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Articles 121 - 150 of 112912
Full-Text Articles in Entire DC Network
Kenyon Collegian - April 10, 2025
Kenyon Collegian - April 3, 2025
Translating Economics For Stem Minds: An Ai Socratic Tutor That Speaks Their Language, Andre Mccloud
Translating Economics For Stem Minds: An Ai Socratic Tutor That Speaks Their Language, Andre Mccloud
IPHS 300: AI for Humanity
STEM students frequently struggle with economic thinking due to the particular framework of solving problems they acquire from their respective academic disciplines in undergraduate programs. This AI Socratic tutoring system is designed to detect and address discipline-specific misconceptions and gaps frequently holding students back in economics. Using Google’s Gemini Flash model, this tutor can give students hints and feedback and even reroute students thinking when they are confused. It does so by providing manageable explanations tailored to the individual student’s background across STEM fields like mathematics, physics, engineering, and other STEM fields. This system utilizes a customized Q&A bank pre-loaded …
Changing Narratives Of Self-Improvement: Self-Help Literature Across Two Eras, Ayesha Aslam
Changing Narratives Of Self-Improvement: Self-Help Literature Across Two Eras, Ayesha Aslam
IPHS 300: AI for Humanity
This project explores how the narratives of personal growth in self-help literature have evolved between the 1970s and the 2010s. The goal was to identify which themes persisted across eras and how others shifted in response to broader cultural and technological changes. I hypothesized that 1970s texts would emphasize self-control and traditional success, while 2010s texts would highlight flexibility, mental well-being, and authenticity, with some shared focus on motivation and habit-building. To test this, I selected five bestselling books from each decade and applied Latent Dirichlet Allocation (LDA) topic modeling using a Colab-based notebook. The top 30 most salient terms …
Leveraging Ai Agents And Multi-Agent Debate To Automate Mlb Front Office Decisions And Roster Construction, Parker Gibbons
Leveraging Ai Agents And Multi-Agent Debate To Automate Mlb Front Office Decisions And Roster Construction, Parker Gibbons
IPHS 484: Senior Seminar
This project leverages artificial intelligence Agents and Multi-Agent Debate (MAD) to evaluate Major League Baseball players and construct a twenty-six player MLB roster. The AI Agents evaluate each player based on statistics and grades them according to a five-tool scale, eventually resulting in a single numerical rating. MAD is then employed alongside optimization techniques to select thirteen hitters and thirteen pitchers, maximizing team performance according to agent consensus, while staying within a specified salary cap. The operating hypothesis is that AI agents can effectively evaluate Major League Baseball players based on performance statistics, even with large and complex datasets. By …
Understanding Human-Ai Interactions: What 17,000 Conversations Reveal About Creativity And Chatgpt, Hannah Sussman
Understanding Human-Ai Interactions: What 17,000 Conversations Reveal About Creativity And Chatgpt, Hannah Sussman
IPHS 484: Senior Seminar
This study uses topic modeling to analyze over 17,000 English-language conversations from the WILDCHAT-FULL dataset, a large-scale collection of human-ChatGPT interactions. By applying Latent Dirichlet Allocation (LDA) across 17 time-based segments spanning one year, the research identifies major themes and temporal shifts in user engagement. Creative writing emerged as the dominant topic category, accounting for nearly 40% of all identified topics. Subcategories such as character development, fight scenes, and sexual content offer further insight into how users creatively engage with ChatGPT. By combining large-scale topic modeling with close qualitative review, this study demonstrates a scalable yet nuanced approach to analyzing …
Ai's Creative Boundaries: A Cross-Model Pattern Analysis Of Identity-Based Narratives, Maisie Jane Brigham
Ai's Creative Boundaries: A Cross-Model Pattern Analysis Of Identity-Based Narratives, Maisie Jane Brigham
IPHS 300: AI for Humanity
This research project examines creative writing outputs from five leading large language models (Claude 3.7 Sonnet, ChatGPT 4o, Grok 3, Gemini 2.5 Flash, and Deepseek R1) as they generate and respond to prompts focused on diverse identity experiences. By analyzing stories centered on immigrant, Black, LGBTQ+, transgender, and Indigenous experiences, I identify recurring patterns, tropes, and limitations across different AI systems. This study illuminates how algorithmic storytelling currently relies on a limited repertoire of narrative elements, raising important questions about the representation of diverse human experiences in AI-generated creative content and the potential impacts of these patterns as AI writing …
Peak : An Ai Voice Coach For Emotion-Aware Performance Tracking In High-Stakes Fields, Ayman Wadud
Peak : An Ai Voice Coach For Emotion-Aware Performance Tracking In High-Stakes Fields, Ayman Wadud
IPHS 484: Senior Seminar
High-stakes performers, such as athletes, artists, and professionals, often lack tools that integrate objective performance metrics with subjective mental states. This disconnect can hinder effective training and optimization. PEAK addresses this gap by combining customizable performance analytics with real-time emotional insights via Hume's Empathic Voice Interface (EVI). Through natural voice interaction, PEAK correlates emotional expression with performance data, enabling personalized feedback and data-driven reflection. The platform empowers users to understand their emotion-performance dynamics and develop targeted strategies for sustainable peak performance.
