Aluno: Michael Jonathan Wright
Resumo
This thesis investigates the integration of Artificial Intelligence (AI) tools in higher
education, focusing on their impact on students' intrinsic motivation and academic success
through the lens of SDT. By examining how AI supports the psychological needs of
autonomy, competence, and relatedness, the research explores whether these tools promote
sustained motivation or inadvertently hinder critical aspects of learning. The study
highlights the transformative potential of AI tools, such as ChatGPT, in personalizing
learning, providing instant feedback, and fostering engagement. However, it also reveals
key challenges, including over-reliance on AI, diminished critical thinking, and a reduction
in meaningful human interactions.
The qualitative research design involved semi-structured interviews with 10 higher-
education students who experienced both traditional and AI-integrated learning
environments. Participants shared their experiences of using AI tools in academic tasks,
providing insights into how these tools influence motivation and learning outcomes.
The findings reveal a dual nature of AI: while it enhances short-term efficiency, motivation,
and academic performance, it may also undermine deeper learning processes and long-term
resilience by fostering dependency and superficial engagement.
The study underscores the importance of a balanced approach to AI integration. While AI
can democratize access to education and complement traditional teaching methods, it
cannot replace the human elements crucial for fostering creativity, critical thinking, and
social-emotional development. Limitations of the study include its focus on a specific
demographic and disciplines, which limits generalizability. Future research should explore
AI’s impact across diverse educational contexts and learner populations and examine how
educators can effectively mediate its use in classrooms. The findings contribute to ongoing
discussions about the ethical and effective integration of AI in education, offering practical
recommendations for leveraging AI to enhance learning while mitigating its potential risks.
Trabalho final de Mestrado