to mediate skills, content, and students' backgrounds all within the bounds of a systematically flawed educational institution. For now, AIs that aid in writing bypass that kind of meaningful work as AIs reflect the corpus of published literature that overwhelmingly reflects historically problematic hierarchical biases.

Deepwhalenet: A Climate Change-Aware Fft-Based Neural Network For Underwater Passive Acoustic Monitoring, Nicholas Ryan Rasmussen

Dissertations and Theses

In the face of escalating climate threats, the conservation of whale species has become increasingly critical. Traditional acoustic monitoring methods, burdened by extensive pre-processing and post-processing, need more adaptability and efficiency for effective marine mammal surveillance. This study introduces DeepWhaleNet, a novel deep-learning framework tailored for Underwater Passive Acoustic Monitoring (UPAM). DeepWhaleNet is designed to streamline whale detection by directly analyzing raw log-power spectrograms, thus extracting essential acoustic features to conserve these endangered species. The framework employs an extensive short-time Fourier transform (STFT) for input processing and a customized ResNet-18 architecture for classification, distinguishing whale vocalizations from ambient noise and …

Mivt: Medical-Informed Vision Transformer For Early Epilepsy Diagnosis, Md Masum Rana

Dissertations and Theses

Epilepsy is a neurological disorder characterized by recurrent, unprovoked seizures, and early diagnosis is crucial for effective management and treatment. However, the diagnosis of epilepsy, particularly in its early stages, remains challenging due to the subtle nature of seizures and the complexity of brain activity patterns. In this research, we introduce the Medical-Informed Vision Transformer (MIVT), a deep learning architecture specifically designed to improve early epilepsy diagnosis from multimodal neuroimaging data. Our model integrates insights from both medical knowledge and state-of-the-art Vision Transformers (ViTs) to enhance the accuracy and interpretability of seizure detection and localization. The MIVT leverages the rich …

Development Of A Modular Lab Automation System With Applications To Animal And Bacteria Cell Culture, Timothy William Hartman

Dissertations and Theses

The challenges faced while executing wet lab protocols encourage the development of automation systems to come alongside human scientists. Today’s cutting-edge experiments involve complex protocols with precise measurements usually performed manually. Even simpler biological protocols can be tedious and prone to error, as was seen during the COVID-19 pandemic and society’s demand for high-volume, rapid sample analysis. Moreover, reproducibility suffers when there is excessive variability and insufficient data. Here, we leveraged the Stanford Biodesign process to develop a modular lab automation system and image analysis workflow to address challenges like these. This flagship automation platform at The University of South …

Artificial Intelligence And News Consumption: A Study Of Trust, Credibility And Transparency In Automated Journalism, Julia Lobo Paes

Dissertations and Theses

According to Gallup poll (2023), over the last 50 years there has been a decline in how much Americans trust mass media. While in the 1970’s 72% of the population responded that they trust the media a 'great deal/fair amount', this number dropped to 34% in 2023. Given the decreasing public trust in news, this thesis focused particularly on analyzing trust in the organization, trust in the news story and perceived credibility in AI generative content. In addition to articles created by AI, this study also aimed to analyze how the public perceives information that has been personalized and distributed …

Unveiling User Perspectives: Exploring Themes In Femtech Mobile App Reviews For Enhanced Usability And Privacy, Nidhi Nellore, Tania Mishra, Michael Zimmer

Computer Science Faculty Research and Publications

Femtech, a growing sector in mobile healthcare technology, caters to women's needs across various life stages with digital solutions like period tracking and pregnancy management apps. Maintaining robust data privacy is crucial due to the sensitive nature of the information involved, such as menstrual cycles and pregnancy status. Our research analyzes user feedback from platforms like the Apple App Store and Google Play Store to understand perceptions of femtech apps, covering accessibility, interface, features, and privacy concerns. Understanding user perspectives helps developers enhance usability and trust, driving further adoption. Prioritizing privacy also fosters industry advancement. This paper stresses the importance …

Remember The Human: A Systematic Review Of Ethical Considerations In Reddit Research, Casey Fiesler, Michael Zimmer, Nicholas Proferes, Sarah A. Gilbert, Naiyan Jones

Computer Science Faculty Research and Publications

Reddit is one of the world's most prominent social media platforms, and also a valuable source of data for internet researchers. However, working with this kind of data also presents novel ethical complications for researchers, including issues around privacy, vulnerable populations, and unintended consequences. This paper describes an analysis of 134 papers that rely on Reddit data while also including some discussion of ethical implications and/or considerations by the researchers. Our analysis of these papers reveals common ethical issues and ethically motivated methodological decisions, as described by the researchers themselves, while also exposing some gaps for further ethical contemplation for …