Biolinkbert-Pr: A Large Language Model For Diagnosing Pediatric Rheumatological Disorders, Juliette Lowe
Biolinkbert-Pr: A Large Language Model For Diagnosing Pediatric Rheumatological Disorders, Juliette Lowe
IPHS 300: AI for Humanity
Pediatric rheumatology is an understudied and underprovided field in medicine. Currently, there are only 850 pediatric rheumatologists in the United States (1). This can make it incredibly difficult to get a diagnosis, since pediatric rheumatologic disorders are rare and thus easily missed. For example, eight states have no pediatric rheumatologists at all, and only 25% of children with arthritis are able to see a rheumatologist (2). AI applications in pediatric rheumatology are lacking, likely due to the combination of a lack of interest and a lack of data. This project utilizes a large language model (LLM) to create an AI …
Yunique: Adaptive Intelligence For Convertible Bond Investing, Yunhan Zhao
Yunique: Adaptive Intelligence For Convertible Bond Investing, Yunhan Zhao
IPHS 484: Senior Seminar
No abstract provided.
Nlp Analysis Of The Septuagint: Topic Modeling And Sentiment Analysis Of Biblical Domestic Terms, Anne-Duncan Enright
Nlp Analysis Of The Septuagint: Topic Modeling And Sentiment Analysis Of Biblical Domestic Terms, Anne-Duncan Enright
IPHS 484: Senior Seminar
This study conducts an exploratory data analysis (EDA) of topic modeling and sentiment analysis applied to the Septuagint (LXX – the Greek translations of the Old Testament and the New Testament in the original Koine Greek) as well as four English translations of the Bible (LSV, Darby, DR, and KJV). Utilizing Latent Dirichlet Allocation (LDA) for topic modeling, I compare the Vulgate-based translations to Septuagint-based translations, discovering marked differences between the two categories of translations. The Vulgate is the Latin translation of the Bible done by Jerome in 900 A. D. which is already one step away from the original …
Scraping Sermonsusing Natural Language Processing To Compare Protestant Churches, Annalia Fiore
Scraping Sermonsusing Natural Language Processing To Compare Protestant Churches, Annalia Fiore
IPHS 484: Senior Seminar
This project compares sermons from three Christian traditions: Evangelical, Charismatic, and Reformed. Using data scraped from church youtube channels based in the Columbus, Ohio area, I ran thousands of sermons through Topic Modeling to evaluate the differing emphases of each tradition. Many of the topics corresponded with what we might expect from their respective tradition. But others were surprising. Most significantly, there was a strong emphasis within the Charismatic tradition on tithing and finances, concerns with resisting sexual temptation among the Evangelicals, and a focus on ecclesiology within the Reformed tradition. This project also indicates that further topic modeling on …
Chalmers Library Research Award Winner 2 2025, Chau Vu
Chalmers Library Research Award Winner 2 2025, Chau Vu
Chalmers Library Research Award
No abstract provided.
Chalmers Library Research Award Winner 1 2025, Tasnim Islam Orco
Chalmers Library Research Award Winner 1 2025, Tasnim Islam Orco
Chalmers Library Research Award
No abstract provided.
