Our study aims to identify the impact of artificial intelligence (AI) among undergraduate students’ performance and development during the introductory computer science courses.

As subjects of our study, we used a sample of 150 students from a computer science university, and we divided them into two groups. These two groups were considered one the experimental group and the other the control group. The experimental group aimed to begin learning assisted by technologies that involve and are based on artificial intelligence, while the second group maintained classic teaching-learning methods.

The data collected from the two groups include initial tests, to have an overview of the knowledge base from which we start, so that we can know the starting level, but also tests at the end of the course to see the level of knowledge acquired. Also, during the course, in addition to the start-end comparison between the two distinct groups, we asked the students to complete questionnaires that reflected the degree of satisfaction and contentment with the methods and practices used during the course.

The results indicate that the experimental group shows a significant increase in the degree of interest given to the course, the methods and techniques applied capturing the attention of the students and at the same time significant improvements in knowledge (p < 0.05), and a positive and optimistic feedback regarding the interest of the students and the recommendation to continue applying these methods, and these results confirm the importance of technology-assisted courses, the conclusion of Wayne Holmes' study on Artificial intelligence in education [1].

Therefore, the study contributes to increasing the relevance and importance of artificial intelligence-based technology as a teaching and study support. Further exploring this topic for a future research study would be to analyze and interpret the long-term impact of such approaches, not just immediate results as in this article.

References:
[1] Holmes, W., Bialik, M., Fadel, C., (2019). Artificial intelligence in education. DOI: 10.58863/20.500.12424/4276068

Keywords: Artificial Intelligence (AI), Personalized Learning, Learning Analytics, Student Engagement, Computer Science Education.