# ChatGPT for Education and Research: Opportunities, Threats, and Strategies
## 2 Related Literature  
In this section, we present recent studies on education and research using ChatGPT from the perspective of educators and learners. We also summarize published studies that use ChatGPT for different educational fields, including science, medicine, and engineering. Due to the novelty of the topic, we found few peer-reviewed scholarly papers. However, we reviewed preprints (non-peer-reviewed academic papers) in different educational branches. [PERSON] [22] presented the potential of AI and NLP to improve academic performance. The study employed a case study using ChatGPT, which significantly enhances academic research on economics and finance. [PERSON] and collaborators [23] discovered the benefits of ChatGPT for their research in finance. They also mentioned the ethical implications of this revolutionary AI tool. [PERSON] et al. [24] discussed the opportunities and challenges of using ChatGPT in education. Moreover, some basic features and user interfaces of ChatGPT were presented in [24]. Furthermore, several studies [9; 10; 11; 12; 14] have published applications of ChatGPT in education. [PERSON] et al. [25] tested the mathematical capabilities of ChatGPT on GHOSTS and handcrafted datasets. GHOSTS is the first collection of data expressed in natural language that was created and maintained by active mathematicians. Their experimental results proved that \"_the mathematical abilities of ChatGPT are significantly below those of an average mathematics student. ChatGPT often understands the question but does not provide correct solutions.\"_ The performance of ChatGPT as an assistant in medical education is also significant. [PERSON] et al. [26] evaluated the performance of ChatGPT on the US Medical Licensing Exam, which includes three exams: Step 1, Step 2 CK, and Step 3. Their experimental results show that ChatGPT performed close to or near the minimum requirement on all three exams despite receiving no specific guidance or support. [PERSON] et al. [27] investigated the performance of ChatGPT on the medical licensing exam. These compelling results mean that ChatGPT can support medical education. A summary of articles related to medical education using ChatGPT can be found in [28]. Computer programming is a complex task requiring correct logical and syntactic implementation. AI-based models have achieved plausible success on a variety of programming tasks, including code repair, summarization, completion, correction, classification, and generation [20; 29]. Alphacode [30] is a state-of-the-art LLM developed and trainedspecifically to support competitive-level programming. Both ChatGPT and Alphacode perform coding-related tasks by digesting a large amount of human-generated text [31]. ChatGPT is a more general conversation engine, whereas Alphacode is more specialized for programming [31], even though these two systems use _\"virtually the same architecture\"_[31]. Moreover, although ChatGPT was not designed and developed for automatic code repair, this tool is still suitable for it. The performance of code debugging with ChatGPT has been presented in the study [32]. Their experimental results show that the bug-fixing performance of ChatGPT is competitive with deep learning models such as Codex and CoCoNut. Nevertheless, ChatGPT has significantly outperformed traditional code-repair approaches [32]. [PERSON] et al. [33] studied the performance of ChatGPT in solving software testing curriculum questions. ChatGPT could generate correct/partially correct answers and explanations in approximately 44% and 57% of cases, respectively. [PERSON] and collaborators [34] studied the impact of ChatGPT on higher (university) education, especially on subjects related to computer programming. They demonstrated the effectiveness and usability of ChatGPT for handling programming assignments, exams, and homework using collected data. They also presented the misuse and benefits of ChatGPT for computer science education.