Short, Full, Best: Analysis Of Different Conference Papers, Miguel Williams

Graduate Research Theses & Dissertations

Research, publish, repeat. This is the basic cycle of anyone in academia. Individuals in academia conduct research, write up your research into a paper or journal article, submit to a conference or journal, and repeat the process. If you're skilled you may even obtain the coveted best paper award from the conference. In this research, I compare full papers to short papers and full papers to best papers. I start by fine-tuning three transformer models for classification capabilities. After I calculate lexical diversity and readability metrics of the papers, I use the features to train three traditional machine learning models. …

Ai-Based Defect Detection In Aerospace Ultrasonic Signals, Rami Issac Lake

Graduate Research Theses & Dissertations

Ensuring the safety and integrity of materials and structures throughout the manufacturing cycle is a critical concern across various industries, including aerospace, automotive, oiland gas, and civil engineering. Non-Destructive Inspection (NDI) techniques allow for the examination of materials without causing damage or alteration, enabling the early detection of potential issues before materials are utilized in the field. The inspection of fuselage composites presents a particular challenge due to their complex structures, diverse materials, and differences in thickness, making defect detection a challenging yet crucial task. Moreover, defects of various types and causes can emerge across all depths of the material …

Volume 15, Connor Thompson, Emily Steffenhagen, Emily Robertson, Luis Fernando Dos Reis, Emily Farmer, Samuel Villa, Robert Allison, Zachary Chessor, Megan Borden, Austin Burnett, Larry W. Grant Jr., Tristan Marowski, Emma Moore, Pearl Siff

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Amorette Barber, Director, Office of Student Research

From the Editor Dr. Hannah Dudley-Shotwell

Artist’s Statement Connor Thompson

On Mentorship Dr. John Miller

The Meat of the Matter: Alien, Human, and Animal in Terry Bisson’s “They’re Made Out of Meat” by Emily Steffenhagen

“Please REBLOG!”: An Ethical Analysis of Doxxing, Internet Vigilantism and Racists Getting Fired by Emily Robertson

Journaling: Paper Has More Patience Than People by Luis Fernando Dos Reis

The Effects of Climate Change on the Archaeological World by Emily Farmer

Lowered Seat Height Does Not Impair Wingate Performance in Untrained Cyclists by Samuel Villa, Robert Allison, …

Machine Learning And Rna Bioinformatics, Jason Rafe Miller

Graduate Theses, Dissertations, and Problem Reports (ETD)

The applied science of bioinformatics encompasses computational analysis of molecular biology data. Advances in genomics and DNA sequencing technology have enabled computational analysis of ribonucleic acids (RNAs), which play diverse and critical roles in most cells. To assist the study of human RNA, we trained machine learning models on RNA nucleotide sequences, devoid of domain knowledge. We built models that distinguish long non-coding lncRNA from protein-coding mRNA, and models that predict the cytoplasmic vs. nuclear preferences of lncRNAs. In a review of published lncRNA subcellular localization classifiers, we show that the commonly used validation protocol generates optimistic performance measures, and …

On Confidence And Sense Of Belonging In Cybersecurity Students: Analysis & Prediction, Sadaf Amna Sarwari

Graduate Theses, Dissertations, and Problem Reports (ETD)

In recent years, there has been a rapid expansion of cybersecurity programs across higher education institutions in response to the widening skills gap in the cybersecurity job market. This study adopts quantitative and qualitative approaches to identify factors influencing West Virginia University (WVU)’s LANE Department of Computer Science and Electrical Engineering (LCSEE) students’ confidence and sense of belonging in the cybersecurity field. The results are based on data collected from surveys administered to LCSEE students in April 2022 and April 2023. The responses were analyzed using descriptive & inferential statistics and logistic regression techniques. Additionally, the 2023 data was utilized …

Simulation Of A Pick And Place System For Electronic Cards Using A Yumi Cobot, Derrick Sze, Rosula Sj Reyes, Patricia Angela R. Abu

Electronics, Computer, and Communications Engineering Faculty Publications

Collaborative Robots are one of the main drivers of Industry 4.0, which started as a vision focusing on industrial production. It addresses several challenges in the current manufacturing industry such as performing repetitive work and requiring highly skilled workers. The goal of the research is to be able to simulate a pick and place environment with electronic cards using a YuMi cobot and mobile platforms in Coppeliasim. The mobile robot is responsible for transporting the electronic cards to the target location through path planning implemented using the OMPL plug-in. After arriving at the target location, YuMi will then perform the …

Optimizing Sports Outcome Prediction Through Feature Engineering And Machine Learning, Vitor S. Freitas

Graduate Theses/Dissertations

The challenge of predicting the outcome of a team game lies in the high complexity and dynamics of the sports data. This thesis focuses on the aspect of using feature engineering and the genetic algorithm to predict the winner and the score of various sports events. Generally, it deals with how machine learning algorithms are combined with state-of-the-art feature engineering techniques in sports datasets derived from various sports disciplines. In this thesis, five different machine learning models have been applied, classification and regression trees (CART), random forest (RF), stochastic gradient boosting (SGB), eXtreme gradient boosting (XGBoost), and extreme learning machine …

