Doctor of Education (Educational Leadership), Youngstown State University, 2024, Department of Teacher Education and Leadership Studies

The rapid ascent of increasingly capable artificial intelligence (AI) brings new potential to revolutionize education—for better or worse. This study investigates the attitudes of high school teachers toward the integration of Chat Generative Pre-Trained Transformer, commonly known as ChatGPT, to support teaching and learning. This research seeks to understand the key factors that influence teachers' acceptance or resistance to using ChatGPT, focusing on the potential benefits and challenges posed by this advanced AI technology. The Unified Theory of Acceptance and Use of Technology (UTAUT) is used as the theoretical framework to forecast teachers' willingness to adopt ChatGPT for educational purposes. The research employs the quantitative attributes of a Q-methodological approach to classify and analyze the perspectives of high school educators. The study examines how some perceive ChatGPT as an asset to teaching and learning. Conversely, findings also illuminate concerns that ChatGPT will have a negative impact, thereby instilling a sense of caution about its integration. Participants in this study, 18 high school teachers, completed a web-based Q-sort that revealed three distinct viewpoints: Learning to Fly, Welcome to the Machine, and Comfortably Numb, which collectively accounted for 53% of the variability in the data. The results revealed varied opinions regarding technical confidence, openness to integration, perceived benefits, and potential liabilities. The findings provide insights into the diverse attitudes and beliefs held by high school educators regarding the educational use of generative AI tools like ChatGPT. The findings of this research contribute to the ongoing debate about the role of AI in education. The results emphasize a need for professional development programs to build teachers' capacity to effectively incorporate AI tools in the classroom. Ultimately, this study seeks to shed light on the factors that promote or inhibit the adopt (open full item for complete abstract)

Committee: Karen Larwin Ph.D. (Committee Chair); Danielle Thomas Ph.D. (Committee Member); Peter Zagray Ph.D. (Committee Member) Subjects: Artificial Intelligence; Education; Education Policy; Educational Software; Educational Technology; Educational Theory; Ethics; Information Technology; Instructional Design; Mathematics Education; School Administration; Science Education; Secondary Education; Teaching; Technology

Honors Theses, Ohio Dominican University, 2024, Honors Theses

Artificial Intelligence (AI) has grown exponentially over the past few decades. One of the products of the technological advancements in AI is ChatGPT. ChatGPT has revolutionized the way humans view AI due to its numerous capabilities. After its release, it has slowly been incorporated into numerous industries including education. This study aims to analyze how ChatGPT has been integrated into higher education in the present day. Surveys were distributed to both students and professors via their official Ohio Dominican University emails. Students were asked about their ChatGPT usage. Professors were asked about the current ChatGPT usage in their classes by their students as well as their opinions about the future of AI in their field of study. In addition, this research will attempt to find what subjects students are more likely to use ChatGPT in and what professors from different areas of expertise think about the technology. After data analysis, the conclusion is that students are more likely to use ChatGPT in courses within the humanities than others and professors understand the implications that comes with ChatGPT as well as the benefits. Some are open to the idea of incorporating ChatGPT into their teaching methods, while others are still very skeptical.

Committee: Alae Loukili (Advisor); Christopher Martin (Other); Mike Godsey (Other) Subjects: Artificial Intelligence; Computer Science

Doctor of Philosophy, The Ohio State University, 2024, EDU Teaching and Learning

Since the release of advanced Large Language Models (LLMs) like ChatGPT in the winter of 2022, educators have been challenged to integrate AI in educational contexts without adequate preparation. This multimethod study aims to provide valuable insights into how students and teachers can make effective, responsible use of AI tools for writing. Specifically, it focuses on the impact of ChatGPT-powered English writing instruction on writing development among emerging multilinguals in Korea. The study examines students' usage patterns of ChatGPT's five key functionalities—vocabulary support, grammar checking, feedback and revision, sentence generation, and paraphrasing/summary—and explores how these patterns correlate with writing development. 50 undergraduate students from four different universities voluntarily participated in a four-week ChatGPT-powered English writing course designed based on the AI literacy framework (Warschauer et al., 2023). Data were collected from pre- and post-TOEFL writing tests, ChatGPT chat histories, demographic surveys, perception surveys, and interviews. Quantitative data were analyzed using linear multiple regressions, correlation analyses, and paired-samples t-test, while qualitative data underwent content analysis. The findings revealed that students showed significant improvement in their writing scores after receiving ChatGPT-powered instruction. Students expressed high satisfaction with ChatGPT, particularly appreciating its immediate feedback and its contribution to writing fluency. Self-perceived English proficiency levels and prior English writing achievement emerged as significant factors influencing writing development, while qualitative analysis further highlighted the importance of ChatGPT familiarity as a contributing factor. Among the five key functionalities of ChatGPT, feedback and revision emerged as the most frequently used and the only statistically significant contributor to writing development. However, qualitative (open full item for complete abstract)

