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Innovation Unleashed: Students Explore Data Science Research

During the Fall 2023 semester the DSA worked with the Office of Undergraduate Research (OUR) to fund three OUR Research Assistants. These three students were able to make strides in computing, K-12 STEM education, and AI research.

Nithya Janapati

My research is focused on conducting a meta-review of research and practice on integrating AI core concepts with K-12 STEM education. Integrating AI-integrated STEM curriculum is essential for K-12 since real-world STEM problem-solving involves AI-based solutions. Conducting a systematic review of the literature identifies evidence-based best approaches for improving teaching and learning for AI-integrated STEM education. It also helps us identify and address gaps in research and practice in this area. To aid in this process, my research has been centered on a meta-review of related scientific papers. Being a research assistant has helped me to better understand concepts relevant to AI-infused STEM education and to gain skills in the areas of literature review and CS education research.

Jeff Powell

Over the past semester, my project has focused on accelerating the calculation of many-body van der Waals forces using specialty hardware known as GPUs. This semester, I have shifted more closely to work with one of the grad students in my lab who has been able to make use of my work to complete work towards his preliminary examinations and a research paper. I have largely expanded the variety of models that can be used in these calculations. The research assistant position has played a key role in providing me with valuable connections, mentorship, and an engaging problem domain. This experience has deepened my understanding of computational chemistry and given me practical skills in GPU programming and parallel computing. The support and guidance received from my lab and the funding provided by the DSA have been instrumental in driving the success of this project.

Shiva Gadireddy

As an OUR Research Assistant at the Game2Learn Lab at NC State, a computer science lab led by Distinguished Professor Dr. Tiffany Barnes with a focus on using cutting-edge and innovative technology to improve computer science education, I have undertaken a project that seeks to explore the role of artificial intelligence in advancing this mission.

With the fairly recent introduction of large language models (LLMs) such as ChatGPT and Github Copilot to the public, their effects on computing education (CE) have yet to be thoroughly investigated. My research team, consisting of myself, Ph.D. students Benyamin Tabarsi and Heidi Reichert, have set out to perform a systematic literature review (SLR) with a focus on large language models and their use in computing education, along with conducting a text mining investigation to identify existing patterns and trends in LLM research. So far, our team has been able to filter through over 6,000 database search results and has shortlisted roughly 40 research papers to be rigorously reviewed with a set of quality criteria. Data extraction and coding from these research papers will then be carried out to answer our research questions and present conclusions and recommendations for future research.

To conduct our text mining investigation, we were able to utilize data science techniques such as Latent Dirichlet Allocation (LDA) to perform topic modeling on our corpus of chosen research papers. The programming language R was used to write scripts to pre-process our data, tokenize and clean it to only contain relevant information, and create preliminary data visualizations such as bigram graphs in order to analyze our results. We hope that our text mining investigation will help visually uncover patterns in existing LLM research and allow for a deeper understanding of the topics currently being pursued in the literature.

The Research Assistant position, which has been graciously funded by the Data Science Academy and the Office of Undergraduate Research, has allowed me to continue working on this research project during the course of the Fall Semester so that our team can work towards getting our paper submitted for publication as soon as possible. In a field like AI research where new discoveries are being made at a rapid pace, it is crucial that our research team work swiftly and responsibly to make positive contributions to our field.