A Unified Framework For Contextual And Factoid Question Generation, Chenhe Dong, Ying Shen, Shiyang Lin, Zhenzhou Lin, Yang Deng

Research Collection School Of Computing and Information Systems

Question generation (QG) aims to automatically generate fluent and relevant questions, where the two most mainstream directions are generating questions from unstructured contextual texts (CQG), such as news articles, and generating questions from structured factoid texts (FQG), such as knowledge graphs or tables. Existing methods for these two tasks mainly face challenges of limited internal structural information as well as scarce background information, while these two tasks can benefit each other for alleviating these issues. For example, when meeting the entity mention “United Kingdom” in CQG, it can be inferred that it is a country in European continent based on …

Effort Of Reproducibility: Metrics, Methods, And Models To Navigate The Landscape Of Reproducible Research, Akhil Pandey Akella

Graduate Research Theses & Dissertations

Validating scientific claims is an elaborate process that involves researchers investing considerable time and effort to discover the validity of claims. It involves repeatability, reproducibility, and replicability, where each subsequent step requires increased effort and time. With the evolving nature of computational experiments and the exponential pace at which scientific publications are disseminated, researchers find it challenging to devote time, energy, and resources to assess claims made in papers of interest. Preemptive signals for reproducible effort can be helpful to researchers in filtering academic works of interest, thereby allowing them to adjust efforts based on need. Through this research, I …

Evaluating Computational Reproducibility Of Jupyter Notebooks Using Machine Learning And Natural Language Processing, A S M Shahadat Hossain

Graduate Research Theses & Dissertations

In recent years, computational reproducibility, which refers to achieving consistent results upon rerunning an experiment, has become one of the major concerns of various research communities. Jupyter Notebook, as a web-based computational notebook application, offers useful features for running and publishing computational experiments through interactive environments. However, rerunning notebooks does not always reproduce the experimental results. This thesis aims to develop novel methods to evaluate reproducibility by comparing different types of outputs between original and rerun notebooks. It also explores the idea of using machine learning models to predict reproducibility of notebooks automatically without the need of rerunning them. Through …

Bidirectional In-Situ Analysis And Visualization Of Fluid Structure Interactions With Applications In Blood Flow, Nazariy Tishchenko

Graduate Research Theses & Dissertations

Interactive blood flow simulation has applications in the understanding of complex fluids,training medical professionals, diagnostics, and surgical procedure planning. Bidirectional in situ visualization and analysis are much needed to streamline the analysis of large-scale patient-specific blood flow simulations. The in situ component ensures the live visualization of the simulation results while the simulation is running, and the bidirectional component allows for real-time control and configuration of the simulation parameters (i.e., setting and retrieving the simulation parameters and data based on need). In this project, a highly accurate multiphysics simulation was instrumented to work with an existing bidirectional in situ framework. …

Hack24f: Ai Attacking Ai, Emry Hankins, Sofia Escobar, Yinxin Wan

Paul English Applied Artificial Intelligence (AI) Institute Publications

As MLaaS gains popularity, it also attracts new threats, in particular, model extraction attacks. These attacks involve unauthorized attempts to access and replicate AI models by querying and analyzing the response. Not only do these attacks pose a threat to security and safety but also compromises valuable intellectual property. Because businesses are increasing accessibility to their models that contain sensitive data, it is crucial that they are able to keep them safe and secure.

Hack24f: Careplus: Ai Chatbot, Arianna Fernandez, Sophia Cherkaoui

Paul English Applied Artificial Intelligence (AI) Institute Publications

90% of patients Google symptoms before they talk to their doctor. What are we developing? An app that asks for user symptoms and personal information, users AI to determine medical conditions and provides a plan of action, including recommended medications and suggested doctors to visit.

Hack24f: Llms And World Knowledge Problems, Chengtaon Lin, Joseph Lobo, Huuthanhvy Nguyen, Brian Santos, Ting Xu

Paul English Applied Artificial Intelligence (AI) Institute Publications

While AI “hallucinations” have been widely publicized by the media as shortcomings of Large Language Models (LLMs), there is much less awareness about shortcomings that derive from the potential lack of understanding of the world, from a potential lack of commonsense knowledge. We want to raise awareness among our student body about the potential fallibility of LLMs when they the problems that they need to solve require a basic understanding of the world. We hope that this awareness will prompt everyone to question more carefully the outputs generated by LLMs.

Hack24f: The Empathy Architects, Michael Rejtig, Ajanee Igharo, Emma Kelminson, Jackson Comeau

Paul English Applied Artificial Intelligence (AI) Institute Publications

Problem Statement: We want to help patients from underserved communities feel more safe, respected and comfortable in interacting with healthcare providers during the initial in-person encounters while also helping providers build empathy and implement socio-emotionally competent communication behaviors. Solution: Empathy Evolution is an AI-powered role-playing game that helps patients simulate their ideal communication with healthcare providers.