Committee: Peter Sayer (Committee Member); Becky Huang (Advisor); Youngjoo Yi (Advisor) Subjects: Education; Educational Software; Educational Technology; English As A Second Language

Doctor of Education (Ed.D.), University of Findlay, 2024, Education

This dissertation investigates the impact of the Ohio Blended Collaborative (OBC) on fostering 21st century skills among students. Utilizing a mixed-methods research design, this study aims to understand how participation in the OBC influences perceptions and self-assessments of critical thinking, collaboration, communication, and creativity. The quantitative analysis is derived from a validated instrument consisting of 30 Likert-style questions, complemented by qualitative insights from open-ended survey questions. The demographic data of 227 students and 29 teachers provided a foundation for understanding the context of the research participants. Quantitatively, both students and teachers reported high levels of confidence in collaboration and communication skills, with notable strengths in problem-solving and teamwork. Qualitatively, themes emerged around increased engagement, confidence, and student-centered learning, underscoring the value of personalized learning environments fostered by the OBC. Notably, the study identified a discrepancy between students' self-perceptions and teachers' assessments, particularly regarding the application of knowledge to a new contextual situation. Additionally, the interrelatedness of the four skill categories was highlighted, indicating a holistic approach to 21st century skill development. This dissertation contributes to the field of education by offering insights into the benefits and challenges of implementing personalized learning with ongoing collaboration and support through a structured professional learning community. The findings suggest that while the OBC positively impacts the development of 21st century skills, ongoing support and adjustments are essential for maximizing student outcomes. Recommendations for practice, limitations of the study, and future research directions are discussed, providing a comprehensive overview of the OBC's implications for stakeholders in education.

Committee: Nicole Schilling (Committee Chair); Brian Bowser (Committee Member); Amanda Ochsner (Committee Member) Subjects: Curriculum Development; Education; Teaching

MS, University of Cincinnati, 2024, Engineering and Applied Science: Electrical Engineering

It has always been an important development strategy for software to keep pace with its evolution and meet stakeholder needs. Therefore, many software systems have very short release cycles. When many releases appear, how to test them becomes more and more important. Since the new features are often innovative, there are no conventional tools to test them, and manual testing is actually very cumbersome, not to mention that there are many non-testable features. This thesis mainly investigates the testability of the 109 features of 16 versions of the Mozilla Firefox browser from May, 2022 to July, 2023. The objects are the features of Firefox browser itself under the Windows 11 operating system, excluding additional plug-ins or Firefox browsers under other operating systems. Through manual testing and analyses, the features of the Firefox browser are divided into testable and non-testable, and the reasons why features are non-testable are given. Since the object being tested is the features of the browser, Selenium—a tool dedicated to testing browsers is considered. In this thesis, the Selenium package based on Python is used to simulate manual testing. By comparing the results of manual testing and the results generated by Selenium, we can gain insights into the limitations of Selenium testing, which contributes to improving automated testing in the future work. In this thesis, we also employ OpenAI's ChatGPT (version 3.5) to assess the testability of each feature. We then compare ChatGPT's answers with the manual analysis results.

Committee: Nan Niu Ph.D. (Committee Chair); Rui Dai Ph.D. (Committee Member); Boyang Wang Ph.D. (Committee Member) Subjects: Computer Science

MS, University of Cincinnati, 2023, Engineering and Applied Science: Mechanical Engineering

The assessment and representation of intricate design and simulation results for organic geometries through traditional devices (tablets, computers, phones) possess a set of significant limitations. Consequently, identifying potential manufacturability, design issues, and opportunities for design enhancements remains challenging in the early design stage. The inability to identify these possible areas often leads to time-consuming and costly design revisions and iterations. In contrast, Virtual Reality (VR) offers many benefits over the conventional 3D computer-aided design (CAD) environment, particularly regarding visualization and analysis of complex organic geometries. The advantages of VR may be more visible as designs become more organic or complex. This thesis aims to investigate and develop an immersive environment that enables designers and engineers to explore complex organic geometries. This thesis focuses on generating an Immersive Virtual Reality (ImVR) environment that could allow designers to evaluate and identify critical design areas of a part model based on the design for additive manufacturing (DfAM) parameters. Custom Python scripts and Visualization Toolkit (VTK) algorithms perform surface and volume rendering across the CAD model in the virtual environment. Two case studies of different organic designs with tools and an immersive visualization environment are presented to analyze the effect of immersive design analysis of a CAD model. The ImVR toolset also includes a collaborative multiplayer feature and an artificial intelligence (AI) chatbot powered by ChatGPT. The chatbot can provide real-time guidance to users within the immersive environment, while the collaborative feature enables multi-user interaction and visualization in the immersive environment.

Committee: Sam Anand Ph.D. (Committee Chair); Manish Kumar Ph.D. (Committee Member); Jillian Aurisano Ph.D. (Committee Member) Subjects: Mechanical Engineering