# Large Language Models in Computer Science Classrooms: Ethical Challenges and Strategic Solutions
## 3 LLMs for Computer Science Studies: Advantages and Challenges
### Opportunities for Computer Science Teachers
#### 3.2.2 Adapting Assignments to the Era of LLMs
These findings suggest that, when paired with carefully structured educational interventions, ChatGPT does not adversely affect the learning outcomes of novice programmers. They highlighted the importance of thoughtful integration and active oversight in leveraging AI tools responsibly, ensuring that students engage with course materials while developing essential programming skills. These findings underscore the need to adapt teaching strategies to balance the benefits of AI tools with the development of critical competencies. In a related domain, [PERSON] et al. [67] explored the implications of LLMs in data science education. They advocated for a pedagogical shift that emphasizes strategic skills such as LLM-informed creativity, critical thinking, and interdisciplinary knowledge, rather than traditional hands-on coding. [PERSON] et al. argued that, while LLMs can enhance personalized learning and serve as powerful educational tools, they should complement rather than replace human intelligence. Their recommendations call for curricula that balance technical skills with critical thinking and ethical awareness, ensuring that students are proficient in these technologies while understanding their broader societal impacts. Building on this theme, [PERSON] et al. [39] emphasized fostering a genuine desire to learn and cultivating deep research skills to counterbalance the potential downsides of LLMs. They advocated for engaging with students through activities such as writing conferences, in order to promote collaboration and skill development, while acknowledging the logistical challenges associated with large class sizes. The findings of the above studies are summarized in Table 3, which outlines the key skills developed by students in computer science education, the strategies employed to nurture these skills, the impacts of large language models (LLMs) on skill development, and the sources that discuss these findings. \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline  
In conclusion, while over-reliance on LLMs can hinder essential skills such as problem-solving, independent learning, and critical thinking, their thoughtful and responsible integration within educational settings can yield substantial benefits. Properly employed, LLMs have the potential to foster creativity, enhance technical proficiency, and promote ethical awareness. Striking the right balance between leveraging their capabilities and nurturing foundational skill development is essential for maximizing their educational potential. In particular, adapting courses thoughtfully becomes imperative. Unadapted challenges and assignments risk fostering excessive reliance on LLMs, which may undermine the critical and creative abilities of students. Conversely, when course materials are carefully redesigned to align with the capabilities of LLMs, these tools can become transformative educational aids. In such scenarios, students' problem-solving skills and technical proficiency are not only preserved but are often significantly enhanced, enabling them to fully harness the advanced capabilities of these technologies. However, the integration of LLMs into educational settings raises questions that extend beyond pedagogical considerations. As discussed in previous sections, LLMs have a profound impact on how students approach learning, how teachers design and assess assignments, and how institutions adapt to evolving technologies. Alongside these opportunities, ethical challenges have emerged as a central concern. The potential for misuse, the risks of plagiarism, and the erosion of academic integrity are critical issues that must be addressed to ensure that LLMs are used responsibly and equitably.