Large Language Models, ChatGPT and DeepSeek, Demonstrate Strong Capabilities in Education and Research Affairs
Summarize this article with:
Large language models are rapidly transforming fields from healthcare to engineering, and their potential within education and research is now under intense scrutiny.
Md Mostafizer Rahman from Tulane University, Ariful Islam Shiplu from Dhaka University of Engineering and Technology, and Md Faizul Ibne Amin from The University of Aizu, alongside Yutaka Watanobe and Lu Peng, present a detailed analysis of two leading models, ChatGPT and DeepSeek, to understand their strengths and weaknesses in these crucial areas. Their work combines rigorous testing of the models’ abilities in tasks like text generation, programming, and complex problem-solving with valuable feedback from students, educators, and researchers who have used them. The results reveal that ChatGPT excels at general language tasks, while DeepSeek proves more efficient in programming, and importantly, both models demonstrate a capacity for accurate medical diagnoses and effective mathematical reasoning, offering a significant step towards integrating these powerful tools into learning and discovery. ChatGPT and DeepSeek, a Comparative Analysis This study provides a comprehensive evaluation of ChatGPT and DeepSeek, examining their capabilities and potential uses. The research focuses on a side-by-side comparison of the models, assessing performance across a range of tasks to highlight where each excels and falls short. DeepSeek, and its variants like DeepSeek-Coder, DeepSeek-VL, and DeepSeek-R1, demonstrates strength in areas requiring specialized knowledge, such as code, and multimodal understanding, combining vision and language. The models also benefit from being more open-source friendly, allowing for greater customization and research. ChatGPT is acknowledged as a powerful and versatile model, particularly strong in general language tasks, creative writing, and conversational AI. However, the research acknowledges limitations in both models, including potential inaccuracies and hallucinations, struggles with complex mathematical problems, and the possibility of biased outputs. Future research should focus on improving accuracy, enhancing mathematical reasoning, addressing bias, and promoting open-source development. ChatGPT and DeepSeek, A Comparative Benchmark Researchers benchmarked model performance across text generation, programming, and specialized problem-solving tasks to explore trade-offs between accuracy, efficiency, and user experience. The methodology involved rigorous testing of each model’s capabilities in diverse areas, including medical diagnostics and complex mathematical problems, to establish a comparative performance profile. To assess text generation abilities, the team employed a range of prompts and evaluated the resulting outputs for coherence, relevance, and grammatical accuracy. In programming tasks, models were challenged with code creation, repair, and classification, with performance measured by code execution success and efficiency. The study further incorporated a real-world user survey, gathering insights from students, educators, and researchers regarding the practical benefits and limitations of these models. Researchers analyzed survey responses to identify key themes and patterns, revealing user perceptions of model usability, reliability, and potential applications.
The team specifically investigated how effectively each model supports tasks like code structure building, repair, classification, generation, and summarization. ChatGPT and DeepSeek, Strengths in Diverse Tasks Researchers benchmarked performance in text generation, programming, and specialized problem-solving, revealing distinct strengths for each model. Experiments demonstrate that ChatGPT excels in general language understanding and text generation tasks, showcasing its ability to produce fluent and coherent responses across a wide range of topics. Conversely, DeepSeek demonstrates superior performance in programming tasks, attributable to its efficiency-focused design and mixture-of-experts architecture. The study details how both models effectively solve complex mathematical problems and deliver medically accurate diagnostic outputs, highlighting their potential in STEM education and research. Researchers complemented these quantitative findings with a user survey involving students, educators, and researchers, gaining deeper insights into practical benefits and limitations.
This research establishes that both models offer opportunities for accessibility, personalization, and efficiency, while also acknowledging risks such as misinformation and academic dishonesty. This comprehensive analysis provides a balanced discussion of the responsible integration of large language models into educational and research ecosystems. ChatGPT and DeepSeek, A Comparative Analysis This research presents a systematic investigation into ChatGPT and DeepSeek, examining their technical foundations, performance across various applications, and user perceptions. The study involved detailed comparative analysis of the models’ architectures and capabilities, alongside extensive generative experiments validated by domain experts.
Results demonstrate that ChatGPT excels in general language understanding and text generation, while DeepSeek demonstrates superior performance in programming tasks, attributable to its design prioritizing computational efficiency. Furthermore, the research highlights the models’ effectiveness in specialized areas, showing both are capable of generating medically accurate diagnostic outputs and solving complex mathematical problems. A comprehensive user survey provided valuable insights into practical experiences and usability, complementing the quantitative findings. The authors acknowledge potential limitations, including concerns that over-reliance on such models could diminish critical thinking skills. Future work should focus on responsible development, ongoing evaluation, and effective governance as these technologies continue to evolve and impact society, ensuring their benefits are realized while mitigating potential risks. 👉 More information 🗞 Large Language Models for Education and Research: An Empirical and User Survey-based Analysis 🧠 ArXiv: https://arxiv.org/abs/2512.08057 Tags: