The Impact of Artificial Intelligence on the Learning Experience: A Systematic Literature Mapping

Abstract

Context: the emergence of new tools such as AI-assisted search engines or chatbots is reshaping educational practices, fostering more personalized and dynamic learning environments. Objective: this study analyzes the incorporation of AI in traditional assessment methods and explores the challenges associated with implementing these new tools in student evaluation within the technological university context. Method: a systematic mapping of the literature was conducted to synthesize findings from existing research on the impact of AI on learning experiences and assessment practices. Results: the analysis reveals a paradigm shift in both teaching and assessment methodologies. AIs are progressively transforming traditional exams with more automated and, presumably, more efficient assessment systems. However, the integration of these tools requires teachers and students to acquire new skills to maximize their effectiveness. Additionally, ethical considerations regarding the use of AI, including privacy concerns and the potential displacement of human educators, highlight the importance of maintaining a humanistic approach in the digital age. The literature reviewed emphasizes the need for a balanced and thoughtful use of AI technologies in education, along with a critical understanding and clear frameworks to mitigate risks and optimize benefits.