Can Advanced Chatbots Help Us Navigate Educational Advocacy? Understanding The Potential Of Large Language Models As Assistants And Guides Within An Iep (Individualized Education Program) Meeting Context, Nava Bahrampour
IPHS 300: AI for Humanity
Hundreds of thousands of parents and students in New York City’s school district alone (Fancsali and Farley 2018) go through the Individualized Education Program (IEP) process every year, attending meetings and evaluations in order to determine adequate services and students with disabilities’ educational trajectories. However, most parents, especially those new to public education policy, report difficulty navigating the system or acquiring the resources necessary to successfully advocate for their children at IEP meetings (Advocates for Children 2025, Kurth et al. 2020). The rise of generative artificial intelligence and increased linguistic capabilities of interactional chatbots provokes questions about such technologies’ ability …
Following The Crowd? A Topic Modeling Analysis Of Twitter Discourse And Supreme Court Decisions, Jessica Daughterty
Following The Crowd? A Topic Modeling Analysis Of Twitter Discourse And Supreme Court Decisions, Jessica Daughterty
IPHS 300: AI for Humanity
This project uses topic modeling to compare the top topics from Twitter posts with the text of the Supreme Court’s Dobbs v. Jackson ruling, which overturned Roe v. Wade in 2022. I analyzed whether the Court’s reasoning reflected public concerns or was disconnected. While some analysis of the Twitter data exists on the Kaggle dataset I used, I conducted this research independently of those results. By putting the Court’s language and public sentiment side by side, this project explores whether institutions are responding to what people care about.
Exploring The Potential Of Ai For Swim Technique Evaluation And Athlete-Centered Coaching, Gwen Eisenbeis
Exploring The Potential Of Ai For Swim Technique Evaluation And Athlete-Centered Coaching, Gwen Eisenbeis
IPHS 300: AI for Humanity
This project explores the use of AI-powered video analysis to simulate elite-level coaching in butterfly stroke technique. Using Google’s Gemini 2.5, the goal of the project is to determinewhether a large multimodel, trained on technique videos of elite swimmers, can generate detailed and personalized feedback that mirrors the insight of a well-informed human swim coach. Training videos featuring Olympic-level butterfly swimmers were used to establish an internal reference model of an ideal butterfly technique. The model was then presented with videos of collegiate swimmers and prompted to deliver coaching-style feedback. Overall, this project demonstrates the potential for AI systems to …
Ai Proof Benchmarking: Evaluating Mathematical Reasoning In Open-Source Llms Via Taylor Series Analysis, Godwin Idowu
Ai Proof Benchmarking: Evaluating Mathematical Reasoning In Open-Source Llms Via Taylor Series Analysis, Godwin Idowu
IPHS 300: AI for Humanity
This research project investigates large language models’ (LLMs) abilities to develop conceptually and mathematically correct proofs by using a benchmark based on the Taylor Series representation. The task examines LLM models for their capacity to adhere to definitions, theorems, and calculus. A range of models of varying sizes was tested, including Qwen, Gemma and LLaMA. Models under 2B parameters demonstrate poor understanding of Taylor and geometric series and apply wrong theorems while lacking logical reasoning about convergence. Models with at least 27B parameters typically generate proofs that are both coherent and almost complete. The research identifies existing constraints in symbolic …
Authenticity Under Review: How Well Does Genai Write College Admissions Essays?, Adrian Mangine
Authenticity Under Review: How Well Does Genai Write College Admissions Essays?, Adrian Mangine
IPHS 300: AI for Humanity
With nearly 30% of people ages 14-22 reporting frequent AI use, increasing AI assistance in college admissions essays poses a new consideration with ethical AI use (Rubin et al., 2024). This study investigates how well three generative AI models write college admissions essays: ChatGPT o3, Gemini 2.5 Pro, and Grok. Each model responded to a Common App 2025-2026 application prompt as three distinct applicants: Elijah, Grace, and Malik (Common App, 2025). Each student represented a common college applicant archetype: Elijah, an academically successful dual sports recruit; Grace, a near-perfect award-winning scholar; and Malik, a gifted student from an underrepresented background. …
Kenyon College - March 27, 2015
Kenyon Collegian - March 20, 2025
Resume: Aniwar Mamat, Aniwar Mamat 艾尼瓦尔
Resume: Aniwar Mamat, Aniwar Mamat 艾尼瓦尔
Zhou Documents
This resume was written in Chinese. It consists of the artist's education, work experience, and the exhibitions he has participated in from 1985 to 1994. (Yifan Shang '25)
Kenyon Collegian - February 27, 2025
Kenyon Collegian - February 20, 2025
Kenyon Collegian - February 13, 2025
Kenyon Collegiate - February 7, 2025
Kenyon Collegian - February 6, 2025
Kenyon Collegian - January 30, 2025