WHAT ARE THE CONSEQUENCES OF INTEGRATING ARTIFICIAL INTELLIGENCE TECHNOLOGIES INTO THE COMPUTER SCIENCE EDUCATIONAL PROCESS?

Introduction

The major challenge in modern societies is integrating AI technologies with the learning process, particularly in computer science. This inquiry has implications beyond academia, affecting the future of education. AI technologies have transformed various sectors, including education (Xu & Ouyang, 2022).

In STEM industries, there is a growing demand for AI, leading to the integration of AI and education, known as AI-STEM. This integration creates a complex system involving subject matter, information medium, and environment (Gligorea et al., 2023). AI chatbots respond to students' queries in real-time, design personalized learning paths, and promote active learning (Labadze et al., 2023). AI-powered assessments in STEM education are also becoming common (Ouyang et al., 2023).

However, AI in education faces challenges such as overlooking important skills, creating biases, and ethical concerns related to data privacy (Selwyn, 2019; Crawford, 2016). The rapid development of AI technologies requires dynamic research to keep pace with changes.

As a young AI researcher, I am fascinated by the potential of AI to improve education and driven by concerns about ethical dilemmas. This study aims to explore how AI is applied in computer science education, considering both benefits and ethical challenges. It seeks to answer the following questions:

What are the effects of AI on student performance in computer science?

What are the disadvantages and ethical concerns of AI in education?

What approaches can mitigate the problems of integrating AI in education?

Literature Review

Positive Consequences

AI technologies offer several benefits to computer science education. AI-driven learning platforms enable personalized and flexible learning, improving outcomes (Gligorea et al., 2023). AI-based tools identify student weaknesses and provide targeted interventions (Kim & Kim, 2022), creating a more personalized and effective learning environment.

AI chatbots handle student inquiries in real-time, customize learning paths, and foster interactive and engaging class environments (Labadze et al., 2023). AI solutions help teachers make informed decisions by analyzing data on student performance and providing immediate feedback (Ouyang et al., 2023).

Negative Consequences

Despite the benefits, AI in education has drawbacks. Over-reliance on technology can diminish interpersonal interactions and critical thinking skills (Selwyn, 2019). AI tools can perpetuate biases and stereotypes present in historical data (Crawford, 2016), leading to discriminatory patterns.

AI automation in assessments may reduce critical thinking and problem-solving skills developed through manual review. Increased AI-driven interactions could undermine the development of interpersonal skills, empathy, and collaboration (Selwyn, 2019).

Methodology

This study used qualitative research methods, including interviews with students and educators. Interviews explored the types of AI tools used, their frequency, potential benefits and drawbacks, ethical issues, and strategies for integrating AI into the curriculum.

Results

Students reported using AI tools like ChatGPT and IBM Watson for research and problem-solving. They highlighted benefits such as personalized learning, immediate feedback, and increased efficiency. However, they also noted risks like dependency on AI, potential data privacy issues, and the dissemination of incorrect information.

Educators emphasized the need for training on the ethical use of AI and developing guidelines to mitigate risks. They suggested incorporating AI to create adaptive learning environments and personalized study plans.

Discussion

The findings indicate that while AI can enhance computer science education, careful consideration is needed to address ethical concerns and potential drawbacks. Balancing AI integration with traditional teaching methods is crucial to maintaining critical thinking and interpersonal skills.

Conclusion

AI has the potential to revolutionize computer science education by offering personalized and efficient learning experiences. However, ethical issues such as data privacy and algorithmic bias must be addressed. Implementing guidelines and training on the ethical use of AI can help mitigate these problems. Future research should focus on developing strategies to balance AI integration with traditional education methods, ensuring a holistic approach to learning.